Analytics software, compared
Most procurement teams choose between spreadsheets, a BI suite, a planning platform and an enterprise data platform. Each is right for something. This page sets them against the questions procurement teams actually ask, and shows what each needs before the first answer.
Excel or Google Sheets, with exports pasted in and formulas rebuilt each period. Suits a one-off question that will not come back.
Business intelligence tools for modelling data, building dashboards and sharing reports. Suits an organisation standardising reporting across many teams.
Platforms for budgeting, forecasting and scenario planning, connected to the ledger and other systems. Suits a finance team replacing spreadsheet budgeting across the organisation.
Platforms that integrate an organisation's systems into one governed model and build applications and AI on top of it. Suits a programme to connect many systems across the whole organisation.
Reads the exports procurement teams already produce and answers the questions below, with every figure computed by our tools and checked. Set up for you within a week.
| Time to the first answer | What it needs | Who builds it | Where “why” comes from | |
|---|---|---|---|---|
| Spreadsheets | Hours, and the same hours again every month | An analyst's time each period | An analyst, by hand, every period | Whatever the analyst builds that month, checked by whoever has time |
| BI suites | Usually days to weeks: a data model built, measures written in the tool's own language, reports designed | A clean data source or warehouse, a data model, and someone who can write the tool's measures | A BI developer or analyst, often in a central data team | A dashboard shows what changed; explaining why is usually a new report someone builds |
| FP&A and planning platforms | Usually months: models built, the ledger and other systems integrated, often with an implementation partner | Model builders, integration with the ERP or general ledger, and an implementation project | Certified model builders, internal or from a partner | Built to produce the plan; explaining the month's variance often goes back to a spreadsheet |
| Enterprise data platforms | Usually weeks to months: sources integrated, a data model or ontology built, then applications on top | Integration work across source systems, a data model, and engineers who build and maintain it | Data engineers, often with the vendor's own engineers or a partner | Possible once the model is built, as an application someone designs for it |
| Covirage | Minutes on a file you already export; set up for you within a week | The exports your systems already produce. No warehouse, no modelling language, no data team | We map the columns once and set the dashboard up for you | An explain block splits every change into its causes; the lines sum to the change, and each opens to its rows |
These are typical patterns, not a verdict on any product. Each kind of tool is right for somebody; the table shows who does the work before procurement teams get an answer.
| The question | The measure | What Covirage returns |
|---|---|---|
| How much of the claimed saving actually landed? | Savings realised against claimed | Invoiced volume at the new price against the forecast, with the volume at old prices and off contract, by site. |
| Who is buying off contract, and what? | Maverick spend by requester | Spend outside contracted suppliers by requester, site and category, with the items. |
| How much of each category is under contract? | Contracted share by category | Spend with contracted suppliers over category spend, with the tail of suppliers behind the rest. |
| Are we paying to the agreed terms? | Payment terms compliance | Invoices paid inside terms over invoices, by supplier, and the early payments' cost. |
| Which suppliers are deteriorating? | Supplier performance against own baseline | Delivery, quality and price against each supplier's own history, with the ones sliding. |
| Which contracts expire with no plan? | Contract expiry coverage | Contracts expiring in the window against those with a renewal or tender under way, by category. |
Every one is an export your systems already produce. Every way data can arrive is listed on the upload page.
Savings realised. Savings are reported at contract signature and seldom revisited against invoices.
Invoices paid early. Terms are negotiated by procurement and ignored by the payment run.
Maverick spend by requester. Reported as a percentage, which prompts a policy. As a list of names it prompts ten conversations.
Each page sets out what the product is built for, where it is strong, and when a lighter option fits better.
Alteryx alternatives · Domo alternatives · Palantir Foundry alternatives
Databricks AI/BI alternatives · Looker alternatives · Metabase alternatives · Power BI alternatives · Qlik Sense alternatives · Sigma alternatives · Sisense alternatives · Tableau alternatives · Zoho Analytics alternatives
Adaptive Planning alternatives · Anaplan alternatives · Pigment alternatives · Planful alternatives · Vena alternatives
It depends on what is in place. With a warehouse and a data team, a BI suite or a data platform gives the most control. With exports and a question that recurs every month, a tool that reads the files and answers the question directly gets there sooner. The table on this page sets the options side by side for the questions procurement teams ask.
Not to start. The measures on this page are computed from exports procurement teams already produce: payables ledger, contract file, purchase orders, invoice lines. A warehouse helps when many systems must be joined continuously; it is not a prerequisite for the first answer.
It varies by approach: usually days to weeks: a data model built, measures written in the tool's own language, reports designed for a BI suite, usually months: models built, the ledger and other systems integrated, often with an implementation partner for a planning platform, and minutes on a file with Covirage, set up for you within a week.
In Covirage the AI model never does the arithmetic. It chooses the measure and explains the result; our tools compute every figure and check that the totals reconcile before anything is shown.
Asset managers · Commercial banking · Compliance · Construction and building materials · Consulting and advisory · Customer service · Distributors · Education · Finance and FP&A teams · Financial services · FMCG and CPG brands · Foodservice distributors · Freight brokers and 3PLs · Healthcare and med-tech · Hospitality · Industrial distributors · Industrial manufacturers · Insurance brokers · Investment banking · Law firms · Oil and gas services · Pharma · Retail banking · SaaS · Sales teams · Shipping and logistics · Sports · Supply chain · Tax and accounting · Telecoms and connectivity · Trading · Wealth managers
Bring an export you already produce. The data map opens next, every column mapped once, and the first question is answered in minutes. Free, in your browser, no account. Or talk to us and we will set it up for you.