Solutions
Solve the friction that slows the mission.
Start with the operating problem. Define the change people need. Put digital tools and AI to work where they can make that change useful and measurable.
Strategy and alignment
Turn a broad modernization goal into a clear decision and an actionable delivery path.
The work can include:
- Mapping the current process and the people who depend on it.
- Defining the mission outcome, constraints, and decision owners.
- Prioritizing changes by value, effort, and delivery dependencies.
- Building a roadmap with a practical first increment and measures of success.
The intended result: A shared direction and a clear starting point for execution.
Metrics to Mission Outcome Mapping
Choose measures that connect time, cost, agility, user experience, and resilience to the mission result. Establish what can be measured and how the evidence will inform decisions.
Investment Horizon Portfolio Strategy
Build one view of capabilities being evaluated, piloted, expanded, sustained, or retired. Connect investment choices to maturity, mission value, dependencies, and delivery timing.
TBM Portfolio Visibility
Use Technology Business Management to connect capabilities, services, and spending. Give leaders a consistent view of overlap, ownership, and rationalization choices as the organization changes.
Modernization Decision Analytics
Compare modernization choices using mission value, feasibility, and expected improvement. Make the reasoning behind sequencing, scaling, restructuring, and retirement decisions visible.
Divest-to-Reinvest
Plan the retirement of redundant or obsolete technology alongside transition and reinvestment choices. Clarify dependencies and continuity needs before an existing capability is removed.
Adaptive Roadmaps
Connect portfolio decisions and delivery schedules in a roadmap that can change as mission needs, funding, and technology maturity change.
Structured Challenges
Define a mission problem and a structured way to gather, evaluate, and test ideas. Plan how learning and promising results can move toward adoption.
Digital delivery and workflow automation
Reduce the manual steps and disconnected handoffs that make work take longer than it should.
The work can include:
- Designing a simpler workflow around real user needs.
- Automating repeatable steps and connecting existing tools where practical.
- Making status, ownership, and information easier to see.
- Planning rollout, user support, and the handoff to steady operation.
The intended result: A workflow people can use, maintain, and improve.
Operating Model and Workflow Design
Clarify responsibilities, decision rights, service boundaries, and handoffs. Simplify repetitive dependencies before introducing automation or AI.
Digital Engineering Delivery
Connect architecture, software development, integration, testing, release, and sustainment. Deliver working increments with the engineering and operational handoff needed to use them.
Agile & Resilient Contracting
Support acquisition and work-package design around the intended delivery model. Align requirements, pilot pathways, transition plans, and outcome measures with how capability is expected to evolve.
Enterprise Service Designations
Prepare the analysis for an enterprise-service decision: capability maturity, redundancy, stakeholder needs, exceptions, and ongoing measures.
Enterprise Service On-Ramp
Plan how teams can adopt a designated enterprise service. Address migration, dependencies, exceptions, and the sequencing of local-tool retirement.
AI-enabled work
Apply AI to bounded work with a clear user, a defined purpose, and a way to judge usefulness.
The work can include:
- Identifying tasks where AI assistance may reduce repetitive effort.
- Testing focused uses such as finding information, preparing a first draft, or organizing inputs for review.
- Defining the review and escalation steps around the workflow.
- Comparing quality, time, and user experience before expanding use.
The intended result: A tested AI-enabled workflow, with evidence to decide whether to adopt, improve, scale, or stop.
AI Workflow Automation Fabric
Design automation and orchestration around a defined workflow. Reduce repetitive routing and handoffs while making ownership, review points, and exceptions explicit.
Recognize the bottleneck.
These examples show the kinds of problems we want to help address. They are illustrative, not client case studies.
The same information entered more than once
Map why each entry exists, simplify the handoff, and explore automation. Measure repeated effort and rework before and after the change.
Mission visibility, built into execution.
Connect delivery tools to capture execution evidence automatically and make progress, bottlenecks, and outcomes available on demand. Use AI to summarize changes and flag exceptions, with people accountable for validation and decisions. Generate scheduled summaries from the same traceable evidence. Measure success through reduced processing time, fewer errors, and more time returned to the mission.
Useful knowledge that is hard to find
Understand the information environment and test a focused way to locate and review relevant material. Measure task completion and answer usefulness with the people doing the work.
One mission outcome. A practical next step.
We can begin by discussing the process, the people affected, and the result you need. From there, the right scope can take shape.