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Blog · Alternatives and comparisons · Consulting and advisory

How to choose analytics software for consulting and advisory: questions, data and traps

How consulting firms 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 consulting firms 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 consulting firms 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
Who is busy, and who is actually earning? Utilisation against realisation
Which projects are overrunning their plan? Project margin against plan
Is there enough sold work for the bench? Sold work against the bench
Which proposals are we winning and losing? Proposal win rate
Which clients use one practice where they could use three? Cross-practice share per client
How many weeks of backlog do we hold? Backlog in weeks

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

The data you already hold

  • Timesheets
  • Billing
  • Proposal log
  • Signed work
  • Resource plan
  • Project ledger

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 consulting and advisory

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

  • Time: Available hours = chargeable + non-chargeable + leave
  • Realisation: Chargeable hours at standard = billed + written off + work in progress
  • Proposals: Proposals = won + lost + withdrawn + open
  • Backlog: Opening backlog + signed − delivered = closing backlog

The traps

Utilisation beside realisation. Utilisation is reported weekly and rewarded. Realisation per person rarely is.

Win rate by source. One blended win rate hides that open tenders win at a tenth and cost the most to prepare.

Sold work against the bench. Sales and resourcing meet when the project is due to start.

Measures to leave out

Utilisation alone. It rewards overrun.

Proposals submitted. Cost, until the win rate by source is known.

Pipeline value unweighted and undated. See coverage against the measured win rate instead.

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 consulting and advisory compared, AI analytics for consulting and advisory and Covirage for Consulting and advisory.

For the measures in full, with formulas and exports, read Commercial KPIs for consulting and professional services firms.

Questions people ask

What should consulting firms 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 consulting firms?

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 consulting firms already hold?

Usually: timesheets, billing, proposal log, signed work, resource plan, project ledger. Most analytics questions in this industry can be answered from those exports.

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