Does Your Organization Have A Balanced Data Diet?

Growing up in the eighties, I remember learning about the importance of having a balanced diet. Public service announcements during Saturday morning cartoons encouraged us to have equal servings from each of the following food groups: vegetables, fruits, grains, dairy, and protein foods. Because “You are what you eat,” my generation learned we couldn’t just eat protein or carbohydrates alone to maintain good health. Consuming a wide range of foods from different food groups provided us with the nutrients and energy we needed for endurance, resilience, and clarity of mind.

When it comes to data communication, many organizations have an imbalanced data diet. While data has become an integral focus at most companies, many have unknowingly concentrated their data communication efforts in only one or two areas. Instead of maximizing’s data’s full potential, organizations often limit its impact by over-relying on just a few types of communication. It’s not uncommon to see organizations drowning in dashboards and reports but lacking more meaningful insights and deeper explanation of core issues.

As a result, firms that are information rich but insight poor have developed anemic data cultures with weak data-driven decision-making. To get the full ‘nutritional’ value of their data investments, organizations must reevaluate how they approach data communication and ensure they consume balanced portions of each data communication type.

During different crises such as the Great Depression or World War II, USDA (United States Department of Agriculture) nutritionists offered dietary guidance to parents on what to feed their children to prevent nutritional deficiencies and chronic diseases. In 2011, the USDA introduced its most recent version of food groups with MyPlate, which replaced the food pyramid design with a relatable plate graphic.

Today, we’re at a crossroad where many companies are questioning the value they receive from data and the investments they’ve made. Some leaders may wonder if AI can magically fix the problem, not realizing it will simply amplify and streamline the output but not necessarily enhance its quality. To tackle this issue and reduce the ambiguity around data communication, I’d like to use a similar guidelines approach to help organizations understand what’s needed to enjoy a more healthy, balanced data communication diet.

MyDataPlate: The four food groups of data communication

The field of analytics and business intelligence hasn’t done a good job of clarifying what the various forms of data communication are. Many data vendors promote their tools as “Swiss Army knives” that can do everything, which only adds to the confusion. To help untangle the pile of competing aspects of data communication, I’m going to focus on four core categories—Monitor, Explore, Report, and Explain—in a similar framework, I call MyDataPlate.

This simple and relatable framework helps organizations identify and address gaps in their data communication strategy. It is designed to ensure companies maintain a healthy balance of monitoring metrics, exploring patterns, reporting outcomes, and explaining insights that drive action. Let’s take a closer look at each data communication type.

1. Monitor: Is anything happening that needs our immediate attention?

Monitoring tracks key metrics in real time or at regular intervals (hourly, daily, weekly). It is valuable for detecting anomalies and changing conditions that may need an immediate tactical response. Frequently, monitoring tools such as dashboards and alerts emphasize the current state against historical norms or predefined targets. They are designed to be straightforward and easy to consume. Due to their real-time delivery, they generally lack added interpretation or context.

Monitor scenarios:

• Are sign-ups dropping below our daily baseline today?
• How many support calls did we receive this morning?
• What’s the marketing campaign’s click-through rate right now?
  

2. Explore: What can we learn or discover?

Exploratory communication tools provide structured environments with multiple inquiry paths and no prescribed conclusions. These tools are designed to transfer analytical control to the end users, who can build their own understanding by interacting directly with the numbers to answer key questions. With their rich filter and drill-down capabilities, these interactive BI tools, charts, and notebooks invite active engagement rather than passive consumption. They offer more flexibility and greater access to more granular information.

Explore scenarios:‍

• What factors are correlated with customer churn?
• What patterns exist in customer support tickets across different product lines?
• How does user engagement differ between mobile and desktop users?

3. Report: What happened during a specific time period?

Reporting focuses on providing structured, periodic summaries of business performance and key activities. It generally looks at a longer time frame such as a month or quarter. It is useful for tracking progress towards goals, documenting outcomes, and informing strategic decision making. Reports are generally delivered as presentations or documents that focus on a specific area and are standardized for consistency. They balance detail with accessibility and may offer some interpretation or added context.

Report scenarios:

• How did our Q1 sales compare to Q4?
• What was our customer retention rate for each region last month?
• How did actual production output compare to forecasts for the past six months?

4. Explain: Why does this matter, and what should we do?

Explanatory communications translate complex findings and insights into accessible, guided narratives that include interpretation, synthesis, and ample context. This approach excels at building comprehension, influencing decisions, and driving action by connecting data to real-world implications. Typically delivered as presentations or documents, they weave data, narrative, and visuals into curated, compelling data stories that make insights both concrete and meaningful.

