Reduce Manual Repetitive Work With IT Automation

Free up time for value-adding jobs.

ANALYST PERSPECTIVE

Automation cuts both ways.

Automation can be very, very good, or very, very bad.
Do it right, and you can make your life a whole lot easier.
Do it wrong, and you can suffer some serious pain.
All too often, automation is deployed willy-nilly, without regard to the overall systems or business processes in which it lives.
IT professionals should follow a disciplined and consistent approach to automation to ensure that they maximize its value for their organization.

Derek Shank,
Research Analyst, Infrastructure & Operations
Info-Tech Research Group

Executive summary

Situation

• IT staff are overwhelmed with manual repetitive work.
• You have little time for projects.
• You cannot move as fast as the business wants.

Complication

• Automation is simple to say, but hard to implement.
• Vendors claim automation will solve all your problems.
• You have no process for managing automation.

Resolution

• Begin by automating a few tasks with the highest value to score quick wins.
• Define a process for rolling out automation, leveraging SDLC best practices.
• Determine metrics and continually track the success of the automation program.

Info-Tech Insight

1. Optimize before you automate.The current way isn’t necessarily the best way.
2. Foster an engineering mindset.Your team members may not be process engineers, but they should learn to think like one.
3. Build a process to iterate.Effective automation can't be a one-and-done. Define a lightweight process to manage your program.

Infrastructure & operations teams are overloaded with work

• DevOps and digital transformation initiatives demand increased speed.
• I&O is still tasked with security and compliance and audit.
• I&O is often overloaded and unable to keep up with demand.

Manual repetitive work (MRW) sucks up time

• Manual repetitive work is a fact of life in I&O.
• DevOps circles refer to this type of work simply as “toil.”
• Toil is like treading water: it must be done, but it consumes precious energy and effort just to stay in the same place.
• Some amount of toil is inevitable, but it's important to measure and cap toil, so it does not end up overwhelming your team's whole capacity for engineering work.

Info-Tech Insight

Follow our methodology to focus IT automation on reducing toil.

Manual hand-offs create costly delays

• Every time there is a hand-off, we lose efficiency and productivity.
• In addition to the cost of performing manual work itself, we must also consider the impact of lost productivity caused by the delay of waiting for that work to be performed.

Every queue is a tire fire

Queues create waste and are extremely damaging. Like a tire fire, once you get started, they’re almost impossible to stamp out!

Increase queues if you want

• “More overhead”
• “Lower quality”
• “More variability”
• “Less motivation”
• “Longer cycle time”
• “Increased risk”

(Source: Edwards, citing Donald G. Reinersten: The Principles of Product Development Flow: Second Generation Lean Product Development )

Increasing complexity makes I&O’s job harder

Every additional layer of complexity multiplies points of failure. Beyond a certain level of complexity, troubleshooting can become a nightmare.

Today, Operations is responsible for the outcomes of a full stack of a very complex, software-defined, API-enabled system running on infrastructure they may or may not own.
– Edwards

Growing technical debt means an ever-rising workload

• Enterprises naturally accumulate technical debt.
• All technology requires care and feeding.
• I&O cannot control how much technology it’s expected to support.
• I&O faces a larger and larger workload as technical debt accumulates.

The systems built under each new technology paradigm never fully replace the systems built under the old paradigms. It’s not uncommon for an enterprise to have an accumulation of systems built over 10-15 years and have no budget, risk appetite, or even a viable path to replace them all. With each shift, who bares [SIC] the brunt of the responsibility for making sure the old and the new hang together? Operations, of course. With each new advance, Operations juggles more complexity and more layers of legacy technologies than ever before.
– Edwards

Most IT shops can’t have a dedicated engineering team

• In most organizations, the team that builds things is best equipped to support them.
• Often the knowledge to design systems and the knowledge to run those systems naturally co-exists in the same personnel resources.
• When your I&O team is trying to do engineering work, they can end up frequently interrupted to perform operational tasks.

Personnel resources in most IT organizations overlap heavily between “build” and “run.”

IT operations must become an engineering practice

• Usually you can’t double your staff or double their hours.
• IT professionals must become engineers.
• We do this by automating manual repetitive work and reducing toil.

Build your Sys Admin an Iron Man suit

Some CIOs see a Sys Admin and want to replace them with a Roomba. I see a Sys Admin and want to build them an Iron Man suit.
– Deepak Giridharagopal, CTO, Puppet

Use automation to reduce risk

Consistency

When we automate, we can make sure we do something the same way every time and produce a consistent result.

Auditing and Compliance

We can design an automated execution that will ship logs that provide the context of the action for a detailed audit trail.

Change

• Enterprise environments are continually changing.
• When context changes, so does the procedure.
• You can update your docs all you want, but you can't make people read them before executing a procedure.
• When you update the procedure itself, you can make sure it’s executed properly.

Follow Info-Tech’s approach: Start small and snowball

• It’s difficult for I&O to get the staffing resources it needs for engineering work.
• Rather than trying to get buy-in for resources using a “top down” approach, Info-Tech recommends that I&O score some quick wins to build momentum.
• Show success while giving your team the opportunity to build their engineering chops.

Because the C-suite relies on upwards communication — often filtered and sanitized by the time it reaches them — executives don’t see the bottlenecks and broken processes that are stalling progress.
– Andi Mann

Info-Tech’s methodology employs a targeted approach

• You aren’t going to automate IT operations end-to-end overnight.
• In fact, such a large undertaking might be more effort than it’s worth.
• Info-Tech’s methodology employs a targeted approach to identify which candidates will score some quick wins.
• We’ll demonstrate success, gain momentum, and then iterate for continual improvement.

Invest in automation to reap long-term rewards

• All too often people think of automation like a vacuum cleaner you can buy once and then forget.
• The reality is you need to perform care and feeding for automation like for any other process or program.
• To reap the greatest rewards you must continually invest in automation – and invest wisely.

To get the full ROI on your automation, you need to treat it like an employee. When you hire an employee, you invest in that person. You spend time and resources training and nurturing new employees so they can reach their full potential. The investment in a new employee is no different than your investment in automation.– Edwards

Measure the success of your automation program

1 15 FTEs x 80k/yr.; 20% of time on MRW, reduced by 20%
2 15 FTEs x 80k/yr.; 30% project capacity, increased by 30%
3 25k/hr. of downtime.; 5 hours per year of downtime caused by errors

Automating failover for disaster recovery

CASE STUDY

Industry Financial Services
Source Interview

Challenge

An IT infrastructure manager had established DR failover procedures, but these required a lot of manual work to execute. His team lacked the expertise to build automation for the failover.

Solution

The manager hired consultants to build scripts that would execute portions of the failover and pause at certain points to report on outcomes and ask the human operator whether to proceed with the next step.

Results

The infrastructure team reduced their achievable RTOs as follows:
Tier 1: 2.5h → 0.5h
Tier 2: 4h → 1.5h
Tier 3: 8h → 2.5h
And now, anyone on the team could execute the entire failover!

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

“Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.”

Guided Implementation

“Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.”

Workshop

“We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.”

Consulting

“Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”

Diagnostics and consistent frameworks used throughout all four options

Reduce Manual Repetitive Work With IT Automation – project overview

Contents

Create a Data Management Roadmap

Ensure the right capabilities to support your data strategy.

EXECUTIVE BRIEF

Analyst Perspective

Establish a data management program to realize the data strategy vision and data-driven organization.

Data is one of the most valuable organizational assets, and data management is the foundation – made up of plans, programs, and practices – that delivers, secures, and enhances the value of those assets.

Digital transformation in how we do business and innovations like artificial intelligence and automation that deliver exciting experiences for our customers are all powered by readily available, trusted data. And there’s so much more of it.

A data management roadmap designed for where you are in your business journey and what’s important to you provides tangible answers to “Where do we start?” and “What do we do?”

This blueprint helps you build and enhance data management capabilities as well as identify the next steps for evaluating, strengthening, harmonizing, and optimizing these capabilities, aligned precisely with business objectives and data strategy.

Frame the problem

Executive Summary

Info-Tech Insight

Use value streams and business capabilities to develop a prioritized and practical data management plan that provides the highest business satisfaction in the shortest time.

Data Management Capabilities

Data is a business asset and needs to be treated like one

Data management is an enabler of the business and therefore needs to be driven by business goals and objectives. For data to be a strategic asset of the business, the business and IT processes that support its delivery and management must be mature and clearly executed.

Industry spotlight: Risk management in the financial services sector

Industry spotlight: Operational excellence in the public sector

Industry spotlight: Operational excellence and client intimacy in major league sports

Industry spotlight: Operational excellence and service delivery within manufacturing and supply chain services

Industry spotlight: Intelligent product innovation and strong product portfolios differentiate consumer retailers and CPGs

Changes in business and technology are changing how organizations use and manage data

To differentiate and remain competitive in today’s marketplace, organizations are becoming more data-driven

	Analytic Competitor “Given the unforgiving competitive landscape, organizations have to transform now, and correctly. Winning requires an outcome-focused analytics strategy.” (Ramya Srinivasan, Forbes, 2021)
Data and the use of data analytics has become a centerpiece to effective modern business. Top-performing organizations across a variety of industries have been cited as using analytics five times more than lower performers (MIT Sloan).

The strategic value of data

Power intelligent and transformative organizational performance through leveraging data.

Despite investments in data initiatives, organizations are carrying high levels of data debt

Data debt is the accumulated cost that is associated with the suboptimal governance of data assets in an enterprise, like technical debt.

(Source: Experian, 2020)

Build a right-sized roadmap

Formulate an actionable roadmap that is right-sized to deliver value in your organization.

• When building your data management roadmap, ensure you do so through an enterprise lens. Be cognizant of other initiatives that might be coming down the pipeline that may require you to align your data governance milestones accordingly.
• Apart from doing your planning with consideration for other big projects or launches that might be in-flight and require the time and attention of your data management partners, also be mindful of the more routine yet still demanding initiatives.
• When doing your roadmapping, consider factors like the organization’s fiscal cycle, typical or potential year-end demands, and monthly/quarterly reporting periods and audits. Initiatives such as these are likely to monopolize the time and focus of personnel key to delivering on your data management milestones

Insight summary

Overarching insight

Tactical insight

Data management is the program and environment we build once we have direction, i.e. a data strategy, and we have formed an ongoing channel with the guiding voice of the business via data governance. Without an ultimate goal in a strategy or the real requirements of the business, what are we building data systems and processes for? We are used to tech buzz words and placing our hope in promising innovations like artificial intelligence. There are no shortcuts, but there are basic proven actions we can take to meet the digital revolution head on and let our data boost our journey.

Measure the value of this blueprint

Info-Tech offers various levels of support to best suit your needs

Create a Data Management Roadmap project overview

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is 8 to 12 calls over the course of 4 to 6 months.

What is the current situation?

Info-Tech’s Data Management Framework

What Is Data Management?

“Data management is the development, execution, and supervision of plans, policies, programs and practices that deliver, control, protect and enhance the value of data and information assets throughout their lifecycles.” (DAMA International, 2017)

Adapted from DAMA-DMBOK and Advanced Knowledge Innovations Global Solutions

Info-Tech’s Approach

Info-Tech’s Data Management Framework is designed to show how an organization’s business model sits as the foundation of its data management practice. Drawing from the requirements of the underpinning model, a practice is designed and maintained through the creation and application of the enablers and dimensions of data management.

Build a data management practice that is centered on supporting the business and its use of key data assets

Business Resources Data subject areas provide high-level views of the data assets that are used in business processes and enable an organization to perform its business functions. Classified by specific subjects, these groups reflect data elements that, when used effectively, are able to support analytical and operational use cases of data. This layer is representative of the delivery of the data assets and the business’ consumption of the data. Data is an integral business asset that exists across all areas of an organization

For a data management practice to be effective it ultimately must show how its capabilities and operations better support the business in accessing and leveraging its key data assets.* *This project focuses on building capabilities for data management. Leverage our data quality management research to support you in assessing the performance of this model.

Information dimensions support the different types of data present within an organization’s environment

Information Dimensions Components at the Information Dimensions layer manage the different types of data and information present with an environment. At this layer, data is managed based on its type and how the business is looking to use and access the data. Custom capabilities are developed at this level to support: Structured data Semi-structured data Unstructured data The types, formats, and structure of the data are managed at this level using the data management enablers to support their successful execution and performance.

Build a data management practice with strong process capabilities

Use Info-Tech’s assessment framework to support your organization’s data management planning

Create a Data Management Roadmap

Phase 1

Build Business Context and Drivers for the Data Management Program

Step 1.1

Review the Data Management Framework

Activities

1.1.1 Walk through the main parts of the best-practice Data Management Framework

Data Management Capabilities

Build a Robust & Comprehensive Data Strategy

Info-Tech’s Data Governance Framework

Info-Tech’s Reporting and Analytics Framework

Formulating an enterprise reporting and analytics strategy requires the business vision and strategies to first be substantiated. Any optimization to the data warehouse, integration, and source layers is in turn driven by the enterprise reporting and analytics strategy. The current states of your integration and warehouse platforms determine what data can be used for BI and analytics.

Your enterprise reporting and analytics strategy is driven by your organization’s vision and corporate strategy.

Info-Tech’s Data Architecture Framework

Info-Tech’s methodology: Prioritize your core business objectives and identify your business driver. Learn how business drivers apply to specific tiers of Info-Tech’s five-tier data architecture model. Determine the appropriate tactical pattern that addresses your most important requirements.
Select the areas of the five-tier architecture to focus on. Measure your current state. Set the targets of your desired optimized state.
Roadmap your tactics. Manage and communicate change.

Info-Tech’s Enterprise Content Management Framework

Metadata management/Data cataloging

Info-Tech’s Data Integration Framework

On one hand… Data has massive potential to bring insight to an organization when combined and analyzed in creative ways. On the other hand… It is difficult to bring data together from different sources to generate insights and prevent stale data. How can these two ideas be reconciled? Answer: Info-Tech’s Data Integration Onion Framework summarizes an organization’s data environment at a conceptual level and is used to design a common data-centric integration environment.

Info-Tech’s Data Integration Onion Framework

Data-centric integration is the solution you need to bring data together to break down data silos.

Info-Tech’s Master Data Management Framework

Master data management (MDM) “entails control over Master Data values and identifiers that enable consistent use, across systems, of the most accurate and timely data about essential business entities” (DAMA, 2017). Fundamental objective of MDM: Enable the business to see one view of critical data elements across the organization.

Data architecture and modeling processes

Info-Tech Insight

The Conceptual data model adds relationships to your business data glossary terms and is the first step of the modeling journey.

Data operations

Objectives of Data Operations Management Implement and follow policies and procedures to manage data at each stage of its lifecycle. Maintain the technology supporting the flow and delivery of data (applications, databases, systems, etc.). Control the delivery of data within the system environment. Indicators of Successful Data Operations Management Effective delivery of data assets to end users. Successful maintenance and performance of the technical environment that collects, stores, delivers, and purges organizational data.

