Last month, McKinsey published an article titled “Advanced analytics can drive the next wave of growth for transportation and logistics companies” arguing that while T&L companies are laggards in implementing the best practices in customer-facing analytics, they largely have the data they need and are well-positioned to capture the low-hanging fruit.
The distributed sales forces common to trucking carriers and 3PLs have a hard time systematically improving their processes. In trucking specifically, a lack of communication and data-sharing between sales and operations can result in salespeople chasing unprofitable volumes and neglecting accounts with superior margins. The industry has already made substantial improvements in sales productivity: after speaking with leading freight brokerages, we estimate that the average number of loads covered per day by an individual freight broker has grown 3-5x in the past decade. In general, though, McKinsey found that transportation and logistics’ commercial analytics are behind typical B2B companies.
“Catching up shouldn’t be daunting,” McKinsey writes, “T&L companies already have much of the data they need and can turn to analytics programs that are proven to work. Based on our experience, companies in the sector that embrace analytics can generate an additional 3 to 5 percent return on sales.”
McKinsey’s article centered around three key recommendations: wrangle the data you already have; invest in explaining the data and keeping it simple for the sales team; and embed analytics in daily routines. Before investing time and resources in building a new data set, it’s worth it for companies to examine what they already have and make sure that the data lands in the right hands—often valuable metrics are siloed in departments and databases where they can do no good.
“Accessing operational data from within your own company is surprisingly hard. The commercial team needs to find way to learn about what operational data exists and how it is being used by talking to operational leaders about what data they use, asking data analysts who work on operational topics, or taking a step back and looking at the companywide master data,” McKinsey wrote.
Data-driven transportation and logistics companies enjoy investors’ favor and richer valuations compared to their tech-lagging peers. Stifel (NYSE: SF) equities analyst Bruce Chan specifically cited Echo Global Logistics’ (NASDAQ: ECHO) automated customer-facing platforms as a driver of EBIT per employee and sales agent growth.
“We believe Echo has plenty of runway to drive operating income faster than net revenue via continued process improvement and the deployment of automated technology tools, including customer-facing platforms across the portfolio, as well as internal back office systems, to focus carrier and shipper reps on higher-service value-added functions,” Chan wrote in an October 25 research note.
In September, transportation equities analysts at Goldman Sachs (NYSE: GS) released a research report about the technology-driven commoditization of brokerage and logistics services.
“We expect automation will reduce processing time which will allow agents to spend more time focused on sales. Landstar (NASDAQ: LSTR) testimonials suggest up to 30% time saved on processing a load with new software which would allow for an additional 20% in revenue without the need for more headcount,” wrote Goldman’s Matt Reustle.
Just a few days ago, on October 31, Susquehanna’s Bascome Majors bumped C.H. Robinson’s (NASDAQ: CHRW) price target to $114 from $113 partially based on management’s optimistic guidance on employee productivity metrics. Operating income per employee in CHRW’s core North American Surface Transportation (NAST) business grew 34.7% year-over-year in the third quarter of 2018, and executives said that the company will continue driving it higher.
There’s an emerging consensus that capital expenditure on technology is critical to unlocking meaningful per-broker productivity improvements, whether this comes in the form of using analytics products to translate operational data into actionable recommendations to salespeople, or simply automating repetitive tasks to allow individual employees to process more volume. What’s clear is that transport and logistics companies perceived as technology laggards will be discounted against their peers.
The evolution of American freight markets—including a trend toward a growing percentage of brokered loads, faster transit times, more visibility, greater price transparency, and more collaborative customer service—has created a Red Queen dynamic. In Lewis Carroll’s Through the Looking Glass (1871), the Red Queen tells Alice “it takes all the running you can do, to keep in the same place.” Transportation and logistics companies are in a similar place: they find themselves in an industry environment where continuous innovation is necessary to simply to keep up with, much less outperform, their competitors.
McKinsey concluded its article by encouraging transportation and logistics companies to jump data analytics—to start small, fast, and simple in order to establish data-driven habits, and build from there.
“Even basic analytics can deliver value, so companies should not hesitate because they believe they need perfect data. After all, insights are useless if they take too long to develop.”