SUPPLY CHAIN DATA MISTAKES TO AVOID
data, says Bob Patel, managing partner, practice head, supply chain and retail planning with Highspring, a professional services organization. Often, it’s assumed that IT departments “own” any data. While IT may be stewards of the data, they usually don’t own it, Patel says. Instead, ownership often lies with the business units, such as the supply chain organization. Not only does the data impact how these areas operate, but
they’re best positioned to understand how the data will be used. NO DATA STRATEGY Not all data is good data, says Brian Cupp, vice president, operations, enablement, and strategic initiatives with IntelliTrans, a provider of multimodal transportation management solutions. Supply chain leaders need to identify and focus on the data relevant to their operation. A shipper moving freight
across North America doesn’t need every GPS ping from every truck. “That quickly becomes noise,” Cupp says. More helpful is a curated set of signals that lets the shipper anticipate risk and make better decisions, he explains. This could include exception- based location data, so the team is alerted when a load stops somewhere unexpected or dwells too long. Cost and service data at the lane level can help procurement see where they’re paying too much for poor service, so they can look for new providers. ALWAYS SEEKING PERFECTION While it’s important to minimize mistakes, the goal isn’t perfect data for the sake of perfect data. It’s informed decision-making, Wang says, adding that not every decision requires a high level of data accuracy. For instance, a company working against a tight timeline may need to begin searching for a new facility in parallel with the actual design work. By using rough estimates and making reasonable assumptions on critical factors, such as operational space and the level of automation, it can produce ballpark estimates on building footprints. These can guide its initial search, Wang says. POOR CONNECTION POINTS Supply chain data is an enterprise-wide issue, says Susana Gonzalo, managing director and lead of the commercial industry supply chain team with Huron Consulting Group. It can’t be solved by focusing on a single function, as many data issues occur at the connection points between internal functions and external partners. It’s also necessary to watch for gaps in external data, like supplier networks and transportation ows. “As supply chains become more dynamic, having real-time visibility beyond the four walls is essential for proactive decision-making,” she says.
SPOTLIGHT THE POWER OF PREDICTIVE PARTS DATA Few legacy information systems were built to support the speed and complexity of today’s supply chain environment, says Emanuela Delgado, group vice president of growth and innovation at Parts Town Unlimited, a provider of replacement parts for foodservice equipment, residential appliances, and HVAC systems. This makes it di cult to maintain synchronized inventory data, accurate parts identification, and up-to-date substitution information across business partners. As a distributor, Parts Town prioritizes accurate, real-time data for customers and partners, Delgado says. The company invested heavily in improving data accuracy and accessibility across its supply chain by working closely with OEM partners and enhancing its digital infrastructure. One result is PartPredictor. By analyzing data from millions of successful technician repairs, this platform allows service teams to accurately and quickly find the parts they need, minimizing down time. “Supply chains are becoming increasingly data-driven, and organizations that prioritize accurate, connected, and real-time information will be better positioned to respond quickly and operate more e ciently,” Delgado says.
Parts Town Unlimited prioritizes precise, real-time data and works closely with customers and OEM partners to ensure data accuracy and accessibility across its supply chain.
128 Inbound Logistics • July 2026
Powered by FlippingBook