Chapter 1
It Should Be So SimpleâWhy
We Fail to Deliver
What You Will Learn in This Chapter
How to recognize whether your supply chain is not functioning correctly The key root causes of poor delivery performance Why your enterprise resource planning system may be making the problem worse rather than better How to understand your supply chain using a value stream map So What Is the Problem?
Around the time I sat down to write the first chapter of this book, I was invited to the annual sales conference of a new customer. The customer was a company that manufactured and distributed a large range of industrial chemicals, mainly for use in the dairy industry and commercial cleaning. Their products were sold through farm retail chains and cleaning chemical distributors and often sat on the shelf next to very similar competitive products.
The reason the CEO invited me to the sales conference was to provide some reassurance to the sales team that their new Lean project was going to focus on addressing the businessâs chronic delivery problems. After an initial introduction to the project and my background and credentials, what followed was a fairly heartbreaking hour listening to the frustration of the sales representatives from all around Australia. Their concerns represented a litany of pretty much everything that goes wrong in supply chains. Some of their comments were
Why do we run out of stock of our most important products when we have so many slow-moving products on the shelf? Why is the stock never accurate on our computer system? What should I say to a customer when he asks me when an item on back order will be delivered? Nobody at the factory seems to know. Why is the production manager the only one who seems to know when things will get made? Most of the time I canât contact him, and I donât feel I should need to contact him anyway. The salespeople at this business estimated that they spent at least two hours per day parked by the side of the road on their phones trying to find out when a product would be available. They lacked confidence to win new business because they did not believe that the goods that they promised to the customer would be delivered on time. The products were really good, customers wanted them, but if they could not get reliable supply, customers bought a competitive productâeven if the quality was not as good as theirs.
Like many businesses in this situation, relationships between sales and production were toxic. The production manager resented the constant badgering calls demanding product almost as much as the sales team resented having to make those calls.
However, the frustrations of the sales team were just the tip of the iceberg. Toward the end of the discussion, the chief financial officer (CFO), who was also at the conference, pointed out quietly that despite all the frustration about shortages and backorders, the business had more than three monthsâ worth of inventory. When this was added to the two months it typically took for customers to pay their bills, the company had to wait an average of five months from the time it purchased packaging and materials to the time customers paid their bills. This placed an enormous cash flow burden on the business and meant it was saddled with debt to fund all that excess working capital.
So to sum up, missed deliveries, shortages, disappointed sales teams, and frustrated customers go hand in hand with excess inventory, obsolete write-offs, and cash flow difficulties. It sounds like a paradox: too much stock, but constant shortages impacting on delivery. How can this occur?
Six Reasons Why Companies Have
Too Much Stock and Canât Deliver
In my experience, there are a number of reasons for the situation that faced our client described above. You are likely to recognize some or all these in your business.
Reason 1: The Customer Cannot Forecast Accurately
This is not actually a reason for poor performance; it is an excuse. The oldest saying in business is that âthe customer is always right.â To me, this saying should not be taken literally. What it really means is that the customer can decide who they purchase from. Therefore, if you cannot meet the customerâs unreasonable unforecasted needs, they will purchase what they need from someone else, if at all possible. This begs the question of whether your company is truly able to serve this customer, and whether in fact you might better allow this customer to buy from someone else. However, if the customer is one you want to keep and you are unable to meet their âunreasonableâ needs, then consider that problem as yours, not theirs.
So why am I saying all this in the context of forecasting? The reason is that if the customer is unable to provide you an adequate forecast and you want to keep that customer, then you had better find another way to meet their needs that does not rely on the forecast.
There may be very good reasons why the customer cannot provide a forecast. Perhaps they simply cannot anticipate and forecast future demand. If you consider the supply of ice cream, for example, demand is totally dependent on the weather. Perhaps factors beyond their control impact demand. Builders, for example, are often a source of complaints from my customers in the construction materials industry. However, the life of a builder can be very unpredictable, work can be delayed by other tradespeople held up working on other sites, other materials (other than yours) may be delivered late, unexpected issues on the job site can delay progress, or bad weather can stop work all together.
