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Blog · Alternatives and comparisons · Healthcare and med-tech

How to choose analytics software for healthcare and med-tech: questions, data and traps

How healthcare suppliers should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

By CoviragePublished 24 September 20264 min read
The short answerStart from the questions healthcare suppliers ask every month, not from features. List the exports you already hold, ask every vendor what it needs before the first answer and whether its AI calculates figures, and check that every total reconciles. Then compare the first-year cost, all in.

Most buying decisions for analytics start from a feature list. For healthcare suppliers 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

The question The measure behind it
Which systems earn a lower tier than they are priced at? Tier earned against tier priced
Are we invoicing at the contracted price? Invoiced against contracted price
How compliant is each facility with its system's contract? Contract compliance per facility
Which facilities are not mapped to their system? Facility mapping completeness
Which agreements expire with no renewal under way? Agreement expiry coverage
Where has a category stopped at a facility? Standardisation opportunities

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

The data you already hold

  • Ledger
  • Contract file
  • Membership roster
  • Facility master
  • Contract price file
  • Tier thresholds
  • CRM
  • Market or customer data

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 healthcare and med-tech

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

  • Mapping: Ship-tos = mapped + unmapped; mapped revenue + unmapped revenue = ledger
  • Compliance: Eligible purchases = on contract + off contract
  • Price: Lines = at contract price + above + below
  • Agreements: Agreements = in force + expiring + expired still priced

The traps

Facility mapping. Treated as data cleaning, when it decides whether every other number is right.

Tier earned against tier priced. Tiers are set at signature and rarely checked against trailing volume.

Invoiced against contracted price. A line invoiced at list to a contracted facility inflates revenue and invites a credit and a complaint.

Measures to leave out

Revenue by ship-to. Roll up to facility and system.

Number of contracts held. Compliance and utilisation under each is what counts.

Calls per rep. Coverage at cadence, by facility value.

A scorecard

Criterion Weight Tool A Tool B Covirage
Answers our six questions on our own data High
Time to the first answer High
Needs a warehouse or data team Medium
AI calculates figures, or only explains computed ones High
Every total reconciles; figures open to rows High
First-year cost, all in Medium

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 healthcare and med-tech compared, AI analytics for healthcare and med-tech and Covirage for Healthcare and med-tech.

For the measures in full, with formulas and exports, read Sales KPIs for medical and healthcare suppliers.

Questions people ask

What should healthcare suppliers look for in analytics software?

The answer to their own questions, from the data they already hold, with every figure reconciled. Features matter less than what the tool needs before the first answer and who maintains it.

Is a BI suite enough for healthcare suppliers?

It can be, with a warehouse and someone to build and maintain the model. Without them, the dashboard shows what changed and the explanation is still an analyst's job.

What data do healthcare suppliers already hold?

Usually: ledger, contract file, membership roster, facility master, contract price file, tier thresholds. Most analytics questions in this industry can be answered from those exports.

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