Part 1 – Foundations

Introduction

In the complex landscape of modern business intelligence, the difficulty of delivering quality reporting to business stakeholders remains one of the greatest challenges. Reporting requirements are not merely technical specifications; they are strategic bridges connecting operational insights to organizational decision-making.

When users submit vague reporting requests—a massive data table here, a generalized dashboard there—they are inadvertently revealing a profound communication disconnect. This disconnect is not a failure of users, but an opportunity for Business Intelligence teams to elevate their approach from mere data technicians to strategic organizational partners.

This comprehensive guide will deconstruct the art and science of gathering reporting requirements, transforming what is often perceived as an administrative task into a critical strategic dialogue.

As you delve further into this guide, note that the terms “reports” and “reporting” encompass dashboards, alerts and notifications, paginated reports and other information provided by a business intelligence team.

The Source of Analyst Frustration

Business Intelligence analysts commonly are frustrated by the lack of guidance from those who request reports.  The question frequently asked by analysts, “what do you want your report to look like?” either goes unanswered or is met with generalities. Pressing for clarification results in an annoyed business stakeholder. Left with scant details, the only option is to forge ahead and make it up as you go.

Why are we surprised when, once reports are delivered, we hear the the users’ refrain “this isn’t what I asked for”? It often is not what they asked for, nor what was needed to support the business.

We then hear “we don’t trust the reports,”  and BI teams take it personally. They have invested hours of analysis and testing to ensure underlying data – be it a data warehouse or other source – is accurate and complete.

It’s easy to assign blame to the report requesters.  After all, they could have cooperated more with providing requirements. And we verified that the data is “accurate.”  Users can seem downright ungracious at times. It is no wonder that there is often tension between BI teams and their users.

However, there is an uncomfortable truth to be acknowledged: businesspeople are doing nothing wrong and BI analysts are the ones who need to improve.  In this case, improving means acknowledging the inherent strengths and weaknesses of report requesters, and then adapting our approach as experts in the field of business intelligence.

By applying the techniques in this guide, your BI team will deliver reporting that delights users while contributing significantly greater value to the organization. Let’s stop asking “what do you want in your report” and acknowledge that a new strategy is needed.

A Struggle for Clarity

Every reporting request is a symptom of a deeper organizational need. A seemingly simple dashboard request might signal complex underlying dynamics: leadership uncertainty, performance management challenges, or strategic realignment. It may be surprising that, given the importance of having quality reporting, users find it difficult to convey what they want in a report.

Let’s look at it from the users’ perspective.  Most businesspeople know their jobs extremely well. They have carved out a niche in the organization and are responsible for ensuring their business function is performed with excellence. They are experts at their department and its role in the company.

But reporting requires people to step back from discrete business processes and think analytically about the big picture. This means that they need to anticipate where there is something noteworthy to learn from the data. Technologists will recognize that this means anticipating the best way to slice data, the best way to visualize trends, and how data should be filtered and refined.

Little of the analytical reporting thought process intersects with users’ operational expertise. It is no wonder that they struggle to articulate what they want to see in a report. As a result, users pass their general uncertainty onto analysts as generalized requirements. When you ask clarifying questions, they don’t have the answers to give.  Consequentially, the more you ask for clarity the more annoyed they become.

Analysts will need to develop a new set of muscles that explores business motivation for reports. They will need to understand business context and how value from report is derived.  These are skills that transcend mere data presentation and instead deliver genuine decision support tools.

BI Managers Are On The Hook

Business intelligence managers must recognize that their role will evolve, as well. Rather than simply manage a mechanical software development lifecycle, they need to be present “in the field” among business executives, promoting a new way for the business to interact with the BI team.

Throwing requests over the transom may have achieved an “okay” result in the past, but a modest level of engagement with analysts will dramatically improve the quality of reporting. Businesspeople must be prepared to give deeper context into how reports will be used and how value is derived.

Analysts can step up their game, but report requesters will need to respond in kind.

Quantifying the Value of Business Intelligence

The true value of a business intelligence reports is not in their creation but in their consistent, meaningful utilization. The return on investment for a BI investment can be mathematically represented as:

ROI  ~ (Number of Users) × (Reporting Frequency)

In English, the ROI is proportional to the number report users multiplied by the frequency of report usage. On the surface we talk about reports, however the investment, assessed comprehensively, includes data warehousing, infrastructure, QA, etc.

While the entire investment counts, the only way to achieve meaningful ROI is through users. If a small handful of users take advantage of BI, then your ROI will be small. If many users rely on BI to perform everyday tasks, the ROI will be high.

In their ongoing quest for relevance, every BI team must ask themselves, “how can I get more people to rely on our reports to perform their jobs?” 

Conclusion

The path to transformative business intelligence is not paved with technical prowess alone, but with strategic communication and a profound understanding of organizational dynamics. The journey from data collection to meaningful decision support requires a fundamental reimagining of how reporting requirements are conceived, developed, and implemented.

By recognizing that reporting requests are more than mere technical specifications, Business Intelligence teams can position themselves as critical strategic partners. The key lies in developing a nuanced approach that goes beyond technical execution and focuses on understanding the underlying business motivations, contexts, and value drivers.

This transformation demands a multi-faceted commitment:

1. Business Intelligence analysts must evolve from data technicians to strategic interpreters, developing skills that allow them to probe deeper into the organizational context behind each reporting request.
   
   
2. Business users must be prepared to engage more substantively, providing rich context about how reports will be applied and the specific decision-making challenges they aim to address.
   
   
3. BI managers must create a culture of collaborative requirement gathering, positioning their teams as engaged solution designers rather than passive order-takers.

The ultimate measure of success is not the complexity of the reports created, but their consistent and meaningful utilization across the organization. By focusing on expanding user engagement and demonstrating tangible business value, BI teams can dramatically increase their return on investment and organizational impact.

In an increasingly data-driven world, the most successful organizations will be those that view business intelligence not as a technical function, but as a strategic capability that transforms raw data into actionable insights, driving informed decision-making at every level.

Part 2 of this article will explore in detail the steps analysts should take to capture BI requirements.

Jeff Kanel is the Founder and President of Arch City Analytics. He has served as a corporate executive and analytics expert with over 15 years of management consulting leadership. Throughout his decades-long career Jeff has guided countless executive leaders to achieve a data-driven culture through analytics and AI.