We can also compound the forecasting problem internally. Flagging sales can generate a last-minute promotion, which strips the shelves of stock to meet normal demand. Poor planning around product development can lead to large imbalances in supply and demand for new products and obsolete stock of old products. Overly generous promises can be made to customers without consideration of the businessâs ability to deliver.
Fortunately, the problems we generate internally are slightly easier to manage than problems created by our customers or market conditions. Chapter 4 will introduce sales and operations planning, an effective way to ensure that the various functions in the business talk to each other regularly about demand and the ability of the business to supply that demand. Before that, we are going to have a hard look at the pros and cons of forecasting in Chapter 3.
Reason 2: Long Lead Times
When we complete a value stream map1 A value stream map is a special type of process map used in Lean Thinking. It maps the flow of a product along with the information that controls that flow. It is used to highlight and eliminate waste in the flow. of a process or supply chain, we calculate the lead time in the process. I usually describe this as the time it takes for one unit of raw material to travel from the receiving dock through the plant to shipping. In an extended supply chain, you can take this further and consider the lead time to be from when your supplier receives an order for material and then travels through their process, through your factory or warehouse, through your distribution network, and finally to the customer. This can be a long time, and the longer it is, the worse your supply chain challenge can be. When you add up all these individual lead times for scheduling the production, sourcing the materials, manufacturing the goods, and packing and shipping the goods, total lead times of six months or more are not unusual. This means that the materials you order today will not be delivered to the customer as finished goods for six months. As a result, you need to know or make a judgment call on what specific products and quantities the customer will need in six monthsâ time. This is very difficult, if not impossible. The difference between your six-month-old estimate and what the customer actually needs can be very large. If you get it wrong, then you most likely will have to expedite the materials that you now need and will be faced at the same time with excess stock of products that you have no immediate use for.
Lead time is an evil at every step of the supply chain, and one of the most powerful aspects of the Lean approach is a relentless focus on reducing lead time through reducing non-value-added time. In Chapter 2, we will discuss value stream mapping to reduce lead time in your operations and supply chain.
Reason 3: Big Batch Sizes and Big Shipment Quantities
It is easy to rationalize why big batches or large shipments are âefficient.â Fewer setups, less downtime, and more stable processes mean that big batches appear to lead to greater efficiency. Large shipments mean you can ship âfull containersâ and save money on freight. You may get discounts from suppliers from ordering large shipments. In manufacturing, your measures of efficiency, such as âoverall equipment effectiveness,â will go up when you increase batch sizes. The problem is that big batch sizes and large shipments compound your supply chain problem. The first reason is that they extend your lead times. This is because big batch sizes take longer to run, and it takes longer to consume the inventory from large shipments. Letâs say you make 30 different products and aim to run one batch per day. As a result, on average you will only make an individual product once every 30 days. If an order comes in, then the customer may need to wait up to 30 days (on average 15 days) while you complete batches of other products before they get their orders fulfilled. This additional lead time adds no value, but increases supply chain risk and the amount of inventory your customer needs to hold. Likewise, big shipment quantities take a long time to consume, which means that you only replenish infrequently. The greater the gap between one delivery and the next, the greater the chance that demand will unexpectedly increase, leading to a shortage before the next delivery arrives.
Big batches and large shipment sizes also compound what is called the âbullwhip effectâ (also known as the Forrester effect). This effect, which I discuss more in Chapter 10, is the phenomenon whereby the variation in demand for a product is amplified as you go up the supply chain. This is because the production batch or minimum order size might be many times greater than the typical customer purchase quantity. As a result, customer purchases will not trigger upstream demand until a whole batch or order quantity has been consumed. This process is repeated at each step up the supply chain and this artificial demand pattern (caused by batching) is built into forecasts, multiplying demand variation. Therefore, we often see products with very stable consumer demand through the year (e.g., laundry powder or toilet paper) where the demand on suppliers two or three steps up the supply chain (e.g., packaging suppliers) varies wildly from week to week and month to month.
Of course, if the batch size was equal to the customer order size, then an order for 10 units would trigger a batch for 10 units. Demand would not be amplified. Increasing batch sizes or order quantities, which is often aimed at stabilizing production (by allowing âlonger runsâ), will often increase volatility in the supply chain, making shortages worse and of longer duration, while at the same time increasing inventory (because bigger batches and less frequent replenishme...