Better decisions
before development begins.

A $15M healthcare IT product portfolio serving clinical operations was mid-roadmap planning. The product team had completed a standard discovery cycle — stakeholder interviews, requirements documentation, and feature prioritization — and was preparing to commit engineering capacity to the next build cycle.

The challenge was not a lack of user input — it was the wrong kind. Stakeholder interviews capture what people say they do. In regulated clinical environments, staff are trained to describe the official process, not the actual one. Standard discovery methods were systematically blind to the gap between protocol and practice. The roadmap was confident, well-documented, and pointed in the wrong direction.

Compounding the challenge: challenging a roadmap that had stakeholder sign-off, documented requirements, and executive alignment required workflow evidence strong enough to override organizational momentum. Opinion would not be sufficient.

Conducted direct field observation and contextual inquiry sessions with clinical staff across care settings — watching actual task execution, not listening to task descriptions. Mapped the end-to-end as-is workflow using service blueprinting to capture frontstage actions, backstage processes, system touchpoints, and failure points in a single visual.

The service blueprint revealed a layered system of compensating behaviors: informal routing protocols, manual reconciliation steps between systems, and shadow workarounds that clinical staff had normalized over months. These were not complaints — they were invisible adaptations to a product that had drifted from the actual clinical workflow.

The workarounds were not edge cases or user preference. They were structural signals: the product architecture had diverged from the clinical workflow at a foundational level. Every new feature being planned would be built on top of that misalignment — adding complexity to a broken foundation rather than correcting it. The requirements document was not wrong — it accurately captured the official workflow. The official workflow was not what clinical staff were doing.

Presented the service blueprint and workflow gap analysis directly to product leadership — before sprint planning, before architecture commitment. The case was grounded in observed evidence, not inference: specific workflow steps, named failure points, and quantified frequency of workaround usage. Designed and proposed a future-state workflow model that resolved the structural misfit, redefining what the product needed to do at the architecture level.

The roadmap was halted. The portfolio architecture was realigned to the actual clinical workflow before any additional build investment was committed. This was not a scope change — it was a decision about what the product fundamentally needed to be.

Emerson Electric's global industrial technology business unit was entering a strategic planning cycle with a mandate to identify digital transformation opportunities and rationalize a complex, multi-product portfolio. The business operated across global markets with deeply entrenched operational workflows — ERP dependencies, manual processing touchpoints, and an aging product portfolio with varying levels of market performance. Standard productivity metrics were available but showed only output, not the workflow constraints producing it.

The scale of the operating model made the true scope of transformation opportunity invisible. Legacy process dependencies created a web of interdependencies that standard top-down analysis could not penetrate — each function reported its own metrics, but nobody had mapped how the workflows connected end-to-end across functions and systems. Transformation investment was being evaluated against output measures, not the workflow constraints causing them.

Separately, the product portfolio contained underperforming offerings that had internal champions, existing customer bases, and sunk cost histories — making "stop" decisions politically difficult to execute without incontrovertible workflow impact evidence grounded in data rather than judgment.

Mapped legacy process dependencies end-to-end across the operating model — tracing workflows from customer touchpoint through internal processing, system handoffs, and output delivery. Identified where workflow bottlenecks were compressing throughput, where manual overrides were compensating for system gaps, and where ERP fragmentation was creating redundant effort across functions.

For product portfolio rationalization, conducted Voice of Customer sessions and competitive workflow analysis to assess where each product was delivering versus failing to deliver differentiated operational value to customers. Constructed workflow impact models to quantify the cost of continuation for underperforming products — converting strategic judgment into measurable data.

The $100M+ digital transformation opportunity was not in any single process or system — it was in the accumulated cost of workflow fragmentation across the operating model. Legacy process dependencies were not just inefficient; they were actively masking transformation potential by making it appear that improvement required total system replacement. The workflow map revealed a modular path: targeted interventions at specific dependency points could unlock disproportionate operational improvement without wholesale re-platforming.

For the product portfolio, workflow analysis revealed that several underperforming offerings were not failing due to market dynamics — they were failing because the product's operational model no longer matched how customers' workflows had evolved. The products were solving yesterday's workflow problems.

Presented the $100M+ opportunity analysis and future-state workflow model to C-suite leadership — designing automated future-state workflows that demonstrated specific throughput improvements at each targeted dependency point before any investment was committed. The future-state design was testable and measurable, not conceptual.

For product rationalization, delivered evidence-based "stop" recommendations — not deferrals, not scope reductions — grounded in workflow impact data. Achieved C-suite alignment before execution. For the $500M Aventics acquisition, led cross-functional due diligence that assessed technology stack compatibility and workflow integration points before deal close, preventing integration surprises that would have created post-acquisition rework.