In a world of constrained supply, manufacturers and suppliers are challenged to manage risk by balancing inventory availability and working capital commitments. Procurement and operations leaders need increased visibility into their data and to be able to trust that this data is correct in real time. Deploying new technologies designed to meet company goals is important to achieving those aims. Here are five factors to consider when embarking on the effort to optimize supply networks. 

 Keep it simple. In today’s volatile world, many companies are challenged to balance the risks and opportunities associated with keeping inventory and ensuring working capital availability. They are exploring the implementation of technologies that would help optimize supply networks. But implementing traditional supply chain technology projects is notoriously cumbersome, often taking two to four years to complete. 

New and more advanced technologies and methodologies allow implementation inside of six months’ time, and often a good deal less than that. These new intelligent technologies differ from their predecessors in a few ways. They eliminate time-consuming data preparation by applying artificial intelligence, enabling quicker implementations. With the help of machine learning, they’re able to understand data in divergent systems and formats without having to change the data. And they work with whatever technologies a company already has installed.

When technology implementations are simpler and easier, they’re more likely to succeed. Organizations can generate value from the technology by getting to the inventory and risk outcomes they are seeking. 

 Look for configurable, purpose-built and system-agnostic solutions. Many organizations have considerable investments in enterprise systems like enterprise resource planning (ERP), but they tend to rely on those systems for processes they weren’t built for. ERP systems can’t perform calculations that allow organizations to balance risk and inventory, and usually require extensive customization to work for any specific company. It doesn’t make sense to rely on an ERP system as the solution to perform these specialized tasks. It’s like using a hammer to do a job meant for a screwdriver.  

Purpose-built solutions, by contrast, require little customization, work across a wide variety of companies and verticals, and are compatible with technologies a company already has deployed. Implementing such systems increases the chances of success in achieving desired outcomes and promotes greater confidence in the achievement of those goals. 

 Seek sustainability. Optimizing supply networks fundamentally involves reducing excess inventory that companies accumulate as a safety net. Keeping excess inventory contributes to supply chain waste. When inventory becomes obsolete, it gets written off and dumped, clogging already overburdened landfills. Excess inventory requires companies to manage more warehousing space, which consumes and wastes resources on many levels. Systems that streamline materials processes advance environmental responsibility goals. 

Sustainability also refers to the continuous business processes promoted by intelligent systems. They use machine learning, neural networks and natural language processing to present trusted results and ongoing, sustainable processes — not a one-off fix. In a volatile environment, it’s not possible to optimize supply chains with a one-and-done approach.

New technologies also contribute to sustainability with their speed of implementation, which takes weeks to months, rather than years, to complete. Old-school supply chain projects, with their years-long timelines, often yield obsolete results by the time they’re completed. Intelligent systems, because they’re able to be deployed rapidly, are able to generate the trust required to be relied on in a rapidly changing environment, delivering continuous and reliable results. 

 Use AI and ML to augment, not replace, your team. Effective supply chain technology implementations don’t seek to replace human judgment. They seek to augment and to scale human effort with the use of artificial intelligence and machine learning. 

Historically, supply chain managers have spent 90% of their time analyzing demand and supply data and 10% executing on strategies. Intelligent systems flip that ratio on its head, allowing managers to spend 10% of their time reviewing recommendations and making decisions, and 90% acting upon them, to improve enterprise materials processes. Humans accept, partially accept, or reject recommendations proposed by the system, and those human decisions are looped back into system processes through machine learning to optimize supply chains. 

The deployment of artificial intelligence and machine learning to optimize supply networks clearly calls for the automation of processes, but not necessarily the elimination of jobs. It simply allows the human team to concentrate more on the execution of strategies that drive real change within supply chains. It also allows the technology to do what it does best: sifting through and analyzing millions of lines of data to get to the right outcomes. In today’s complex supply chain environment, that’s necessary to develop effective solutions and strategies. 

 Streamline operations and procurement initiatives. Operations and procurement organizations have historically pulled companies in opposite directions. Saving money is a feather in procurement’s cap. But operations want to maximize uptime, which often involves inflating inventory needs and spending more.

The solution is to align the goals of both organizations. Intelligent materials systems do that by analyzing the history of materials availability and lead times, and measuring how variability changed over time. The systems factor in a company’s desired service levels and calculate the cost to operations of various lead-time scenarios. Both organizations collaborate to establish minimum and maximum inventory levels, reorder points, and sourcing strategies that get service levels to where they want them. They also view sourcing and inventory situations dynamically, so that they can both manage risk in real time as conditions change. 

Excess inventory is often dealt with at the C-suite level by mandating across-the-board cuts. By using material intelligence systems, procurement and operations can agree on the inventory levels a company requires to satisfy operational needs while maximizing working capital availability.

Verusen: Managing Materials Across Networks

Verusen provides industry with a software-as-a-service (SaaS) materials intelligence platform. “Our North Star is a concept that we call material truth,” says Paul Noble, the company’s founder and chief executive officer.

Resource link: https://verusen.com/demo-reprise-trusted-network-overview-access/

Using Verusen’s solution, organizations get a single view of materials and inventories across their enterprise and networks. “We deliver the perfect balance of capital and risk,” says Noble, “and build trust that you'll have what you need when and where you need it.” 

Verusen’s technology provides data visibility while eliminating the need to clean, categorize and organize data. “Ours is a purpose-built solution that plugs into existing technology stacks,” Noble explains. “Organizations can build drop-in scenario models that allow them to get to a balance of inventory and risk and to work more effectively.”

Verusen analyzes data on an enterprise’s uses of material for three to five years, calculating the variability in lead times. “The purpose is assessing risk,” says Noble. “That way, companies can understand how quickly they can replenish inventory that might run low.”

The solution also identifies where inventory risks and gaps lie. “On top of that, we give users actionable insights on how to close those gaps by changing their stocking strategies,” says Melissa Dietz, head of customer success at Verusen.

The solution incorporates artificial intelligence and machine learning “but also human knowledge to make faster decisions,” says Baljeet Bolina, an industry advisor at Verusen. “It's a process that’s actionable, sustainable and repeatable.”

The Verusen solution “lets users go lean,” says Noble, “while developing sourcing strategies that get service levels right.”