Establish an Analytics Operating Model
Accelerate data-driven decision making.
RETIRED CONTENT
Please note that the content on this page is retired. This content is not maintained and may contain information or links that are out of date.Organizations struggle to understand what's involved in the analytics developer lifecycle to generate reusable insights faster.
- 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.
Trust in data-driven decision making goes up with collaboration, engagement, and transparency.
- Firms become more agile when they realize efficiencies in their analytics operating models and can then quickly implement reusable analytics.
- IT becomes more flexible and efficient in understanding the business' data needs and eliminates redundant processes.
- There is a clear path to continues improvement in analytics.
Book Your Workshop
Onsite 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 onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
Module 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: | Outputs: | |
|---|---|---|
| 1.1 | Review the business context. |
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| 1.2 | Understand your analytics needs. |
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| 1.3 | Draft analytics ideas and use cases. |
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| 1.4 | Capture minimum viable analytics. |
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Module 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: | Outputs: | |
|---|---|---|
| 2.1 | Capture your analytics capabilities. |
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| 2.2 | Map capabilities to a hub-and-spoke model. |
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| 2.3 | Document operating model results. |
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Module 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: | Outputs: | |
|---|---|---|
| 3.1 | Discuss your operating model results. |
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| 3.2 | Review your organizational structure’s pros and cons. |
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| 3.3 | Map resources to target structure. |
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| 3.4 | Brainstorm initiatives to develop your analytics capabilities. |
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Module 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: | Outputs: | |
|---|---|---|
| 4.1 | Document your target organizational structure and RACI. |
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| 4.2 | Establish an analytics engagement model. |
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| 4.3 | Develop an analytics communications plan. |
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