PRYSMAP brings together perspectives on organizational intelligence, measurement, and human systems.
93 articles
An organization can have the right skills and still fail to produce the expected capability. Even when the inventory is accurate, the rules of work may prevent those skills from being used.
Why would a leader hold on to someone who could contribute more in another unit?
A 360 improves an assessment when it preserves what each source observed, from which relationship, and within what limits; averaging first destroys that information.
Even when someone develops a skill, the organization may retain the same constraint if the opportunity, support, or authority to apply it is missing.
Consider an unexpected absence: a capability is fragile when its absence interrupts a critical outcome and no alternative has demonstrated that it can restore that outcome in time.
How do you keep a calibration session from turning into a negotiation over scores? Bring evidence, context, and criteria into the conversation before the number.
Work without Jobs proposes looking beyond the job as a whole and brings into view a layer that skill architectures often overlook: the work that needs to be organized.
Even when usage is high, a model may not yet have been adopted: the decisive evidence appears when it changes a real decision and that change can be reconstructed.
Should the organization create a new role or redistribute the work? The answer depends on the stability, distinctiveness, and accountability of the missing contribution.
Before recommending training in response to a gap, compare four possible sources: individual proficiency, team coverage, interfaces, and the operating model.
Even without a change in hierarchy, lateral mobility can develop judgment by changing the problems, relationships, and decisions a person faces.
What does a space without a conclusion actually mean? It may indicate an absence of observation, an expectation outside the role, or insufficient evidence. Distinguishing these states prevents us from assigning a gap that the data does not demonstrate.