How to Sell a Data Strategy to Business Executives Part 2: Aligning with the Business

Data and analytics leaders have to master formal channels of communication. They need to present an annual strategy, road map, and budget and estimate the return on the company’s investment in data analytics programs and projects. To secure funding for a data strategy, data and analytics leaders need to align their road map with the organization’s stated strategy and goals and the unique needs of influential division heads.

To do that, data leaders need to identify compelling use cases that align with corporate goals and estimate the ROI of those use cases.

Align with Corporate Strategy

To align with corporate strategy, data leaders first need to understand the strategy. That can be harder than it sounds if executives haven’t updated the strategy or if recent events— such as a new CEO, a new competitor, or a pandemic—fundamentally alter it. Whether there is an up-to-date published strategy or not, it’s a good exercise for the data leader to spend time ascertaining the company’s current strategic goals and initiatives:

• Documents and Meetings: To read the strategic tea leaves, a data leader needs to peruse the company’s annual report, investment filings, and any memo or presentation given by the president or other executives. With small or midsize companies, it might be possible to take an executive to lunch or attend an executive strategy review meeting. These efforts might generate a few tidbits to guide or enhance a data strategy.
• Strategy map: When executives are aloof, distant, or somewhat skeptical of data initiatives, the data leader should form a small cross-functional team and create a facsimile of a corporate strategy map. The team needs one or two business analysts who interact frequently with top executives and understand their interests, motivations, and political challenges. For example, we’ve created strategy maps with a small, four-person team in three hours.

This pseudo strategy team can start by articulating a future vision for the company to the best of its ability, followed by goals to achieve that vision, then critical success factors (CSFs) to achieve the goals. The vision is a forward-looking statement, such as “Lead the transformation of the XYZ Device industry into digital, subscription-based solutions.” The goals are measurable targets, such as “Generate more revenue from software subscriptions than sales of hardware.” Critical success factors are new corporate behaviors needed to achieve the goals, such as “Establish a culture of software innovation” and “Improve customer and market knowledge.”

Next, plot the CSFs on a strategy map with the four balanced scorecard perspectives: financial, customer, internal (operations), and learning/growth. Then, brainstorm objectives for each perspective for each CSF. If possible, link the objectives between and within perspectives to create a cause-effect diagram.

Find Compelling Use Cases

The point of creating a strategy map is not to create a corporate strategy that you hand to the executive team—that’s a surefire way to alienate your executive partners! Rather, the goal is to start thinking like a business executive and learn to speak their language. Most important, the strategy map becomes a great way to brainstorm use cases that align with corporate strategy. It ensures that you’ve considered every facet of the business that’s important to executives and heightens your chances of selling a data strategy to them. It also helps you avoid pushing use cases and technical initiatives that will hit a dead end.

Once the team identifies a couple of dozen use cases, it should prioritize them by stakeholder (i.e., department) to ensure every department is represented. Each entry should include a short description to ensure everyone agrees what the use case is and its prioritization score (high, medium, or low). From there, highlight the top three or four use cases based on team consensus. Prioritizing by stakeholder helps ensure a broad-based set of use cases and makes it easier to discuss which department holds the most clout.

From there, the team should flesh out requirements for top use cases, reprioritize them by risks and rewards, and then identify the technical capabilities required to support them. The team should also identify common dimensions and metrics across use cases. Clusters of capabilities and dimensions indicate a path for development.

Finally, the team should create a simple road map by subject area that defines the key use cases and/or stakeholders that will be served each quarter for the next three years. We find that executives like these simple road maps because they’re easy to read and see exactly when their departmental needs will be met. This helps build acceptance for the plan.

Evaluate ROI

To sell a data strategy to business executives requires speaking the language of money— or more specifically, return on investment (ROI). Although it’s challenging to calculate the ROI gained from better decisions and plans, it’s worth trying. Calculating ROI turns a data leader into a businessperson who communicates in terms executives understand. Moreover, with concrete evidence of ROI, executives are much more likely to approve future data projects. The ultimate sales tool for a data leader is a track record of delivering financial results.

Companies employ various techniques for estimating the value of projects. To estimate ROI—as well as calculate it post project—data leaders should enlist a finance person and a business analyst to dig into the details and adhere to an approved financial methodology. Costs are often easier to calculate than upsides. New technical infrastructure—such as master data management or a customer data warehouse—can streamline operations, saving countless hours of data analysts who must piece together data to answer business questions or put together budgets or close the quarterly books. These cost savings can be added up and defended before an executive team.

Although trickier, upsides can be calculated, too, especially if the data team creates high potential use cases aligned with business strategy. Executives are likely to see the benefits and revenue gains from a new Customer 360 implementation that improves customer service, marketing, and sales.

Today, most leading data analytics programs estimate ROI before a project begins. This injects a measure of discipline and accountability that helps project success. Such estimations help companies avoid projects with low potential ROI and give greater urgency to approved projects. Accountability for project ROI sends an important message: there is no going back, so we’d better make this succeed.