Anyone who works in a commercial manufacturing business will be all too aware that there is continuous pressure to achieve service excellence while reducing stock levels, costs and component prices. And, with growing focus upon penetrating emerging markets, off shore manufacturing and increasing ‘low cost’ competition, that pressure just gets greater but harder to achieve.
One of the main barriers, for many companies, to achieving a step change in Supply Chain, Operations and Procurement performance is their use of sku level forecasts to drive replenishment through DRP and MRP calculations. These generate replenishment recommendations aimed at achieving safety stock levels but, because forecasts are inevitably incorrect (which sends stock to wrong places and drives manufacture of the wrong product mix) and are always being updated, the exception messages never cease (irrespective of whichever forecast consumption technique has been selected) and warehouses, factories and suppliers are frequently asked to amend and change their schedules at short notice.
This, as the ‘queuing theory’ behind ‘Factory Physics’ (1) clearly proves, leads to unplanned machine changeovers and lost capacity with inevitable knock on effects up and down the supply chain which cause lead times (and WIP) to fluctuate frequently, requiring everyone to have to respond, at short notice, to apparent changes in their customers’ requirements. Unfortunately, the greater the level of variability that a supply chain experiences, and the higher are desired levels of capacity utilisation the longer (and at higher levels of capacity utilization the lead times increase exponentially) and, significantly, more volatile lead times become which is absolutely antithetical to the core MRP tenet that they be stable.
As if these forecast induced volatilities aren’t bad enough by themselves, they are a whole lot worse when the end to end supply chain is affected by ‘bullwhip’, which it always is when ‘forecast push DRP/MRP’ techniques are used. ‘Bullwhip’ occurs when small changes in consumer demand get amplified by the forecast as they are passed up the supply chain. It is caused by batching and the various players within the supply chain behaving in way which, while well intentioned, actually amplifies volatility, as can be explained by engineering control theory, systems theory and, even, chaos theory (2). ‘Bullwhip’ causes warehouses, factories and suppliers to respond to very much higher levels of sku demand variability (and its attendant costs) than they otherwise would.
So, if your operations and suppliers are working hard to eradicate sources of variability then your ‘forecast push DRP/MRP’ driven replenishment and ordering process is simply adding another source of that same variability which is increasing costs, generating service issues and, usually, also causing high levels of stock and extended response lead times. Any instability, of course, can also disrupt and slow down the CI process as everyone focuses on meeting the latest backorder instead!
The impact upon product costs of bullwhip volatility has been demonstrated to reduce margins by up to 30% (3). This is due to the stock holding costs, the wasted unplanned capacities and because all operations (ie. those of factories, warehouses and freight as well as those of suppliers) perform most efficiently when under stable conditions as any Operations Manager will tell you.
If the only way to avoid generating forecast induced volatility and bullwhip is to stop using the forecast to drive replenishment, is there an alternative? Fortunately there is and it’s called ‘Demand Driven Planning & Replenishment’ (DDPR) in which, at each stock location for each item, an appropriate non-forecast based replenishment technique is selected and, across the full end to end supply chain, the techniques, replenishment triggers and buffers are aligned to ensure they successfully support each other and the rates of consumption at each and every echelon. These techniques, of course, don’t just apply to a company’s internal supply chain, they can also be the basis for collaboration with suppliers and customers.
From a stability perspective, these techniques protect Operations and Suppliers from demand volatility by preventing it being amplified into ”bullwhip” and ensuring that any remaining is correctly buffered. The key ‘make to stock’ demand driven replenishment techniques that can be used are, broadly, the following
- Consumption-based pull – in which inventory buffers are located, as appropriate, in the supply chain to decouple processes and minimize lead times. Supply activities (eg. inventory movements, production and purchase orders) are scheduled according to a time phased cycle and the quantities triggered, rounded as necessary, replace what has been taken from the location immediately downstream. This affords protection against demand uncertainty and minimises amplification by only building to a replenishment signal, not to a forecast. This technique can be used even if demand has trend or is seasonal so long as the replenishment parameters reflect future demand patterns appropriately.
- Rate-based or Level Schedule – where demand is high and relatively stable (as it often is for mature products and for upstream items before sku specific customisation takes place), supply can be levelled at a suitable fixed rate, subject to periodic review . In Lean language this is called ‘heijunka’ or ‘mixed model scheduling’ and it works best when it involves high frequency/small batch production. Level Schedule is also very useful for new product launches as a means of achieving stable production when demand is notoriously fickle.
Whereas ‘forecast push’ requires the forecast to be accurate on a time phased basis, which it never can be, these ‘demand pull’ processes allow the supply chain to autonomously respond to demand variations. This enables Planners to concentrate properly upon Inventory Planning. Inventory is now effectively managed as ‘capacity’ to respond to demand and meet service requirements. Through replenishment parameter management, inventory planning therefore has as significant a role to play as conventional capacity planning. The parameters up and down the supply chain need to be aligned and should include an element of safety stock to reflect demand uncertainty. Unlike ‘forecast push’, however, these safety stocks are actually planned to be used and are designed to protect operations against any residual variability. Despite the criticality of effective inventory planning however, the replenishment parameters should not be changed every month (if they were you may as well use the forecast!); they should certainly be reviewed regularly but only c5% will actually need amending at any one time.
