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Note
This article forms part of the Power BI implementation planning series of articles. This series focuses primarily on the Power BI experience within Microsoft Fabric. For an introduction to the series, see Power BI implementation planning.
This article introduces the business intelligence (BI) strategy series of articles. The BI strategy series is targeted at multiple audiences:
Defining your BI strategy is essential to get the most business value from data and analytics. Having a clearly defined BI strategy is important to ensure efforts are aligned with organizational priorities. In some circumstances, it's particularly important.
We recommend that you pay special attention to these articles if your organization is:
In short, this series of articles is about defining a BI strategy. It describes what a BI strategy is, why it's important, and how you can plan your BI strategy. The articles in this series are intended to complement the Fabric adoption roadmap.
Successful adoption and implementation of analytics solutions helps an organization meet their business objectives. To achieve successful adoption and implementation, you need a BI strategy. A BI strategy might sometimes be described as an analytics strategy or becoming data driven.
A BI strategy is a plan to implement, use, and manage data and analytics to better enable your users to meet their business objectives. An effective BI strategy ensures that data and analytics support your business strategy.
Your business strategy should directly inform your BI strategy. As your business objectives evolve, your BI processes and tools might also need to evolve, especially as new data needs arise. New opportunities and insights learned from BI solutions can also lead to changes to your business strategy. Understanding and supporting the relationship between your business and BI strategies is essential in order to make valuable BI solutions, and to ensure that people use them effectively.
The following diagram depicts how a BI strategy supports the business strategy by enabling business users.
The diagram depicts the following concepts.
Item | Description |
---|---|
The business strategy describes how the organization will achieve its business objectives. | |
The business strategy directly informs the BI strategy. The primary purpose of the BI strategy is to support—and potentially inform—the business strategy. | |
The BI strategy is a plan to implement, use, and manage data and analytics. | |
BI objectives define how BI will support the business objectives. BI objectives describe the desired future state of the BI environment. | |
To make progress toward your BI objectives, you identify and describe BI key results that you want to achieve in a specific time period. These key results describe paths to your desired future state. | |
To achieve your BI key results, you plan and implement BI solutions and initiatives. A solution might be developed by a central IT or BI team, or by a member of the community of practice as a self-service solution. | |
The purpose of BI solutions and initiatives is to enable business users to achieve their key results. | |
Business users use BI solutions and initiatives to make informed decisions that lead to effective actions. | |
Business users follow through on the business strategy with their achieved results. They achieve these results by taking the right actions at the right time, which is made possible in part by an effective BI strategy. |
Note
In the objectives and key results (OKRs) framework, objectives are clear, high-level descriptions of what you want to achieve. In contrast, key results are specific, achievable outcomes to measure progress toward one of your objectives.
Further, initiatives or solutions are processes or tools built to help you achieve one or more key results. Solutions address specific data needs for users. A solution can take many forms, such as a data pipeline, a data lakehouse, or a Power BI semantic model or report.
For more about OKRs, see Get to know OKRs (Microsoft Viva Goals).
Consider the following, high-level example for a hypothetical organization.
Area | Example |
---|---|
Business strategy | The organizational objective is to improve customer satisfaction and reduce customer churn. One business strategy to achieve this objective is to reduce the number of late customer deliveries. |
BI strategy | • BI objective: To support the business strategy, the BI objective is to improve the effectiveness of orders and deliveries reporting. • BI key results: To achieve the BI objective, the organization defines specific BI key results for the quarter. One such key result is to reduce the time to produce reports about on-time delivery by 80%, so that reports are available daily, instead of weekly. Another key result is to provide combined inventory and orders data for the largest distribution center. Demand planners can use inventory data to improve delivery planning. • BI solutions and initiatives: To achieve these BI key results, the organization plans BI solutions and initiatives, like implementing automated data pipelines, and a consolidated data lakehouse that stores business-ready orders and inventory data to support reporting and analytics. They enact a training program to enable users to make the most of the newly available data. |
Business users | Enabled by these BI solutions and initiatives, business users can more effectively identify and mitigate potential late deliveries. These solutions result in fewer late deliveries and improved customer satisfaction, allowing the organization to achieve progress toward its business objectives. |
Your BI strategy describes how successful Fabric adoption and Power BI implementation will deliver business value to your organization. However, a BI strategy transcends tools and technologies. While your BI strategy might start small, it can grow to encompass all of your analytical data, tools, and processes when you experience success. Furthermore, the concepts in a BI strategy are also important in a broader data strategy. While a BI strategy is about the use of data and tools for analytical purposes, a data strategy is concerned with the wider management and use of data within the organization. Thus, your BI strategy is a subset of your data strategy, as they share many related concepts.
The following diagram depicts how a BI strategy is a subset of a data strategy, and how they share concepts related to data culture and technology.
The diagram depicts the following concepts.