Step 1.2

Understand and Align to Business Drivers

Activities

1.2.1 Define your value streams

1.2.2 Identify your business capabilities

1.2.3 Categorize your organization’s key business capabilities

1.2.4 Develop a strategy map tied to data management

Build Business Context and Drivers

Identifying value streams

1.2.1 Define value streams

Input: Business strategy/goals, Financial statements, Info-Tech’s industry-specific business architecture

Output: List of organization-specific value streams, Detailed value stream definition(s)

Materials: Whiteboard/kanban board, Info-Tech’s Reference Architecture Template – contact your Account Representative for details, Other industry standard reference architecture models: BIZBOK, APQC, etc., Info-Tech’s Archimate models

Participants: Enterprise/Business Architect, Business Analysts, Business Unit Leads, CIO, Departmental Executive & Senior managers

Unify the organization’s perspective on how it creates value.

1. Write a short description of the value stream that includes a statement about the value provided and a clear start and end for the value stream. Validate the accuracy of the descriptions with your key stakeholders.
2. Consider:
   • How does the organization deliver those benefits?
   • How does the customer receive the benefits?
   • What is the scope of your value stream? What will trigger the stream to start and what will the final value be?
3. Avoid:
   • Don’t start with a blank page. Use Info-Tech’s business architecture models for sample value streams.

Contact your Account Representative for access to Info-Tech’s Reference Architecture Template

Define or validate the organization’s value streams

Example of value streams – Retail Banking

Example value stream descriptions for: Retail Banking

Value streams enable the organization to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech’s Industry Reference Architecture for Retail Banking.

Example of value streams – Higher Education

Example value stream descriptions for: Higher Education

Value streams enable the organization to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech’s Industry Reference Architecture for Higher Education.

Example of value streams – Local Government

Example value stream descriptions for: Local Government

Value streams enable the organization to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech’s Industry Reference Architecture for Local Government.

Example of value streams – Manufacturing

Example value stream descriptions for: Manufacturing

Value streams enable the organization to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech’s Industry Reference Architecture for Manufacturing.

Define the organization’s business capabilities in a business capability map

1.2.2 Identify your business capabilities

Input: List of confirmed value streams and their related business capabilities

Output: Business capability map with value streams for your organization

Materials: Your existing business capability map, Business Alignment worksheet provided in the Data Management Assessment and Planning Tool, Info-Tech’s Document Your Business Architecture blueprint

Participants: Key business stakeholders, Data stewards, Data custodians, Data leads and administrators

Confirm your organization's existing business capability map or initiate the formulation of a business capability map:

• If you have an existing business capability map, meet with the relevant business owners/stakeholders to confirm that the content is accurate and up to date. Confirm the value streams (how your organization creates and captures value) and their business capabilities reflect the organization’s current business environment.
• If you do not have an existing business capability map, complete this activity to initiate the formulation of a map (value streams and related business capabilities):
  1. Define the organization’s value streams. Meet with senior leadership and other key business stakeholders to define how your organization creates and captures value.
  2. Define the relevant business capabilities. Meet with senior leadership and other key business stakeholders to define the business capabilities.

Note: A business capability defines what a business does to enable value creation. Business capabilities are business terms defined using nouns such as “Marketing” or “Research and Development.” They represent stable business functions, are unique and independent of one another, and typically will have a defined business outcome.

1.2.3 Categorize your organization’s key capabilities

Input: Strategic insight from senior business stakeholders on the business capabilities that drive value for the organization

Output: Business capabilities categorized and prioritized (e.g. cost advantage creators, competitive advantage differentiators, high value/high risk) See next slide for an example

Materials: Your existing business capability map or the business capability map derived in Activity 1.2.2

Participants: Key business stakeholders, Data stewards, Data custodians, Data governance working group

Determine which capabilities are considered high priority in your organization.

1. Categorize or heatmap the organization’s key capabilities. Consult with senior and other key business stakeholders to categorize and prioritize the business’ capabilities. This will aid in ensuring your data governance future-state planning is aligned with the mandate of the business. One approach to prioritizing capabilities with business stakeholders is to examine them through the lens of cost advantage creators, competitive advantage differentiators, and/or by high value/high risk.
2. Identify cost advantage creators. Focus on capabilities that drive a cost advantage for your organization. Highlight these capabilities and prioritize programs that support them.
3. Identify competitive advantage differentiators. Focus on capabilities that give your organization an edge over rivals or other players in your industry.

This categorization/prioritization exercise helps highlight prime areas of opportunity for building use cases, determining prioritization, and the overall optimization of data and data governance.

For more information, refer to Info-Tech’s Document Your Business Architecture.

1.2.4 Develop a strategy map tied to data management

Input: Strategic objectives as outlined by the organization’s business strategy and confirmed by senior leaders

Output: A strategy map that maps your organizational strategic objectives to value streams, business capabilities, and ultimately data programs

Materials: Your existing business capability map or the one created in Activity 1.2.2, Business strategy (see next slide for an example)

Participants: Key business stakeholders, Data stewards, Data custodians, Data governance working group

Identify the strategic objectives for the business. Knowing the key strategic objectives will drive business–data governance alignment. It’s important to make sure the right strategic objectives of the organization have been identified and are well understood.

1. Meet with senior business leaders and other relevant stakeholders to help identify and document the key strategic objectives for the business.
2. Leverage their knowledge of the organization’s business strategy and strategic priorities to visually represent how these map to value streams, business capabilities, and ultimately data and data governance needs and initiatives. Tip: Your map is one way to visually communicate and link the business strategy to other levels of the organization.
3. Confirm the strategy mapping with other relevant stakeholders.

Step 1.3

Build High-Value Use Cases for Data Management

Activities

1.3.1 Build high-value use cases

Build Business Context and Drivers

1.3.1 Build high-value use cases

Input: Value streams and business capabilities as defined by business leaders, Business stakeholders’ subject area expertise, Data custodian systems, integration, and data knowledge

Output: Use cases that articulate data-related challenges, needs, or opportunities that are tied to defined business capabilities and hence, if addressed, will deliver measurable value to the organization

Materials: Your business capability map from Activity 1.2.2, Info-Tech’s Data Use Case Framework Template, Whiteboard or flip charts (or shared screen if working remotely), Markers/pens

Participants: Key business stakeholders, Data stewards and business SMEs, Data custodians, Data leads and administrators

This business needs gathering activity will highlight and create relevant use cases around data-related problems or opportunities that are clear and contained and, if addressed, will deliver value to the organization.

1. Bring together key business stakeholders (data owner, stewards, SMEs) from a particular line of business as well the relevant data custodian(s) to build cases for their units. Leverage the business capability map you created for facilitating this act.
2. Leverage Info-Tech’s Data Use Case Framework Template as seen on the next slide.
3. Have the stakeholders move through each breakout session outlined in the use case worksheet. Use flip charts or a whiteboard to brainstorm and document their thoughts.
4. Debrief and document results in the Data Use Case Framework Template.
5. Repeat this exercise with as many lines of the business as possible, leveraging your business capability map to guide your progress and align with business value.

Tip: Don’t conclude these use case discussions without substantiating what measures of success will be used to demonstrate the business value of the effort to produce the desired future state, as relevant to each particular use case.

Download Info-Tech’s Data Use Case Framework Template

The following is the list of use cases as articulated by key stakeholders at [Organization Name].

The stakeholders see these as areas that are relevant and highly valuable for delivering strategic value to [Organization Name].

Use Case 1: Customer/Student/Patient/Resident 360 View

Use Case 2: Project/Department Financial Performance

Use Case 3: Vendor Lifecycle Management

Use Case 4: Project Risk Management

Prioritization of use cases

Problem statement:

• We are not realizing our full growth potential because we do not have a unified 360 view of our customers/clients/[name of external stakeholder].
• This impacts: our cross-selling; upselling; talent acquisition and retention; quality of delivery; ability to identify and deliver the right products, markets, and services...

If we could solve this:

• We would be able to better prioritize and position ourselves to meet evolving customer needs.
• We would be able to optimize the use of our limited resources.

1. What is the number one risk you need to alleviate?
   • Loss of potential revenue, whether from existing or net new customers.
     • How?
       • By not maximizing opportunities with customers or even by losing customers; by not understanding or addressing their greatest needs
       • By not being able to win potential new customers because we don’t understand their needs
2. What is the number one opportunity you wish to see happen?
   • The ability to better understand and anticipate the needs of both existing and potential customers.
3. What is the number one pain point you have when working with data?
   • I can’t do my job with confidence because it’s not based on comprehensive, sound, reliable data. My group spends significant time reconciling data sets with little time left for data use and analysis.
4. What are your challenges in performing the activity today?
   • I cannot pull together customer data in a timely manner due to having a high level of dependence on specific individuals with institutional knowledge rather than having easy access to information.
   • It takes too much time and effort to pull together what we know about a customer.
   • The necessary data is not consolidated or readily/systematically available for consumption.
   • These challenges are heightened when dealing with customers across markets.

5. What does “amazing” look like if we solve this perfectly?
   • Employees have immediate, self-service access to necessary information, leading to better and more timely decisions. This results in stronger business and financial growth.
6. What other business unit activities/processes will be impacted/improved if we solve this?
   • Marketing/bid and proposal, staffing, procurement, and contracting strategy
7. What compliance/regulatory/policy concerns do we need to consider in any solution?
   • PII, GDPR, HIPAA, CCPA, etc.
8. What measures of success/change should we use to prove the value of the effort (KPIs/ROI)?
   • Win rate, number of services per customer, gross profit, customer retention, customer satisfaction scores, brand awareness, and net promoter score
9. What are the steps in the process/activity today?
   • Manual aggregation (i.e. pull data from systems into Excel), reliance on unwritten knowledge, seeking IT support, canned reports

10. What are the applications/systems used at each step?
    • Salesforce CRM, Excel, personal MS Access databases, SharePoint
11. What data elements (domains) are involved, created, used, or transformed at each step?
    • Bid and proposal information, customer satisfaction, forecast data, list of products, corporate entity hierarchy, vendor information, key staffing, recent and relevant news, and competitor intelligence

Use case worksheet

Objective: This business needs gathering activity will help you highlight and create relevant use cases around data-related problems or opportunities. They should be clear and contained and, if addressed, will deliver value to the organization.

Use case worksheet (cont’d.)

Objective: This business needs gathering activity will help you highlight and create relevant use cases around data-related problems or opportunities. They should be clear and contained and, if addressed, will deliver value to the organization.

Use case worksheet (cont’d.)

Objective: This business needs gathering activity will help you highlight and create relevant use cases around data-related problems or opportunities. They should be clear and contained and, if addressed, will deliver value to the organization.

Use case worksheet (cont’d.)

Objective: This business needs gathering activity will help you highlight and create relevant use cases around data-related problems or opportunities. They should be clear and contained and, if addressed, will deliver value to the organization.

Use case worksheet (cont’d.)

Objective: This business needs gathering activity will help you highlight and create relevant use cases around data-related problems or opportunities. They should be clear and contained and, if addressed, will deliver value to the organization.

Step 1.4

Create a Vision and Guiding Principles for Data Management

Activities

1.4.1 Craft a vision

1.4.2 Create guiding principles

Build Business Context and Drivers

1.4.1 Craft a vision

Input: Organizational vision and mission statements, Stakeholder survey results and elicitation findings, Use cases, Business and data capability map

Output: Vision and mission statements

Materials: Markers and pens, Whiteboard, Online whiteboard, Vision samples and templates

Participants: Key business stakeholders, Data managers, Data owners, Business leads and SMEs, Project team, Project sponsor

Complete the vision statement to set the direction, the “why,” for the changes we’re making. The vision is a reference point that should galvanize everyone in the organization and set guardrails for technical and process decisions to follow.

1. Bring together key business stakeholders (content owners, SMEs, and relevant IT custodians) to craft a data management vision statement.
2. Start by brainstorming keywords, such as customer-focused, empower the business, service excellence, findable and manageable, protected, accessible, paperless.
3. Highlight the keywords that resonate most with the group. Refer to example vision statements for ideas.

Create compelling vision and mission statements for the organization’s future data management practice

Data Management Vision and Mission Statements: Draft

Information management framework

The information management framework is a way to organize all the ECM program’s guidelines and artifacts

The vision is a statement about the organization’s goals and provides a basis to guide decisions and rally employees toward a shared goal. The principles or themes communicate the organization’s priorities for its information management program. Policies are a set of official guidelines that determine a course of action. For example: Company is committed to safety for its employees. Procedures are a set of actions for doing something. For example: Company employees will wear protective gear while on the production floor.

Craft your vision

Use the insights you gathered from users and stakeholders to develop a vision statement The beginning of a data management practice is a clear set of goals and key performance indicators (KPIs). A good set of goals takes time and input from senior leadership and stakeholders. The data management program lead is selling a compelling vision of what is possible. The vision also helps set the scope and expectations about what the data management program lead is and is not doing. Be realistic about what you can do and how long it will take to see a difference. Example vision statements: The organization is dedicated to creating an enabling structure that helps the organization get the right information to the right people at the right time. The organization is dedicated to creating a program that recognizes data as an asset, establishing a data-centric culture, and ensuring data quality and accessibility to achieve service excellence.

The vision should be short, memorable, inspirational and draw a clear picture of what that future-state data management experience looks like. Is it modern and high end, with digital self-service? Is it a trusted and transparent steward of customer assets?

1.4.2 Create guiding principles

Input: Sample data management guiding principles, Stakeholder survey results and elicitation findings, Use cases, Business and data capability map

Output: Data management guiding principles

Materials: Markers and pens, Whiteboard, Online whiteboard, Guiding principles samples and templates

Participants: Key business stakeholders, Data managers, Data owners, Business leads and SMEs, Project team, Project sponsor

Draft a set of guiding principles that express your program’s values as a framework for decisions and actions and keep the data strategy alive.

1. Bring together key business stakeholders (data owners, SMEs, and relevant IT custodians) to craft a set of data management guiding principles.
2. Refer to industry sample guiding principles for data management.
3. Discuss what’s important to stakeholders and owners, e.g. security, transparency, integrity. Good guiding principles address real challenges.
4. A helpful tip: Craft principles as “We will…” statements for the problems you’ve identified.

Create a Data Management Roadmap

Phase 2

Assess Data Management and Build Your Roadmap

Step 2.1

Assess Your Data Management Capabilities

Activities

2.1.1 Define current state of data management capabilities

2.1.2 Set target state and identify gaps

Assess Data Management and Build Your Roadmap

2.1.1 Define current state

Input: Stakeholder survey results and elicitation findings, Use cases, Business and data management capability map

Output: Current-state data management capabilities

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Assign a maturity level value from 1 to 5 for each question in the assessment tool, organized into capabilities, e.g. Data Governance, Data Quality, Risk.

1. Bring together key business stakeholders (data owners, SMEs, and relevant IT custodians) to assign current-state maturity levels in each question of the worksheet.
2. Remember that there is more distance between levels 4 and 5 than there is between 1 and 2 – the distance between levels is not even throughout.
3. To help assign values, think of the higher levels as representing cross-enterprise standardization, monitored for continuous improvement, formalized and standardized, while the lower levels mean applied within individual units, not formalized or tracked for performance.
4. In tab 4, “Current State Assessment,” populate a current-state value for each item in the Data Management Capabilities worksheet.
5. Once you’ve entered values in tab 4, a visual and summary report of the results will be generated on tab 5, “Current State Results.”

