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AI Use Case Prioritization Worksheet for ERP

Most ERP AI programmes stall because the first use case was picked by enthusiasm instead of evidence. This worksheet forces every idea through the same four questions and gives you a ranked list you can defend to the steering committee.

Download:

Use case	ERP area	Business value (1-5)	Feasibility (1-5)	Data readiness (1-5)	Risk (1-5)	Priority score (0-100)	Business owner
						82
						72
						70
						67
						75
						71

Average priority score

72.8333

Highest score

Use cases listed

Score = (value x 0.4 + feasibility x 0.25 + data readiness x 0.25 + inverted risk x 0.1) x 20. Change the weights by editing your Excel copy after export. Start with the top three that score above 70 and carry risk of 2 or lower.

Get a second opinion on your shortlist

Send us your top three use cases and we will tell you which ERP tables or documents each one needs and what a read-only pilot would involve.

Optional. The tool and every export work without this. No spam.

How to use the worksheet

List every candidate use case, including the ones vendors have pitched you. Have the business owner score value, and have IT score feasibility and data readiness. Score risk by asking what happens if the answer is wrong and nobody notices for a week. The priority score is calculated per row, so you can sort the exported Excel file and read the order directly. Replace the sample rows with your own before you share it.

Score value in money or hours, not feelings
Score data readiness by looking at the actual tables or documents
Use risk 4 or 5 for anything that writes to the ledger or touches safety records
Rescore after a pilot, because feasibility is usually overestimated

The scoring method

Value carries 40 percent because a cheap, easy use case that saves nothing is still a waste. Feasibility and data readiness carry 25 percent each, since most ERP AI failures come from messy master data or hard integration, not from the model. Risk is inverted and carries 10 percent: it acts as a tie breaker, not a veto. If a row has risk 5, treat it as a human-approval project regardless of its score.

Reading the ranking

Scores above 70 are good first pilots, usually read-only questions and drafting tasks. Scores between 50 and 70 need a data cleanup or integration step first. Below 50, park the idea. In the sample rows, the open PO question scores high because the data sits in structured ERP tables and a wrong answer is easy to spot. Auto-posting invoices scores low despite high value, because risk and feasibility pull it down.

Common mistakes

Teams often score every item 4 or 5 on value, which makes the ranking meaningless. Force a spread by capping the number of 5s. Another mistake is ignoring who owns the outcome: a use case without a named business owner will not survive the pilot. Finally, do not mix use cases of very different size in one list without splitting the large ones, such as a full procurement agent, into smaller steps.

Frequently Asked Questions

How many use cases should I score?

Between 10 and 25 is practical. Fewer than 10 usually means the brainstorm was too narrow. More than 25 means the list needs grouping by ERP area before scoring, otherwise the committee loses focus.

Can I change the weights?

Yes. Export to Excel and edit the formula. Regulated plants often raise the risk weight, while teams with a strict budget raise value. Keep the weights fixed once you start scoring so the comparison stays fair.

Should risky use cases be excluded?

No, but they need a different path. High risk items such as posting transactions should use human approval, an audit trail and a longer pilot, so they rarely make good first projects.

Who should fill this in?

A small group: one business owner per ERP area for value, one IT lead for feasibility and data readiness, and someone from quality or compliance for risk. Scoring alone tends to skew the result.

If you want the top-ranked use cases tested against your live ERP data, we can run a read-only proof of concept on your own hardware or private cloud.

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