Building Trust through an Insights Framework

Are you a business decision-maker who references multiple reports to find insights that support a crucial business decision? Is this a cumbersome and time-consuming process? Or, are you responsible for implementing data visualization or advanced analytics solutions that assist the business strategy and promote ease of decision-making? In this effort, you need to ensure that the insights presented in dashboards, reports, and scorecards are objectively the most valuable to the organization. Your chosen KPIs and metrics must seamlessly connect strategy to day-to-day operations.

The moves you make will accelerate the development of your organization’s analytics capabilities from descriptive (What happened?), to diagnostic (Why did it happen?), to predictive (What will happen?), and finally to prescriptive (What should we do?). Along the way, you’re responsible for nurturing trust in the insights presented, blazing the trail to an insights-driven culture.

In our research, “data and technology” is cited as the top transformation area for businesses across industries in 2020 (53 percent of organizations).1 Transforming this capability starts with understanding the insights that can help your organization drive its strategic agenda forward. In this blog, we’ll explore opportunities to distill data for dashboards, scorecards, and reports, ultimately arming you with an approach to unlocking differentiated insights and building trust in analytics.

The “Why” Game

Remember the infamous “Why?” game that children often play? Perhaps you’ve been subjected to it, or maybe you are guilty of frustrating adults with it in the recent past. All annoyances aside, the game has practical utility in helping organizations determine the ideal insights and metrics to present in dashboards or scorecards. For example, one metric that a business team might request is sales over time by product, geography, customer segment, and sales channel:

  • Why? “Because we would like to understand if the changes in sales have been due to seasonality, product mix, geography, customer segment, or sales channel.”
  • Why? “Because we would like to know if we need to make any product mix, marketing, or supply chain changes, or maintain our current course.”
  • Why? “Because one of our strategic priorities is to improve sales by 15 percent this year.”

In this example, we can classify this line of thinking as follows:

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By applying this course of thinking, we ensure that the chosen metric will provide an insight that will help inform data-driven business decisions aligned to strategic priorities.

A Top-Down Alternative

The incessant “why” questioning follows a bottom-up approach that validates whether the metrics and insights presented are indeed viable. An insights framework, on the other hand, involves a top-down approach, starting with the strategic priorities that are often set at the overall organization or department level.

For example, a sales organization might follow a series of steps to develop an insights framework aligned to its strategic priorities:


  1. Understand the organization’s strategic sales priorities, outcomes, or objectives. These goals may include market development, diversification, market penetration, or product development.
  2. Brainstorm the possible business decisions needed to support the strategic priorities, outcomes, or objectives.
  3. Identify the business insights that can inform those decisions.
  4. Define the KPIs and metrics relevant to those insights. In the context of a sales organization, the team might consider sales, revenue, conversion rate, average sales price, number of customers, volume, or volume per sale.
  5. Define the dimensions by which the KPIs can be sliced or filtered. In this example, dimensions could include time, region, product, product category, sales representative, customer segment, and sales channel.
  6. Design the portfolio of dashboards, reports, and scorecards that support the framework.

Examples of Dashboard Visualizations

Depending on the business challenge at hand, you may find it useful to deploy one or both approaches to distilling the insights needed to inform decision-making. In an organization where there are already multiple reports presenting a considerable volume of metrics, both the top-down and bottom-up approaches may be necessary. In an organization that’s newly establishing an insights-driven culture, the top-down approach may be more suitable.

When decision-makers are unsure of the dashboard or report that can help them make well-informed, data-driven decisions, they may question the integrity of the organization’s data and analytics capabilities altogether. Our research shows that trust in insights is one of the core characteristics of an organization that leads the market on analytics. An intentional framework clearly and transparently outlines the “why,” keeps both users and developers informed, presents answers to the most pressing business questions, and bolsters trust and understanding. It's one of the essential building blocks of a sustainable insights-driven culture. It can help analytics leaders play a driving role in aligning data to business strategy by transforming the organization’s analytics capabilities from descriptive to predictive, and ultimately, to prescriptive.

1 September 2019 North Highland-sponsored survey of > 700 business leaders with annual revenues > $1B and that are headquartered in the U.S. or the U.K.