Professionals with strong technical backgrounds often encounter feedback indicating that clients find presented results, reports, or modelling and simulation work difficult to understand, frequently likening these methods to a “black box”. This is becoming more prevalent due to the application of Machine Learning (ML) and Artificial Intelligence (AI) approaches used by data scientists and more generally. One of the key challenges in such assignments is becoming deeply involved in technical detail and inadvertently assuming clients possess similar knowledge.
Communicating both the methodology and subsequent results through effective storytelling is essential to ensure alignment with client objectives and expectations. Bridging the gap between interpreting technical outcomes and meeting clients at their level of understanding is crucial, especially as many may not share a technical background. Below are important considerations to bear in mind when conducting technical work while maintaining meaningful engagement with clients:
Acquisition Phase:
- Ensure client requirements are thoroughly defined.
- Clarify the value expected from the assignment’s outcomes.
- Confirm that project boundaries and information comprehensively address client needs.
- Identify other stakeholders who may have an interest in the work; consider workshops to facilitate engagement and alignment.
- Evaluate whether initial solutions introduce bias and assess any overlooked elements.
Planning:
- Avoid immediate problem-solving; even a brief planning session can help identify key steps and benefit from peer or client review.
- Incorporate sufficient granularity into plans to facilitate demonstrating measurable progress.
- Establish clear billing segments for larger tasks to support business cash flow, which sometimes may be overlooked in larger organizations by technical professionals.
Progress:
- Regularly communicate updates to clients and managers to build and maintain confidence in your approach and capabilities.
- Set achievable intermediate objectives to show ongoing progress, as clients may equate a lack of information with a lack of advancement.
Outcomes:
- Validate details and conduct reviews to mitigate errors in deliverables.
- Articulate results in terms relevant to the client.
- Provide insights by comparing findings to industry benchmarks, standards, and norms.
- Remain adaptable to changes over the course of assignments, discussing scope changes transparently with clients to add value.
- Assess how evolving project parameters may affect the overall value delivered.
- Adapt the level of detail according to organizational hierarchy:
- Executive-level audiences typically require concise summaries (two to three pages).
- Technical professionals, such as reliability engineers, often need comprehensive reports referencing applicable codes and standards.
Engineers, scientists, and related professionals must remain attuned to the sources of value perceived by clients. Effectively conveying technical information tailored to the audience is critical; otherwise, work may be misunderstood as a black box, prompting scrutiny regarding its validity and relevance.
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