On February 24, 2022, when Russian tanks rolled into Ukraine, it was not quite the final nail in the global supply chain coffin. The chain had long crumbled and was in tatters. Nothing sums up the fate of the global supply chain and its management better than this post from Think Tank: "Those alarmed by the confluence of supply chain-crushing global events — a lingering pandemic and what's turning into an all-out economic war with Russia — would do well to remember that the Great Fire of London occurred during an outbreak of plague. People don't get a break on other disasters just because they're in the middle of a crisis, and that includes those managing international supply chains."
Global auto sales dropped in the last two years because of semi-conductor shortages. Even the United States, the world's wealthiest nation, has faced shortages of several vaccines recommended for childhood immunization in the past. Some of these shortages were widespread, while others were localized. The reasons for this were multi-factorial, including companies leaving the vaccine market, manufacturing or production problems, and insufficient stockpiles
In sum, supply chains designed for a perfect world were utterly unprepared for a VUCA (volatility, uncertainty, complexity, and ambiguity) scenario. Some would point fingers at the JIT (just-in-time) philosophy. A quick analysis of inventory as a percentage of sales of the top industries in the US as of date reveals it was 17%. Of this, the non-cash working capital portion was higher at 24%. If JIT was indeed the go-to management mantra, it was not working in some of the top global industries that make up the lion's share of the worldwide Industry 4.0 landscape.
Let us focus on the inventory part, however, where most global think tanks and software powerhouses have been optimizing for the most part of supply chain management history. Inventory optimization has been the first pit-stop of most supply chain transformation and optimization projects. Even now, 36% of supply chain professionals say that one of the top drivers of their analytics initiative is optimizing inventory management to balance supply and demand. In 2020, despite the top dollar opting for getting the inventory right, out-of-stock items were estimated at USD 1.14 trillion, and overstock accounted for USD 626 billion in retail. It begs the question: Are we solving the right problem? Perhaps we have been only treating the symptom, not the cause.
The inventory problem is only a symptom, the tip of the iceberg, so to say. When consultants tackle inventory optimization with statistical methods—ABC analysis, segmentation, clustering—it amounts to putting the cart before the horse. Even if the mandate is only to treat the symptoms, one must be aware that it is a temporary fix. A slight change in variables and the same symptoms will crop up again. A symptomatic treatment approach, therefore, necessarily requires continuous interventions.
Companies may face inventory problems due to:
- Zero visibility into demand
- Lack of collaboration among partners and suppliers
- Lack of coordination among and cooperation between internal organizational functions of sales, marketing, production and engineering, and procurement
- Complete breakdown of communication between partners
- Quality and reliability of service from suppliers
The best way to tackle a low-asset turnover is to identify the communication breakdown that caused the inventory buildup. Let us start with the basics: Why do we need an inventory? Maintaining an inventory is a risk mitigation approach. A high safety stock, low pipeline inventory, or high re-order point means high uncertainty in the supply chain. If it is related to uncertain/inconsistent product quality, the problem is exacerbated because you are carrying inventory not to satisfy demand but to keep your production running. Is there a better solution? There certainly is! It means working with your suppliers and your internal manufacturing operations team for defect detection for in-process products. Using off-the-shelf products rather than purpose-built ones can help reduce new product development (NPD) time in aerospace and automotive by 30% or more. NPD time ranges from three to four years in automotive to seven or more in aerospace. The chief reasons for this long gestation period are the requirement for new tooling and fixtures, purpose-built components, etc. Bill of Materials (BOM) optimization is the first activity that should be taken up for any new product development process. This can happen only if R&D, engineering, and manufacturing are involved right from the product conceptualization phase. In the absence of collaboration between these key functions, tools that help in defect detection in parts and propose alternates can go a long way in BOM and, thus, inventory optimization. More importantly, this activity must be undertaken by acknowledging that BOM and inventory optimization in manufacturing are primarily engineering problems requiring an expert solution rather than a mathematical solution right at the outset.