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Executive Intelligence · Decision Intelligence and Simulation

Decision Outcome Learning

After a decision, records the expected outcome and later the actual outcome, measured from verified sources.

Demonstration: Pinecrest Foods plc (fictional) · Food manufacturing. Fictional data and a scripted answer.

The situation

Organisation
Pinecrest Foods plc (fictional)
Who is asking
Chief executive
Industry
Food manufacturing
What happened
The executive committee wants to learn from the last year's major decisions by checking what was expected against what happened.

The question asked

How did last year's major decisions actually turn out against what we expected, and what should we learn?

What it reads, and who can see the result

  • Decision log registerDecisions with the expected outcome at the time.
  • Outcome data exportWhat actually happened.
Reads
The decision log and measured outcomes.
Does not read
Private notes of the discussions.
Permission
Chief of staff access to the log.
Who sees it
The CEO and the executive committee.

Try it

Review each flagged record: confirm it or dismiss it. The totals and the answer below follow your decisions.

DecisionExpectedActualShortfall vs expected (GBP)FindingDecision
Open second bakery lineOutput +20%+21%0MatchedNone needed
Switch flour supplierSave 400,000Saved 410,0000MatchedNone needed
Launch plant-based rangeSales 3.0 millionSales 1.8 million1,200,000Sales 40% below the expectation in the plan
Automate packing lineSave 900,000Saved 450,000450,000Half the expected saving; delayed commissioning
Close the regional depotSave 300,000Saved 120,000180,000Hidden transport costs not in the case
Raise prices 3%Margin +1.1 ptsMargin +1.0 pts0MatchedNone needed
Flagged
3 of 6 · GBP 1,830,000
Record as a lesson
0 · GBP 0
Explained by events
0 · GBP 0
Undecided
3 · GBP 1,830,000

The answer

Simulated answer. Written for this fictional case, not produced by a live model. Only the figures in it are computed, from what you decided above.

3 of 6 decisions fell short of expectation, by GBP 1,830,000 in all.

Most decisions delivered what was expected; three did not [S1][S2]. A shortfall is not always a bad decision: a delayed commissioning date is an execution problem, a missed sales forecast a judgement problem, and hidden transport costs a business-case problem.

You have recorded 0 as lessons (GBP 0 of shortfall) and 0 as explained by events (GBP 0); 3 are undecided. The learning is in the sort of mistake, not the size of it.

Relies on: S1 · Decision log, last yearS2 · Measured outcomes

Review and approval

The chief executive decides. Approving records the lessons in the decision log for use in future business cases. It does not assign blame or change any decision.

Not ready to approve. 3 flagged decisions are still undecided. Confirm or dismiss each one first.

In the product this is a different person with the right permission. Here you play that role to see the rule.

What it produces

registerDraft, not approved

Decision lessons

  • Lessons recorded: 0, GBP 0 of shortfall.
  • Explained by events: 0.

Limits of this example

  • A single year of decisions is a small sample.
  • Expected outcomes recorded afterwards would be unreliable; the log must be written at the time.
  • This is a scripted demonstration on fictional data. No model was called and no real organisation, person or result is shown.