Our data science team is struggling during the project execution phase of a predictive analytics model because the client keeps changing the data compliance requirements mid-project. Is stakeholder management the sole responsibility of the project manager, or should technical leads step in to explain execution limits?
3 answers
The project manager must always serve as the primary shield and main point of contact to maintain consistent messaging. However, during highly technical execution phases, having a data scientist join the discussion can add immense credibility. The project manager handles the contractual and timeline impacts of changing compliance rules, while the technical lead explains the algorithmic limitations and data architectural constraints directly to the client's technical team.
Shouldn't the project charter explicitly define these technical communication boundaries before execution begins? If the client doesn't know who handles scope decisions versus technical parameters, you risk getting conflicting answers.
The project manager handles the timeline buffer and budget impacts, while the technical specialist translates the actual engineering realities. It must be a coordinated tag-team effort.
Exactly, Douglas. Clients accept technical limitations much better when a specialist explains the data architecture, while the manager focuses on preserving the project timeline.
Kenneth, our original charter was vague on that front. To fix this, we just set up a structured weekly alignment meeting where I handle the scope adjustments and our lead data scientist directly addresses the technical compliance hurdles.