Case Study
Building a platform from a client’s own decisions.
Client
BroadReach Consulting
Industry
Management consulting
Professional services
Engagement
Iterative co-design
Outcome
Hypercube Intelligence
Live on Azure
The challenge
The decisions that mattered most had the least structure
BroadReach had just completed an AI enablement programme. The capability was there, and the appetite was there. What became obvious during that work was that the firm’s most consequential decisions, the ones that determine whether it wins work and places the right people, were also the least supported by anything systematic.
These were not architectural problems of the kind the advisory practice normally resolves. Nothing was broken between source systems. The gap was that decisions of real commercial weight were being made on instinct, at volume, under deadline, with no structure underneath them.
Tender pipelines managed in spreadsheets
Opportunities tracked manually, scored by gut feel, with no consistent framework for deciding which bids were worth the effort.
Candidate shortlisting was time-intensive and subjective
Reviewing CVs against role requirements took hours, with no consistent scoring model and no way to show why one candidate ranked above another.
Tender responses drafted from scratch every time
Each bid required consultants to rebuild capability narratives and section structure under deadline pressure.
The approach
The requirements came from the room, not from a brief
Rather than scope a product and build it at a distance, we ran the work as a co-design process inside the enablement sessions themselves. Each session opened with the team describing a decision they actually had to make that week. We built a first-cut solution to that decision in the room, then the group pulled it apart and we iterated until the output matched what the work genuinely required.
That structure meant no requirement was ever hypothetical. The weighting model in the talent module exists because the team argued about how much technical skill should outweigh availability, and settled it. The tender scoring dimensions exist because the business development lead could name the bids they regretted and explain what would have flagged them earlier.
Two modules emerged from that process. Tenders WA Intelligence, covering the tender lifecycle from opportunity identification through to a drafted response. Talent Intelligence, covering weighted candidate matching through to a client-ready CV. Both were built to BroadReach’s specification because BroadReach wrote the specification, one session at a time.
The outcomes
A platform the team already knew how to use
Delivered as working software, not recommendations
The engagement ended with a deployed platform on Azure rather than a roadmap. Each module went live having already been used, in draft form, by the people it was built for.
Adoption was settled before launch
Because the team specified and refined each module in session, there was no handover gap and no training phase. The people who would use the platform had already shaped every part of it.
Bid decisions moved from instinct to evidence
Opportunity scoring gave the business development team a consistent basis for deciding which tenders to pursue, and a decision ledger that accumulates the firm’s actual win history.
Shortlisting became explainable
Weighted matching replaced individual judgement with a transparent model, so a shortlist can be defended with a per-dimension breakdown rather than a recommendation.
The platform this became
Hypercube Intelligence
Explore Hypercube Intelligence →
The strongest specifications come from the people doing the work. If you have decisions worth structuring, that is where we start.