More than
Consider the longer term. “Think about how you want the solution to look years down the road before you get into the nitty-gritty of the architecture,” says Kristin Toth, president and chief operating ocer with Fernish, a premium furniture rental company. Account for growth and dierent users as you plan, she adds. Meld technical skills and operational expertise. “The marriage of great operations and software can be powerful,” says Jerey Smith of the Deep Space Logistics Gateway Program. Operations experts can remain focused on what the system needs to do, and the engineers can focus on getting there. Confirm data quality. For technologies like AI to work eectively, data structure and quality matter. “If you’ve been managing dispatch planning on the back of an envelope, you likely have work to do before implementing technology,” says Balaji Guntur, COO of Hoptek. Know how much data you have. AI works best when it’s working with massive volumes of data, says Dean Runic, senior vice president, Europe and International, with SymphonyAI Retail. Allow time for the technology to learn. Just like a new employee, solutions like machine learning require time to get up to speed, Rnic says. Act on the information. If you’re accessing data, but not fundamentally changing processes to make real time decisions based on the information you’ve assembled, you won’t get the full benefit of these technologies, says Atul Vashistha, chair and chief executive ocer with Supply Wisdom, which oers risk intelligence. Decide when to involve humans. At what threshold do you want employees involved in the decision-making? Issues involving low-value items or low risk are probably a better candidate for automated action than higher value products or higher risk scenarios. Prepare workers. It took time for operators at Werner Electric to see that ACB, while creating what seemed like weird picking paths, actually was shortening their trips. To help employees get accustomed to the technology, Werner started gradually. Workers used the solution several times each week and then compared the results to manual clustering. Eventually, employees saw how the technology was helping. Focus on the vision. Astrategic vision should guide your investments in technology. Otherwise, you risk ending up with “random acts of digital,” says Aaron Parrott, managing director, Deloitte.
of respondents to a Gartner supply chain survey said technology is a source of competitive advantage.
Before the pandemic, even many large and sophisticated supply chain operations limped along with minimal investment, Hartley of LevaData says. The result often was a hodgepodge of of ine processes and a lack of transparency that left companies unable to make optimal, fact-based decisions, he adds. That’s changed, and companies’ focus on supply chain technology appears likely to continue. What’s more, many are backing this up with investments. For example, by 2026, 75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operations, Gartner reports. And while many applications likely will focus on straightforward operational visibility and ef ciency solutions, a few are heading in different directions. Swaroop says Cepham is dedicating resources to learn about machine learning tools that can decipher ancient Ayurvedic texts. (Ayurveda is a system of holistic medicine with roots in India.) This will help his team better understand plants and their potential uses in self-care.
100 Inbound Logistics • January 2023
Powered by FlippingBook