If you want to better understand the true impact of the pandemic, spend a day shadowing the supply chain-planning managers within a manufacturing organization. By and large, you’ll experience stress, chaos and desperate attempts to address the crises of the moment. The good news is that the pandemic showed just how rigid supply chains can be and that the current methodologies for planning and execution do not provide for a significant amount of flexibility.
When manufacturers place materials orders for production plans based on demand forecasts, and those demand forecasts change, it becomes agonizingly clear that this issue is systemic of a larger problem. The true problem is that manufacturers rely on forecasts that are almost always wrong and do not incorporate lead time or batch size at discrete levels.
Manufacturers exist in a chronically reactive and imbalanced state with too much inventory in some locations and too little in others. Even worse, real supply chain cost-drivers like lead time and capacity are hidden, which leaves only a single lever to reduce cost: unit cost. To reduce unit-cost production, supply chains have become more global, longer and rigid. Unit cost comes down, but agility, competitive advantage and total cost are all impacted negatively, especially in the event of extended unplanned demand.
The common response to this problem is to improve forecasting through better technology that more quickly incorporates more data from more inputs. While better forecasting is always appreciated, the problem of inaccurate lead times and batch size needs at a discrete level still exists. Forecasts will always have a margin of error.
To increase both effectiveness and efficiency, manufacturers need to link their tactical supply chain plan with organizational strategy and the long-term forecast with the manufacturer’s operations while digitizing and automating these same processes. Accurate forecasting and advanced planning are not going away, but they will be augmented with new capabilities. Capacity, lead times, operational parameters, service levels, inventory substitutability and location precision will be continually measured and understood as well the underlying causes of when and how those metrics fluctuate.
This is accomplished by integrating data throughout your supply chain, automating analysis of event streams and actions, and analyzing your complete supply chain through a new lens that doesn’t just look at outcomes but examines how those outcomes were delivered. This is called process mining. It is a capability that can be linked to organizational strategy and supply chain-process planning and execution. The information delivered not only provides a new method for managing and operating supply chains, but also is used to understand bottlenecks and segments to prioritize digitalization efforts.
The way forward involves being able to measure more than just unit cost, but also understanding key capabilities like flexibility and responsiveness as well as leveraging analytics coupled with automated actions. In this way, supply chain planners can focus on more strategic tasks and have the right information to guide them in their decisions.
Sean Riley is Software AG’s vice president of industry solutions