How can personality data be used to diagnose inefficiencies in an existing EOS Accountability Chart, specifically to inform the creation of new, optimally designed seats?

Question

Tyler Smith · Accepted Answer

Diagnosing inefficiencies in an existing EOS Accountability Chart isn't always about fixing existing roles; sometimes, it's about realizing a *new* seat is required, and personality data provides the precise intelligence needed for optimal design. When teams exhibit recurring bottlenecks, communication breakdowns, or areas of chronic underperformance that don't seem tied to individual GWC issues, the problem might be a **missing seat** – a set of responsibilities and accountabilities that no one is naturally wired to fulfill consistently. For example, if an Integrator (typically high "Quick Start" Kolbe, high 'D' DISC) is consistently bogged down by meticulous data analysis and process refinement (high "Fact Finder" Kolbe, high 'C' DISC), it indicates a *gap* in the chart. This isn't a failure of the Integrator, but rather a misallocation of conative energy. Personality assessments can highlight these **"conative stress points"** across the leadership team. By aggregating the unfulfilled conative and behavioral needs, a clear picture emerges of the specific *type* of personality required for a potential new seat. This isn't just about defining tasks but designing a seat for a person with the natural instincts to excel at those tasks. For instance, a new "Process Optimization Leader" seat might be designed explicitly for someone with high "Fact Finder" and "Follow Thru" Kolbe, ensuring natural alignment with the deep-dive analysis and systematic implementation required. This strategic use of personality data ensures that new seats are not merely reactive fixes but **proactive, dynamically compatible additions** that enhance the overall strength and efficiency of the EOS Accountability Chart.