Try this
Raise a firm's two capability scores to 10. Its point closes every positive-area upper-right rectangle for that pair. Then lower one score and move the entrant sliders to see when the shaded area becomes reachable.
Dimensions and modelling assumptions
All six scales run from 0 to 10. Equal distances are treated as comparable only for this exercise; the dimensions are not established as statistically independent. A higher score means more of the chosen input, not a better business outcome.
The search uses thresholds on a 0.1 grid and includes rectangle boundaries: a point on a boundary makes that rectangle occupied. “Largest” means greatest area on this grid, not an exact continuous optimum. Automatic selection deliberately chooses the four dimensions with the largest sum across their six plots; those areas overlap and do not represent a six-dimensional market volume.
Editable capability scores
These illustrative inputs retain the original toy numbers with fictional labels. They are not assessments of named companies. Changes last for this visit; download the CSV to keep them.
Choose four dimensions
Six pairwise plots show the selected dimensions. Uncheck one before selecting a replacement.
● Fictional firms ◆ Entrant hypothesis ▧ Empty upper-right region in the entered scores
Entrant hypothesis
Sliders change only the entrant. They do not alter which regions are empty among the five firms.
Largest empty areas in the inputs
Turn the picture into questions
Could a small service combine programme controls, reusable tools and industrial data skills? Treat this as a design prompt: specify the customer problem, delivery capacity, evidence and contract terms needed to make it credible.
- An empty region can reflect an unattractive combination or a missing observation.
- Changing scale definitions or adding another firm can change the result.
- A two-dimensional gap can conceal trade-offs elsewhere in the six scores.
- The geometry does not estimate revenue, risk, adoption or the entrant's ability to deliver.
Worked hypothesis: Controls + Twin + Contract
This speculative offering from the original exercise is a design to investigate, not a conclusion produced by the scores or a claim about a gap left by real competitors. Imagine an industrial transformation studio serving a capital programme or an existing operating asset.
- OT/IT data spine. Connect operational-technology records, historians and edge systems with information-technology records, using explicit data ownership and governance. The hypothesis is that a reusable spine could reduce repeated integration work; it would need testing against actual access, security and data-quality constraints.
- Digital twin / critical-asset model. Use a model of selected assets to help prioritise work on reliability, energy use or integrity. Test which decisions the model could change and how its outputs would be checked; a visual representation alone would not establish those benefits.
- Instrumented programme controls. Explore schedule-risk simulation, scope/change telemetry and traceability intended to support claims or assurance. Ask what evidence each control requires and how a reviewer would connect an output back to the underlying records. “Claims-ready” remains an intended capability to demonstrate.
Commercial hypothesis: package the work as modular capability units, with gainshare or measurement-warranty arrangements as possibilities to test. A gainshare proposal would need an agreed baseline, attribution rules and a way to verify improvement; a measurement warranty would need a precise scope, exclusions and a party able to carry the promised risk. The chart does not establish that such contracts are viable.
Use the entrant sliders to describe the capabilities this offering would require, then identify what would make that profile credible: reusable delivery assets, engineering experience, evidence of controls working and sufficient operating capacity. Operator-embedded delivery could be a seventh dimension in a future version; it is not measured by this six-dimension app.
What this particular geometry leaves out
The upper-right, or “high–high”, search encodes a strategy of combining high capability scores. It does not search for cost leadership or an underserved middle segment; those questions would need different dimensions or a different empty-region criterion.
Each fictional firm is represented by one point. An alternative model could use a distribution across teams, sub-practices, locations or uncertain assessments. A single point hides that variation, so an apparently empty area should become a question about the inputs before it becomes an offering claim.
Origin of the exercise
The original creation prompt asked for capability dimensions, numerical scores, six pairwise small multiples and an entrant profile. It named real consulting firms without supplied evidence. This edition preserves the exploration and numerical examples while using fictional firms and removing unsupported market conclusions.