2.1.2 Set target state and identify gaps

Input: Stakeholder survey results and elicitation findings, Use cases, Business and data management capability map to identify priorities

Output: Target-state data management capabilities, Gaps identification and analysis

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Assign a maturity level value from 1 to 5 for each question in the assessment tool, organized into capabilities, e.g., Data Governance, Data Quality, Risk.

1. Bring together key business stakeholders (data owners, SMEs, and relevant IT custodians) to assign target-state maturity levels in each question of the worksheet.
2. Remember that there is more distance between levels 4 and 5 than there is between 1 and 2 – the distance between levels is not even throughout.
3. To help assign values, think of the higher levels as representing cross-enterprise standardization, monitored for continuous improvement, formalized and standardized, while the lower levels mean applied within individual units, not formalized or tracked for performance.
4. In tab 6, “Target State & Gap Analysis,” enter maturity values in each item of the Capabilities worksheet in the Target State column.
5. Once you’ve assigned both target-state and current-state values, the tool will generate a gap analysis chart on tab 7, “Gap Analysis Results,” where you can start to decide first- and second-line priorities.

Step 2.2

Build Your Data Management Roadmap

Activities

2.2.1 Describe gaps

2.2.2 Define gap initiatives

2.2.2 Build a data management roadmap

Assess Data Management and Build Your Roadmap

2.2.1 Describe gaps

Input: Target-state maturity level

Output: Detail and context about gaps to lead planners to specific initiatives

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Based on the gaps result, describe the nature of the gap, which will lead to specific initiatives for the data management plan:

1. In tab 6, “Target State & Gap Analysis,” the same tab where you entered your target-state maturity level, enter additional context about the nature and extent of each gap in the Gap Description column.
2. Based on the best-practices framework we walked through in Phase 1, note the specific areas that are not fully developed in your organization; for example, we don’t have a model of our environment and its integrations, or there isn’t an established data quality practice with proactive monitoring and intervention.

2.2.2 Define gap initiatives

Input: Gaps analysis, Gaps descriptions

Output: Data management initiatives

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Based on the gap analysis, start to define the data management initiatives that will close the gaps and help the organization achieve its target state.

1. In tab 6, “Target State & Gap Analysis,” the same tab where you entered your target-state maturity level, note in the Gap Initiative column what actions you can take to address the gap for each item. For example, if we found through diagnostics and use cases that users didn’t understand the meaning of their data or reports, an initiative might be, “Build a standard enterprise business data catalog.”
2. It’s an opportunity to brainstorm, to be creative, and think about possibilities. We’ll use the roadmap step to select initiatives from this list.
3. There are things we can do right away to make a difference. Acknowledge the resources, talent, and leadership momentum you already have in your organization and leverage those to find activities that will work in your culture. For example, one company held a successful Data Day to socialize the roadmap and engage users.

2.2.3 Build a data management roadmap

Input: Gap initiatives, Target state and current-state assessment

Output: Data management initiatives and roadmap

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Start to list tangible actions you will take to address gaps and achieve data objectives and business goals along with timelines and responsibility:

1. With an understanding of your priority areas and specific gaps, and referring back to your use cases, draw up specific initiatives that you can track, measure, and align with your original goals.
2. For example, in data governance, initiatives might include:
   • Assign data owners and stewards for all data assets.
   • Consolidate disparate business data catalogs.
   • Create a data governance charter or terms of reference.
3. Alongside the initiatives, fill in other detail, especially who is responsible and timing (start and end dates). Assigning responsibility and some time markers will help to keep momentum alive and make the work projects real.

Step 2.3

Organize Business Data Domains

Activities

2.3.1 Define business data domains and assign owners

Assess Data Management and Build Your Roadmap

2.3.1 Define business data domains

Input: Target-state maturity level

Output: Detail and context about gaps to lead planners to specific initiatives

Materials: Data Management Assessment and Planning Tool

Participants: Key business stakeholders, Business leads and SMEs, Project team, Project sponsor, Data leads, Data custodians

Identify the key data domains for each line of business, where the data resides, and the main contact or owner.

1. We have an understanding of what the business wants to achieve, e.g. build customer loyalty or comply with privacy laws. But where is the data that can help us achieve that? What systems is that data moving and living in and who, if anyone, owns it?
2. Define the main business data domains apart from what system it may be spread over. Use the worksheet on the next slide as an example.
3. Examples of business data domains: Customer, Product, Vendor.
4. Each domain should have owners and associated business processes. Assign data domain owners, application owners, and business process owners.

Related Info-Tech Research

	Build a Robust and Comprehensive Data Strategy Key to building and fostering a data-driven culture.
	Understand the Data and Analytics Landscape Optimize your data and analytics environment.
	Build a Data Pipeline for Reporting and Analytics Data architecture best practices to prepare data for reporting and analytics.

Research Contributors

Bibliography

AIIM, “What is Enterprise Content Management (ECM)?” Intelligent Information Management Glossary, AIIM, 2021. Web.

BABOK V3: A Guide to Business Analysis Body of Knowledge. IIBA, 2014. Web.

Barton, Dominic, and David Court. "Three Keys To Building a Data-Driven Strategy." McKinsey and Company, 1 Mar. 2013. Web.

Boston University Libraries. "Data Life Cycle » Research Data Management | Boston University." Research Data Management RSS. Boston University, n.d. Accessed Oct. 2015.

Chang, Jenny. “97 Supply Chain Statistics You Must Know: 2020 / 2021 Market Share Analysis & Data.” FinancesOnline, 2021. Web.

COBIT 5: Enabling Information. ISACA, 2013. Web.

CSC (Computer Sciences Corporation), Big Data Infographic, 2012. Web.

DAMA International. DAMA-DMBOK Guide. 1st ed., Technics Publications, 2009. Digital.

DAMA International. “DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK2 Guide).” 2nd ed., 2017. Accessed June 2017.

Davenport, Thomas H. "Analytics in Sports: The New Science of Winning." International Institute for Analytics, 2014. Web.

Department of Homeland Security. Enterprise Data Management Policy. Department of Homeland Security, 25 Aug. 2014. Web.

Enterprise Data Management Data Governance Plan. US Federal Student Aid, Feb. 2007. Accessed Oct. 2015.

Experian. “10 signs you are sitting on a pile of data debt.” Experian, 2020. Accessed 25 June 2021.

Fasulo, Phoebe. “6 Data Management Trends in Financial Services.” SecurityScorecard, 3 June 2021. Web.

Georgia DCH Medicaid Enterprise – Data Management Strategy. Georgia Department of Community Health, Feb. 2015. Accessed Oct. 2015.

Hadavi, Cyrus. “Use Exponential Growth of Data to Improve Supply Chain Operations.” Forbes, 5 Oct. 2021. Web.

Harbert, Tam. “Tapping the power of unstructured data.” MIT Sloan, 1 Feb. 2021. Web.

Hoberman, Steve, and George McGeachie. Data Modeling Made Simple with PowerDesigner. Technics Pub, 2011. Print.

“Information Management Strategy.” Information Management – Alberta. Service Alberta, Nov.-Dec. 2013. Web.

Jackson, Brian, et al. “2021 Tech Trends.” Info-Tech Research Group, 2021. Web.

Jarvis, David, et al. “The hyperquantified athlete: Technology, measurement, and the business of sports.” Deloitte Insights, 7 Dec. 2020. Web.

Bibliography

Johnson, Bruce. “Leveraging Subject Area Models.” EIMInsight Magazine, vol. 3, no. 4, April 2009. Accessed Sept. 2015.

Lewis, Larry. "How to Use Big Data to Improve Supply Chain Visibility." Talking Logistics, 14 Sep. 2014. Web.

McAfee, Andrew, and Erik Brynjolfsson. “Big Data: The Management Revolution,” Harvard Business Review, vol. 90, no. 10, 2012, pp. 60-68.

Meyer-Cuno, Doug. “Is A Vision Statement Important?” Forbes, 24 Feb. 2021. Web.

MIT. “Big Data: The Management Revolution.” MIT Center for Digital Business, 29 May 2014. Accessed April 2014.

"Open Framework, Information Management Strategy & Collaborative Governance.” MIKE2 Methodology RSS, n.d. Accessed Aug. 2015.

PwC. “Asset Management 2020: A Brave New World.” PwC, 2014. Accessed April 2014.

Riley, Jenn. Understanding Metadata: What is Metadata, and What is it For: A Primer. NISO, 1 Jan. 2017. Web.

Russom, Philip. "TDWI Best Practices Report: Managing Big Data." TDWI, 2013. Accessed Oct. 2015.

Schneider, Joan, and Julie Hall. “Why Most Product Launches Fail.” Harvard Business Review, April 2011. Web.

Sheridan, Kelly. "2015 Trends: The Growth of Information Governance | Insurance & Technology." InformationWeek. UBM Tech, 10 Dec. 2014. Accessed Nov. 2015.

"Sports Business Analytics and Tickets: Case Studies from the Pros." SloanSportsConference. Live Analytics – Ticketmaster, Mar. 2013. Accessed Aug. 2015.

Srinivasan, Ramya. “Three Analytics Breakthroughs That Will Define Business in 2021.” Forbes, 4 May 2021. Web.

Statista. “Amount of data created, consumed, and stored 2010-2020.” Statista, June 2021. Web.

“Understanding the future of operations: Accenture Global Operations Megatrends research.” Accenture Consulting, 2015. Web.

Vardhan, Harsh. “Why So Many Product Ideas Fail?” Medium, 26, Sept. 2020. Web.

Build an ITSM Tool Implementation Plan

Plan ahead with a step-by-step approach to ensure the tool delivers business value.

EXECUTIVE BRIEF

Analyst perspective

Take control of the wheel or you might end up in a ditch.

An ITSM tool implementation is a complex project with direct impact on IT’s ability to support the business. With that level of risk, you need to take control early on.

Yes, your vendor will support or execute the technical implementation, but they depend on you to tell them how to configure ITSM parameters and workflows that affect user interface, the ability to manage incidents, and governance over assets and IT changes.

If you leave the configuration completely to the vendor, at best you might get the same setup as in your old tool (and not realize the benefits that leadership is expecting). At worst you end up with default values that don’t fit your process needs, i.e., confusion and not realizing expected benefits.

A successful implementation requires early planning from a wide range of resources including ITSM tool experts (supported by the vendor), process experts, and a project manager to methodically step through the hundreds of parameters you will need to define before implementation.

Frank Trovato
Research Director, Infrastructure and Operations
Info-Tech Research Group

Executive Summary

Info-Tech Insight

As with any large project, a key step is tackling it one bite at a time – but also understanding the size of the whole meal. This is where organizations often fail with ITSM implementations: not understanding upfront the volume of work required for a successful implementation.

Your Challenge

Organizations implementing a new ITSM tool often face these pitfalls:

• Selecting the Wrong Resources: You need ITSM technology and process experts, because this is not just a technology project but also a process improvement opportunity. You will need to configure ITSM parameters and workflows in the new tool – which directly affects processes. Take advantage of that opportunity to fix pain points. For example, if your existing ticket categories are not effective, implement a better categorization scheme rather than just configure the same old, ineffective scheme.
• Over-Reliance on the Vendor to Optimize Your Tool: Yes, the vendor will typically install and set up the tool but they will not fix your processes for you. On installation day, if you are not prepared with the categories, ticket templates, and so on that you wish to configure, your vendor will just go with the default or migrate your old parameters from your old ITSM tool.
• Not Preparing for Data Migration: Data migration is complex. You need to determine what data to migrate, if any, and how that data will be mapped to the new environment. That takes planning and must be defined well before the vendor is ready to implement your tool.
• Insufficient IT and End-User Training: A link to the ITSM tool manual is not enough. Staff and users need training on how your processes will be executed in the new tool.

A survey of implementation challenges for ServiceNow’s customers

26% Resistance to change

43% Lacked a clear roadmap

38% Planning for resources

Source: Acorio, 2019

Info-Tech’s approach

Divide the implementation project into controllable phases for an effective implementation.

STOP: Use this blueprint after you have selected an ITSM solution

Leverage our SoftwareReviews service and related blueprints to assist with ITSM tool selection, and then use this blueprint to plan the implementation.

Info-Tech’s methodology to build an ITSM Tool Implementation Plan

Insight summary

Blueprint deliverables

This blueprint includes tools and templates to help you accomplish your goals:

ITSM Tool Implementation Checklist Identify the most common decisions you will need to make and prepare for your implementation project.	ITSM Tool Project Charter Template Review and edit the template to suit your project requirements
	ITSM Tool Deployment Plan Template Prioritize and prepare tool rollout plan
	ITSM Tool Training Schedule Use the checklist to create your new tool training roadmap

Blueprint benefits

Measured value from using this blueprint

Use this guide as an example to calculate your total cost savings from the ITSM tool implementation project.

Info-Tech offers various levels of support to best suit your needs

Diagnostics and consistent frameworks used throughout all four options

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization. A typical GI is between 6 to 8 calls over the course of 3 to 6 months.

Phase 1

Identify Stakeholders, Scope, and Preliminary Timeline

This phase will walk you through the following steps:

1. Define scope
2. Define roles and responsibilities
3. Identify preliminary timeline

Step 1.1

Define scope

Activities

This step will walk you through the following activities:

• Define the scope of the implementation project
• Establish the future processes and functionalities the tool will support

This step involves the following participants:

• CIO
• IT Director/Manager
• Service Manager
• Project Manager and the project team

Outcomes of this step

• Specifying the implementation project
• Identifying the business units that are needed to support the project
• Defining the ongoing and future service management processes the tool will support

1.1.1 Use the Project Charter Template to capture scope, stakeholders, and timeline as outlined in Phase 1

Follow the instructions in Phase 1 (step 1.1, 1.2, and 1.3) to gather information needed to create a project charter to define project parameters.

Specific subsections are listed below and described in more detail in the remainder of this phase.

1. Project Overview: Includes deliverables, scope, milestones, and success metrics.
2. Governance and Management: Includes roles, responsibilities, and resource requirements.
3. Project Risks, Assumptions, and Constraints: Includes risks and mitigation strategies as well as any assumptions and constraints.
4. Project Sign-Off: Includes IT and executive sign-off (if required).

Download the ITSM Tool Implementation Project Charter Template

1.1.2 Leverage the Implementation Checklist to guide your preparation

The checklist tabs align to each phase of this blueprint.

• Phase 1 (Tab 1) – Identify Stakeholders, Scope, and Preliminary Timeline
• Phase 2 (Tab 2) – Prepare to Implement Incident Management and Service Request Modules
• Phase 3 (Tabs 3+4) – Prepare to Implement Additional ITSM Modules (e.g. Change Management)
• Phase 4 (deployment section in each tab) – Create a Deployment Plan (Communication, Training, Rollout)

Download the ITSM Tool Implementation Checklist

1.1.3 Review goals that drove the ITSM tool purchase

Identify the triggers for the selection and implementation of your new ITSM tool.

Whether this is your first ITSM tool or a replacement for your old tool, the project was likely triggered by pain points that must be addressed by the new tool to improve your service desk. Having a clear understanding of these pain points throughout the implementation of your new tool will help to prevent them from reoccurring.

