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Report Requirement Reset

Are you building exactly what stakeholders asked for — and still missing what they actually needed?

A focused working session that turns output requests into business questions, decisions and success criteria worth building against.

Start with what is actually happening.

  • Requirements arrive as “Can you add a chart?” or “We need a dashboard.”
  • Developers start with fields and visuals before understanding the decision.
  • Stakeholders ask for multiple variants because the original purpose was unclear.
  • A report is delivered correctly but still does not solve the business problem.

Good work starts with better questions.

01

What decision will this support?

02

Who will make that decision?

03

What action should change because of the information?

04

What does success look like?

05

Which assumptions are we treating as facts?

The scope follows the problem.

I do not force every engagement through the same checklist. These are the areas that may matter; the agreed scope determines how deep we go.

Business objective

Decision and action

Success measures

Known assumptions

Business meaning of metrics

User, urgency and frequency

Information and level of detail

Delivery format only after the need is clear

Something you can use after the conversation ends.

The output should help you make a decision, change a practice or move the work forward. It should not exist simply to prove that work happened.

01

Decision Questions

The questions the solution genuinely needs to answer.

02

Success Measures

A clearer definition of what “useful” means for this piece of work.

03

Information Needs

Prioritised information rather than an unfiltered feature list.

04

Assumption Log

What still needs validation before development goes too far.

05

Build / Don’t Build Decisions

A conscious decision about what is worth creating now.

Enough structure to make the work clear. Not so much process that the process becomes the work.

01

Context

We start with a short conversation about what is happening, what matters and what has already been tried.

02

Review

I analyse the relevant parts of the solution or operating model at the depth agreed for the engagement.

03

Prioritise

I organise observations around impact, risk and usefulness — not around how many issues I can find.

04

Walkthrough

We go through the findings together, challenge assumptions and discuss trade-offs.

05

Next step

You decide what happens next: implement internally, continue together or stop because the focused engagement was enough.

I keep the client-side time demand deliberately light. A focused assessment usually needs a kickoff conversation, access or materials, and a final review session. We agree the exact involvement before we start.

This is likely to help if...

  • A report request feels larger or less clear every time you discuss it.
  • Business and technical teams are using the same words to mean different things.
  • You want to reset before committing more development effort.
  • The requirement is already clear and you only need implementation.
  • The challenge is primarily a technical architecture decision.

If the problem is real but the format is wrong, that is useful to know early. I would rather redirect the conversation than force the challenge into the wrong service.

This does not automatically lead to another engagement.

Sometimes the focused piece of work is enough. If it reveals a useful next step, these are some of the directions that may make sense.

Are you building exactly what stakeholders asked for — and still missing what they actually needed?

Bring me the problem, not a polished brief. A few sentences about what is happening and what you would like to change are enough to start.

Tell me what's happening

Send me a message.

You do not need a polished brief. Whether the topic is Power BI, Fabric, AI, team training, mentoring, coaching or simply a challenge that needs untangling, leave a few details and we can start from there.

SIGNALMESSAGECONVERSATION

AI & TRANSPARENCY

AI supports selected parts of my work — it does not replace my judgement, responsibility or relationship with the client.

I use AI tools for tasks such as research, organising information, structuring content and preparing materials. I treat AI as support for my work — not as an autonomous author or decision-maker. Anything I publish or use professionally remains my responsibility.

In coaching, I do not use AI to automatically assess, diagnose or make decisions about a client. AI does not replace attention, confidentiality or human responsibility for the coaching relationship.

AI may support the process. Human responsibility remains.