Solving Supply Chain Challenges with Tech Tools

Until relatively recently, few people outside of the logistics world had uttered the words “supply chain.” But when the COVID-19 pandemic hit, some countries instituted nationwide lockdowns, leading much of the world to experience labor shortages that resulted in drop-offs in production. Suddenly, IT managers struggled to find vendors capable of filling routine orders for IT solutions such as servers, computers and networking gear. People across numerous industries discussed the supply chain regularly because these disruptions greatly affected their business.

The worst of the supply chain crisis has largely passed, but organizations now have an opportunity to strengthen their systems and insulate themselves from these issues in the future. Technology can help organizations achieve this objective. As IT and business leaders look to the future of their supply chains, they should consider using these four technology tools and strategies.

Years ago, conversations about the Internet of Things tended to focus on innovations, such as the smart refrigerator. Well, I’m still waiting for my fridge to automatically order milk when I’m running low, but IoT solutions are making a dramatic impact in the world of logistics.

The use of IoT solutions such as radio-frequency ID tags, computer vision and smart scales can help generate crucial, real-time information about supply chains. These solutions have already trickled down to consumers. Think about the way you’re able to see the exact location of your FedEx package as the delivery truck inches its way through your neighborhood. This would have sounded completely futuristic not that long ago.

Wherever possible, organizations should explore ways to use IoT to increase predictability and reliability in their own supply chains.

In logistics, data science is essentially the art of taking all the information generated by IoT solutions and other systems related to the supply chain and then doing something valuable with it. Data science leverages real-time data to generate forecasts against factors such as demand, production, capacity and the number of workers available.

None of these initiatives would be possible without skilled technology workers. As anyone who has tried to fill even a single IT position in recent years can tell you, it is more challenging than ever to recruit and retain top tech talent.

According to a recent supply chain report from EY, workforce retention and reskilling ranks among organizations’ most important outcomes over the next year, with 61 percent of respondents listing it as a top-three priority. Third-party providers such as CDW can help shore up talent gaps through staff augmentation, managed services, or training and coaching.

Organizations must be able to trust supply chain data. If a manufacturer plans to receive 100,000 units of a certain part, and a truck shows up with only 88,000 units, that could lead to a 12 percent drop in production. This, in turn, could lead to a missed quota in the present and a potential cascade of fulfillment-related problems in the future.

Supply chain data can be skewed for numerous reasons. Maybe the pallets that were loaded onto the truck weren’t recorded accurately, or maybe a logistics management initiative resulted in some trucks or pallets being rerouted. Organizations need to invest in data governance tools and processes that give managers confidence in the veracity of the information in front of them. Only then can they make decisions and adjustments that will keep their supply chains intact, even during the most challenging times.

Story by Christopher Marcolis