Common ITSM pain points include:

1. Poor communication with end users on ticket status.
2. Lack of SLA automation to escalate issues to the appropriate channels.
3. Poor self-service options for end users to perform simple requests on their own.
4. Undeveloped knowledgebase for users to find answers to common issues.
5. Lack of reporting or mistrust in reporting data.
6. Lack of automation, including ticket templates.
7. Overcomplicated ticket categories resulting in categories being misused.
8. Overconfiguration prevents future upgrades.
9. Lack of integration with other tools.

If you haven't already selected an ITSM tool, leverage the IT Service Management Selection Guide to select the right tool.

Download the IT Service Management Selection Guide

1.1.4 Plan to interview staff to support organizational change management

Identify challenges with the existing tool and processes as well as potential objections to the new tool.

Incorporate this feedback in the implementation to drive buy-in and a successful rollout.

Implementing a new ITSM tool will force changes in how IT staff do their work:

• At a minimum, it means learning a new interface.
• It could also mean leveraging features that improve IT operations but could change the process or tasks for the staff.
• Their input on the current tool and process challenges can be critical for the project.
• Solving at least some of their challenges can help bring them onboard to use this tool properly and follow associated process changes.

Info-Tech Insight

Keep management in the loop through every stage of the implementation process. They are the ones who are paying for the software, so they need to be informed throughout implementation and feel that their needs and feedback are being heard to prevent pushback further into the implementation.

1.1.5 Identify the modules and features you will plan to implement

Consider these factors when deciding what modules and features you want to implement:

• Specific ITSM modules based on the recommended order and any unique business requirements
• Key features that drove the tool purchase and address key issues
• High-level process changes needed to address challenges and realize expected benefits from the new ITSM tool (e.g. if a key goal was automated ticket routing based on categories, then the project needs to include developing a good categorization scheme)

Recommended order for implementation:

1. Incident Management and Service Request

This is the core of service management and typically has the highest impact on the organization. Include knowledgebase development as part of this implementation.

2. Change Management

A foundational component of service management, it allows organizations to minimize disruptions to IT services when making changes to services and critical systems.

3. Asset Management

A foundational component of service management, it allows organizations to track their assets’ locations, how they are used, and when changes are made to them.

1.1.6 Determine if data migration is required

If you are switching from a previous ITSM tool, carefully weigh the pros and cons as well as the necessity of migrating historical transactional data before deciding to import it into the new tool.

Importing your old transactional data will allow you to track metrics over time, which can be valuable for data analysis and reporting purposes.

However, ask yourself what the true value of your data is before you import it.

You will not get value out of migrating the old data if:

• You have incomplete or inaccurate data (a high percentage of incidents did not have tickets created in the old system).
• The categorization of your old tickets was not useful or was used inconsistently.
• You plan on changing the ticket categorization in the new system.

“Don’t debate whether you can import your old data until you’ve made sure that you should.”

– Barry Cousins, Practice Lead at Info-Tech Research Group

Info-Tech Insight

If you decide to migrate your data, keep in mind that it can be a complex process and proper time should be budgeted for planning, structuring the data, and importing and testing it.

Step 1.2

Define roles and responsibilities

Activities

This step involves the following participants:

• CIO
• IT Director/Manager
• Service Manager
• Project Manager and the project team

Outcomes of this step

• Decision on whether to hire professional services for the implementation
• Clearly defined roles and responsibilities for the project

1.2.1 Identify key internal roles and responsibilities

Review the tasks outlined in the Implementation Checklist to help you identify appropriate roles and specific staff that will be needed to execute this project.

RACI = Responsible, Accountable, Consulted, and Informed

Assign individuals to roles through each step of the implementation project in the governance and management chart in the Project Charter Template.

Download the Project Charter Template

1.2.2 Key external roles and responsibilities

Determine whether you will engage professional services for the implementation.

Step 1.3

Identify preliminary timeline

Activities

This step involves the following participants:

• CIO
• IT Director/Manager
• Service Manager
• Project Manager and the project team

Outcomes of this step

• Specifying the target dates for the implementation project

1.3.1 Identify preliminary internal target dates

Identify high-level start and end dates based on the following:

• Existing process maturity
• Process changes required (to address process issues or to realize targeted benefits from the new tool)
• Data migration requirements (if any)
• Information to prepare for the implementation (review the Checklist Tool)
• Vendor availability to support implementation
• Executive mandates that have established specific milestone dates

Create an initial project schedule:

• Review the remaining phases of this blueprint for more details on the implementation planning steps.
• Review and update the Checklist Tool to suit your implementation goals and requirements.
• Assign task owners and target dates in the Checklist Tool.

Note: This is a preliminary schedule. Monitor progress as well as requirement changes, and adjust the scope or schedule as needed.

Update the columns in the Checklist Tool to plan and keep track of your implementation project.

1.3.2 Identify target dates for vendor involvement

Plan when you'll be ready for the vendor and identify the key points for when the vendor will come in.

Are dates already scheduled for tool installation/configuration/customization?

If yes:

• Clarify vendor expectations for those target dates (i.e. what do you have to have prepared in advance?).
• Determine options to adjust dates if needed.

If no:

• Defer scheduling until you have reviewed and updated the Implementation Checklist. The checklist will help you determine your readiness for vendor involvement.

Consider if the vendor will implement the ITSM tool in one go or if they will help setup the tool in stages. Keep in mind that ITSM implementation projects typically take anywhere from 9 weeks to 16 months and plan accordingly depending on the maturity of your processes and the modules and features you plan to implement.

Use your internal target dates to estimate when you'll be ready for the vendor to set up the tool and implement the setting that you've defined.

Phase 2

Prepare to Implement Incident Management and Service Request Modules

This phase will walk you through the following steps:

• Review your existing solution and challenges
• Plan ticket management and workflow implementation
• Plan data migration, knowledgebase setup, and integrations
• Plan the module rollout

Additional Info-Tech Research

The Implementation Checklist Tool summarizes what you need to prepare for the implementation. If you need more assistance with developing the underlying ITSM processes, use the tools, templates, and guidance in these blueprints.

Standardize the Service Desk

Build core elements of service desk operations, including incident management and service request workflows, ticket categorization schemes, and ticket prioritization rules.

Optimize the Service Desk With a Shift-Left Strategy

Implement tools such as an improved knowledgebase and self-service portal to enable lower tier support staff and end users to resolve incidents or fulfill service requests.

Incident and Problem Management

Develop a critical incident management workflow and create standard operating procedures for problem management.

Step 2.1

Review your existing solution and challenges

Activities

This step involves the following participants:

1. Service Manager and Service Desk Team
2. Project Manager and Core Project Team
3. Subject Matter Experts and Tool Administrator, if applicable

2.1.1 Configure your tool, don’t customize it

Your tool may require at least some basic configurations to align with your processes, but in most cases customization of the tool is not recommended.

Case Study

Consider the consequences of over-customizing your solution.

INDUSTRY: Education

SOURCE: IT Director

2.1.2 Review your existing process to identify opportunities for improvement

Documenting your existing processes is an effective method for also reviewing those processes and identifying inefficiencies. Take advantage of this project to fix your process issues.

1. Document your existing workflows for incident management and service requests.
2. Review your workflows to identify opportunities to optimize through process refinement (e.g. clarifying escalation guidelines) or by leveraging features in your new ITSM tool (e.g. improved workflow automation).
3. Similarly, review the challenges identified through stakeholder interviews: is there an opportunity address those challenges through process changes or leveraging your new ITSM tool?
4. Address those challenge and issues as you execute the tasks outlined in the Implementation Checklist Tool. For example, if inconsistent ticket routing was identified as a challenge due to a vague categorization scheme, that’s a driver to review and update your scheme rather than just carry forward your existing scheme.

Regardless of your existing ITSM maturity, this is an opportunity to review and optimize existing processes. Even the most-mature organizations can typically find an area to improve.

Case Study

Reviewing and defining processes before the implementation can be a project in itself.

INDUSTRY: Defense

SOURCE: Anonymous

Step 2.2

Plan ticket management and workflow implementation

Activities

This step involves the following participants:

1. Service Manager and Service Desk Team
2. Project Manager and Core Project Team
3. Subject Matter Experts and Tool Administrator, if applicable

Outcomes of this step

Tool is designed and configured to support service desk processes and organization needs.

Checklist overview

The ITSM Tool Implementation Checklist will help you estimate resources required to support demand, based on your ticket volume.

TAB 2	TAB 3	TAB 4
Incident and Service Modules Checklist	Change Management Modules	Asset Management Modules

How to follow this section:

The following slides contain a table that explains why each task in the module matters and what needs to be considered. Complete the checklist modules referring to this section.

2.2.1 Define ticket classification values

Ticket classification improves reporting, workflow automation, and problem identification.

Review your existing ticket classification values to identify what to carry forward, drop, or change. For example, if your categorization scheme has become too complex, this is your opportunity to fix it; don’t perpetuate ineffective classification in the new tool.

2.2.2 Define ticket templates for common incident types and service requests

Ticket templates are the backbone of automation. A common complaint is that tickets take too much time. However, a little planning can reduce the time it takes to create a ticket to less than a minute.

2.2.3 Plan your ticket intake channels

Consider possible ticket intake channels and evaluate their relevance to your organization.

2.2.4 Design a self-service portal

Map your processes to the tool by defining your ticket input, categories, escalations, and workflows.

Don’t forget about the client-facing side of the solution. It is important to build a self-serve portal that has an easy-to-use interface where the user can easily find the category for the help they’re looking for. It is also necessary to educate the users on where to find the portal or how to access it.

2.2.5 Plan your knowledgebase (KB) implementation in the new tool

Evaluate how onerous KB migration will be for you. Is this an opportunity to improve how the KB is organized?

2.2.6 Design your ticket status notification processes and templates

2.2.7 Identify required user accounts, access levels, and skills/service groups

2.2.8 Review and update your workflows and escalation rules

2.2.9 Identify desired reporting and relevant metrics to track

Documentation of key metrics of service desk performance and end-user satisfaction that you wish to improve through the new solution is key to evaluate the success of your implementation.

Step 2.3

Plan data migration and integrations

Activities

This step involves the following participants:

1. Service Manager and Service Desk Team
2. Project Manager and Core Project Team
3. Subject Matter Experts and Tool Administrator, if applicable

Outcomes of this step

• Decisions made around data migration, integrations, automation, and reporting.
• ITSM Tool Implementation Checklist

2.3.1 Create a data migration and archiving plan

2.3.2 Identify and plan required integrations

Consider and plan for any necessary integrations with other systems.

A major component of the implementation that should be carefully considered throughout is if and how to integrate your ITSM tool with other applications in the environment.

Step 2.4

Plan the module rollout

Activities

This step involves the following participants:

1. Service Manager and Service Desk Team
2. Project Manager and Core Project Team
3. Subject Matter Experts and Tool Administrator, if applicable

Outcomes of this step

Identify and plan for additional modules and features to be implemented

2.4.1 Repeat the methodology for additional ITSM modules, using the Checklists as a guide

The preparation completed in Phase 1 and 2 to this point provide a foundation for additional ITSM modules.

This blueprint starts with the incident management and service request modules as those are typically implemented first since they are the most impactful to day-to-day IT service management.

In addition, the methodology outlined in Phase 1 and 2 to this point provides a model to follow for additional ITSM modules:

• If you did not already account for additional modules in Phase 1, then repeat the steps in Phase 1 to define scope, stakeholders, and timeline.
• The Implementation Checklist Tool provides tabs for Change Management and Asset Management to outline the specific details for those topic areas, but they follow the same high-level steps as Phase 2 (e.g. review existing processes, design relevant workflows).
• If you are planning to implement other modules (e.g. Problem Management), create additional tabs in the Implementation Checklist Tool as needed, using the existing tabs as a base.

2.4.2 Leverage these blueprints to help you implement change and asset management modules

The Implementation Checklist Tool summarizes what you need to prepare for the implementation. If you need more assistance with developing the underlying ITSM processes, use the tools, templates, and guidance in the blueprints below.

Optimize IT Change Management

Define change management workflows, key roles, and supporting elements such as request-for-change forms based on best practices.

Implement Hardware Asset Management

Create an SOP and associated process workflows to streamline and standardize hardware asset management.

Implement Software Asset Management

Build on a strong hardware asset management program to also properly track and manage software assets. This includes managing software licensing, finding opportunities to reduce costs, and improving your software audit readiness.

Phase 3

Create a Deployment Plan (Communication, Training, Rollout)

This phase will walk you through the following steps:

1. Create a communication plan (for IT, users, and business leaders)
2. Create a training plan
3. Plan how you will deploy, monitor, and maintain the solution

ITSM Tool Training Schedule		ITSM Tool Deployment Plan Template
Use the template to document and plan the communications and training needs prior to deployment of the new tool.		Use the deployment plan template to document the strategy and decisions made for making the transition to the new ITSM tool.
	Download the ITSM Tool Training Schedule		Download the ITSM Tool Deployment Plan Template

Step 3.1

Create a communication plan (for IT, users, and business leaders)

Activities

This step involves the following participants:

1. CIO/IT Director
2. IT Manager
3. Service Manager

Outcomes of this step

Plan for communicating the change with business executives, service desk agents, and end users.

3.1.1 Ensure there is strong communication from management throughout the implementation and deployment

A common contributing factor for unsuccessful implementation is a lack of communication around training, transitioning, and deploying the new tool.

Common Pitfall:

Organizational communication and change management should have been ongoing and tightly monitored throughout the project. However, cut-over is a time in which critical communication regarding deployment and proper user training can be derailed when last-minute preparations take priority. Not only will general user frustration increase, but unintended process workarounds will emerge, eroding system effectiveness.

Mitigating Actions:

Deliver training for end users that will be engaged in testing. For all other users, deliver training prior to go-live to avoid the risk of training too early (where materials may not be ready or users are likely to forget what was learned). If possible, host quick refresher training a week or two prior to go-live.

Aim to communicate the upcoming go-live. The purpose of communication here is to reiterate expectations, complexities, and ramifications on business going forward. Alleviate performance anxiety by clearly stating that temporary drops in productivity are to be expected and that there will be appropriate assistance throughout the transition period.

Transition: Have the project/program manager remain on the project team for some time after deployment to oversee and assure smooth transition for the organization.

Complete training: Have a clear plan for training those users that were missed in the first round of training as well as a plan for ongoing training for those that require refresher training, for new joiners to your organization, and for any training requirements that result from subsequent upgrades.

3.1.2 Base your communications timeline on a classic change curve

It’s important to communicate the change ahead of the implementation, but also to reinforce that communication after implementation to recover from any resistance that occurs through the implementation itself.

Stages in a typical change curve:

1. Change is announced. Some people are skeptical and resistant, but others are enthusiastic. Most people are fence sitters; if they trust senior leadership, they will give the benefit of the doubt and expect change to be good.
2. Positive sentiment declines as implementation approaches. Training and other disruptions take people’s time and energy away from their work. Project setbacks and delays take credibility away from project leaders and seem to validate the efforts of saboteurs and skeptics.
3. Overall sentiment begins to improve as people adjust and see real progress made. Ideally, early successes or quick wins neutralize saboteurs and convert skeptics. At the very least, people will begin to accept and adapt to new realities.
4. If the project is successful and communication is reinforced after implementation, sentiment will peak and level out over time as people move on to other projects.

