Organizational HealthDEMO DATA

Diagnostic

A six-axis read on the operating model's health. Use this to decide where to invest in the Mixing Board next, and to ground the case you make to leadership.

Overall
61
/100 · WATCH
I'm here to

See where the operating model is healthy and where it's hurting before you redesign it.

What I'll click

Scan the radar for off-balance axes, then expand any card to read its sub-questions.

What I'll have when done

A short list of weak axes you should prioritize on the Mixing Board and Design Canvas.

Six-axis radarOuter ring = 100 · inner ring = 25
Strategic Clarity72 · GOODDecision Effectiveness58 · WATCHOperating Discipline65 · WATCHTalent Health68 · GOODInnovation Capacity54 · WATCHChange Readiness49 · LOW

Strategic Clarity

72

Strategy is articulated and cascaded; the gap is the front-line translation.

Sub-questions to check
  • Can a randomly-sampled manager explain the strategy in 60 seconds?
  • Do every leader's OKRs visibly ladder to enterprise strategy?
  • Is there a single up-to-date strategy document people refer to?

Decision Effectiveness

58

Decisions land but cycle times are 18-24 days; governance forums overlap.

Sub-questions to check
  • Do decisions get made at the right level? Or escalated unnecessarily?
  • Are forums duplicating each other's mandate?
  • Is the decision-rights matrix documented and current?

Operating Discipline

65

Mature in Operations; gaps in Customer Experience and Tech delivery.

Sub-questions to check
  • Are process owners named for every value-creating workflow?
  • Is there a single metric tree linking inputs to outcomes?
  • Do post-mortems lead to documented process changes?

Talent Health

68

Engagement is strong; capability gaps in AI and data engineering.

Sub-questions to check
  • Do you know your top 5% of talent by name and engagement?
  • Is the future-state capability map mapped to current skills?
  • Is voluntary attrition trending up, down, or flat?

Innovation Capacity

54

AI utilization at 45% with significant remaining lift in Operations.

Sub-questions to check
  • How many novel AI use cases moved from pilot to production this year?
  • Is there a portfolio view of innovation bets vs. baseline runs?
  • Do you have a working data foundation that compounds?

Change Readiness

49

Past initiative load is high; the org's appetite for new change is depleted.

Sub-questions to check
  • How many concurrent transformation programs is the org carrying?
  • Are change-program leaders measuring adoption (not just rollout)?
  • Is there a sequenced 'change calendar' to prevent collisions?
  1. 1Read the overall score in the header to set context.
  2. 2Scan the radar for which axes pull the shape off-balance.
  3. 3Open each axis card to read its one-line narrative + sub-questions.
  4. 4Use the answers to decide which Mixing Board levers to move next.
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