B2G deep dive

The bookings tree is the same shape as the ecommerce GMV tree from b1, but every leaf moves on a government clock. Qualified pipeline is built over months of capture work; win rate turns on a proposal and an evaluation panel; average contract value is set by the scope of a solicitation you often cannot change. A percentage change in any one leaf still passes straight to bookings - the multiplicative rule does not care how slow the cycle is.

{
  "unit": "$",
  "root": {
    "label": "Contract bookings", "op": "x",
    "children": [
      { "label": "Qualified pipeline", "value": 40, "unit": "opps" },
      { "label": "Win rate",           "value": 0.25, "pct": true },
      { "label": "Avg contract value", "value": 250000, "unit": "$" }
    ]
  }
}

The long cycle sharpens the leading-versus-lagging split more than any other domain. The further left you look, the earlier the warning.

• Leading: pipeline coverage (pipeline / target), number of proposals submitted, capture rate on pursued deals. These move quarters ahead.
• Lagging: bookings, obligations (funds actually committed), and program outcomes - all of which close the book on decisions made long ago.
• The rule: if coverage slips under about 3x this quarter, next year's bookings are already at risk - and no amount of end-of-year selling can rebuild a pipeline that takes months to qualify.

• A re-compete lost -> the Win rate leaf drops. An incumbent contract went to a competitor at renewal. Owner: capture and proposal teams.
• Budget delays (a continuing resolution, an appropriations slip) -> the Qualified pipeline slips right - deals do not vanish, they move to a later quarter. Owner: capture, and honestly, Congress.
• Scope cuts -> the Avg contract value leaf shrinks. The agency de-scoped the solicitation. Owner: the customer, but pricing and solutioning respond.

On the bookings tree in Demo 1, edit Win rate from 25% down to 20% - a five-point drop, the kind a single lost re-compete can cause. Bookings fall from $2.5M to $2.0M, a 20% hit from a five-point move, because 5 points is one-fifth of 25. That is the multiplicative pass-through: a proportional change in one leaf is a proportional change in the top line. Say which team owns win rate and what a five-point recovery would take.

Coverage is a ratio, so model the numerator as a tree and read it against the target. Here is qualified pipeline summed across stages - an additive tree. Total it, then compare to the $2.5M bookings target to get coverage.

{
  "unit": "$",
  "root": {
    "label": "Qualified pipeline", "op": "+",
    "children": [
      { "label": "Prospect",    "value": 4000000, "unit": "$" },
      { "label": "Proposal",    "value": 2500000, "unit": "$" },
      { "label": "Negotiation", "value": 1000000, "unit": "$" }
    ]
  }
}

Your program hits its bookings target exactly, but the mission top line slides - fewer people served, cost per outcome up, an SLA missed. Which top line matters more, and to whom?

• It depends on who is asking, and both are true at once. To the contractor's finance team and shareholders, bookings are the number that keeps the company solvent. To the agency, the taxpayer, and the citizen the program exists to serve, the mission outcome is the entire point - bookings are just the means.
• The honest answer refuses the trade. A program that banks the money and fails the mission is failing, even with green bookings. Sustained outcome misses also cost future bookings: agencies remember, and re-competes are won or lost on past performance.
• The lesson: decompose and report both top lines side by side. The moment you optimize only the one that pays, Goodhart takes the other. Mission and money are two scoreboards, and a mature team keeps its eyes on both.