Item | Description |
---|---|
A data strategy describes the focus areas and objectives for the wider use and management of data in an organization. A data strategy encompasses more than only BI. | |
The BI strategy is a subset of a data strategy. | |
Data culture is important in both a BI strategy and a data strategy. Different data culture areas describe a vision for behaviors, values, and processes that enable people to work effectively with data. An example of a data culture area is data literacy. | |
Technology is important in both a BI strategy and a data strategy. Different technical areas support the business data needs and use cases. An example of a technical area is data visualization. |
A BI strategy can encompass many data culture and technical areas. However, when planning your BI strategy, you should be cautious not to attempt to address too many of these areas at first. A successful BI strategy starts small. It focuses on a few focus areas and broadens scope over time, ensuring consistent progress. Later, as you experience sustainable success with your BI strategy, it can incrementally evolve to encompass more areas.
Important
This series of BI strategy articles focuses on the Power BI workload in Fabric. However, planning a BI strategy is a technology-agnostic exercise. As such, the concepts described in the articles can apply irrespective of your chosen BI tools and technologies.
There are many ways to define a BI strategy. Typically, when you define a BI strategy, you begin by identifying the focus areas for which you describe your BI objectives. Based upon these objectives, you define time-bound, prioritized actions in key results. To achieve these key results, you build solutions and enact specific key initiatives. You then incrementally scale your BI strategy to encompass more focus areas and additional objectives as you experience success.
The following diagram depicts how you can define your BI strategy at three different planning levels, as depicted in the following diagram.
The diagram depicts the following three planning levels.
Item | Description |
---|---|
Strategic planning: You begin by defining your strategic BI focus areas and objectives, and how they support your business strategy. These BI objectives are high-level descriptions of what you want to achieve and why. | |
Tactical planning: You then identify your specific BI key results. These key results are specific, measurable, short-term actions that describe how you'll make progress toward your long-term, strategic BI objectives. | |
Solution planning: The BI solutions and initiatives that you create should be a direct result of tactical planning. These solutions enable you to achieve your BI key results and make progress toward your BI objectives. |
Important
Defining a BI strategy requires prioritization, planning, and active involvement from many teams and individuals across your organization.
The following high-level, hypothetical example explains how you can transition from business objectives to BI objectives. It then explains how to transition from BI objectives to key results, and then to BI solutions and initiatives.
In this example, the organization has set an objective to increase sales effectiveness. One strategy the business uses to achieve this objective is to sell more high-margin products to its top customers.
To achieve the business strategy, the organization wants the salespeople to adopt data-driven decision making. To this end, the BI team works with the sales teams to understand their data needs, and to define long-term, strategic BI focus areas and objectives.
In this example, the BI focus areas and objectives are:
Note
In this example, many other factors might be important. However, the organization has identified these particular focus areas and objectives to support the business strategy.
To achieve their BI objectives, the BI team conducts tactical planning to identify and describe their short-term key results. The BI team creates an introductory data literacy program for the salespeople. Also, the BI team drafts a user enablement plan and an accountability plan for salespeople who want to perform self-service analytics. These plans allow the salespeople to request access to data after they've completed specific training materials and signed a self-service user acknowledgment.
In this example, the BI key results in the first quarter are:
To achieve its key results, the organization aims to enact the following key initiatives, or design and deploy the following BI solutions.
Note
This example describes a simple scenario for the purpose of explaining the three planning levels of a BI strategy. In reality, your strategic BI objectives, key results, and key initiatives and solutions are likely to be more complex.
Your BI strategy should evolve as you scale and as your organization experiences change. For these reasons, planning your BI strategy is a continuous, iterative process.
Iteratively planning your BI strategy is beneficial for two reasons.
It's unrealistic to expect all-encompassing, long-term planning to survive beyond 12-18 months. For instance, attempting to create an exhaustive three to five-year plan can result in over-investment, a failure to keep up with change, and an inability to support changes in your business strategy. Instead, you should define and operationalize your strategies by using iterative approaches, with achievable outcomes in a maximum period of 18 months.
There are many ways to iteratively plan your BI strategy. A common approach is to schedule planning revisions over periods that align with existing planning processes in the organization.
The following diagram depicts recommendations for how you can schedule planning revisions.
The diagram depicts how you can iteratively structure your BI strategy planning the following concepts.
Item | Description |
---|---|
Avoid detailed, long-term planning: Long-term, detailed plans can become outdated as technology and business priorities change. | |
Strategic planning (every 12-18 months): This high-level planning focuses on aligning business objectives and BI objectives. It's valuable to align this strategic planning with other annualized business processes, like budgeting periods. | |
Tactical planning (every 1-3 months): Monthly or quarterly planning sessions focus on evaluating defining the specific, actionable, key results that are time-bound to the planning period. This planning should take iterative business feedback and changes in business or technology into account. | |
Continuous improvement (every month): Monthly sessions focus on feedback and urgent changes that impact ongoing planning. If necessary, decision makers can make decisions, take corrective action, or influence ongoing planning. |
This series of articles presents a structured framework that helps you to plan the three levels of your BI strategy, as depicted in the following diagram.
The diagram shows three levels of BI strategy planning, which are each described in separate articles. We recommend that you read these articles in the following order.
Tip
Before you read the BI strategy articles, we recommend that you're already familiar with the Fabric adoption roadmap. The adoption roadmap describes considerations to achieve Fabric adoption and a healthy data culture. These BI strategy articles build upon the adoption roadmap.
In the next article in this series, learn about BI strategic planning.
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