21 Décembre 2025
In most consulting firms and IT services providers, staffing often resembles a game of Tetris.
Each week, the staffing committee faces the same equation:
On one side, a client engagement starting Monday.
On the other, a list of consultants between engagements.
In the middle, two primary filters: Technical Skill (Do they know the technology?) and Availability (Are they free?).
If both boxes are green, the consultant is assigned. On paper, the problem is solved: the utilization rate is maintained, and the client is served.
Yet, weeks later, some projects derail. The team doesn't come together. Deliveries are slow, the atmosphere is heavy. Why? Because human dynamics were treated as a purely logistical variable.
Modern staffing cannot be reduced to managing capacity. It must integrate a third critical dimension: compatibility.
The traditional approach relies on a risky assumption: believing that two senior consultants with identical technical skills will deliver the same results in the same context.
The reality is more nuanced.
Expert A is autonomous, excellent in pure R&D, but uncomfortable with unclear stakeholder expectations.
Expert B is a facilitator, average in pure code, but excellent at structuring a junior team and reassuring a client.
Placing Expert A on an engagement requiring intense stakeholder coordination is a casting error, even if the technical knowledge is perfect.
Staffing by availability alone ignores the delivery friction that impacts project margins.
To move from "gut feeling" staffing to informed staffing, compatibility must be objectified. It is not about evaluating personalities, but describing how people work.
Three measurable dimensions can enrich the decision matrix:
Does the engagement require following a strict process (Banking, Pharma) or figuring it out as you go (startups, research labs)?
Some teams perform through constant oral exchange and collective reflection. Others perform through writing and concentration.
Some consultants thrive when the scope is defined. Others thrive when they have to define the scope.
Integrating these criteria implies collecting reliable data. This can be done simply via a declarative grid:
Define a minimal repository: 3 to 5 key questions (e.g., "I prefer... 1. Total autonomy / 4. Regular checkpoints").
Project Profiling: The manager defines the "ideal profile" of the project on these same scales.
Matching: The comparison highlights gaps. A gap is not necessarily a blocker, but it becomes a point to monitor.
It is crucial to clarify one point: searching for compatibility does not mean searching for affinity or "clones."
Affinity is personal (getting along well).
Compatibility is professional (working well together).
The objective is not to create teams of friends, nor teams where everyone looks alike. The goal is to align the conditions for performance. Members can be very different (complementary) while sharing the same need for clarity on objectives.
The goal is not to ignore the availability constraint (a project must start), but to refine the decision.
Technical competence is the prerequisite. Compatibility is the multiplier.
When multiple profiles are available, choosing the one whose working style fits best with the team dynamics is a strategic move. By shifting from "filling slots" to "building teams," project risks are reduced and avoidable turnover decreases.