Weighted Decision Matrix: 5 Checks for Reliable AI Decisions

1. Define the choice before creating a weighted decision matrix

Start with the decision the team actually faces. Here, the question is how Synopsys could enter simulation and analysis: build the capability, buy Ansys, or continue through a partnership. A generic instruction to “compare the options” leaves the model to decide what the alternatives mean. Name them and define the business objective before asking it to score anything.

The lesson fixes five criteria: time to market, cost, control of the technology, access to Ansys’s customers, and execution risk. Each of three options receives a rating on each criterion. That produces fifteen ratings. The number of cells is a count of the comparison; it says nothing about the quality of the evidence supporting those cells.

Make the direction of the scale explicit. The original weighted decision matrix uses a one-to-five scale where higher is better for Synopsys on every criterion. A five on cost means lower total cost. A five on execution risk means lower risk. Without those definitions, a reviewer could read a high “risk” score as high risk and reverse the intended meaning.

ASQ’s decision-matrix guidance also stresses consistent rating direction and calculating weighted totals. Its guidance supports the method; the case’s fifteen ratings remain specific judgments that require their own evidence. Do not transfer authority from a general method to an individual score.

Before creating your weighted decision matrix, write a one-sentence definition of each option and the meaning of the scale’s endpoints. “Partner” might mean an existing commercial agreement, a new joint venture or a licensing arrangement. Those are different alternatives. If the definition changes halfway through the comparison, reset the affected ratings rather than keeping an apparently comparable score.

1.1 The original scorecard prompt

Build an interactive Build / Buy / Partner comparison for Synopsys's move into simulation and analysis. Score each option on time to market, cost, control of the technology, access to Ansys's customers and execution risk, let me change the weights with sliders, and explain which option wins and why.

The prompt asks for a usable page, a defined comparison and an explanation. It does not turn unknown build costs or partnership economics into known inputs. Add those missing items to the review list.

2. Keep evidence separate from weighted decision matrix judgments

A sourced statement and a rating are different objects. An announcement or filing may support a fact about a transaction or business. Deciding that the fact deserves four points instead of three is an analytical judgment. The weighted decision matrix should retain both the source statement and the explanation connecting it to the rating.

In the original case, Claude explicitly describes its one-to-five scores and default weights as its own judgment. The default gives customer access 30%, control 25%, time to market 20%, execution risk 15% and cost 10%. Those percentages reflect the model’s reading of the deal rationale. They are not disclosed management priorities or a board-approved allocation.

The original artifact also identifies information missing from the supplied materials: internal build cost and timeline, partnership economics, customer overlap and the probability of regulatory approval. Preserve that status. A score can express a provisional judgment despite an information gap; it must not silently imply that the missing quantity has been measured.

For your weighted decision matrix, keep four fields beside each rating: evidence, source location, judgment and unresolved question. For example, a source may describe an existing partnership. The rating then expresses how that arrangement affects speed or control under the exercise’s definitions. The unresolved question might concern the terms of a different partnership the team has not negotiated.

A citation is a place to begin a check. Open it and confirm the specific statement used in the rationale. The original response itself flags an Ansys relationship reference for checking against the filing. The existence of fifteen source references is not proof that fifteen rationales have been independently verified.

Keep score ownership visible as well. A model-generated first pass may help the team identify disagreements, but the person presenting the weighted decision matrix should state which scores the team accepted, changed or left provisional. Record the reason for a change. Replacing a three with a four without an explanation makes the final ranking harder to assess.

3. Recalculate one weighted decision matrix result

Read the formula before trusting the animated bars. A weighted decision matrix multiplies each criterion’s rating by its normalized weight, then adds the contributions for each option. In this case, the five default percentages sum to 100%, so they can be used directly as decimal weights.

Ratings and default weights: original AI Lab artifact. Totals independently recalculated from those inputs. The ratings are judgments, not new company facts.

For Buy, the calculation is 4 × 0.20 + 1 × 0.10 + 4 × 0.25 + 5 × 0.30 + 3 × 0.15 = 3.85. The 1.50 contribution from customer access is the largest component. That tells the reviewer where an important part of the lead comes from.

Next, read how the sliders work. In the original artifact, the slider inputs are normalized by their sum. A raw slider value of 25 does not necessarily mean 25% of the total. If the other four raw values still total 90, a cost input of 25 represents 25 ÷ 115, or about 21.74%. Read the displayed shares before describing a scenario.

