SBI: Turning Expert Services Into a Product

SBI sold growth expertise to enterprise sales and revenue teams. Analysts pulled information from CRM, finance, HR, and assessment systems, synthesized it, and delivered recommendations.

The service created value, but delivery depended on analyst capacity. Every engagement meant manual aggregation, interpretation, and presentation. The customer received an output, while the method stayed inside the consulting team.

SBI wanted to move toward software and subscription revenue. The product had to carry enough of the method that customers could use it directly, while preserving the judgment that made the work credible.

The opportunity was to automate the assembly, preserve the judgment, and make the plan useful after delivery.

The platform before: separate tools, one deliverable at a time

Where the work broke down

I interviewed business analysts, decision-makers, internal users, and external partners, and observed live workflow sessions to see where people stalled and which tasks took the most time.

The work followed a predictable sequence: prepare data, compare results, generate reports, interpret signals, turn recommendations into action. Analysts spent most of it gathering and structuring information. The judgment clients paid for came last, and was often rushed. That set the product direction:

• Automate aggregation and structure.
• Keep the evidence visible.
• Leave the recommendation editable.
• Carry the work forward into planning.

The consulting workflow, mapped to the product

Phase 1: digitizing the consulting method

The first phase turned three repeatable consulting frameworks into self-service workflows.

Phase 2: one growth plan instead of separate tools

The three workflows produced useful scores, but customers still needed to know what to do next. Progress depended on personal initiative and an advisor’s guidance. I designed a growth roadmap to put that progression inside the platform. It shows clients:

• their current position in the growth plan and which assessments come next
• current scores, and the training and initiatives they require
• completed, upcoming, and outstanding work, with owners, stages, and progress

Outputs from the three workflows fed one connected plan. The roadmap turned separate analyses into a guided operating workflow, and gave clients a reason to return as the plan moved.

The growth roadmap: assessments, training, and initiatives in one plan

Phase 3: AI without removing expert control

The platform then added AI-assisted analysis and reporting. A user selects the business context, connects data, chooses a growth lever, and receives a structured recommendation with sources, calculations, and suggested next actions, editable and connected to roadmap work. The design challenge was trust.

I rejected a fully automated recommendation flow: it removed the analyst judgment customers relied on. The final approach encoded the repeatable method and kept interpretation visible and editable.

Iterating on report creation

Production use also showed what prompting alone could not fix. Chat lacked persistent access to the client’s data, users had to restate context to refine an analysis, and exploring a second hypothesis derailed the first. The second version shipped with persistent connected data and parallel threads, so chat became one layer of the workspace rather than all of it. Later, at S&P Global, I met the reverse problem: structured work forced through chat.

One foundation for the portfolio

As the sole designer, I built a 40-component system across the product portfolio: shared tokens, light and dark analytical environments, chart and table patterns, status states, navigation, and dense dashboard layouts. Standardization covered repeated behavior; product-specific patterns stayed local where they needed to.

One component library shared across two products

Adoption

Assessments, roadmap progress, and analysis in one place

Customers could launch assessments, review scores, see their position in the growth plan, and track completed and upcoming work directly in the product, and they returned to monitor progress. Analysts moved repeated assessment setup, reporting, roadmap guidance, and progress tracking into the platform, and stayed involved in interpretation and advisory work.

How the 30% was measured

The team ran two-week sprints and tracked every task in Jira with story points and status. I grouped stories by comparable point ranges, compared median active-to-done time before and after the shared foundation was in regular use, and excluded backend-only work, incidents, and unusually large initiatives. The result was a 30% reduction in design-to-production cycle time for comparable UI work.

A measurement framework for the product

I defined the core funnel from first assessment to ongoing execution: analysis started → recommendation reviewed → roadmap item created → roadmap revisited → progress updated.

What it changed commercially

• continued use between advisory interactions
• clearer value across assessments, training, reporting, and planning
• more analyst capacity through self-service delivery

Those are the product mechanics a subscription model needs. This case does not attribute a specific revenue increase to design.

Building the shared foundation first slowed early delivery. I accepted that, because shipping each workflow on its own would have recreated the fragmentation the product was meant to solve.

I also limited standardization. Some analytical patterns needed different densities or navigation. Forcing them into one component would have hurt usability and pushed teams to bypass the system.

I started out treating the work as a redesign of several tools. Research showed the deeper opportunity was to change what the customer received.

The strongest decision was separating repeatable assembly from expert judgment. Assembly moved into the product; interpretation stayed visible and editable.