There is risk in almost everything we do. It is unavoidable. Supply chains are no exception facing all kinds of unexpected but inevitable surprises. Some can be very costly to the company. It is imperative that the management are prepared to deal with unfavorable issues when they occur without building too much redundancy increasing the cost of operations. In a typical supply chain, having thousands of SKU’s and suppliers as well as other factors such as geopolitical issues, labor related issues and demand volatility, makes the supply chain operation very complex and in the absence of appropriate tools almost impossible to manage in an efficient manner. The key is to identify the potential risks before they happen so that adequate measures can be put in place.
There are many ways to assess risk vs cost and reward. As an example, one can use Multi Echelon Inventory Optimization (MEIO) to assess risk of on-time delivery vs cost. This can be done by SKU and customer. For certain customers, the desired delivery performance must remain at 98% or higher. Obviously this can be accomplished at a higher cost of inventory at different stages of the supply chains. On the other hand, for many other customers, a delivery performance of 90% might be acceptable at much lower cost of operations. As the demand patterns change, MEIO behaves as an almost perfect postponement strategy, to show where and when inventory is needed for a desired delivery performance and cost by customer and SKU. This algorithmic approach, based on probability distribution and queuing theory, is by far superior to the traditional methods of historical data such as moving averages and/or min-max types of approach.
Having visibility into meeting the financial goals of the company is critical. Any risks associated with that must be detected as early as possible and addressed. Likewise, meeting delivery performance for certain key customers, making sure that the right mix of inventory is available to keep the production running, knowing what options are available in case of capacity shortage, or material running out (or not delivered in time) are all factors that may increase delivery risks, increase cost and even cause loss of market share. Optimization models of systems designed to assess the impact of risks can act as a crystal ball to provide visibility to the end users and furthermore provide guidelines and advise end users as to what the best course of action would be. It is a proactive way of responding to potential risks than reactive.
One other critical use of systems is to perform what-if stress tests on the entire supply chain. By either overloading the supply chain model or trying to break certain links in the chain, one can observe the consequences of such events and what can go wrong, what the financial impact would be and what can be done from the convenience of your desk, before it happens! Preventing such potential disasters are how modern heroes are made of in the world of leading companies! Learn more about Supply Chain Risk Resiliency by clicking this link.