Make a list of all the choices your team makes. Next to each one, write how often it happens and how bad it would be to get it wrong.
The decision inventory is a simple table. One row per decision, with columns for how often it happens, how long it takes, what's at stake and whether it can be undone. Sort it and the best places to start become obvious.
Maintain a decision inventory per role or process: decision, options, owner, volume, handling time, stakes, reversibility, data available and current error rate. Rank candidates for decision support by volume multiplied by handling time, filtered by stakes and reversibility.
The columns
| Column | Example |
|---|---|
| Decision | Approve or query an expense claim |
| Options | Approve, query, reject |
| Owner | Line manager |
| How often | 400 a month |
| Time per decision | 3 minutes |
| Stakes | Low (most claims under £100) |
| Reversible? | Yes, within the pay cycle |
| Data available | Claim, receipt, policy, history |
| Known error rate | Unknown, so sample 50 to find out |
Filling it in
Start from the task list you built from O*NET or ESCO. For each task, ask where someone chooses between options. Then check the numbers against system data: approval logs, ticket histories and audit trails usually hold more than people expect.
Leave cells blank rather than guessing. A blank tells you what to find out.
Reading it
Multiply frequency by time per decision to get the hours spent each month. Sort by that. Then look at stakes and reversibility. High-volume, low-stakes, reversible decisions are the natural first candidates for a decision model. High-stakes, irreversible decisions are where people should stay in charge, with better information rather than automation.
Keep it alive
Review the inventory quarterly. Volumes change, policies change, and a decision that wasn't worth touching last year may be now.