Besides the small introduction, subscribers and consulting clients within this management domain have access to:
Data should be at the foundation of your organization’s evolution. The transformational insights that executives and decision makers are constantly seeking to leverage can be unlocked with a data strategy that makes high-quality, trusted, and relevant data readily available to the users who need it.
This template will help you gather insights around stakeholder business goals and objectives, current data consumption practices, the types or domains of data that are important to them in supporting their business capabilities and initiatives, the challenges they face, and opportunities for data from their perspective.
Data strategy optimization anchored in a value proposition will ensure that the data strategy focuses on driving the most valuable and critical outcomes in support of the organization’s enterprise strategy. The template will help you facilitate deep-dive sessions with key stakeholders for building use cases that are of demonstrable value not only to their relevant lines of business but also to the wider organization.
Bring data to the C-suite by creating the Chief Data Officer role. This position is designed to bridge the gap between the business and IT by serving as a representative for the organization's data management practices and identifying how the organization can leverage data as a competitive advantage or corporate asset.
Use this template to document and formulate your data strategy. Follow along with the sections of the blueprint Build a Robust and Comprehensive Data Strategy and complete the template as you progress.
Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Establish the business context for the business strategy.
Substantiates the “why” of the data strategy.
Highlights the organization’s goals, objectives, and strategic direction the data must align with.
1.1 Data Strategy 101
1.2 Intro to Tech’s Data Strategy Framework
1.3 Data Strategy Value Proposition: Understand stakeholder’s strategic priorities and the alignment with data
1.4 Discuss the importance of vision, mission, and guiding principles of the organization’s data strategy
1.5 Understand the organization’s data culture – discuss Data Culture Survey results
1.6 Examine Core Value Streams of Business Architecture
Business context; strategic drivers
Data strategy guiding principles
Sample vision and mission statements
Data Culture Diagnostic Results Analysis
Build use cases of demonstrable value and understand the current environment.
An understanding of the current maturity level of key capabilities.
Use cases that represent areas of concern and/or high value and therefore need to be addressed.
2.1 Conduct key business stakeholder interviews to initiate the build of high-value business-data cases
Initialized high-value business-data cases
Build out a future state plan that is aimed at filling prioritized gaps and that informs a scalable roadmap for moving forward on treating data as an asset.
A target state plan, formulated with input from key stakeholders, for addressing gaps and for maturing capabilities necessary to strategically manage data.
3.1 Understand the current data environment: data capability assessment
3.2 Understand the current data practice: key data roles, skill sets; operating model, organization structure
3.3 Plan target state data environment and data practice
Data capability assessment and roadmapping tool
Consolidate business and data needs with consideration of external factors as well as internal barriers and enablers to the success of the data strategy. Bring all the outputs together for crafting a robust and comprehensive data strategy.
A consolidated view of business and data needs and the environment in which the data strategy will be operationalized.
An analysis of the feasibility and potential risks to the success of the data strategy.
4.1 Analyze gaps between current- and target-state
4.2 Initiate initiative, milestone and RACI planning
4.3 Working session with Data Strategy Owner
Data Strategy Next Steps Action Plan
Relevant data strategy related templates (example: data practice patterns, data role patterns)
Initialized Data Strategy on-a-Page
"In the dynamic environment in which we operate today, where we are constantly juggling disruptive forces, a well-formulated data strategy will prove to be a key asset in supporting business growth and sustainability, innovation, and transformation.
Your data strategy must align with the organization’s business strategy, and it is foundational to building and fostering an enterprise-wide data-driven culture."
Crystal Singh,
Director – Research and Advisory
Info-Tech Research Group
Formulate a data strategy that stitches all of the pieces together to better position you to unlock the value in your data:
Your data strategy is the vehicle for ensuring data is poised to support your organization’s strategic objectives.
The dynamic marketplace of today requires organizations to be responsive in order to gain or maintain their competitive edge and place in their industry.
Organizations need to have that 360-degree view of what’s going on and what’s likely to happen.
Disruptive forces often lead to changes in business models and require organizations to have a level of adaptability to remain relevant.
To respond, organizations need to make decisions and should be able to turn to their data to gain insights for informing their decisions.
A well-formulated and robust data strategy will ensure that your data investments bring you the returns by meeting your organization’s strategic objectives.
Organizations need to be in a position where they know what’s going on with their stakeholders and anticipate what their stakeholders’ needs are going to be.
Most organizations today will likely have some form of data management in place, supported by some of the common roles such as DBAs and data analysts.
Most will likely have a data architecture that supports some form of reporting.
Some may even have a chief data officer (CDO), a senior executive who has a seat at the C-suite table.
These are all great assets as a starting point BUT without a cohesive data strategy that stitches the pieces together and:
you’re missing the mark – you are not fully leveraging the incredible value of your data.
Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions
Your data strategy needs to align with your organizational strategy.
Main Organizational Strategic Drivers:
“The companies who will survive and thrive in the future are the ones who will outlearn and out-innovate everyone else. It is no longer ‘survival of the fittest’ but ‘survival of the smartest.’ Data is the element that both inspires and enables this new form of rapid innovation.” – Joel Semeniuk, 2016
The transformational insights that executives are constantly seeking to leverage can be unlocked with a data strategy that makes high-quality, well-integrated, trustworthy, relevant data readily available to the business users who need it.
Whether hoping to gain a better understanding of your business, trying to become an innovator in your industry, or having a compliance and regulatory mandate that needs to be met, any organization can get value from its data through a well-formulated, robust, and cohesive data strategy.
