How To Ensure Your Data & Analytics Project Meets User Requirements

Michael Solomon Mar 6 6 min read

Have you ever noticed how some of the most accomplished sportspeople are not known for being especially athletic? Think Tom Brady, Lionel Messi. Or how some of the highest regarded singers don’t pack too many notes in a single syllable or second? Anyone heard of Pavarotti or Sting? Millions of people can pass a ball or sing a song, but it’s the few that make the right choices, in the moment, that can elevate the task to achieve a real quality outcome. The same applies whether it’s sport, music, or Data & Analytics project scoping.

It’s the decisions that often differentiate the elite from the good. Knowing why to choose a particular method enables you to repeat these decisions and elevate your performance on a consistent basis. This article is not a How To, there are many places you can search for required steps. Instead, we’ll explore the Why To, to help understand the decisions to make to consistently elevate your business performance.

The core requirements of a data and analytics project scoping exercise may be understated simply as to source data and present it to an audience in a way to help them make decisions. A scoping session for this may run along the lines of “How do I get this data as an input?” “How would you like it presented as an output?”  However, this doesn’t consider so many factors and could result in a poor outcome, ranging from providing half a solution, to a solution that performs poorly, to in a worst case, the audience even deciding not to use the resulting analytics solution despite meeting those basic functional requirements.

There’s no denying that any requirements gathering needs to include questions about the data, the sources, any logic to be used, the grain of the result set, and more. This may extend to deep dives on the data, reviewing data quality, volumes, integrity checks etc. Likewise, the output may be determined by a workshop, using wireframes and information flow.

We’ve all seen the cartoons that show the differences between how the customer requested it, how the analyst explained it, how the programmer developed it, how the consultant delivered it, and what the customer actually needed. 

It’s the context of how the data fits into the world of the audience, and how it will be used that instructs how it should be delivered.

To understand that context should be the goal of scoping. To this end the business audience must be included in the scoping process. It cannot be left up to the data owners to know all the requirements of the business. After all, the requirements are of the business audience, not the data keepers.

The following is a potential list of areas that should be addressed to ensure your data and analytics project or program scoping, meets user requirements.

1. Involve Program Stakeholders

Clearly identify roles and responsibilities and assign these to appropriate people in the program. These may include roles such as Project Sponsor, Project Lead, IT Sponsor, Data Lead, and Business Champion(s).  Ensure regular communication between these people during all phases of the program.

2. Understand The Drivers & Challenges

Asking questions of the end users directly to understand drivers and challenges like “Why do you want this report?”, “What’s driving the need?”, “Why implement this now?”, “How will this help you?”, “ Is visibility into the data domain an issue?”, “Or is it currently an inefficient process to produce insights?”, and “Are there data reliability issues?” Paint a picture that can only be described by the primary user that will help you understand what you’re trying to deliver. Understanding current pain points clarifies where real value can be added.

3. Define Key Measures Of Success

Define what would be considered a successful outcome.  This may range from a feature of the new asset, a change in user behaviour, impact to a KPI, increased data reliability or visibility, delivered within budget.

4. Know Your Audience

Who will use the report? How will they use it? Speak to them directly. Executives may want high level overviews, areas of focus, trends, KPIs. Analysts on the other hand may want underlying detail for verification, or outlier investigation. Knowing who will use a report will help determine report page flows, visualisation layouts, and highlights. For example, it may be a factor in deciding if a table of results is prominent on the first page, or a sidebar on the second page, or whether to show a Top 10 chart at all.

5. Get To Know Business Processes

What do users do on a Monday morning? Are there any period-end processes that may impact the data refresh rate requirements on the first or last day of the week or month? Simply asking how often the data is to be refreshed often doesn’t reveal the details that are factors in that last few percent of decision making.

6. Time Factors

Are there any time pressures in delivery? Are there any dependencies on other pieces of work? Are all the necessary prerequisites ready? Answers to these questions may materially impact the feasibility, timing, or order of performing program tasks.

7. Clarify The Scope

Ensure that inclusions, exclusions, and assumptions in the program delivery are understood by all involved. It is not uncommon for scoping sessions to digress or have ideas floated that may be intended for a future phase. Once a topic is mentioned it should be made clear whether it is included in the agreed scope.

8. Reviews And User Acceptance Testing

To ensure delivery is on track, conduct regular reviews and enable business user testing on several levels of the delivery. This includes highlighting any issues as they arise, testing data, testing user interface suitability, and iterations of these if the delivery method allows.

With any Data and Analytics Program, basic requirements gathering will produce basic results. To ensure a program meets user requirements a thorough understanding of who will use the output, why they need it, why they’ll use it, and how and when it will be used, is needed.  Success of the program also needs to consider other factors such as resourcing, timing and budgets.

A thorough data and analytics project scoping process will recoup its value several times over. It provides the understanding of not just How To, but Why To, and really sets you up to make the right decisions during delivery. You may not end up singing like Pavarotti, but it will enable consistent, high-quality results.