- Organizations are struggling to understand what's involved in the analytics developer lifecycle to generate reusable insights faster.
- Discover what it takes to become a citizen analytics developer. Identify the proper way to enable self-serve analytics.
- Self-serve business intelligence/analytics is misunderstood and confusing to the business, especially with regards to the roles and responsibilities of IT and the business.
- End users are dissatisfied due to a lack of access to the data and the absence of a single source of truth.
Our Advice
Critical Insight
Organizations that take data seriously should:
- Decouple processes in which data is separated from business processes and elevate the visibility of the organization's data assets.
- Leverage a secure platform where data can be easily exchanged for insights generation.
- Create density for analytics where resources are mobilized around analytics ideas to generate value.
Analytics is a journey, not a destination. This journey can eventually result in some level of sophisticated AI/machine learning in your organization. Every organization needs to mobilize its resources and enhance its analytics capabilities to quickly and incrementally add value to data products and services. However, most organizations fail to mobilize their resources in this way.
Impact and Result
- Firms become more agile when they realize efficiencies in their analytics operating models and can quickly implement reusable analytics.
- IT becomes more flexible and efficient in understanding the business' data needs and eliminates redundant processes.
- Trust in data-driven decision making goes up with collaboration, engagement, and transparency.
- There is a clear path to continuous improvement in analytics.
Establish an Analytics Operating Model Research & Tools
Start here – read the Executive Brief
Read our concise Executive Brief that outlines Info-Tech’s methodology for assessing the business' analytics needs and aligning your data governance, capabilities, and organizational structure to deliver analytics faster.Besides the small introduction, subscribers and consulting clients within this management domain have access to:
- Establish an Analytics Operating Model – Phases 1-3
1. Define your analytics needs
This phase helps you understand your organization's data landscape and current analytics environment so you gain a deeper understanding of your future analytics needs.
- Establish an Analytics Operating Model – Phase 1: Define Your Analytics Needs
2. Establish an analytics operating model
This phase introduces you to data operating model frameworks and provides a step-by-step guide on how to capture the right analytics operating model for your organization.
- Establish an Analytics Operating Model – Phase 2: Establish an Analytics Operating Model
- Analytics Operating Model Building Tool
3. Implement your operating model
This phase helps you implement your chosen analytics operating model, as well as establish an engagement model and communications plan.
- Establish an Analytics Operating Model – Phase 3: Implement Your Analytics Operating Model
Workshop: Establish an Analytics Operating Model
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.
1 Define Your Analytics Needs
The Purpose
Achieve a clear understanding and case for data analytics.
Key Benefits Achieved
A successful analytics operating model starts with a good understanding of your analytical needs.
Activities
1.1 Review the business context.
1.2 Understand your analytics needs.
1.3 Draft analytics ideas and use cases.
1.4 Capture minimum viable analytics.
Outputs
Documentation of analytics products and services
2 Perform an Analytics Capability Assessment
The Purpose
Achieve a clear understanding of your organization's analytics capability and mapping across organizational functions.
Key Benefits Achieved
Understand your organization's data landscape and current analytics environment to gain a deeper understanding of your future analytics needs.
Activities
2.1 Capture your analytics capabilities.
2.2 Map capabilities to a hub-and-spoke model.
2.3 Document operating model results.
Outputs
Capability assessment results
3 Establish an Analytics Operating Model
The Purpose
Capture the right analytics operating model for your organization.
Key Benefits Achieved
Explore data operating model frameworks.
Capture the right analytics operating model for your organization using a step-by-step guide.
Activities
3.1 Discuss your operating model results.
3.2 Review your organizational structure’s pros and cons.
3.3 Map resources to target structure.
3.4 Brainstorm initiatives to develop your analytics capabilities.
Outputs
Target operating model
4 Implement Your Analytics Operating Model
The Purpose
Formalize your analytics organizational structure and prepare to implement your chosen analytics operating model.
Key Benefits Achieved
Implement your chosen analytics operating model.
Establish an engagement model and communications plan.
Activities
4.1 Document your target organizational structure and RACI.
4.2 Establish an analytics engagement model.
4.3 Develop an analytics communications plan.
Outputs
Reporting and analytics responsibility matrix (RACI)
Analytics engagement model
Analytics communications plan
Analytics organizational chart