Coupa has launched a Business Spend Index developed with the MIT Data Science Lab. Drawing on business transaction data, the index forecasts spending trends up to 90 days ahead.
The inaugural report uses Coupa's broader dataset of USD $10 trillion in business spend and a model built from an anonymised subset of USD $877.9 billion in 2025 procurement spending. It covers 1,487 Coupa customers across High Technology, Manufacturing, Financial Services, Business Services, and Healthcare & Life Sciences.
The index is intended as an economic indicator based on actual procurement transactions rather than survey responses. Coupa said this enabled it to detect a manufacturing turning point three months before it appeared in the ISM PMI.
Findings from the first edition point to a broad slowdown in April. All five sectors tracked by the index recorded month-on-month declines in spend, from 0.8% in Manufacturing to 3.3% in Business Services, even as ISM PMI manufacturing and services surveys signalled expansion that month.
The report also forecasts further weakness in several industries over the summer. It predicts procurement spending will contract in High Technology, Financial Services, and Healthcare & Life Sciences, with Financial Services expected to see the steepest drop of the three.
Sector signals
High Technology was one of the report's more notable areas. Procurement spend in the sector has risen by more than 40% since mid-2024, reaching what Coupa described as a four-year cycle high.
The data tracks enterprise software and services procurement. Coupa said the trend suggests enterprise demand is beginning to catch up with heavy investment in AI infrastructure.
The Manufacturing data also points to the effects of trade disruption and subsequent policy stabilisation. Smaller US manufacturers cut spending by 17.5% during tariff volatility in 2025, compared with 14.6% among larger manufacturers.
The report said a Supreme Court tariff ruling later provided greater policy stability and helped businesses move away from short-term defensive spending decisions. That shift supported a return to longer-term investment in automation and AI-enabled execution systems.
It also identified a rise in internal Manufacturing spending despite muted customer demand. Coupa said late-2025 Manufacturing spend increased even though new orders remained soft, linking the increase to tax incentives that encouraged companies to invest in automation and supply chain resilience.
Method and aims
The index applies data science, seasonal adjustment, and machine learning to procurement data from Coupa's network of more than 10 million buyers and suppliers. Its stated aim is to provide a near real-time view of business spending and a short-term forecast without relying on the revisions typical of some conventional economic series.
This sets it against widely watched indicators such as gross domestic product and business surveys, which may be revised after publication or reflect sentiment rather than committed expenditure. The report argues that procurement transactions offer a more direct reading of how companies are responding to changing trade conditions, demand, and pricing pressures.
For finance and procurement executives, the launch comes as companies try to judge the impact of tariffs, geopolitical shifts, and AI investment on spending plans. The report presents procurement data as a way to monitor those pressures through observed purchasing behaviour across sectors.
"With visibility into trillions of dollars of actual business spend, you don't guess where the economy is going, you see it unfolding in real-time," said Kevin Iaquinto, Chief Marketing Officer, Coupa. "By leveraging Coupa's unmatched proprietary dataset and combining it with the best macroeconomic indicators and AI, MIT Data Science Lab and Coupa have collaborated to deliver a report that has tremendous business value for procurement, supply chain, and other business leaders who are debating and actioning future spend decisions."
According to the report, MIT Data Science Lab contributed the econometric modelling and statistical analysis behind the index. The academic partner said the transaction data showed leading relationships with several established macroeconomic indicators.
"Coupa has a very unique dataset that offers the basis for incredible economic insights. By applying rigorous econometric modeling and statistical analysis, we have mathematically observed that Coupa's data has strong leading signals relative to numerous established macroeconomic indicators, such as FRED, IDEA, ISM PMI, and Real GDP," said David Simchi-Levi, William Barton Rogers Professor and Head of the MIT Data Science Lab (Retired).