Key takeaways from the results

Too many companies still rely on manual processes

There are still too many companies (44% amongst our survey respondents) that rely on manual or mostly manual freight procurement processes, especially for getting internal stakeholder alignment and approvals, as well as with bid setup and RFP creation. As one supply chain executive commented, “Our processes are still manual; it’s hard to keep up with it.” Another said, “Our procurement process is mainly manual. It is very difficult for us to distinguish between carriers and brokers.” This is surprising given that a September 2022 Indago survey revealed that 79% of member executives agreed they could no longer rely on spreadsheets to manage their transportation processes and needed to invest in new technologies, with 41% strongly agreeing. These results suggest that moving away from spreadsheets and manual processes has been slower than anticipated, at least when it comes to freight procurement.

Do you agree or disagree with the following lesson from the past two years related to transportation management?

We can't rely on spreadsheets anymore.

Do you agree or disagree with the following lesson from the past two years related to transportation management?

We can't rely on spreadsheets anymore.

Data-driven decision-making is limited

Although half of respondents said that “data is a major factor in their procurement strategy,” only 6% said their freight procurement decisions are “highly data-driven with real-time inputs.” The other 45% said they make decisions based “mostly on experience and instinct,” or they use “some reports, but they are limited or static,” or they reference data regularly “but it’s not central to decisions.”

"Meaningful market data [to inform the procurement process] is very tough to find and integrate.” - Supply chain executive from 2025 survey

Challenge #1

Finding meaningful market data

Such as real-time data on rates, capacity and service performance metrics that is accurate and relevant to their transportation operations.

Challenge #2

Integrating market data with TMS

In order to facilitate and streamline the decision-making process, and to ultimately automate the procurement process.

Challenge #1

Finding meaningful market data

Such as real-time data on rates, capacity and service performance metrics that is accurate and relevant to their transportation operations.

Challenge #2

Integrating market data with TMS

In order to facilitate and streamline the decision-making process, and to ultimately automate the procurement process.

These comments suggest there are two challenges involved with becoming more data-driven. The first challenge is finding “meaningful” market data, such as real-time data on rates, capacity and service performance metrics that is accurate and relevant to their transportation operations (across modes, lanes, equipment types, etc.). Obtaining predictive data and insights on capacity needs, such as “lane-level volume forecasts,” is also a struggle This latter point aligns with previous research findings. In a November 2024 Indago survey on transportation forecasting, less than half the executives surveyed (41%) said they generate transportation forecasts (based on demand forecasts, promotions, point-of-sale data and other demand signals) and share them with their carriers. And almost two-thirds of them (64%) use “Excel spreadsheets” to generate these forecasts.

Do you currently use demand forecasts and other data to generate and share short-term, lane-level forecasts of capacity requirements with your truckload carriers?

The second challenge is integrating the market data with transportation management systems (TMS) or other tools to facilitate and streamline the decision-making process, and to ultimately automate the procurement process. Or, in other words, obtaining the data required is not enough; you also need a way to leverage it efficiently and intelligently at scale.

Do you currently use demand forecasts and other data to generate and share short-term, lane-level forecasts of capacity requirements with your truckload carriers?

There’s high demand for predictive capabilities, but confidence in forecasting is low

want predictive insights on rate and capacity trends

feel confident in their forecasting ability

want predictive insights on rate and capacity trends

feel confident in their forecasting ability

More than half the respondents (53%) want predictive insights on rate and capacity trends, but only 21% feel confident in their forecasting ability and no respondents feel very confident. “Having real-time insights that incorporate historical lane analysis and predictive future demand for lanes,” is how one executive characterized an ideal future procurement process. Another executive commented, “With access to more information via benchmarking, we can focus on the lanes that move the needle.” The low confidence in forecasting ability is likely driven by several factors, including not having access to real-time market data, a lack of forecasting tools, and a lack of data science or forecasting expertise inhouse to build and interpret predictive models. These factors are probably more acute for small companies, as this executive comment suggests: “We are a small company, so I make most decisions on my own.”

"With access to more information via benchmarking, we can focus on the lanes that move the needle." - Supply chain executive from 2025 survey

CONNECT WITH US