Update to Forward Deployed

{
  "description": "Build and test the business case, ROI and economics of an enterprise AI investment or service. Use for revenue, decision quality, expert capacity, delivery economics, and expansion choices where the architecture and changed work determine the return.",
  "included_files": [
    {
      "relative_path": "references/new-service-economics.md",
      "size_in_bytes": 6521
    }
  ],
  "name": "value-case",
  "skill_md_contents": "---\nname: value-case\ndescription: Build and test the business case, ROI and economics of an enterprise AI investment or service. Use for revenue, decision quality, expert capacity, delivery economics, and expansion choices where the architecture and changed work determine the return.\n---\n\n# Value case\n\nBuild the economic argument for the decision at hand: investigate, deploy, redesign, price, or expand. Compare the proposed capability with what the organization would otherwise do over the relevant horizon. Make a recommendation and calculate the assumptions that could reverse it.\n\n## Establish how value is created\n\nFollow the capability to an operating or customer result. Use the mechanisms that fit:\n\n- **Revenue and new services:** who buys what, adoption or conversion, price, retention, time to revenue, and incremental contribution after fulfillment costs. Include cannibalization where the service replaces existing revenue.\n- **Decision quality:** which decision changes and how that affects an outcome. Evaluate better choices, useful discoveries, or avoided losses against comparable work.\n- **Capacity and coverage:** which scarce expertise is released, what work it will take on, and whether the receiving operation can use it.\n- **Service performance:** what earlier, broader, or more reliable work makes possible, such as reaching customers previously uneconomic to serve.\n- **Cash savings:** which purchased service, overtime, hiring, or other expenditure changes and when.\n\nKeep a useful operating measure when monetary conversion is weak. For a new service, test demand through use, a commercial offer, or paid delivery. Build the case around the population the funded scope can reach.\n\n## Cost the delivered outcome\n\nChoose a unit that carries value through the workflow: a completed implementation, resolved investigation, accepted customer deliverable, or retained subscriber. Keep acceptance and timing consistent across alternatives. Include abandoned and unresolved work in the entered population.\n\nModel the materially different paths, including retries, review, correction, fallback, and subsequent completion. For mutually exclusive paths:\n\n```text\nexpected cost per entered case = Σ path share × full path cost\ndelivery cost per accepted outcome = total delivery cost / accepted outcomes\nhuman demand = entered volume × Σ path share × human time\n```\n\nCharge both attempts when assistance fails and a person completes the work. Connect machine consumption to the workflow: investigation depth, tool use, refresh frequency, and reused work. A cheaper model can cost more overall if it creates expensive recovery.\n\nSeparate build cost, fixed operation, usage costs, and human delivery effort. Include integration, evaluation, support, transition, and maintenance where they affect the choice. Use current prices and measured consumption when available.\n\n## Make volume and capacity agree\n\nCompare human demand with productive time available after existing obligations. Include ongoing customer support and supervision, as well as individual case handling. Averages establish capacity arithmetic; delivery deadlines may require arrival and handling distributions or a queue simulation.\n\nModel the effects of expansion. More complex cases can increase price, investigation effort, and review together. Wider coverage can lower conversion and create downstream work. A second deployment may reuse context and tools while adding local policies, integration, and support costs.\n\nReleased salary time is capacity until the operating plan converts it into avoided expenditure or additional output. Do not add a labor-equivalent benefit to revenue earned with the same hours, count avoided hiring and staffing reductions twice, or repeat shared benefits across several workflows.\n\n## Price the commitment and test the return\n\nUse period cash flows when build cost, adoption ramp, benefit lag, or useful life matters. For a paid service, show contribution per customer, service margin, onboarding effort, and the continuing obligation at the proposed price. For investment appraisal, state the horizon and any discount rate; positive unit margin alone does not recover a build.\n\nFind the thresholds that matter: paid demand needed to cover fixed cost, accepted volume needed for payback, human effort compatible with capacity, or price needed to sustain the service. Read [the new-service economics example](references/new-service-economics.md) for a worked model linking all four.\n\nRecommend the commitment that the evidence supports. Where uncertainty dominates, price the next test and specify which investment decision its result will resolve. Reconcile realized value against comparable case mix, participation, accepted outcomes, total cost, and the use of released capacity. Deliver an editable model and a short explanation of the recommendation, including the assumption that most threatens it.\n"
}