Project Management

Using analytical thinking to bridge the gap between business needs and tech?

SA Asked by Sarah Jenkins · 22-06-2023
0 upvotes 8,958 views 0 comments
The question

As a Business Analyst, I often find a disconnect between what stakeholders want and what the dev team can actually build. I’m looking for ways to use analytical thinking to better deconstruct vague business requests into precise technical requirements. How do you guys use logical decomposition to ensure that no critical detail is "lost in translation" during the initial discovery phase?

3 answers

0
KI
Answered on 24-06-2023

The key to bridging this gap is using the "Five Whys" technique combined with structured modeling like BPMN (Business Process Model and Notation). When a stakeholder gives a vague request, keep digging into the 'why' until you hit the core business value. Once the value is clear, use analytical decomposition to break the process into its smallest logical parts. Documenting these in a visual flow helps the technical team see the logic path and edge cases that a simple text description might hide. This rigorous analysis ensures the developers understand the "business logic" before they ever write a single line of code.

0
RO
Answered on 26-06-2023

When you are deconstructing these requests, do you find it more effective to focus on the data entities involved or the user's sequential journey first?

JA 27-06-2023

Robert, I always start with the user journey but apply a "functional decomposition" lens. By analyzing the actions first, the necessary data entities usually reveal themselves logically. If you start with data, you might miss the nuance of how a user actually interacts with the system, which is where most business requirements get misinterpreted. Analytical thinking requires balancing both, but the workflow is usually the best starting point.

0
JE
Answered on 28-06-2023

I’ve had great success using "Decision Tables" for complex logic. It’s a purely analytical way to map out every possible combination of inputs and their expected outputs so there is zero ambiguity for devs.

SA 29-06-2023

Decision tables are a lifesaver, Jennifer! They are the ultimate analytical tool for preventing "if-then" logic errors, which are the most common cause of bugs in new feature deployments.

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