Car Acquisition Decision Matrix Template

This template is a simple yet powerful decision‑matrix workbook that lets you evaluate several car models against up to five criteria you define. The workbook contains three sheets: Cars, Criteria, and Summary. In the Cars sheet you list each vehicle in its own row and enter a numeric score (0‑10) for every criterion column. The Criteria sheet holds the names of the five categories (e.g., Cost, Fuel Efficiency, Safety, Comfort, Resale Value) and lets you assign an optional weight if you want some factors to count more heavily. The Summary sheet automatically calculates the weighted average for each car, ranks the models, and highlights the top recommendation with a traffic‑light icon.

Use this template whenever you need a structured, data‑driven way to decide which car to buy—whether you’re a private buyer comparing family sedans, a fleet manager selecting vehicles for a company, or a dealership advisor helping clients. By turning subjective pros and cons into numeric scores, the workbook removes bias, speeds up the discussion, and provides a transparent rationale that can be shared with stakeholders.

The template helps you track each model’s performance across all chosen dimensions, instantly see which cars excel or lag, and produce a single, objective recommendation based on the calculated averages. It also keeps a historical record of past evaluations, so you can revisit decisions or adjust criteria as market conditions change.

How to use

1. Open the Cars sheet and list every vehicle you are considering in column A.
2. In the next five columns, enter a score from 0 (very poor) to 10 (excellent) for each criterion defined in the Criteria sheet.
3. (Optional) Adjust the weight values in the Criteria sheet if some factors matter more; the Summary sheet will recalculate weighted averages automatically.
4. Switch to the Summary sheet to see each car’s overall rating, ranking, and the highlighted top recommendation.

Expected benefits: you’ll cut down the time spent debating subjective opinions, gain a clear visual ranking, and make a more confident, data‑backed purchase decision.