The other key demand driven replenishment technique options are those used when demand volatility is so great that it is uneconomic to provide an ex-stock service. In these situations, time can be used as the buffer and, depending on the required service strategy, the technique chosen might be ‘assemble to order’ (ATO) in association with postponement strategies, or ‘make to order’ (MTO). These techniques can be used when customer demand is genuinely volatile (eg. response to tenders and price promotions) as well as forming part of an ‘abnormal demand’ management process. In this way postponement with ATO, and supported as necessary by appropriate ‘design for manufacture’ and asset configuration, combined with upstream ‘demand pull’ can deliver cost effective ‘Agility with Stability’.
The choice of replenishment technique is an essential part of the ‘Demand Driven Planning & Replenishment’ process and should be undertaken for each material at every echelon. The criteria for selection is the item’s demand profile (volume and variability) and ranges from level schedule for high volume / low variability items, through ‘demand pull’ or ‘make/ship to replace’ to ATO and MTO for the high variability items.
S&OP of course, is an essential support process for demand driven replenishment as it is forward looking and, in addition to aligning commercial and SC operations with the financial plan, one of its aims is to align material and capacity availability with the demand plan.
If DDPR is so effective, it’s reasonable to ask why it isn’t practiced more widely? In fact ‘pull’ is increasingly common within the factory walls and, in some industries, with suppliers (eg. grocery multiples and automotive) but is rarely seen all the way across companies’ distribution channels and linked into their factories through to suppliers. This might explain why many companies often find that all their Lean Factory and Supplier Engineering efforts haven’t translated into the significant performance benefits they expected. By now the reader will know why.
The reasons for the relative scarcity of “end to end” DDPR can only be speculative but might include the fact that it is counter intuitive, neither widely or fully understood and difficult to implement successfully without appropriate software support.
Clearly Warehouse, Factory and Procurement Managers have an interest in how their company’s supply chain is managed if it has a significant impact upon their performance and their ability to contribute to the bottom line, let alone if it could prevent material shortages and service issues. In some companies the CEO might also be interested?
Fortunately, the outlook for DDPR is positive with the impact of a Lean education upon the new generation of supply chain leaders and the emergence of specialist “software as a service” (SaaS) DDPR vendors such as Orchestr8(UK), Ultriva and Demand Driven Technologies (both US).
It is important however, not to assume that DDPR is an easy fix. Successful implementation requires a clear understanding of its rationale and benefits (a successful pilot is often an important element here), adequately robust, user friendly and functionality rich planning systems, senior cross functional leadership support and a capable and interested supply chain team that includes Order Management through to Supply Management.
How would successful implementation of DDPR affect Planning and Supply Management activities? The good news is that it will remove a lot of tedious and non -value added work such as continuously cutting and re-cutting of supply plans, expediting and then having to explain why there are service/inventory issues, inbound late deliveries and lost production hours. Planners should be able to allow Operations to “respond to what they can” while they plan what is necessary. These planning activities will include S&OP, demand profile analysis, replenishment technique selection and management of replenishment cycles and inventory parameters…………all of which might be termed supply chain “conditioning” or “tuning”. Other key activities which can now receive adequate focus will be collaboration initiatives with customers and suppliers (using DDPR principles!), new product launch planning, promotions and tenders management and, by exception, the abnormal demand (and maybe supply) management process. Supplier Management teams will also be able to spend more time on their value add activities such as supplier S&OP, price/cost analysis, supplier development etc.
Additional significant benefits are that warehouses, factories and suppliers will all notice that their daily ‘work to’ lists become far more predictable and stable. In consequence adverse cost variances and unplanned overtime should diminish significantly, and more quality time can be spent on CI initiatives that minimise supply variability and cost instead of chasing the latest service problem. Supplier Management should be able to share their now relatively stable requirements with suppliers and allow them to reliably schedule their operations accordingly and, perhaps, even manage their own replenishment schedules if working with a collaboration platform. Perhaps, very importantly, suppliers should be able to operate far more efficiently and some of the consequent cost savings should accrue to their customers!
1 – Hopp & Spearman (1996) “Factory Physics”
2 – See for instance
-Disney, Dejonckheere, Lambrecht, Towill (2003) “Measuring and avoiding the bullwhip effect: a control heretic approach” European Journal of Operational Research 147(3), p567-590
– Sterman (2006) “Operational and Behavioural Causes of Supply Chain Instability” p17-56The Bullwhip Effect in Supply Chains: A Review of Methods, Components and Cases
-Wilding (1998) “Chaos Theory; Implications for Supply Chain Management”, International Journal of Logistics Management, 9(1), p43-56
3 – Metters (1997) “Quantifying the bullwhip effect in supply chains”. Journal of Operations Management 15(2) p89-100