This distinction matters when testing a weighted decision matrix. Raising one raw value changes the normalized shares of the other criteria even if their sliders stay still. You have changed their relative importance, not just a single percentage in isolation. Save the full normalized weight vector with the result so another person can reproduce it.

Check that valid weights have a positive total. An all-zero set does not express priorities and should not produce a meaningful recommendation. Also check that the displayed totals, contribution table and ranking use the same inputs. Recalculate the three default totals before testing more scenarios; the arithmetic check is small enough to do independently.

The precision of 3.85 should be read correctly. It is a calculated total from coarse one-to-five ratings. It is not a probability, valuation multiple, percentage return or measured confidence level. A weighted decision matrix makes the implications of the inputs clearer; decimal places do not make the underlying judgments more precise.

4. Test where the weighted decision matrix changes its answer

The lesson’s useful turn comes when the analyst changes the priorities. At the default weights, Buy leads at 3.85 against Partner at 3.40. At equal weights, Partner leads at 3.60 against Buy at 3.40; Build scores 2.40. The ratings have stayed the same. The change in ranking comes from the weighting decision.

That is a sensitivity result, not a new discovery about the companies. It shows that the preferred option depends on what the decision maker values. A weighted decision matrix should make that dependence easy to see, especially when the initial recommendation favors a capital-intensive acquisition.

The original artifact describes a cost-weight flip point of about 22%. This can be checked from its scores. If the other four criteria retain their default relative proportions, Buy’s advantage over Partner on those criteria is 0.75 divided by 0.90, or about 0.8333. On cost, Buy trails by three rating points. With cost share x, their total difference is 0.8333 × (1 − x) − 3x.

The tie occurs at x = 5 ÷ 23, approximately 21.74%. Above that share, Partner overtakes Buy under this particular test. Keep the condition attached to the number: the other four weights retain their relative proportions, and the fifteen ratings stay fixed. “Buy loses above 22% cost weight” is incomplete without those conditions.

Now test the ratings, not only the weights. If the evidence for a score is weak, ask what happens when the team gives it a neighboring rating. Keep that exercise separate from the weight test, so the reader knows whether the change came from new priorities or a different assessment of an option.

For a practical weighted decision matrix review, save the baseline, the equal-weight scenario and one justified alternative. For each, record the ratings, normalized weights, totals, winner and reason for the scenario. A screenshot of the winning bar alone loses the information needed to explain why it won.

Use the disagreement to direct further work. If a result depends heavily on an uncertain control score, identify the evidence needed to resolve that score. If the disagreement concerns cost versus access, put that priority choice to the decision maker. Repeatedly adjusting sliders until a preferred option wins does not strengthen the case.

5. Carry weighted decision matrix conditions into the memo

The next step in the original video is file creation: Claude produces a Word board memo using the previous work. The value is continuity between the scorecard and the written recommendation. Keep the same checked inputs, scenario labels and source references when moving from a weighted decision matrix to a document.

5.1 The original Word-file prompt

Write a two-page board memorandum recommending the acquisition. Cover the strategic gap, why acquisition rather than building or partnering, why now, the key deal numbers, and the main risks with mitigations. Insert the growth-gap chart and save it as a Word file.

This prompt explicitly asks the model to recommend the acquisition. It sets a position for the writing task; it is not an independent finding that acquisition is the best option. Read the result with that instruction in mind. The equal-weight comparison must remain visible even when the assigned document argues for Buy.

A defensible handover states that Buy leads under the specified priorities, while Partner leads at equal weights. Then explain why the decision maker prefers one set of priorities. That connects the recommendation to an accountable choice. A weighted decision matrix should not disappear into an unconditional sentence that its own scenarios cannot support.

Keep three labels distinct in the memo: source facts, calculated figures and proposals. The original Word file labels the channel-neutrality mitigation as a proposal. That wording matters because a suggested response is not evidence of a company commitment. Check the file’s text rather than assuming the chat’s description matches it.

Open the actual download and check the requested length, chart, table and sources. A two-page instruction is a specification, not proof of a two-page result. The original demonstration includes rendering and trimming during document creation. On your own file, inspect the final pages after downloading it, including any small chart labels or material moved onto another page.

Claude’s file-creation guidance describes downloadable Word and other file outputs. The analyst still reviews the document. Keep the checked table and chart available in the continuing conversation; if you start a new chat, supply them explicitly rather than assuming the previous calculations have followed you.