1. Honeymoon of “Uninformed Optimism”: Tentative support and enthusiasm for change before people have really felt or understood what it involves.
2. Backlash of “Informed Pessimism” (leading to “Valley of Despair”): People realize they’ve overestimated the benefits (or how soon they’ll be achieved) and underestimated the difficulty of change.
3. Valley of Despair and beginning of “Hopeful Realism”: Sentiment bottoms out and people begin to accept the difficulty (or inevitability) of change.
4. Bounce of “Informed Optimism”: More optimism and support when people begin to see bright spots and early successes.
5. Contentment of “Completion”: Change has been successfully adopted and benefits are being realized.

3.1.3 Communicate new processes

1. Communicate with business unit leaders and users:

• Focus on the benefits for end users to encourage buy-in for the change.
• Include preliminary instructions with a date for training sessions.

• Teach users how to contact the service desk and submit a ticket.
• Set expectations for IT’s response.
• Record all your training sessions so it can used for recursive training.

• IT must point users toward the new process, but ad hoc requests should still be expected at first. Deal with these politely but encourage all employees to use the new service desk ticketing process, if applicable.

• Continue to adjust communications if processes aren’t being followed to ensure SLAs can be met and improved.

“Communicate with your end users in phase 1 to let them know what will be changing, get feedback and buy-in, and inform them that training will be happening, then ensure you train them once the tool is installed. A lot of times we’ll get our tool set up but people don’t know how to use it."

– Director of ITSM Tools

Info-Tech Insight

If there is a new process for ticket input, consider using a reward system for users who submit a ticket through the proper channel ;(e.g. email or self-serve portal) instead of their old method (e.g. phone). However, if a significant cultural change is required, don’t expect it to happen right away.

Step 3.2

Create a training plan

Activities

This step involves the following participants:

• IT Director
• Project Manager
• Service Desk Manager

Outcomes of this step

• Training modules for different users of the tool.
• Assignment of training modules to users and schedule for completion.

3.2.1 Target training session(s) to the specific needs of your service desk and IT staff

Create targeted role-based training programs for your service desk analysts; they care about the portion of the solution they are responsible for, not the functionality that is irrelevant to their job.

Create and execute a role-based training program by conducting training sessions for targeted groups of users, training them on the functions they require to perform their jobs.

Use a table like this one to help identify which roles should be trained on which tasks within the ITSM tool.

The need for targeted training:

• IT personnel may challenge the need for training. They may feel they don’t require training on the use of tools or that they don’t have time to dedicate to training when there is so much work to be done.
• Providing targeted training focused on only the functions of the solution that each tier is responsible for can help to overcome that resistance.
• Targeted training may include basic training for level 1 technicians and more advanced in-depth training for administrators, power users, or level 2/3 technicians.

Info-Tech Insight:

Properly trained users promote adoption and improve results. Always keep training materials updated and available. New employees, new software integration, and internal promotions create opportunities for training employees to align the ITSM tool with their roles and responsibilities.

3.2.2 Provide training

Training must take place before deployment to ensure that both your service desk agents and end users will use the tool in the way it was intended and improve end-user satisfaction.

• Implementing a new ITSM tool will likely bring with it at least some degree of organizational and cultural change. It’s important to manage that change through proper training. Your training needs will vary depending on the maturity of the organization and the amount of cultural and process change being implemented.
• If this is your first ITSM solution with many new changes for staff to take on board, it will be important to dedicate training time not only before deployment but also several months after the initial installation, to allow staff to gain more experience with the new tool and processes and formulate questions they may not think to ask during implementation.
• A training plan should take into account not only training needs for the implementation project but also any ongoing training requirements that may be required. This may include:
  • Training for new personnel.
  • Training on any changes to the tool.
  • Training on any new processes the tool will support.
• Better agent training will lead to better performance and improved end-user satisfaction.

The blue graph line charts new-agent training hours against first contact resolution and the orange graph line charts the trendline for the dataset.

Source: MetricNet, 2012

3.2.3 Choose an appropriate training delivery method

Training should include use cases that focus on not only how the tool’s interface works but also how the tool should be used to support process activities.

1. Training through use cases highlights how the tool will support the user in role-based tasks.
2. If new processes are being introduced along with the tool, training should cover both in an integrated way.
3. Team leadership and management commitment ensures that all agents take their training seriously and are prepared for all use cases by the deployment date.

Info-Tech Insight:

Ensure that the training demonstrates not only how the tool should be used, but also the benefits it will provide your staff in terms of improved efficiency and productivity. Users who can clearly see the benefits the tool will provide for their daily work will accept the tool more readily and promote it across the organization.

Step 3.3

Plan how you will deploy, monitor, and maintain the solution

Activities

This step involves the following participants:

• IT Director
• Project Manager
• Service Desk Manager

Outcomes of this step

Deployment plan, including a plan for cut-over from the old tool (if applicable), release of the new tool, and post-deployment support and maintenance of the tool.

3.3.1 Plan the transition from your old tool to ensure continual functionality

If you will have a transitional period during which the current tool will be used alongside the new tool, develop a clear plan for the transition to ensure continued service for your end users.

• If there will be an interim period during which only some aspects of the new ITSM tool are functional, you will need to determine how the new system and old systems will work together for that period of time. This may require creating interfaces as well as providing user documentation and/or SOPs on how the business processes will operate during the interim period.
• Cut-over is the period during which the changeover to the new system occurs. Cut-over activities need to be tightly choreographed for a successful deployment. If improperly planned, chaos may erupt when unforeseen issues are encountered during deployment, the deployment may be jeopardized, and the organization may encounter costly interruptions to its daily operations.
• Many organizations may leave any open tickets in the old tool until they are closed, which requires that tool run alongside the new tool for a transitional period. In this case, it is necessary to create guidelines around how long the open tickets will remain in the old system and ensure there is clear communication around these processes.

Be prepared for the transition:

1. Create a robust cut-over plan that includes when the old tool will be decommissioned, what activities are necessary during the cut-over, and what the contingency plan is in case of unforeseen issues.
2. Plan for and perform mock cut-overs to establish the timeline and dependencies for all steps that need to be performed to successfully complete the changeover. Do this to avoid any surprises or delays during the true cut-over period.
3. Establish cut-over logistics: Create a schedule for resources to work in shifts to avoid burn-out during cut-over, which can lead to lapses in judgment and easily avoidable mistakes. Allocate dedicated workspaces for cut-over activities, e.g. “war rooms” for the triage of issues.

3.3.2 Choose a cut-over approach that works for you

Approaches and insights from three case studies

3.3.3 Deploy the solution and any new processes simultaneously to ease the transition

Follow a deployment plan for introducing new processes alongside the new tool to ensure changes to both process and technology are adopted simultaneously.

If you’re introducing new processes alongside the new tool, it’s important to maintain the link between process and tool. Typically, the processes and tool should be deployed simultaneously unless there is a strong reason not to do so.

Deployment can be done as a big-bang or phased approach. The decision to employ a phased deployment depends on the number and size of business units the tool will support, as well as the organization’s geography and infrastructure (deployment locations).

Before deployment, conduct readiness assessments to understand whether:

The people are ready to accept the new system (have received the proper training and communications and understand how their jobs will change when the switch is flipped).

The technology is ready (test results are favorable, workarounds and a plan for closure have been identified for any open defects, and the system is performing as expected).

The data is ready (data for final conversion has been cleansed, and all conversions have been rehearsed).

The post-deployment support model is ready (infrastructure and technical support is in place, sites are ready, knowledge transfer has been conducted with the support organization, and end users understand procedures for escalation of issues).

3.3.4 Have a post-deployment support plan in place

Ensure that strong internal support for the project and tool will continue after deployment.

The stabilization period after a new software deployment can last between three and nine months, during which there may be continued training needs and fine-tuning of processes. Internal support from project leaders within your organization will be critical to recover from any dip in operational efficiency and deliver the benefits of the tool.

Consider the following to prepare better for your support plan:

What are the roles and responsibilities for ongoing tool administration support?

What level of support will exist to assist service desk staff after deployment?

How much time will project team resources devote to tackling upcoming issues and assisting with ongoing support?

Who will be responsible for ongoing training needs and documentation?

If your organization is spread across multiple locations, what level of support/assistance will be available at each site?

How will new code releases or system upgrades be managed and communicated?

Info-Tech Insight:

Deployment is only the first step in the system lifecycle. Full benefit realization from the tool requires ongoing investment and learning to be sustained. Unless processes and training are updated on an ongoing basis, benefits gained will start to decrease over time. If your service desk efficiency stagnates at the level it was at prior to implementation, the tool has failed to serve its objective.

Establish ongoing tool maintenance, improvement structures, and processes

People, processes, and organizations change over time, and your ITSM tool will need to change to meet expectations.

Develop and execute a plan for the maintenance of the solution and its infrastructure components.

Assign responsibility for ongoing maintenance. Hold regular meetings for the following activities:

1. Inspect data and reports.
2. Assess whether you’re meeting SLAs.
3. Predict any upcoming changes that may impact ticket volume (e.g. a new operating system or security patch).
4. Create new ticket templates for recurring or upcoming issues.
5. Create new knowledgebase articles.
6. Determine whether ticket categories are being used correctly.
7. Ask team if there are any problems with the tool.

3.3.5 Monitor success metrics defined in Project Charter

Revisit your goals for the solution and assess if they are being met by evaluating current metrics. If your goals have not yet been met, re-evaluate how to ensure the tool will deliver value.

Sample High-Level Goals:

1. Improved service desk efficiency
2. Improved end-user satisfaction
3. Improved self-service options for end users
4. Improved data and reporting capabilities

Related Info-Tech Research

Optimize IT Change Management

Define change management workflows, key roles, and supporting elements such as request-for-change forms based on best practices.

Standardize the Service Desk

Build core elements of service desk operations, including incident management and service request workflows, ticket categorization schemes, and ticket prioritization rules.

Optimize the Service Desk With a Shift-Left Strategy

Implement tools such as an improved knowledgebase and self-service portal to enable lower tier support staff and end users to resolve incidents or fulfill service requests.

Incident and Problem Management

Develop a critical incident management workflow and create standard operating procedures for problem management.

IT Service Management Selection Guide

Identify the best-of-breed solution to make the most of your investment and engage the right stakeholders to define success.

Analyze Your Service Desk Ticket Data

Develop a framework to track metrics, clean data, and put your data to use for pre-defined timelines.

Bibliography

Adiga, Siddanth. “10 Reasons Why ITSM Implementations Fail.” Could Strategy, 6 May 2015. Web.

Hastie, Shane, and Stéphane Wojewoda. “Standish Group 2015 Chaos Report.” InfoQ, 4 October 2015. Web.

“How to Manage Change in the Implementation of an ITSM Software.” C2, 20 April 2015. Web.

Lockwood, Meghan. “First Look: Annual ServiceNow Insight and Vision Executive Summary [eBook].” Acorio, 31 October 2019. Web.

Mainville, David. “7 Steps to a Successful ITSM Tool Implementation.” Navvia, 2012. Web.

Rae, Barclay. “Preparing for ITSM Tool Implementation.” Joe the IT Guy, 24 June 2015. Web.

Rae, Barclay. “Successful ITSM Tool Implementation.” BrightTALK, 9 May 2013. Webcast.

Rumburg, Jeffrey. “Metric of the Month: Agent Training Hours.” MetricNet, 2012. Web.

Establish Data Governance

Deliver measurable business value.

Analyst Perspective

Establish a data governance program that brings value to your organisation.

Data governance does not sit as an island on its own in the organisation – it must align with and be driven by your enterprise governance. As you build out data governance in your organisation, it's important to keep in mind that this program is meant to be an enabling framework of oversight and accountabilities for managing, handling, and protecting your company's data assets. It should never be perceived as bureaucratic or inhibiting to your data users. It should deliver agreed-upon models that are conducive to your organisation's operating culture, offering clarity on who can do what with the data and via what means. Data governance is the key enabler for bringing high-quality, trusted, secure, and discoverable data to the right users across your organisation. Promote and drive the responsible and ethical use of data while helping to build and foster an organisational culture of data excellence.

Crystal Singh

Director, Research & Advisory, Data & Analytics Practice

Info-Tech Research Group

Executive Summary

Your Challenge

The amount of data within organisations is growing at an exponential rate, creating a need to adopt a formal approach to governing data. However, many organisations remain uninformed on how to effectively govern their data. Comprehensive data governance should define leadership, accountability, and responsibility related to data use and handling and be supported by a well-oiled operating model and relevant policies and procedures. This will help ensure the right data gets to the right people at the right time, using the right mechanisms.

Common Obstacles

Organisations are faced with challenges associated with changing data landscapes, evolving business models, industry disruptions, regulatory and compliance obligations, and changing and maturing user landscape and demand for data. Although the need for a data governance program is often evident, organisations miss the mark when their data governance efforts are not directly aligned to delivering measurable business value. Initiatives should support key strategic initiatives, as well as value streams and their underlying business capabilities.

Info-Tech's Approach

Info-Tech's approach to establishing and sustaining effective data governance is anchored in the strong alignment of organisational value streams and their business capabilities with key data governance dimensions and initiatives. Organisations should:

• Align their data governance with enterprise governance, business strategy and value streams to ensure the program delivers measurable business value.
• Understand their current data governance capabilities so as to build out a future state that is right-sized and relevant.
• Define data leadership, accountability, and responsibility. Support these with an operating model that effectively manages change and communication and fosters a culture of data excellence.

Info-Tech Insight

Your organisation's value streams and the associated business capabilities require effectively governed data. Without this, you face elevated operating costs, missed opportunities, eroded stakeholder satisfaction, and increased business risk.

Your challenge

This research is designed to help organisations build and sustain an effective data governance program.

• Your organisation has recognised the need to treat data as a corporate asset for generating business value and/or managing and mitigating risk.
• This has brought data governance to the forefront and highlighted the need to build a performance-driven enterprise program for delivering quality, trusted, and readily consumable data to users.
• An effective data governance program is one that defines leadership, accountability. and responsibility related to data use and handling. It's supported by a well-oiled operating model and relevant policies and procedures, all of which help build and foster a culture of data excellence where the right users get access to the right data at the right time via the right mechanisms.

As you embark on establishing data governance in your organisation, it's vital to ensure from the get-go that you define the drivers and business context for the program. Data governance should never be attempted without direction on how the program will yield measurable business value.

