Blog · Alternatives and comparisons · Finance and FP&A teams
How finance teams should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.
Most buying decisions for analytics start from a feature list. For finance teams 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.
| The question | The measure behind it |
|---|---|
| What is driving my cost increase? | Cost bridge |
| Which cost centres are over budget, and on what? | Cost centres over threshold |
| How much of the variance is timing? | Timing in the variance |
| Where is headcount above plan? | Headcount against plan |
| Will the year land? | Run rate |
| Who forecasts high or low, every month? | Forecast accuracy and bias |
Any tool you consider should answer these from your data, not from a sample. Ask to see it.
If a vendor needs a warehouse built before it can read these, count that in the cost and the time.
Ask whether the tool enforces these, and what it does when they fail:
| 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 |
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 finance and FP&A teams compared, AI analytics for finance and FP&A teams and Covirage for Finance and FP&A teams.
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.
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.
Usually: ledger actuals, budget, forecast, headcount, timing and one-off files, timing items file. Most analytics questions in this industry can be answered from those exports.