"We need this report in Power BI" - How to Gather Reporting Requirements

Many reporting requests have a common starting point - existing reports.

These might be Excel workbooks, large PowerPoint slide decks, or bundles of reports scattered across other technologies. For one reason or another, these reports need to be re-made, re-designed or migrated over to Power BI. “They need to be in Power BI, and they need to be there now.” The business has urgent needs, and there’s pressure from management to see the result. But where do we start? What do we make? Defining the right requirements is essential if we want to make an effective report that is used and delivers value. Otherwise, it will just be collecting digital dust & cobwebs in an abandoned app…

Here I will discuss 3 common approaches to collecting reporting requirements, arguing in favour of the third approach - working iteratively & collaboratively with business users.

How Not To Drown: Improving Data Literacy in your Organization

If users don’t understand your data solution or the data behind it, it doesn’t matter how beautiful, performant or powerful it is - it won’t deliver business value. Data literacy is fundamental for an effective organisation and is a keystone for any successful data & analytics project. It is clear, however, that data literacy is a challenge area in many businesses, and society as a whole. A 2018 survey of business decision-makers found only 24% were “confident in their ability to read, work with, analyze and argue with data” [1], a finding recapitulated in the lay public [2] and demonstrated plainly during the global COVID-19 pandemic [3].

To traverse these rapids, we are in need of more than tools, but a wide knowledge of how they are used and the data concepts behind them. In this talk, we examine the impact of Data Literacy on business data projects through an in-depth case study of a Sales Compensation Plan to:

I. Illustrate concretely the concept of data literacy and the threat poor data literacy poses to an organisation.
II. Understand that data literacy is about people and not solutions.
III. Define practises and report design techniques to improve data literacy with consistent interventions.

Without data literacy, we will fail to navigate the waters of information that are ever-rising; we risk not only falling overboard, but even drowning. However, instilling data in organisational values, engaging people with and about information in the right ways, and implementing accessible design practises can not only keep us afloat, but propel us onward to brave new worlds of effectiveness and value.

[1] How to Drive Data Literacy in the Enterprise (2018)
[2] Borner, K. et al. (2016) Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors. Information Visualization 15(3) 198-213.
[3] Advancing Data Literacy in the Post-Pandemic World (2021)

Find and Seek: Leveraging visual & functional best practices for actionable Power BI reports

Three seconds. When a user arrives at a Power BI report, that’s how long you have to seize their attention with the most critical facts. As they mouse-over the report, they search for their most important categories and trends, then their details-on-demand… do they quickly find answers to their questions, or do they drown in the data of yet another report? The answer isn’t solely determined by elegant and performant visuals or deep AI and analytics; Power BI developers need to first know their users, then design a holistically effective, logical user experience. This experience, known as the Information-Seeking Mantra – or the 3/30/300 rule - leverages visual best practices to split the report into three parts: The information gained by the user in (A) three seconds, (B) thirty seconds and (C) three hundred seconds. In the deeper layers, interactivity in Power BI enables powerful, self-driven question-and-answer data exploration. Effectively combining both these visual and functional elements in a user-oriented way can lead to powerhouse reporting that can revolutionize a workplace. With these reports, Business users can test their ideas and questions to get reliable answers, and, more importantly, use them to drive actions to get the desired results.

In this talk, we will explain three principles we employ in an effort to design quality, usable Power BI reports that allow business users to quickly answer both basic and complex questions in an action-oriented way. We see these principles as valuable best practice guidelines for (1) co-creating reports with users, as well as (2) visual and (3) functional guidelines for design. For (1), we will illustrate our typical approach to user-oriented design using examples. For (2), we will illustrate key data visualization principles and demonstrate how they are typically executed when designing a report in Power BI using the default visualization types. For (3) we will demonstrate our experience with effectively leveraging powerful interactions in Power BI like drillthrough, graphical tooltips, page navigation, dynamic measure & dimension selection, and more. In addition, (2) – (3) will include short technical 'recipes' on how to these can be implemented by yourself. Finally, we will put it all together with an example that we hope highlights how the whole is greater than the sum of its parts. By the end of the talk, we hope you will understand this approach to design, and the value it can provide in designing useful Power BI reports.

User Adoption of Your Report - Starting Off on the Right Foot

“If no one’s using your solution, then it’s not a good solution.”

Unused reports and solutions, abandoned in pre-production environments like victims of an apocalyptic data war. We’ve all seen it, heard it or experienced it ourselves. It’s thus not surprising to hear Gartner predict that through 2022, up to 8 in 10 business & analytics projects will fail to help the business. What can we do, then, to help ensure adoption of our Power BI report?

In this talk, I highlight three key areas that impact adoption: measuring success, monitoring data quality, and promoting user engagement. To illustrate my points, I’ll use a hypothetical business case enriched by relatable, real-world experiences. First, I’ll demonstrate some ways that success can be measured, both during development and after launching the reports. Next, I’ll show an easy way to monitor the data quality in your Power BI reports. Finally, I’ll promote a simple post-launch practice to drive user engagement, promote data literacy, and foster an accepting, open data culture between report users and developers.

Achieving success in a business reporting project is a complex endeavor for which there are no quick-win formulas. However, taking steps to ensure proper engagement and collaboration with users can dramatically improve not only chances at success, but also the overall experience.