According to the 2020 Third-Party Logistics Study, data analytics is not only becoming more viable in the logistics industry, but it’s also becoming a necessity and make a difference. With the growing storm that is e-commerce, brick and mortar retailers have had to step twice as fast in order to stay in the game. Especially, when you consider some of the power plays made by the internet titan, Amazon. As one of Amazon’s biggest sources of competition for domestic goods Walmart, in particular, has tightened their game up significantly.
In particular, Walmart uses some stringent policies to ensure that shelves stay stocked and goods are arriving exactly when the retail stores need them to. First is the Must Arrive By Date (MABD) provision, which means that suppliers must have deliveries to the store within a certain delivery window, typically four days, while also having a high invoice accuracy. This is a fairly standard industry practice for retail stores to ensure timely deliveries.
Failure to meet these requirements could mean a 3 percent chargeback per case value of each missing item.
However, Walmart as since followed that up with their heavy-handed On Time In Full (OTIF) policy. Now suppliers must have deliveries at the store within a two-day window, no later and no earlier either (even early deliveries will still be penalized.) Failure to meet these requirements could mean a 3 percent chargeback per case value of each missing item.
As of April 1st of 2018, the company made the policy even harder. Prior to then, the OTIF policy stated that full truckload shipments needed to meet a 75 percent OTIF rating and less-than-truckload shipments needed to meet 33 percent OTIF to avoid fines. Now, FTLs are required to meet an 85 percent standard (down from the lofty 95 percent they had originally planned) while LTL requirements have increased to 36 percent. In addition to the chargebacks, too many violations could cause a shipper to fall out of favor with Walmart and lose supplier status, which would be a major financial hit for most companies.
But what happens if demand is peaked and capacity is booked?
For shippers, OTIF can make for a tight schedule. But what happens if demand is peaked and capacity is booked? What if there’s a major weather event that has the logistics network scrambled? Shippers need better tools at their disposal to keep things running smoothly, and that’s where data analytics comes into play.
How Analytics can Make a Difference
There is a truly astounding amount of data that can be captured within the supply chain. As more companies begin the process of digitizing their operations and automating their systems, just about everything can be tracked, traced, quantified, and speculated. The challenge, however, is making sense of it all. There is such a surplus of data that it leads to a sort of data overload and can turn even the most avid analyst catatonic.
Analytics turns this vast amount of information into insight, according to the 2020 Third-Party Logistics Study by Infosys Consulting, Penn State University and Penske Logistics presented at the CSCMP Edge conference in Anaheim, California. And with this insight, “you stand a much better chance of improving your operations,” says John Langley, professor of Supply Chain Management at Penn State University.
Real-time information can help to match supply with demand. But that’s not all it can do. Far from it, in fact.
To some degree, the logistics industry has already started to use real-time data and analytics. Langley sites dynamic pricing in freight for an example. Here, real-time information can help to match supply with demand. But that’s not all it can do. Far from it, in fact.
For shippers, there is a wide array of challenges they encounter on a daily basis. Of the shippers that responded to the 3PL study, many agreed that the use of analytics would be helpful to many facets of their operations as well as overcoming the challenges they face day to day.
|Type of problem||% of shippers who said analytics would be helpful|
|On-time and complete order fulfillment||69%|
|Freight costs per shipment||60%|
|Cost to serve||58%|
|Order-to-delivery cycle time||58%|
Langley says that analytics is ideal for tracking and improving a KPI like Walmart’s OTIF, because the policy itself is a compound metric. And while it might be easy to villainize Walmart from a shipper’s perspective, they aren’t the only company to use aggressive tactics like this. Target, Kroger, Costco, and others are also tightening their regulations in order to keep their shelves stocked.
Learning From Your Mistakes
Perhaps one of the most powerful tools of data analytics is it gives you a different perspective of your operations and allows you to drill down to pivotal details. Why was your shipment late? Why were there missing pieces? Analytics can determine the cause and effect relationships to target the root cause of the issue while sorting out coincidence and other anomalies. In other words, real-time data analysis allows you to track where things went awry and focus on improving operations so that particular issue doesn’t happen again. “If you can measure it, capture it, analyze it, you can use it to your advantage in terms of knowing more about your own processes,” Langley says.
Getting to be a supplier for Walmart is no small matter.
Getting to be a supplier for Walmart is no small matter. For companies that already have that title, keeping it is important. However, even shippers that don’t have the best scorecards, analytics can prove to be a useful bargaining chip. If you’re able to prove yourself, and that you have the right measures in place to improve operations, it’s likely that you can demonstrate your worth as a supplier and make it to the “in” list.
For a better understanding of how to navigate OTIF and other ways to improve your operational efficiency, check out our white paper: Walmart: the retail-supplier relationship. You can also speak with one of our experts by calling us at 800.MY.SHIPPING, or filling out the form below.