According to a leading North American bank, “More than one petabyte of new data, equivalent to about 1 million gigabytes” is entering the bank’s systems every month. – The Wall Street Journal, 2019
“Although businesses are at many different stages in unlocking the power of data, they share a common conviction that it can make or break an enterprise.”– Jim Love, ITWC CIO and Chief Digital Officer, IT World Canada, 2018
The expression “Data is an asset” or any other similar sentiment has long been heard.
With such hype, you would have expected data to have gotten more attention in the boardrooms. You would have expected to see its value reflected on financial statements as a result of its impact in driving things like acquisition, retention, product and service development and innovation, market growth, stakeholder satisfaction, relationships with partners, and overall strategic success of the organization.
The time has surely come for data to be treated as the asset it is.
“Paradoxically, “data” appear everywhere but on the balance sheet and income statement.”– HBR, 2018
“… data has traditionally been perceived as just one aspect of a technology project; it has not been treated as a corporate asset.”– “5 Essential Components of a Data Strategy,” SAS
According to Anil Chakravarthy, who is the CEO of Informatica and has a strong vantage point on how companies across industries leverage data for better business decisions, “what distinguishes the most successful businesses … is that they have developed the ability to manage data as an asset across the whole enterprise.”– McKinsey & Company, 2019
Data is being touted as the oil of the digital era…
But just like oil, if left unrefined, it cannot really be used.
"Data is the new oil." – Clive Humby, Chief Data Scientist
Source: Joel Semeniuk, 2016
Enter your data strategy.
Data is being perceived as that key strategic asset in your organization for fueling innovation and transformation.
Your data strategy is what allows you to effectively mine, refine, and use this resource.
“The world’s most valuable resource is no longer oil, but data.”– The Economist, 2017
“Modern innovation is now dependent upon this data.”– Joel Semeniuk, 2016
“The better the data, the better the resulting innovation and impact.”– Joel Semeniuk, 2016
Leveraging data as a strategic asset for the benefit of citizens.
Source: Privy Council Office, Government of Canada, 2018
Leveraging data to boost traditional profit and loss levers, find new sources of growth, and deliver the digital bank.
A European bank “turned to machine-learning algorithms that predict which currently active customers are likely to reduce their business with the bank.” The resulting understanding “gave rise to a targeted campaign that reduced churn by 15 percent” (McKinsey & Company, 2017).
A leading Canadian bank has built a marketplace around their data – they have launched a data marketplace where they have productized the bank’s data. They are providing data – as a product – to other units within the bank. These other business units essentially represent internal customers who are leveraging the product, which is data.
Through the use of data and advanced analytics, “a top bank in Asia discovered unsuspected similarities that allowed it to define 15,000 microsegments in its customer base. It then built a next-product-to-buy model that increased the likelihood to buy three times over.” Several sets of big data were explored, including “customer demographics and key characteristics, products held, credit-card statements, transaction and point-of-sale data, online and mobile transfers and payments, and credit-bureau data” (McKinsey & Company, 2017).
Leveraging data and analytics to prevent deadly infections
The fifth-largest health system in the US and the largest hospital provider in California uses a big data and advanced analytics platform to predict potential sepsis cases at the earliest stages, when intervention is most helpful.
Using the Sepsis Bio-Surveillance Program, this hospital provider monitors 120,000 lives per month in 34 hospitals and manages 7,500 patients with potential sepsis per month.
Collecting data from the electronic medical records of all patients in its facilities, the solution uses natural language processing (NLP) and a rules engine to continually monitor factors that could indicate a sepsis infection. In high-probability cases, the system sends an alarm to the primary nurse or physician.
Since implementing the big data and predictive analytics system, this hospital provider has seen a significant improvement in the mortality and the length of stay in ICU for sepsis patients.
At 28 of the hospitals which have been on the program, sepsis mortality rates have dropped an average of 5%.
With patients spending less time in the ICU, cost savings were also realized. This is significant, as sepsis is the costliest condition billed to Medicare, the second costliest billed to Medicaid and the uninsured, and the fourth costliest billed to private insurance.
Source: SAS, 2019
Leveraging data to better understand customer preferences, predict purchasing, drive customer experience, and optimize supply and demand planning.
Netflix is an example of a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects large amounts of data. If you are a subscriber, you are likely familiar with their suggestions messages of the next series or movie you should catch up on. These suggestions are based on your past search data and watch data. This data provides Netflix with insights into your interests and preferences for viewing (Mentionlytics, 2018).
“For the retail industry, big data means a greater understanding of consumer shopping habits and how to attract new customers.”– Ron Barasch, Envestnet | Yodlee, 2019
“We’re the converted … We see the value in data. The battle is getting executive teams to see it our way.”– Ted Maulucci, President of SmartONE Solutions Inc. IT World Canada, 2018
Info-Tech’s IT Maturity Ladder denotes the different levels of maturity for an IT department and its different functions. What is the current state of your data management capability?
You are best positioned to successfully execute on a data strategy if you are currently at or above the Trusted Operator level. If you find yourself still at the Unstable or Firefighter stage, your efforts are best spent on ensuring you can fulfill your day-to-day data and data management demands. Improving this capability will help build a strong data management foundation.
“Organizational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes.”– McKinsey, 2018
Some say it’s the new oil. Or the currency of the new business landscape. Others describe it as the fuel of the digital economy. But we don’t need platitudes — we need real ways to extract the value from our data. – Jim Love, CIO and Chief Digital Officer, IT World Canada, 2018
Our practical step-by-step approach helps you to formulate a data strategy that delivers business value.
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