'Data processing and cleanup can consume more than half of an analytics team's time, including that of highly paid data scientists, which limits scalability and frustrates employees.' – Petzold, et al., 2020

'The productivity of employees across the organisation can suffer.' – Petzold, et al., 2020

Respondents to McKinsey's 2019 Global Data Transformation Survey reported that an average of 30% of their total enterprise time was spent on non-value-added tasks because of poor data quality and availability. – Petzold, et al., 2020

Common obstacles

Some of the barriers that make data governance difficult to address for many organisations include:

• Gaps in communicating the strategic value of data and data governance to the organisation. This is vital for securing senior leadership buy-in and support, which, in turn, is crucial for sustained success of the data governance program.
• Misinterpretation or a lack of understanding about data governance, including what it means for the organisation and the individual data user.
• A perception that data governance is inhibiting or an added layer of bureaucracy or complication rather than an enabling and empowering framework for stakeholders in their use and handling of data.
• Embarking on data governance without firmly substantiating and understanding the organisational drivers for doing so. How is data governance going to support the organisation's value streams and their various business capabilities?
• Neglecting to define and measure success and performance. Just as in any other enterprise initiative, you have to be able to demonstrate an ROI for time, resources and funding. These metrics must demonstrate the measurable business value that data governance brings to the organisation.
• Failure to align data governance with enterprise governance.

78% of companies (and 92% of top-tier companies) have a corporate initiative to become more data-driven. – Alation, 2020.

But despite these ambitions, there appears to be a 'data culture disconnect' – 58% of leaders overestimate the current data culture of their enterprises, giving a grade higher than the one produced by the study. – Fregoni, 2020.

The strategic value of data

Power intelligent and transformative organisational performance through leveraging data.

Respond to industry disruptors

Optimise the way you serve your stakeholders and customers

Develop products and services to meet ever-evolving needs

Manage operations and mitigate risk

Harness the value of your data

The journey to being data-driven

The journey to declaring that you are a data-driven organisation requires a pit stop at data enablement.

The Data Economy

Data Disengaged

You have a low appetite for data and rarely use data for decision making.

Data Enabled

Technology, data architecture, and people and processes are optimised and supported by data governance.

Data Driven

You are differentiating and competing on data and analytics; described as a 'data first' organisation. You're collaborating through data. Data is an asset.

Data governance is essential for any organisation that makes decisions about how it uses its data.

Data governance is an enabling framework of decision rights, responsibilities, and accountabilities for data assets across the enterprise.

Data governance is:

• Executed according to agreed-upon models that describe who can take what actions with what information, when, and using what methods (Olavsrud, 2021).
• True business-IT collaboration that will lead to increased consistency and confidence in data to support decision making. This, in turn, helps fuel innovation and growth.

If done correctly, data governance is not:

• An annoying, finger-waving roadblock in the way of getting things done.
• Meant to solve all data-related business or IT problems in an organisation.
• An inhibitor or impediment to using and sharing data.

Info-Tech's Data Governance Framework

Create impactful data governance by embedding it within enterprise governance

Organisational drivers for data governance

Data governance personas:

Conformance: Establishing data governance to meet regulations and compliance requirements.

Performance: Establishing data governance to fuel data-driven decision making for driving business value and managing and mitigating business risk.

Data Governance is not a one-person show

• Data governance needs a leader and a home. Define who is going to be leading, driving, and steering data governance in your organisation.
• Senior executive leaders play a crucial role in championing and bringing visibility to the value of data and data governance. This is vital for building and fostering a culture of data excellence.
• Effective data governance comes with business and IT alignment, collaboration, and formally defined roles around data leadership, ownership, and stewardship.

Traditional data governance organisational structure

A traditional structure includes committees and roles that span across strategic, tactical, and operational duties. There is no one-size-fits-all data governance structure. However, most organisations follow a similar pattern when establishing committees, councils, and cross-functional groups. Most organisations strive to identify roles and responsibilities at a strategic and operational level. Several factors will influence the structure of the program, such as the focus of the data governance project and the maturity and size of the organisation.

A healthy data culture is key to amplifying the power of your data.

'Albert Einstein is said to have remarked, "The world cannot be changed without changing our thinking." What is clear is that the greatest barrier to data success today is business culture, not lagging technology.' – Randy Bean, 2020

What does it look like?

• Everybody knows the data.
• Everybody trusts the data.
• Everybody talks about the data.

'It is not enough for companies to embrace modern data architectures, agile methodologies, and integrated business-data teams, or to establish centres of excellence to accelerate data initiatives, when only about 1 in 4 executives reported that their organisation has successfully forged a data culture.'– Randy Bean, 2020

Data literacy is an essential part of a data-driven culture

• In a data-driven culture, decisions are made based on data evidence, not on gut instinct.
• Data often has untapped potential. A data-driven culture builds tools and skills, builds users' trust in the condition and sources of data, and raises the data skills and understanding among their people on the front lines.
• Building a data culture takes an ongoing investment of time, effort, and money. This investment will not achieve the transformation you want without data literacy at the grassroots level.

Data-driven culture = 'data matters to our company'

Despite investments in data initiative, organisations are carrying high levels of data debt

Data debt is 'the accumulated cost that is associated with the sub-optimal governance of data assets in an enterprise, like technical debt.'

Data debt is a problem for 78% of organisations.

40% of organisations say individuals within the business do not trust data insights.

66% of organisations say a backlog of data debt is impacting new data management initiatives.

33% of organisations are not able to get value from a new system or technology investment.

30% of organisations are unable to become data-driven.

Source: Experian, 2020

Absent or sub-optimal data governance leads to data debt

Only 3% of companies' data meets basic quality standards. (Source: Nagle, et al., 2017)

Organisations suspect 28% of their customer and prospect data is inaccurate in some way. (Source: Experian, 2020)

Only 51% of organisations consider the current state of their CRM or ERP data to be clean, allowing them to fully leverage it. (Source: Experian, 2020)

35% of organisations say they're not able to see a ROI for data management initiatives. (Source: Experian, 2020)

Embrace the technology

Make the available data governance tools and technology work for you:

• Data catalogue
• Business data glossary
• Data lineage
• Metadata management

While data governance tools and technologies are no panacea, leverage their automated and AI-enabled capabilities to augment your data governance program.

Measure success to demonstrate tangible business value

Put data governance into the context of the business:

• Tie the value of data governance and its initiatives back to the business capabilities that are enabled.
• Leverage the KPIs of those business capabilities to demonstrate tangible and measurable value. Use terms and language that will resonate with senior leadership.

Don't let measurement be an afterthought:

Start substantiating early on how you are going to measure success as your data governance program evolves.

Build a right-sized roadmap

Formulate an actionable roadmap that is right-sized to deliver value in your organisation.

Key considerations:

• When building your data governance roadmap, ensure you do so through an enterprise lens. Be cognizant of other initiatives that might be coming down the pipeline that may require you to align your data governance milestones accordingly.
• Apart from doing your planning with consideration for other big projects or launches that might be in-flight and require the time and attention of your data governance partners, also be mindful of the more routine yet still demanding initiatives.
• When doing your roadmapping, consider factors like the organisation's fiscal cycle, typical or potential year-end demands, and monthly/quarterly reporting periods and audits. Initiatives such as these are likely to monopolise the time and focus of personnel key to delivering on your data governance milestones.

Sample milestones:

Data Governance Leadership & Org Structure Definition

Define the home for data governance and other key roles around ownership and stewardship, as approved by senior leadership.

Data Governance Charter and Policies

Create a charter for your program and build/refresh associated policies.

Data Culture Diagnostic

Understand the organisation's current data culture, perception of data, value of data, and knowledge gaps.

Use Case Build and Prioritisation

Build a use case that is tied to business capabilities. Prioritise accordingly.

Business Data Glossary

Build and/or refresh the business' glossary for addressing data definitions and standardisation issues.

Tools & Technology

Explore the tools and technology offering in the data governance space that would serve as an enabler to the program. (e.g. RFI, RFP).

Key takeaways for effective business-driven data governance

Data governance leadership and sponsorship is key.

Ensure strategic business alignment.

Build and foster a culture of data excellence.

Evolve along the data journey.

Make data governance an enabler, not a hindrance.

Insight summary

Overarching insight

Your organisation's value streams and the associated business capabilities require effectively governed data. Without this, you face the impact of elevated operational costs, missed opportunities, eroded stakeholder satisfaction, and exposure to increased business risk.

Insight 1

Data governance should not sit as an island in your organisation. It must continuously align with the organisation's enterprise governance function. It shouldn't be perceived as a pet project of IT, but rather as an enterprise-wide, business-driven initiative.

Insight 2

Ensure your data governance program delivers measurable business value by aligning the associated data governance initiatives with the business architecture. Leverage the measures of success or KPIs of the underlying business capabilities to demonstrate the value data governance has yielded for the organisation.

Insight 3

Data governance remains the foundation of all forms of reporting and analytics. Advanced capabilities such as AI and machine learning require effectively governed data to fuel their success.

Tactical insight

Tailor your data literacy program to meet your organisation's needs, filling your range of knowledge gaps and catering to your different levels of stakeholders. When it comes to rolling out a data literacy program, there is no one-size-fits-all solution. Your data literacy program is intended to fill the knowledge gaps about data, as they exist in your organisation. It should be targeted across the board – from your executive leadership and management through to the subject matter experts across different lines of the business in your organisation.

Info-Tech's methodology for establishing data governance

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

Data Governance Planning and Roadmapping Workbook

Use the Data Governance Planning and Roadmapping Workbook as you plan, build, roll out, and scale data governance in your organisation.

Data Use Case Framework Template

This template takes you through a business needs gathering activity to highlight and create relevant use cases around the organisation's data-related problems and opportunities.

Business Data Glossary

Use this template to document the key data assets that are to be governed and create a data flow diagram for your organisation.

Data Culture Diagnostic and Scorecard

Leverage Info-Tech's Data Culture Diagnostic to understand how your organisation scores across 10 areas relating to data culture.

Key deliverable:

Data Governance Planning and Roadmapping Workbook

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

Data Governance Initiative Planning and Roadmap Tool

Leverage this tool to assess your current data governance capabilities and plot your target state accordingly.

This tool will help you plan the sequence of activities, capture start dates and expected completion dates, and create a roadmap that can be effectively communicated to the organisation.

Data Governance Program Charter Template

This template will help get the backing required to get a data governance project rolling. The program charter will help communicate the project purpose, define the scope, and identify the project team, roles, and responsibilities.

Data Governance Policy

This policy establishes uniformed data governance standards and identifies the shared responsibilities for assuring the integrity of the data and that it efficiently and effectively serves the needs of your organisation

Other Deliverables:

• Data Governance Initiative Planning and Roadmap Tool
• Data Governance Program Charter Template
• Data Governance Policy

Blueprint benefits

Defined data accountability & responsibility

Shared knowledge & common understanding of data assets

Elevated trust & confidence in traceable data

Improved data ROI & reduced data debt

Support for ethical use and handling of data in a culture of excellence

Measure the value of this blueprint

Leverage this blueprint's approach to ensure your data governance initiatives align and support your key value streams and their business capabilities.

• Aligning your data governance program and its initiatives to your organisation's business capabilities is vital for tracing and demonstrating measurable business value for the program.
• This alignment of data governance with value streams and business capabilities enables you to use business-defined KPIs and demonstrate tangible value.

In phases 1 and 2 of this blueprint, we will help you establish the business context, define your business drivers and KPIs, and understand your current data governance capabilities and strengths.

In phase 3, we will help you develop a plan and a roadmap for addressing any gaps and improving the relevant data governance capabilities so that data is well positioned to deliver on those defined business metrics.

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

'Our team, has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.'

Guided Implementation

'Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keeps us on track.'

Workshop

'We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.'

Consulting

'Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.'

Diagnostics and consistent frameworks are used throughout all four options.

Establish Data Governance project overview

Contact your account representative for more information. workshops@infotech.com 1-888-670-8889

Guided Implementation

What does a typical GI on this topic look like?

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organisation. A typical GI is between 8 to 12 calls over the course of 4 to 6 months.

Workshop overview

Contact your account representative for more information. workshops@infotech.com 1-888-670-8889

Phase 1

Build Business and User Context

'When business users are invited to participate in the conversation around data with data users and IT, it adds a fundamental dimension — business context. Without a real understanding of how data ties back to the business, the value of analysis and insights can get lost.' – Jason Lim, Alation

This phase will guide you through the following activities:

• Identify Your Business Capabilities
• Define your Organisation's Key Business Capabilities
• Develop a Strategy Map that Aligns Business Capabilities to Your Strategic Focus

This phase involves the following participants:

• Data Governance Leader/Data Leader (CDO)
• Senior Business Leaders
• Business SMEs
• Data Leadership, Data Owners, Data Stewards and Custodians

Step 1.1

Substantiate Business Drivers

Activities

1.1.1 Identify Your Business Capabilities

1.1.2 Categorise Your Organisation's Key Business Capabilities

1.1.3 Develop a Strategy Map Tied to Data Governance

This step will guide you through the following activities:

• Leverage your organisation's existing business capability map or initiate the formulation of a business capability map, guided by Info-Tech's approach
• Determine which business capabilities are considered high priority by your organisation
• Map your organisation's strategic objectives to value streams and capabilities to communicate how objectives are realised with the support of data

Outcomes of this step

• A foundation for data governance initiative planning that's aligned with the organisation's business architecture: value streams, business capability map, and strategy map

Info-Tech Insight

Gaining a sound understanding of your business architecture (value streams and business capabilities) is a critical foundation for establishing and sustaining a data governance program that delivers measurable business value.

1.1.1 Identify Your Business Capabilities

Confirm your organisation's existing business capability map or initiate the formulation of a business capability map:

1. If you have an existing business capability map, meet with the relevant business owners/stakeholders to confirm that the content is accurate and up to date. Confirm the value streams (how your organisation creates and captures value) and their business capabilities are reflective of the organisation's current business environment.
2. If you do not have an existing business capability map, follow this activity to initiate the formulation of a map (value streams and related business capabilities):
   1. Define the organisation's value streams. Meet with senior leadership and other key business stakeholders to define how your organisation creates and captures value.
   2. Define the relevant business capabilities. Meet with senior leadership and other key business stakeholders to define the business capabilities.

Note: A business capability defines what a business does to enable value creation. Business capabilities are business terms defined using descriptive nouns such as 'Marketing' or 'Research and Development.' They represent stable business functions, are unique and independent of each other, and typically will have a defined business outcome.

Input

• List of confirmed value streams and their related business capabilities

Output

• Business capability map with value streams for your organisation

Materials

• Your existing business capability map or the template provided in the Data Governance Planning and Roadmapping Workbook accompanying this blueprint

Participants

• Key business stakeholders
• Data stewards
• Data custodians
• Data Governance Working Group

For more information, refer to Info-Tech's Document Your Business Architecture.

Define or validate the organisation's value streams

Value streams connect business goals to the organisation's value realisation activities. These value realisation activities, in turn, depend on data.

If the organisation does not have a business architecture function to conduct and guide Activity 1.1.1, you can leverage the following approach:

• Meet with key stakeholders regarding this topic, then discuss and document your findings.
• When trying to identify the right stakeholders, consider: Who are the decision makers and key influencers? Who will impact this piece of business architecture related work? Who has the relevant skills, competencies, experience, and knowledge about the organisation?
• Engage with these stakeholders to define and validate how the organisation creates value.
• Consider:
  • Who are your main stakeholders? This will depend on the industry in which you operate. For example, customers, residents, citizens, constituents, students, patients.
  • What are your stakeholders looking to accomplish?
  • How does your organisation's products and/or services help them accomplish that?
  • What are the benefits your organisation delivers to them and how does your organisation deliver those benefits?
  • How do your stakeholders receive those benefits?

