How to choose analytics software for foodservice distributors: questions, data and traps

Most buying decisions for analytics start from a feature list. For foodservice distributors the better start is the questions that come back every month, the files already on hand, and the traps that make a tool look right in a demonstration and wrong in the first board meeting.

Start from the questions

Any tool you consider should answer these from your data, not from a sample. Ask to see it.

The data you already hold

• Ledger with category
• Account master
• Delivery file
• Order guide
• Order and shipment files
• Route costs

If a vendor needs a warehouse built before it can read these, count that in the cost and the time.

Ten questions to ask any vendor

1. What does it need in place before the first answer? A warehouse, a data model, a modelling language, a partner? Ask for the list and the typical weeks.
2. Who does the setup, and who maintains it? Your team, the vendor, or a partner, and what that costs after year one.
3. Does the AI calculate figures, or choose from computed ones? A language model that writes queries or code can produce a plausible wrong number. Ask what it is allowed to do.
4. Does every total reconcile to a control figure? Ask to see a bridge that does not sum and what the product does about it.
5. Can every figure be opened to its rows? An answer nobody can check becomes a debate in the meeting.
6. What does it cost in the first year, all in? Licences, consumption, implementation, modelling and training, not only the seat price.
7. How does data arrive, and who holds credentials? A file your systems already export, a scheduled drop, or a live connection with the vendor holding keys.
8. What happens to the data, and where is it stored? Residency, retention, deletion, and whether names can be replaced with identifiers.
9. Can we see it on our own data before we sign? A demonstration on a sample dataset tells you little about your own.
10. What does the tool do when it cannot answer? It should say so. A confident guess does more harm than no answer.

Checks specific to foodservice distributors

Ask whether the tool enforces these, and what it does when they fail:

• Category share: Category spend per kitchen sums to the kitchen's ledger total
• Drop frequency: Every delivery belongs to one kitchen and one day; drops sum to the route total
• Substitutions: Lines ordered = shipped as ordered + substituted + shorted + cancelled
• Chain and site: Site revenue sums to the chain total

The traps

The dropped delivery day. It is in the delivery file, not the sales report, and it leads the revenue decline by four to eight weeks.

Site-level share inside chains. A forty-site group at plan in total can hide six sites at a tenth of the median.

Contribution per drop. Gross margin per case is reported everywhere; what it cost to put the case in the kitchen is not.

Measures to leave out

Cases shipped. Volume without margin or cost. A route can ship more cases and earn less.

Number of active accounts. Counts a cafe and a hospital as one each.

Revenue per rep against last month. Holidays, weather and the calendar. Use the same weeks last year.

A scorecard

Where Covirage fits

Covirage reads the exports above, answers the questions with figures our tools compute and check, and is set up for you within a week. See analytics software for foodservice distributors compared, AI analytics for foodservice distributors and Covirage for Foodservice distributors.

For the measures in full, with formulas and exports, read Sales KPIs for foodservice distributors.