Freight tech has become one of the hottest venture capital marketplaces in the business world, with investment dollars in startups growing 24x from 2014 to 2018, when nearly $3 billion poured into the space. Much of this investment was dedicated to the transportation side of the logistics industry: freight matching, optimizing asset utilization, new transportation management system platforms, track-and-trace technology, and cloud-based analytics products.
Yet something is missing: the warehouse and distribution center side. In our view, far less attention has been paid to the need to gain visibility into facility operations, collect and analyze data, and re-imagine facilities, processes, and people with artificially-intelligent assistants. Warehouses and distribution centers have been relatively neglected despite extraordinarily high costs.
A February 2019 study by Coresight Research and Celect, which analyzed survey responses from 200 senior decision-makers at U.S. retailers, found that companies relying upon manual data entry and communication processes overbought, bought the wrong SKU, or underbought inventory at rates exceeding their tech-enabled competitors. The result is a massive destruction of capital every year.
“We estimate that markdowns cost US non-grocery retailers approximately $300 billion in revenues in 2018, equivalent to around 12% of all US non-grocery retail sales,” wrote Deborah Weinswig, CEO and founder of Coresight Research.
Just 60 percent of non-grocery retail sales are made at full price, the study found, in large part because product is not efficiently delivered to the point of sale when it is demanded. Apparel sales are especially vulnerable to time delays and erroneous orders of the wrong product.
“Misjudgments regarding inventory account for a total of 53% of unplanned markdown costs for retailers, according to our survey results,” Weinswig wrote. Other contributors to markdown costs cited by the survey respondents included external factors like unseasonal weather, sudden changes in consumer behavior, and competitors’ unplanned promotional activities.
The chart below shows the disadvantage faced by retailers relying on basic data entry and manual input tools:
“It is critical that retailers are empowered to make decisive, intelligent orders from their suppliers,” said Chris Kirchner, Co-Founder and CEO of Slync. “The lack of visibility and prediction in inventory management is destroying capital and compressing revenues across retail verticals.”
Slync’s supply chain platform pulls data from wholesale suppliers, retail distribution networks, transportation companies, e-commerce portals, and brick-and-mortar stores, cleans it, and aggregates it on the cloud. From there, machine learning algorithms and artificially intelligent helpers aid human decision-makers in predicting which SKUs will be in demand, the best way for the retailer to source them, and how quickly and inexpensively they can be brought to the consumer.
Adding to the complications that retailers face in their distribution center networks are the sea-changes wrought by e-commerce. New warehouses are smaller and are being built closer to population centers; not only that, but the throughput they need to achieve an acceptable return on capital is high, compared to traditional warehouse facilities.
Warehouse employment has exploded in the last decade—really in the last five years—despite very low unemployment in the broader economy, putting pressure on supply chain participants to increase productivity (which means increasing throughput faster than headcount). Leading companies in supply chain technology are paving the way forward, but progress is unevenly distributed—there’s a long tail of retail shippers who have not benefited from the latest technology and who are at risk of falling behind.
At Stifel’s Transportation and Logistics Conference in Miami Beach earlier this month, Freightos VP Ori Franco related an interesting anecdote about Amazon.
“Amazon’s CFO measures warehouse capacity in cubic feet, not square feet,” Franco said. Clearly, the e-commerce retailer exploits available space more intensively than its competitors. Amazon is literally playing 3D chess when it comes to warehouse operations.
Last summer, Körber Logistics Systems acquired Centriq, consolidating voice-recognition and three-dimensional warehouse modeling technology companies. RightHand, a robotic picker startup, raised a $23 million B round in December. Amazon itself has already deployed more than 100,000 robotic drive-units, which grab containers and reposition them for picking and stowage.
There is obvious interest in robotically powered warehouse operations, but the majority of retailers are not ready for that. Capital-intensive robotics systems need a high return on investment to justify themselves, but a company can only tell its robots what to do if it has the data. That’s where integration layers like Slync’s platform come in.
“Slync is designed to accelerate time-to-decision for any company involved in the supply chain, and we believe leveraging our platform in warehouse and DC operations will generate immediate returns for our customers,” Kirchner said.
