I was talking to another consultant recently about issues one of their customers had with obsolescence in the high tech electronics industry. He said with all the rapid advances in technology, it is becoming increasingly difficult to avoid the effects of product obsolescence and its effects on margins, scrap, and inventory levels. He asked me if I knew of any useful methodologies that could be applied to planning with obsolescence, in order to simulate its effects and thereby try to minimize its negative results. This got me to thinking about my experiences in the pharmaceutical industry, where product expiry and scrap due to expiry are a key planning issue. Could the methodologies we use to mitigate expiry be used when planning for obsolescence? While on the surface it would appear the two are unrelated, when looked at closer from the planning perspective, commonality begins to emerge. Both scenarios deal with supply that is unavailable (or degraded) for use after a period of time, both scenarios deal with material that must be scrapped and disposed of, and both can have severe impacts on inventory and the bottom line. Expiry deals with product which has a defined life, usually due to efficacy and regulatory issues. Obsolescence is much more difficult to define in terms of a definitive lifecycle, but products have a finite lifecycle due to customer demands driven by technology and market changes. While obsolete products don’t necessarily result in product scrap and disposal, dealing with obsolete products can have a significant negative impact on margins and inventory levels, as well as cannibalize market share from newer products that replace them. What if we used expiry planning tools to model obsolescence? If we assign the anticipated time to obsolescence to the minimum shelf life (time remaining to expiry for a product in the market), we can actually model and plan for the ‘expiry’ of our products. Armed with that knowledge, we can look at effects on margins, scrap, disposal costs, and inventory levels. Are those safety stock levels we are currently setting going to result in significant amounts of unusable inventory down the road? Are our minimum economic buy levels really that economical, or are we losing all the cost benefits in obsolete inventory losses? Are our projected margins going to hold, or will we see a drop as obsolete product factors come into play (price cuts to move inventory)? In order to answer these important questions, we could use planning tools to effectively simulate some 'what-if' scenarios. We could play with ‘expiry’ to simulate multiple different scenarios, and look for best case scenarios to minimize scrap risk or margin loss. In order to perform an effective what-if simulation, we would want a tool to be able to handle complex (where a component determines expiry of a parent) as well as simple (the item itself determines expiry) expiry planning. This is because a component or components (a CPU or drive for instance), at several levels in the BoM or supply chain, could actually determine the life of the end product, and we would want to simulate the effects of these relationships. A planning tool can help identify these ‘inflection points’ in the planning cycle, and thereby alert the planners to manage the supply chain in different ways to generate a better outcome for the business. In summary, even though pharma and electronics are very different industries, there are elements of one which can be applied to the needs of another in new ways in order to improve business performance and planning. More food for thought: What can supply chain optimization techniques in the electronics business teach pharma?
Congratulations! It's a digital twin — with a very large extended family
Think about your digital twin as you would a member of your extended family. A twin should be connected to the rest of the family, know its ancestry and be able to ask questions, just as they would around the dinner table.