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data analytics

Data Analytics – Characteristics and Strategies

Having an effective data and analytics strategy is more critical than ever for an organization’s success, as new uses for data make up a significant portion of an organization’s ability to differentiate themselves from their competitors. Data and analytics (D&A) leaders must create a strategy that improves how data drives better decision making to lead to enterprise-wide success.

The typical approach to creating a data and analytics strategy is starting with a multiyear governance effort based on the misconception that data must have the perfect quality and governance before it can be useful. These efforts ultimately end before generating returns because (a) the process takes too long and funding is reallocated, or (b) frustrated by lack of progress, the governance body loses engagement too early. A targeted, iterative data and analytics strategy that is tied to business outcomes is the solution for improving organizational decision making and demonstrating the importance of the data and analytics function.

Definitive Strategy

The data and analytics strategy sets the context for the operating model, while the operating model provides inspiration to the strategy. The capabilities and deficits are the connective tissue between the two. 

The strategy itself needs to demonstrate how the function will succeed in (a) supporting enterprise purpose and abilities, (b) establishing and maintaining relationships and outcomes, and (c) providing ways for the enterprise to create value. A strong data and analytics strategy is made up of the data-driven vision, value propositions and stakeholder outcomes. While the vision is more fixed, value propositions and stakeholder outcomes are likely to shift based on feedback loops.

To get to the strategy though, you will first need to have a defined vision for your D&A function. A good vision will demonstrate what you will achieve for your stakeholders internally and/or externally. Craft your vision using the following formula: We contribute to (strategic goal) for (stakeholder X, Y, Z) by doing (1, 2, 3). Once your vision is established, you can move on to the stakeholder outcomes and value propositions that will combine with the vision to establish your strategy.

A good data and analytics strategy covers the following components that directly speak to stakeholder outcomes and value propositions:

  • Why the strategy is being developed. 

Discuss the internal factors (including business goals) and external factors (changes in the market, new customer demand) driving the need for the strategy.

  • What actions need to be taken. 

Connect the why to the necessary improvements. These improvements link strategy to the business and underlying data capabilities.

  • How the strategy will be operationalized. 

Build a presentation that includes a contextualized roadmap relevant to the audience. The presentation might also include operating models, budgets, and initiative drilldowns if it is aimed at the data and analytics team. Be sure to include who will be involved in each level of the transformation, what will be expected of them and when they can anticipate the changes to take effect by laying out a comprehensive timeline.

  • Where will the organization see success?

Create comprehensive stories explaining what success looks like with either a qualitative description of outcomes or quantitative metrics.

The roadmap in the following Figure includes the “When” and the “Who” along with high-level activities. The row at the bottom clearly states which business capabilities will be impacted in each quarter so that when you are presenting the strategy to leadership, each person can instantly see what they will gain along with their responsibilities in a given time period. Assigning responsibilities at this stage is important because it creates a sense of ownership and participation instead of instruction.

Sample Strategy Roadmap

After mapping out your data and analytics investments, be sure to also acknowledge the risks and assumptions in the strategy. Things like talent, funding and other resources need to be highlighted for business partners to see where they can support the execution of the strategy. You may also include operating models, budgets and initiative drill-downs here, depending on the audience, how much change is required and whether they are crucial to understanding how the strategy will succeed.

Data & Analytics Metrics

Metrics are an important part of your plan because they will show the progress and success of your plans. When determining the metrics for strategic plans, many make the mistake of starting with the question “What can I measure?” This poses a challenge because it establishes metrics from the current region, not what you hope to achieve with your strategic plans. Instead, work backwards by asking yourself “What would success look like for this purpose?” Working back to success will lead you to think about the state of quality end, which will then determine the most important, immeasurable ways.

The role of data and analytics is changing, from being a stand-alone discipline to a digital strategy or revolution. Kanoo Elite with its years of Data Analytics experience, provides expert consultation to Data and Analytics leaders to create a strategy and performance model that conceives data driven business opportunities and organizes business action. We also provide additional resources to assist you in communicating and marketing the program effectively to various stakeholder groups and implementing the strategy.

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