Workflow & Experience Engineering
Workflows that get adopted, not just deployed
We engineer workflows around how work actually gets done — so new systems deliver value on day one, not day never.
- Platform delivery experience
- 40+ years
- Every engagement
- Senior engineers
- Average engagement cost
- $40K – $75K
Where you start
Different starting lines. The same adoption-first approach.
New systems are not getting adopted
You built or bought a new system, but operators are not using it. Workarounds persist. The investment is not delivering value.
Workflows do not fit
The system works technically, but the workflows do not match how work actually gets done. Operators resist or work around it.
De-risk a platform or AI launch
You are about to launch a new platform or AI capability. You want to validate workflows with real operators before deployment to avoid adoption failure.
Most platform and AI failures are adoption failures
The technology works. The architecture is sound. But operators do not use it. Workarounds persist. Support tickets multiply. The old system stays alive because the new one does not fit how work actually gets done.
Adoption failure is not a training problem. It is a design problem. When workflows do not match operators' mental models, resistance is rational. The system was designed for the architecture, not the people who have to use it.
What we deliver
Workflow engineering that connects UX to operations and measures adoption, not just deployment.
Workflow mapping and redesign
Map current workflows and pain points. Redesign around how operators actually work, not how the architecture suggests they should.
UX tied to operational outcomes
UX is not aesthetics. It is a mechanism to reduce adoption risk and operational mistakes. Design decisions are grounded in operator research.
Product and feature prioritization
Prioritize features based on operator impact and adoption risk. Build what matters first. Defer what does not change outcomes.
Adoption enablement and rollout
Adoption enablement is part of delivery, not a separate workstream handed to HR or training. We plan the rollout alongside the build.
Measurement of usage and effectiveness
Adoption rate, task completion time, error rate, and support burden. We measure what matters — not just whether the system was deployed.
Delivery principles
Operators first. Adoption measured. Change treated as a delivery problem.
Operators before architects
Real workflows inform design decisions before architecture hardens.
Adoption criteria before launch
We define measurable go/no-go gates based on operator readiness, not project timelines.
UX as engineering control
UX is not aesthetics. It is a mechanism to reduce adoption risk and operational mistakes.
Measure what matters
Adoption rate, task completion time, error rate, and support burden — not just deployment.
Change is a delivery problem
Adoption enablement is part of delivery, not a separate workstream handed to HR or training.
Engagements & Typical Ranges
Typical ranges shown. Final pricing depends on scope, complexity, and platform constraints.
Workflow Discovery & Design
Map current workflows, identify pain points, define adoption criteria, and design validated solutions — grounded in how operators actually work.
- Current-state workflow mapping and pain-point analysis
- Operator research and task-level walkthroughs
- Measurable adoption criteria defined up front
- Clear next steps — execute with us or your team
Workflow Implementation & Adoption
Build, validate, and roll out workflows with measured adoption. Scoped from Discovery findings.
Ongoing Optimization
Continuous workflow improvement, adoption measurement, and optimization tied to operator outcomes.
How we approach workflow differently
We design around how work actually gets done. Operator walkthroughs before architecture hardens. Adoption criteria before launch. Go/no-go decisions based on measured readiness, not project timelines.
Operator Research
Understand current workflows, pain points, and what success looks like
Adoption Criteria
Define measurable criteria: time to complete, error rate, audit compliance
Design and Prototyping
Design workflows that fit operators' mental models; interactive prototypes tested with real data
Operator Testing
Test with real operators using live data before rollout; measure adoption readiness
Rollout and Measurement
Adoption enablement, change management, usage tracking, effectiveness measurement
What you get
Adoption by design, not by hope
- Workflows validated with real operators before anything hardens
- Measurable adoption criteria that define what "ready" means
- Go/no-go gates based on operator readiness, not project deadlines
- Systems that people use on day one — not systems they work around
How We’ve Helped Our Clients Solve Real, Meaningful Problems
What changes
- Adoption rate up
- Task completion time down
- Support burden down
- Feature usage up
Why this feels different
We do not design screens and hand them off. We engineer workflows with operators, validate adoption before launch, and measure what matters after.
Who this is for
- VP Product and CTO teams launching platforms that must be adopted on day one
- Operations leaders whose teams resist new systems or work around them
- Organizations where previous technology investments failed due to adoption, not technology
- Leaders de-risking platform or AI launches with operator validation
Who this is not for
- Organizations looking for visual design or brand identity work
- Teams that want UX polish without willingness to change workflows
- Buyers who treat adoption as a training problem, not a design problem
Frequently Asked Questions
Ready to design workflows people actually use?
Three to five weeks. We map current workflows, define adoption criteria, and design validated solutions — with your operators at the table from day one.
Talk to our workflow team