Align data governance to the organisation's value realisation activities.

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

Info-Tech Insight

Your organisation's value streams and the associated business capabilities require effectively governed data. Without this, you face the possibilities of elevated operational costs, missed opportunities, eroded stakeholder satisfaction, negative impact to reputation and brand, and/or increased exposure to business risk.

Example of value streams – Retail Banking

Value streams connect business goals to the organisation's value realisation activities.

Example value stream descriptions for: Retail Banking

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech's Info-Tech's Industry Reference Architecture for Retail Banking.

Example of value streams – Higher Education

Value streams connect business goals to the organisation's value realisation activities.

Example value stream descriptions for: Higher Education

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech's Industry Reference Architecture for Higher Education.

Example of value streams – Local Government

Value streams connect business goals to the organisation's value realisation activities.

Example value stream descriptions for: Local Government

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech's Industry Reference Architecture for Local Government.

Example of value streams – Manufacturing

Value streams connect business goals to the organisation's value realisation activities.

Example value stream descriptions for: Manufacturing

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech's Industry Reference Architecture for Manufacturing.

Example of value streams – Retail

Value streams connect business goals to the organisation's value realisation activities.

Example value stream descriptions for: Retail

Value streams enable the organisation to create or capture value in the market in which it operates by engaging in a set of interconnected activities.

For this value stream, download Info-Tech's Industry Reference Architecture for Retail.

Define the organisation's business capabilities in a business capability map

A business capability defines what a business does to enable value creation. Business capabilities represent stable business functions and typically will have a defined business outcome.

Business capabilities can be thought of as business terms defined using descriptive nouns such as 'Marketing' or 'Research and Development.'

If your organisation doesn't already have a business capability map, you can leverage the following approach to build one. This initiative requires a good understanding of the business. By working with the right stakeholders, you can develop a business capability map that speaks a common language and accurately depicts your business.

Working with the stakeholders as described above:

• Analyse the value streams to identify and describe the organisation's capabilities that support them.
• Consider: What is the objective of your value stream? (This can highlight which capabilities support which value stream.)
• As you initiate your engagement with your stakeholders, don't start a blank page. Leverage the examples on the next slides as a starting point for your business capability map.
• When using these examples, consider: What are the activities that make up your particular business? Keep the ones that apply to your organisation, remove the ones that don't, and add any needed.

Align data governance to the organisation's value realisation activities.

Info-Tech Insight

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

For more information, refer to Info-Tech's Document Your Business Architecture.

Example business capability map – Retail Banking

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip:

Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realisation capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Retail Banking

For this business capability map, download Info-Tech's Industry Reference Architecture for Retail Banking.

Example business capability map – Higher Education

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip:

Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realisation capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Higher Education

For this business capability map, download Info-Tech's Industry Reference Architecture for Higher Education.

Example business capability map – Local Government

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip:

Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realisation capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Local Government

For this business capability map, download Info-Tech's Industry Reference Architecture for Local Government.

Example business capability map – Manufacturing

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip:

Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realisation capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Manufacturing

For this business capability map, download Info-Tech's Industry Reference Architecture for Manufacturing.

Example business capability map - Retail

A business capability map can be thought of as a visual representation of your organisation's business capabilities and hence represents a view of what your data governance program must support.

Validate your business capability map with the right stakeholders, including your executive team, business unit leaders, and/or other key stakeholders.

Info-Tech Tip:

Leverage your business capability map verification session with these key stakeholders as a prime opportunity to share and explain the role of data and data governance in supporting the very value realisation capabilities under discussion. This will help to build awareness and visibility of the data governance program.

Example business capability map for: Retail

For this business capability map, download Info-Tech's Industry Reference Architecture for Retail.

1.1.2 Categorise Your Organisation's Key Capabilities

Determine which capabilities are considered high priority in your organisation.

1. Categorise or heatmap the organisation's key capabilities. Consult with senior and other key business stakeholders to categorise and prioritise the business' capabilities. This will aid in ensuring your data governance future state planning is aligned with the mandate of the business. One approach to prioritising capabilities with business stakeholders is to examine them through the lens of cost advantage creators, competitive advantage differentiators, and/or by high value/high risk.
2. Identify cost advantage creators. Focus on capabilities that drive a cost advantage for your organisation. Highlight these capabilities and prioritise programs that support them.
3. Identify competitive advantage differentiators. Focus on capabilities that give your organisation an edge over rivals or other players in your industry.

This categorisation/prioritisation exercise helps highlight prime areas of opportunity for building use cases, determining prioritisation, and the overall optimisation of data and data governance.

Input

• Strategic insight from senior business stakeholders on the business capabilities that drive value for the organisation

Output

• Business capabilities categorised and prioritised (e.g. cost advantage creators, competitive advantage differentiators, high value/high risk)

Materials

• Your existing business capability map or the business capability map derived in the previous activity

Participants

• Key business stakeholders
• Data stewards
• Data custodians
• Data Governance Working Group

For more information, refer to Info-Tech's Document Your Business Architecture.

Example of business capabilities categorisation or heatmapping – Retail

This exercise is useful in ensuring the data governance program is focused and aligned to support the priorities and direction of the business.

• Depending on the mandate from the business, priority may be on developing cost advantage. Hence the capabilities that deliver efficiency gains are the ones considered to be cost advantage creators.
• The business' priority may be on maintaining or gaining a competitive advantage over its industry counterparts. Differentiation might be achieved in delivering unique or enhanced products, services, and/or experiences, and the focus will tend to be on the capabilities that are more end-stakeholder-facing (e.g. customer-, student-, patient,- and/or constituent-facing). These are the organisation's competitive advantage creators.

Example: Retail

For this business capability map, download Info-Tech's Industry Reference Architecture for Retail.

1.1.3 Develop a Strategy Map Tied to Data Governance

Identify the strategic objectives for the business. Knowing the key strategic objectives will drive business-data governance alignment. It's important to make sure the right strategic objectives of the organisation have been identified and are well understood.

1. Meet with senior business leaders and other relevant stakeholders to help identify and document the key strategic objectives for the business.
2. Leverage their knowledge of the organisation's business strategy and strategic priorities to visually represent how these map to value streams, business capabilities, and, ultimately, to data and data governance needs and initiatives. Tip: Your map is one way to visually communicate and link the business strategy to other levels of the organisation.
3. Confirm the strategy mapping with other relevant stakeholders.

Guide to creating your map: Starting with strategic objectives, map the value streams that will ultimately drive them. Next, link the key capabilities that enable each value stream. Then map the data and data governance to initiatives that support those capabilities. This is one approach to help you prioritise the data initiatives that deliver the most value to the organisation.

Input

• Strategic objectives as outlined by the organisation's business strategy and confirmed by senior leaders

Output

• A strategy map that maps your organisational strategic objectives to value streams, business capabilities, and, ultimately, to data program

Materials

• Your existing business capability map or the one created in the previous step
• The strategy map template provided in the Data Governance Planning and Roadmapping Workbook
• Business strategy

Participants

• Key business stakeholders
• Data stewards
• Data custodians
• Data Governance Working Group

Download Info-Tech's Data Governance Planning and Roadmapping Workbook

Example of a strategy map tied to data governance

• Strategic objectives are the outcomes that the organisation is looking to achieve.
• Value streams enable an organisation to create and capture value in the market through interconnected activities that support strategic objectives.
• Business capabilities define what a business does to enable value creation in value streams.
• Data capabilities and initiatives are descriptions of action items on the data and data governance roadmap and which will enable one or multiple business capabilities in its desired target state.

Info-Tech Tip:

Start with the strategic objectives, then map the value streams that will ultimately drive them. Next, link the key capabilities that enable each value stream. Then map the data and data governance initiatives that support those capabilities. This process will help you prioritise the data initiatives that deliver the most value to the organisation.

Example: Retail

For this strategy map, download Info-Tech's Industry Reference Architecture for Retail.

Step 1.2

Build High-Value Use Cases for Data Governance

Activities

1.2.1 Build High-Value Use Cases

This step will guide you through the following activities:

• Leveraging your categorised business capability map to conduct deep-dive sessions with key business stakeholders for creating high-value uses cases
• Discussing current challenges, risks, and opportunities associated with the use of data across the lines of business
• Exploring which other business capabilities, stakeholder groups, and business units will be impacted

Outcomes of this step

• Relevant use cases that articulate the data-related challenges, needs, or opportunities that are clear and contained and, if addressed ,will deliver value to the organisation

Info-Tech Tip

One of the most important aspects when building use cases is to ensure you include KPIs or measures of success. You have to be able to demonstrate how the use case ties back to the organisational priorities or delivers measurable business value. Leverage the KPIs and success factors of the business capabilities tied to each particular use case.

1.2.1 Build High-Value Use Cases

This business needs-gathering activity will highlight and create relevant use cases around data-related problems or opportunities that are clear and contained and, if addressed, will deliver value to the organisation.

1. Bring together key business stakeholders (data owner, stewards, SMEs) from a particular line of business as well as the relevant data custodian(s) to build cases for their units. Leverage the business capability map you created for facilitating this act.
2. Leverage Info-Tech's framework for data requirements and methodology for creating use cases, as outlined in the Data Use Case Framework Template and seen on the next slide.
3. Have the stakeholders move through each breakout session outlined in the Use Case Worksheet. Use flip charts or a whiteboard to brainstorm and document their thoughts.
4. Debrief and document results in the Data Use Case Framework Template.
5. Repeat this exercise with as many lines of the business as possible, leveraging your business capability map to guide your progress and align with business value.

Tip: Don't conclude these use case discussions without substantiating what measures of success will be used to demonstrate the business value of the effort to produce the desired future state, as relevant to each particular use case.

This business needs-gathering activity will highlight and create relevant use cases around data-related problems or opportunities that are clear and contained and, if addressed, will deliver value to the organisation.

1. Bring together key business stakeholders (data owner, stewards, SMEs) from a particular line of business as well the relevant data custodian(s) to build cases for their units. Leverage the business capability map you created for facilitating this act.
2. Leverage Info-Tech's framework for data requirements and methodology for creating use cases, as outlined in the Data Use Case Framework Template and seen on the next slide.
3. Have the stakeholders move through each breakout session outlined in the Use Case Worksheet. Use flip charts or a whiteboard to brainstorm and document their thoughts.
4. Debrief and document results in the Data Use Case Framework Template
5. Repeat this exercise with as many lines of the business as possible, leveraging your business capability map to guide your progress and align with business value.

Tip: Don't conclude these use case discussions without substantiating what measures of success will be used to demonstrate the business value of the effort to produce the desired future state, as relevant to each particular use case.

Input

• Value streams and business capabilities as defined by business leaders
• Business stakeholders' subject area expertise
• Data custodian systems, integration, and data knowledge

Output

• Use cases that articulate data-related challenges, needs or opportunities that are tied to defined business capabilities and hence if addressed will deliver measurable value to the organisation.

Materials

• Your business capability map from activity 1.1.1
• Info-Tech's Data Use Case Framework Template
• Whiteboard or flip charts (or shared screen if working remotely)
• Markers/pens

Participants

• Key business stakeholders
• Data stewards and business SMEs
• Data custodians
• Data Governance Working Group

Download Info-Tech's Data Use Case Framework Template

Info-Tech's Framework for Building Use Cases

Objective: This business needs-gathering activity will highlight and create relevant use cases around data-related problems or opportunities that are clear and contained and, if addressed, will deliver value to the organisation.

Leveraging your business capability map, build use cases that align with the organisation's key business capabilities.

Consider:

• Is the business capability a cost advantage creator or an industry differentiator?
• Is the business capability currently underserved by data?
• Does this need to be addressed? If so, is this risk- or value-driven?

Info-Tech's Data Requirements and Mapping Methodology for Creating Use Cases

1. What business capability (or capabilities) is this use case tied to for your business area(s)?
2. What are your data-related challenges in performing this today?
3. What are the steps in this process/activity today?
4. What are the applications/systems used at each step today?
5. What data domains are involved, created, used, and/or transformed at each step today?
6. What does an ideal or improved state look like?
7. What other business units, business capabilities, activities, and/or processes will be impacted or improved if this issue was solved?
8. Who are the stakeholders impacted by these changes? Who needs to be consulted?
9. What are the risks to the organisation (business capability, revenue, reputation, customer loyalty, etc.) if this is not addressed?
10. What compliance, regulatory, and/or policy concerns do we need to consider in any solution?
11. What measures of success or change should we use to prove the value of the effort (such as KPIs, ROI)? What is the measurable business value of doing this?

The resulting use cases are to be prioritised and leveraged for informing the business case and the data governance capabilities optimisation plan.

Taken from Info-Tech's Data Use Case Framework Template

Phase 2

Understand Your Current Data Governance Capabilities

This phase will guide you through the following activities:

• Understand the Key Components of Data Governance
• Gauge Your Organisation's Current Data Culture

This phase involves the following participants:

• Data Leadership
• Data Ownership & Stewardship
• Policies & Procedures
• Data Literacy & Culture
• Operating Model
• Data Management
• Data Privacy & Security
• Enterprise Projects & Services

Step 2.1

Understand the Key Components of Data Governance

This step will guide you through the following activities:

• Understanding the core components of an effective data governance program and determining your organisation's current capabilities in these areas:
  • Data Leadership
  • Data Ownership & Stewardship
  • Policies & Procedures
  • Data Literacy & Culture
  • Operating Model
  • Data Management
  • Data Privacy & Security
  • Enterprise Projects & Services

Outcomes of this step

• An understanding of the core components of an effective data governance program
• An understanding your organisation's current data governance capabilities

Leverage Info-Tech's: Data Governance Initiative Planning and Roadmap Tool to assess your current data governance capabilities and plot your target state accordingly.

This tool will help your organisation plan the sequence of activities, capture start dates and expected completion dates, and create a roadmap that can be effectively communicated to the organisation.

Review: Info-Tech's Data Governance Framework

Key components of data governance

A well-defined data governance program will deliver:

• Defined accountability and responsibility for data.
• Improved knowledge and common understanding of the organisation's data assets.
• Elevated trust and confidence in traceable data.
• Improved data ROI and reduced data debt.
• An enabling framework for supporting the ethical use and handling of data.
• A foundation for building and fostering a data-driven and data-literate organisational culture.

The key components of establishing sustainable enterprise data governance, taken from Info-Tech's Data Governance Framework:

• Data Leadership
• Data Ownership & Stewardship
• Operating Model
• Policies & Procedures
• Data Literacy & Culture
• Data Management
• Data Privacy & Security
• Enterprise Projects & Services

Data Leadership

• Data governance needs a dedicated head or leader to steer the organisation's data governance program.
• For organisations that do have a chief data officer (CDO), their office is the ideal and effective home for data governance.
• Heads of data governance also have titles such as director of data governance, director of data quality, and director of analytics.
• The head of your data governance program works with all stakeholders and partners to ensure there is continuous enterprise governance alignment and oversight and to drive the program's direction.
• While key stakeholders from the business and IT will play vital data governance roles, the head of data governance steers the various components, stakeholders, and initiatives, and provides oversight of the overall program.
• Vital data governance roles include: data owners, data stewards, data custodians, data governance steering committee (or your organisation's equivalent), and any data governance working group(s).

