Run a client discovery workshop with conflicting stakeholders
In this article (4 sections)
Conflicting stakeholders are normal evidence, not a facilitation failure. A sponsor may want speed while security protects a data boundary, operators protect support capacity and users need override. Discovery should turn those tensions into explicit decisions.
Build the decision artifact
Interview roles separately before the workshop. Map current workflow, decisions, exceptions, data, owners, pain and baseline. In the joint session, separate facts, assumptions, needs, proposed solutions and unresolved decisions. Use a decision log and RACI; time-box experiments for questions that cannot be debated to certainty.
The commercial leadership lab makes the artifact inspectable with authored inputs:
from leadership_cases import discovery_conflict_case
result = discovery_conflict_case()
assert len(result["stakeholders"]) == 4
assert result["unknowns"] == ["representative exception volume", "approved model endpoint"]
assert result["consensus_claimed"] is False
assert result["solution_promised"] is FalseThe fictional workshop preserves four different needs, creates three design decisions and leaves two unknowns. It claims neither consensus nor a promised solution. That is a stronger discovery result than a harmonized summary that removes the real trade-offs.
Protect the decision from weak evidence
The loudest senior attendee can turn a workshop into solution confirmation. Gather user and operator evidence before the meeting, let participants challenge the current-state map and write dissent next to the decision it affects.
Keep these artifacts for review:
- role-based interview notes and workflow map
- fact/assumption/unknown register
- decision rights and conflict log
- experiment or owner for each unresolved question
This practice aligns with the discovery, productisation, client enablement, technical leadership and capstone sequence in the FDE for Professionals course. The course link describes the pathway; the local scenario is fictional and does not claim a client engagement, investment result, hiring decision or certificate.
Practice task
Facilitate a thirty-minute fictional workshop with four roles. End with no slide deck: produce only the workflow, unknowns, decisions and next evidence.
Continue learning
This article is part of the Commercial judgement and delivery leadership sequence. Use the neighbouring tasks when you need the prerequisite or the next application.
- Review the prerequisite or neighbouring task in Estimate the cost of exceptions in an automation business case.
- Continue with Negotiate a scope change using impact evidence.
Reference: GOV.UK Service Manual: Discovery.
Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.
This article is part of our FDE for Professionals programme — 16 weeks (proposed). An accelerated advanced pathway for IT professionals ready to own enterprise AI delivery.
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