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How to Sell Data Analytics to Executives - Part II: Align with the Business

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Read - How to Sell Data Analytics to Executives - Part I: Partner with the Business

In the prior article, we discussed how to create an effective partnership with business executives by learning to “speak” their language and delivering quick wins. We focused largely on informal techniques, such as taking executives to lunch, learning the business before speaking, and letting business managers pitch technical projects. 

But data leaders also have to master formal channels of communications. They need to present an annual strategy, roadmap, and budget, and estimate the return on the company’s investment in data analytics programs and projects. To get funding, data leaders need to align their proposals with the organization’s stated strategy and goals, as well as the unique needs of influential division heads. Specifically, this requires that data leaders understand the company’s strategy, identify compelling use cases that appeal to key executives, and calculate the ROI of those use cases. 

1. Align with Corporate Strategy

To align with corporate strategy, data leaders first need to understand the strategy. That is harder than it seems if executives haven’t updated the strategy recently or events, such as a new CEO, 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 should peruse the company’s annual report, investment filings, and any memo or presentation given by the president or other executives. With small- or mid-sized companies, it’s possible to follow up this research by taking an executive to lunch or grabbing 10 minutes in an operational review meeting or budget presentation. Although time is short, a data leader is likely to get a few juicy morsels upon which to hang 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. 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, and 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.”

Balanced Scorecard. Next, plot the CSFs on a strategy map with the four balanced scorecard perspectives: financial, customer, internal (operations), learning and 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. (See figure 1.) 

Figure 1. Informal Strategy Map

2. 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 speak their language. 

More importantly, 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 is important to executives and heightens your chances of selling a data strategy to executives. It also helps you avoid pushing use cases and technical initiatives that will hit a dead end.  See figure 2.) 

Figure 2. Brainstorming Strategy-Aligned Use Cases

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 on what the use case is and a prioritization score (“High” “Medium” “Low”). From there, highlight the top three or four use cases based on team consensus. Prioritizing by stakeholders helps ensure a broad-based set of use cases and makes it easier to discuss which department holds the most clout. (See figure 3.)

Figure 3. Prioritizing Use Cases

From there, the team should flesh out requirements for top use cases, reprioritize them by risks and rewards, and then identify 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 roadmap 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 executives like this simple roadmap because it’s easy to read and see exactly when their departmental needs will be met. This helps build acceptance for the plan. (See figure 4.)

Figure 4. High-Level, Subject-Oriented Roadmap

3. Evaluate ROI

To sell a data strategy to business executives requires speaking the language of money—or more specifically, return on investment. Although it’s challenging to calculate the ROI from better decisions and plans, the benefits are worth it. The exercise of 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. 

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 a business question or put together a budget 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 more likely to see the benefits and revenue gains from a new Customer 360 implementation that improves customer service, marketing, and sales.  (See figure 5).

Figure 5. Calculating the ROI of Analytics

From Analytics ROI: How to Measure and Maximize the Value of Analytics

Today, most leading data analytics programs estimate ROI before a project begins. This injects a measure of discipline and accountability that ensures project success. Such estimations help companies avoid projects with low potential ROI and give greater urgency to approved projects. 

Accountability for project ROI sends the same message: there is no going back so you better make this succeed.

Hernan Cortes, upon landing in Central America in 1519 told his 600 men “to burn the ships.” Accountability for project ROI sends the same message: there is no going back so you better make this succeed.


To sell to executives, it’s important to think like them and speak their language. The first step is to understand the corporate strategy and engage in strategic thinking exercises. This simplifies the process of creating strategically aligned case studies that are more likely to resonate with business executives and gain budgetary approval. Finally, it’s important to estimate the financial upside of proposed use cases to communicate with executives in a language they understand and win approval for projects.

Read - How to Sell Data and Analytics to Executives - Part III: Deliver a Winning Presentation

Wayne Eckerson

Wayne Eckerson is an internationally recognized thought leader in the business intelligence and analytics field. He is a sought-after consultant and noted speaker who thinks critically, writes clearly and presents...

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