The role of the CDO: the voice of data

The office of the chief data officer (CDO):

• Has a cross-organisational vision and strategy for data.
• Owns and drives the data strategy; ensures it supports the overall organisational strategic direction and business goals.
• Leads the organisational data initiatives, including data governance
• Is accountable for the policy, strategy, data standards, and data literacy necessary for the organisation to operate effectively.
• Educates users and leaders about what it means to be 'data-driven.'
• Builds and fosters a culture of data excellence.

'Compared to most of their C-suite colleagues, the CDO is faced with a unique set of problems. The role is still being defined. The chief data officer is bringing a new dimension and focus to the organisation: "data." '
– Carruthers and Jackson, 2020

Who does the CDO report to?

• The CDO should be a true C- level executive.
• Where the organisation places the CDO role in the structure sends an important signal to the business about how much it values data.

'The title matters. In my opinion, you can't have a CDO without executive authority. Otherwise no one will listen.'

– Anonymous European CDO

'The reporting structure depends on who's the 'glue' that ties together all these uniquely skilled individuals.'

– John Kemp, Senior Director, Executive Services, Info-Tech Research Group

Data Ownership & Stewardship

Who are best suited to be data owners?

• Wherever they may sit in your organisation, data owners will typically have the highest stake in that data.
• Data owners needs to be suitably senior and have the necessary decision-making power.
• They have the highest interest in the related business data domain, whether they are the head of a business unit or the head of a line of business that produces data or consumes data (or both).
• If they are neither of these, it's unlikely they will have the interest in the data (in terms of its quality, protection, ethical use, and handling, for instance) necessary to undertake and adopt the role effectively.

Data owners are typically senior business leaders with the following characteristics:

• Positioned to accept accountability for their data domain.
• Hold authority and influence to affect change, including across business processes and systems, needed to improve data quality, use, handling, integration, etc.
• Have access to a budget and resources for data initiatives such as resolving data quality issues, data cleansing initiatives, business data catalogue build, related tools and technology, policy management, etc.
• Hold the influence needed to drive change in behaviour and culture.
• Act as ambassadors of data and its value as an organisational strategic asset.

Right-size your data governance organisational structure

• Most organisations strive to identify roles and responsibilities at a strategic, and operational level. Several factors will influence the structure of the program such as the focus of the data governance project as well as the maturity and size of the organisation.
• Your data governance structure has to work for your organisation, and it has to evolve as the organisation evolves.
• Formulate your blend of data governance roles, committees, councils, and cross-functional groups, that make sense for your organisation.
• Your data governance organisational structure should not add complexity or bureaucracy to your organisation's data landscape; it should support and enable your principle of treating data as an asset.

There is no one-size-fits-all data governance organisational structure.

Critical roles and responsibilities for data governance

Data Governance Working Groups

Data governance working groups:

• Are cross-functional teams
• Deliver on data governance projects, initiatives, and ad hoc review committees.

Data Stewards

Traditionally, data stewards:

• Serve on an operational level addressing issues related to adherence to standards/procedures, monitoring data quality, raising issues identified, etc.
• Are responsible for managing access, quality, escalating issues, etc.

Data Custodians

• Traditionally, data custodians:

• Serve on an operational level addressing issues related to data and database administration.
• Support the management of access, data quality, escalating issues, etc.
• Are SMEs from IT and database administration.

Example: Business capabilities to data owner and data stewards mapping for a selected data domain

Info-Tech Insight

Your organisation's value streams and the associated business capabilities require effectively governed data. Without this, you face elevated operational costs, missed opportunities, eroded stakeholder satisfaction, and exposure to increased business risk.

Enabling business capabilities with data governance role definitions

Operating Model

Your operating model is the key to designing and operationalizing a form of data governance that delivers measurable business value to your organisation.

'Generate excitement for data: When people are excited and committed to the vision of data enablement, they're more likely to help ensure that data is high quality and safe.' – Petzold, et al., 2020

Operating Model

Defining your data governance operating model will help create a well-oiled program that sustainably delivers value to the organisation and manages risks while building and fostering a culture of data excellence along the way. Some organisations are able to establish a formal data governance office, whether independent or attached to the office of the chief data officer. Regardless of how you are organised, data governance requires a home, a leader, and an operating model to ensure its sustainability and evolution.

Examples of focus areas for your operating model:

• Delivery: While there are core tenets to every data governance program, there is a level of variability in the implementation of data governance programs across organisations, sectors, and industries. Every organisation has its own particular drivers and mandates, so the level and rigour applied will also vary.

The key is to determine what style will work best in your organisation, taking into consideration your organisational culture, executive leadership support (present and ongoing), catalysts such as other enterprise-wide transformative and modernisation initiatives, and/or regulatory and compliances drivers.

• Communication: Communication is vital across all levels and stakeholder groups. For instance, there needs to be communication from the data governance office up to senior leadership, as well as communication within the data governance organisation, which is typically made up of the data governance steering committee, data governance council, executive sponsor/champion, data stewards, and data custodians and working groups.

Furthermore, communication with the wider organisation of data producers, users, and consumers is one of the core elements of the overall data governance communications plan.

Communication is vital for ensuring acceptance of new processes, rules, guidelines, and technologies by all data producers and users as well as for sharing success stories of the program.

Operating Model

Tie the value of data governance and its initiatives back to the business capabilities that are enabled.

'Leading organisations invest in change management to build data supporters and convert the sceptics. This can be the most difficult part of the program, as it requires motivating employees to use data and encouraging producers to share it (and ideally improve its quality at the source)[.]' – Petzold, et al., 2020

Operating Model

Examples of focus areas for your operating model (continued):

• Change management and issue resolution: Data governance initiatives will very likely bring about a level of organisational disruption, with governance recommendations and future state requiring potentially significant business change. This may include a redesign of a substantial number of data processes affecting various business units, which will require tweaking the organisation's culture, thought processes, and procedures surrounding its data.

Preparing people for change well in advance will allow them to take the steps necessary to adapt and reduce potential confrontation. By planning for and efficiently communicating any changes that a data governance initiative may bring, many initial issues can be resolved from the outset.

Attempting to implement change without an effective communications plan can result in disagreements over data control and stalemates between stakeholder units. The recommendations of the governance group must reflect the needs of all stakeholders or there will be pushback.

• Performance measuring, monitoring and reporting: Measuring and reporting on performance, successes, and realisation of tangible business value are a must for sustaining, growing, and scaling your data governance program.

Aligning your data governance to the organisation's value realisation activities enables you to leverage the KPIs of those business capabilities to demonstrate tangible and measurable value. Use terms and language that will resonate with your senior business leadership.

Info-Tech Tip:

Launching a data governance program will bring with it a level of disruption to the culture of the organisation. That disruption doesn't have to be detrimental if you are prepared to manage the change proactively and effectively.

Policies, Procedures & Standards

'Data standards are the rules by which data are described and recorded. In order to share, exchange, and understand data, we must standardise the format as well as the meaning.' – U.S. Geological Survey

Policies, Procedures & Standards

• When defining, updating, or refreshing your data policies, procedures, and standards, ensure they are relevant, serve a purpose, and/or support the use of data in the organisation.
• Avoid the common pitfall of building out a host of policies, procedures, and standards that are never used or followed by users and therefore don't bring value or serve to mitigate risk for the organisation.
• Data policies can be thought of as formal statements and are typically created, approved, and updated by the organisation's data decision-making body (such as a data governance steering committee).
• Data standards and procedures function as actions, or rules, that support the policies and their statements.
• Standards and procedures are designed to standardise the processes during the overall data lifecycle. Procedures are instructions to achieve the objectives of the policies. The procedures are iterative and will be updated with approval from your data governance committee as needed.
• Your organisation's data policies, standards, and procedures should not bog down or inhibit users; rather, they should enable confident data use and handling across the overall data lifecycle. They should support more effective and seamless data capture, integration, aggregation, sharing, and retention of data in the organisation.

Examples of data policies:

• Data Classification Policy
• Data Retention Policy
• Data Entry Policy
• Data Backup Policy
• Data Provenance Policy
• Data Management Policy

See Info-Tech's Data Governance Policy Template: This policy establishes uniformed data governance standards and identifies the shared responsibilities for assuring the integrity of the data and that it efficiently and effectively serves the needs of your organisation.

Data Domain Documentation

Select the correct granularity for your business need

Sources: Dataversity; Atlan; Analytics8

Data Domain Documentation Examples

Data Culture

'Organisational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes.' – Petzold, et al., 2020

A healthy data culture is key to amplifying the power of your data and to building and sustaining an effective data governance program.

What does a healthy data culture look like?

• Everybody knows the data.
• Everybody trusts the data.
• Everybody talks about the data.

Building a culture of data excellence.

Leverage Info-Tech's Data Culture Diagnostic to understand your organisation's culture around data.

Contact your Info-Tech Account Representative for more information on the Data Culture Diagnostic

Cultivating a data-driven culture is not easy

'People are at the heart of every culture, and one of the biggest challenges to creating a data culture is bringing everyone into the fold.' – Lim, Alation

It cannot be purchased or manufactured,

It must be nurtured and developed,

And it must evolve as the business, user, and data landscapes evolve.

'Companies that have succeeded in their data-driven efforts understand that forging a data culture is a relentless pursuit, and magic bullets and bromides do not deliver results.' – Randy Bean, 2020

Hallmarks of a data-driven culture

There is a trusted, single source of data the whole company can draw from.

There's a business glossary and data catalogue and users know what the data fields mean.

Users have access to data and analytics tools. Employees can leverage data immediately to resolve a situation, perform an activity, or make a decision – including frontline workers.

Data literacy, the ability to collect, manage, evaluate, and apply data in a critical manner, is high.

Data is used for decision making. The company encourages decisions based on objective data and the intelligent application of it.

A data-driven culture requires a number of elements:

• High-quality data
• Broad access and data literacy
• Data-driven decision-making processes
• Effective communication

Data Literacy

Data literacy is an essential part of a data-driven culture.

• Building a data-driven culture takes an ongoing investment of time, effort, and money.
• This investment will not realise its full return without building up the organisation's data literacy.
• Data literacy is about filling data knowledge gaps across all levels of the organisation.
• It's about ensuring all users – senior leadership right through to core users – are equipped with appropriate levels of training, skills, understanding, and awareness around the organisation's data and the use of associated tools and technologies. Data literacy ensures users have the data they need and they know how to interpret and leverage it.
• Data literacy drives the appetite, demand, and consumption for data.
• A data-literate culture is one where the users feel confident and skilled in their use of data, leveraging it for making informed or evidence-based decisions and generating insights for the organisation.

Data Management

• Data governance serves as an enabler to all of the core components that make up data management:
  • Data quality management
  • Data architecture management
  • Data platform
  • Data integration
  • Data operations management
  • Data risk management
  • Reference and master data management (MDM)
  • Document and content management
  • Metadata management
  • Business intelligence (BI), reporting, analytics and advanced analytics, artificial intelligence (AI), machine learning (ML)
• Key tools such as the business data glossary and data catalogue are vital for operationalizing data governance and in supporting data management disciplines such as data quality management, metadata management, and MDM as well as BI, reporting, and analytics.

Enterprise Projects & Services

• Data governance serves as an enabler to enterprise projects and services that require, use, share, sell, and/or rely on data for their viability and, ultimately, their success.
• Folding or embedding data governance into the organisation's project management function or project management office (PMO) serves to ensure that, for any initiative, suitable consideration is given to how data is treated.
• This may include defining parameters, following standards and procedures around bringing in new sources of data, integrating that data into the organisation's data ecosystem, using and sharing that data, and retaining that data post-project completion.
• The data governance function helps to identify and manage any ethical issues, whether at the start of the project and/or throughout.
• It provides a foundation for asking relevant questions as it relates to the use or incorporation of data in delivering the specific project or service. Do we know where the data obtained from? Do we have rights to use that data? Are there legislations, policies, or regulations that guide or dictate how that data can be used? What are the positive effects, negative impacts, and/or risks associated with our intended use of that data? Are we positioned to mitigate those risks?
• Mature data governance creates organisations where the above considerations around data management and the ethical use and handling of data is routinely implemented across the business and in the rollout and delivery of projects and services.

Data Privacy & Security

• Data governance supports the organisation's data privacy and security functions.
• Key tools include the data classification policy and standards and defined roles around data ownership and data stewardship. These are vital for operationalizing data governance and supporting data privacy, security, and the ethical use and handling of data.
• While some organisations may have a dedicated data security and privacy group, data governance provides an added level of oversight in this regard.
• Some of the typical checks and balances include ensuring:
  • There are policies and procedures in place to restrict and monitor staff's access to data (one common way this is done is according to job descriptions and responsibilities) and that these comply with relevant laws and regulations.
  • There's a data classification scheme in place where data has been classified on a hierarchy of sensitivity (e.g. top secret, confidential, internal, limited, public).
  • The organisation has a comprehensive data security framework, including administrative, physical, and technical procedures for addressing data security issues (e.g. password management and regular training).
  • Risk assessments are conducted, including an evaluation of risks and vulnerabilities related to intentional and unintentional misuse of data.
  • Policies and procedures are in place to mitigate the risks associated with incidents such as data breaches.
  • The organisation regularly audits and monitors its data security.

Ethical Use & Handling of Data

Data governance will support your organisation's ethical use and handling of data by facilitating definition around important factors, such as:

• What are the various data assets in the organisation and what purpose(s) can they be used for? Are there any limitations?
• Who is the related data owner? Who holds accountability for that data? Who will be answerable?
• Where was the data obtained from? What is the intended use of that data? Do you have rights to use that data? Are there legislations, policies, or regulations that guide or dictate how that data can be used?
• What are the positive effects, negative impacts, and/or risks associated with the use of that data?

Ethical Use & Handling of Data

• Data governance serves as an enabler to the ethical use and handling of an organisation's data.
• The Open Data Institute (ODI) defines data ethics as: 'A branch of ethics that evaluates data practices with the potential to adversely impact on people and society – in data collection, sharing and use.'
• Data ethics relates to good practice around how data is collected, used and shared. It's especially relevant when data activities have the potential to impact people and society, whether directly or indirectly (Open Data Institute, 2019).
• A failure to handle and use data ethically can negatively impact an organisation's direct stakeholders and/or the public at large, lead to a loss of trust and confidence in the organisation's products and services, lead to financial loss, and impact the organisation's brand, reputation, and legal standing.
• Data governance plays a vital role is building and managing your data assets, knowing what data you have, and knowing the limitations of that data. Data ownership, data stewardship, and your data governance decision-making body are key tenets and foundational components of your data governance. They enable an organisation to define, categorise, and confidently make decisions about its data.

Step 2.2

Gauge Your Organisation's Current Data Culture

Activities

2.2.1 Gauge Your Organisation's Current Data Culture

This step will guide you through the following activities:

• Conduct a data culture survey or leverage Info-Tech's Data Culture Diagnostic to increase your understanding of your organisation's data culture

Outcomes of this step

• An understanding of your organisational data culture