DC Velocity - April 2014

10 years. Twenty-six percent had used a TMS between five and nine years, and 31 percent had used this type of software for one to four years. Only 5 percent had used a TMS for less than a year.

When asked what they used their TMS for, 84 percent of respondents said it was to schedule domestic shipments, which is precisely what the software was originally designed to do. Another 79 percent said they used it for tendering loads to carriers, while 57 percent used it for freight bill audit/payment and 46 percent for tracking carrier performance. Only 31 percent used their TMS to schedule international shipments. Although some industry pundits predicted that shippers would use their transportation management systems to help carriers comply with the new truck driver hours-of-service rule, only 33 percent indicated they planned to use the software for that purpose.

Despite talk of more companies using software solutions to improve workforce efficiency, the survey found that only 39 percent of respondents are using labor management systems—either on a standalone basis or as part of their WMS. The results also showed that just 12 percent of respondents had deployed a yard management system, which is used to coordinate the movement of trailers and trucks at a DC site.

GROWING INTEREST IN BIG DATA

In the past year, there’s been considerable talk about the use of big data analysis to fine-tune supply chain operations. As the name implies, big data analysis involves sifting through millions of bits and bytes of information for new insights into a company’s business practices. Typically, the information comes from diverse sources—anything from telematics and sensors on carriers’ equipment to radio-fre-quency identification (RFID) tags affixed to cases or items to social media chatter. The idea is that by analyzing these disparate sets of data, the software might detect hidden connections or patterns that could ultimately be parlayed into supply chain operational improvements.

Despite all the hype, only 43 percent of survey respondents said they were engaging in big data analysis right now. When asked about their reasons for doing so, respondents indicated it was to obtain recommendations for solving operational problems, to better understand their supply chain, and to examine hypothetical situations. (See Exhibit 2.)

The flip side, of course, is that 57 percent of respondents are not engaging in big data analysis at this time. When asked why, 40 percent said they perceived no value from it. Another 19 percent said they didn’t have the time for additional work, and 14 percent said they lacked IT support, generally seen as critical for this undertaking. Another 7 percent said this type of analysis was too expensive. (See Exhibit 3.)

Yet despite the relatively slow uptake, many experts still believe that supply chain and logistics operations are good candidates for big data analysis. Based on reader responses, it appears software vendors may have to develop more low-cost, intuition-based products and then demonstrate their value before logistics managers will be persuaded to take the plunge.