I was in Poland recently looking out the hotel window at the town’s historic clock tower – still in operation after about 400 years – and started pondering how time shapes the modern supply chain. Time is the lens that focuses all supply chain planning decisions. Distance is time. Inventory is time. And Time is money. For any consumer facing organization, our ability to make decisions in a ‘timely manner’ is nothing less than a matter of corporate survival.
Our planners hold the customer satisfaction in their hands. As they balance the dynamics of demand against the constraints and limitations of supply, we need to recognize that the feasible, financially viable options available to planners have been dictated by earlier choices. The decisions that limit their current choices were made days, weeks, or even months earlier. But a planner’s life is pretty straight forward, right? They only have to answer one question: What customer demand can we meet today?
If the answer was, ‘All of it’, the job really would be easy. Yes there would be questions about inventory, but we’ll talk about that later. Very rarely is all demand being satisfied. So more questions get asked:
- If not today, then when?
- When can we ship it?
- When can we make it?
- When can we receive it?
This is where the planner’s job get complicated. As we drill down into each of these questions, we realize that they are interconnected:
- The demand we can meet today depends on what’s in stock.
- If it’s not is stock, it depends on what has shipped within a transportation lead time.
- What we can ship depends on what we produced a manufacturing lead time before that.
- What we can manufacture depends on what we scheduled a planning cycle before that.
- What we can schedule depends on the available components that were ordered a procurement lead time before that.
Let’s go back to the first question as the place to start working our way back through the decision points that drive supply chain strategy and inventory policy. “What customer demand can we meet today?” Before we start crunching numbers to come up with an answer, consider a more fundamental question and one that drives continuous supply chain improvement: How long is the customer willing to wait to take possession of the product? The duration the customer is willing to wait versus the time (and cost) it takes for us to ‘get’ more is the primordial equation of supply chain management. ‘Demand Latency Potential’ (DLP) is the duration a customer will wait between selecting to procure a particular, fully specified item, and taking possession of that item, before selecting an alternate item or foregoing the procurement altogether.
DLP can range from less than a second to years. From the chewing gum impulse buy while standing in line at the grocery store, to waiting for the ‘Back to the Future’ hover-board. We normally think about this in terms of manufacturing Getting strategy. The higher the DLP – the longer the customer is willing to wait – the longer we have to create the product and the further ‘upstream’ we can hold inventory. We don’t craft our supply chain strategies on an empty whiteboard. Our customers have already decided on the boundaries within which we need to work.
The further upstream we can hold inventory, the shorter the ‘Commitment Horizon’. Commitment Horizons are the durations between committing funds to procure, convert, or transport and the customer taking possession and paying for the product. We want the shortest Commitment Horizons possible to collapse the time between spending and collecting money. Most customers will not wait the full value stream lead time for most industries and products with which we work. Take the time to understand, differentiate, and segment customers and products based on DLP. Once we clearly understand DLP, we can compare it to the cumulative value stream lead time.
The difference, along with accounting for variability, is the amount of time and money you need to invest in inventory to bridge the gap. Before each shipment point and point of conversion, we can decide to hold inventory to close the DLP gap. This is where factors relating to demand variability, risk pooling, and total cost analytics are leveraged in multi-echelon inventory optimization.
We are trying to minimize cost while at the same time maximizing feasible planning options. Because of market imperatives, we employ postponement strategies, delaying customization by holding inventory at the component and sub-component level while waiting for a more accurate customer demand signal. Investing in critical, hard to obtain and long lead time raw materials may be part of the strategy to shrink the time to fulfill – and react to changes – customer demand.
Following the DLP vs Strategy Curve in Figure 2 is like traveling back in time through the conversion points in the product structure illustrated in Figure 1. Somewhere along the curve lies the right blend of manufacturing and inventory strategies that are appropriate from an order fulfillment and inventory investment standpoint, to support your business model.
Determining these strategies can quickly become overwhelming. There are powerful Inventory optimization and Strategic Analysis software packages on the market to support this decision-making process. They don’t however, fully take the place of deliberate, clear thinking when crafting a comprehensive supply chain strategy.
So as planners sit down each morning to make the decisions that are driving customer satisfaction, understand that they really make many, interrelated decision over different horizons. When you design your supply chain, take the time to decompose these decisions. Follow them back to the business drivers and create an integrated strategy that allows planners to take powerful actions.