Explain scenarios:

• Why did our NPS decline last quarter, and what should we do?
• Why are certain stores outperforming others, and how can we replicate their success?
• What’s driving the shift in customer needs, and how should we adapt our strategy?

By introducing this MyDataPlate framework, I want to clarify the complementary but different purposes supported by each of the four categories of data communication. The following table summarizes some of the main differences:

Problems with today’s imbalanced analytics approach

While most organizations have invested in data, many have not done so in a balanced manner. Some organizations may be missing key types of data communication. Others may not have the optimal portions that their organization needs. Just like the dietary needs of children, seniors, and athletes are different, there’s no universal “perfect data plate.” Each organization will require slightly different portions based on a variety of factors: organizational maturity, decision-making culture, company size and structure, regulatory environment, industry (B2C vs. B2B), strategic priorities, and so on.

When companies fail to get the right balance of data communication for their specific needs, it can lead to several unfortunate shortcomings:

1. ‍Overemphasis on monitoring and reporting: Many organizations have invested heavily in deploying dashboards and producing reports. Underinvesting in exploration and explanation capabilities has led to data-rich but insight-poor environments.‍
2. Lack of value or action: With insufficient focus on Explain, companies fail to turn findings and insights into action and business value. Executives don’t see the strategic benefits of their data investments other than having more transparency throughout their organizations, causing analytics initiatives to lose support over time.‍
3. Tool-centric rather than purpose-centric: Many organizations select tools first without clearly defining the communication needs they’re trying to address. Once they’re locked into a particular analytics tool, it can lead to mismatches between capabilities and requirements.‍
4. One-size-fits-all approach: Rather than tailoring strategies to specific needs, many analytics teams try to serve all communication requirements with a single tool or approach. When the approaches are blended, they often fail to meet the unique needs of each communication form (e.g., simplicity vs. detail).‍
5. Data cultures stuck in neutral: When organizations haven’t fully embraced data across all four areas, they will appear data-driven on the surface. However, they will lack the fundamental capabilities to leverage data for real competitive advantage.

These imbalances in data communication represent a form of organizational malnutrition that limits companies' ability to extract full value from their data investments. Just as nutritional deficiencies can lead to major health problems, these data communication gaps create blind spots, missed opportunities, and compromised decision making. Fortunately, by recognizing these issues and rebalancing your organization's data communication diet, you can transform your analytics approach from merely informing to influencing business outcomes.

The benefits of tomorrow’s balanced data diets

Far too many organizations have become obese, slow, and weak due to poor data communication approaches. With guidance from the MyDataPlate framework, companies can reset their data journeys and move forward with a clear direction on what gaps they have and how to address them. Having a balanced approach across the Monitor, Explore, Report, and Explain categories is crucial for the following four reasons:

1. ‍End-to-end coverage. Each category serves a distinct purpose in the analytical process. Monitoring identifies immediate issues, reporting provides historical context, exploration uncovers patterns, and explanation drives action. Without all four working together, your organizational understanding will have gaps and will be incomplete.‍
2. Democratized decision-making. Organizations must make decisions at different levels across different timeframes. With a balanced approach, you receive the benefits from operational efficiency (Monitor, Report) but also improvements to strategic effectiveness (Explore, Explain).‍
3. Resource optimization. Each category has different resource requirements. Monitoring and reporting are more likely to be automated or augmented by AI whereas exploration and explanation will require more human involvement. With this understanding, you can shift data team resources to the areas where their human skills are most needed.
4. ‍ROI on data investments. If data doesn’t translate into action, organizations can become stuck in endless cycles of data collection and reporting without meaningful outcomes. A balanced approach ensures data progresses from insights to action, driving value from all the data infrastructure and other resources.

Nutritionists have long understood that overall health depends on consuming a variety of food groups combined with proper exercise. Similarly, to obtain and maintain analytical excellence, organizations must develop a balanced diet of data communication approaches combined with active data-driven decision-making. By assessing your current data practices against the MyDataPlate framework, you can identify which areas need more attention and development. The path to true data maturity and a strong data culture isn't found in more dashboards, more reports, or even more advanced AI tools. It's in creating a balanced environment where each area contributes to more effective decision making at different levels.

When all four elements work in harmony, your organization won't just have data—it will have the full nourishment needed to make better decisions, respond to challenges with agility, and create sustainable competitive advantage in an increasingly data-driven world.

‍