Here are the top 10 elements for having a best practice supply chain planning function.
1. Have a clearly understood and agreed service level agreement (SLA) with your customers
The SLA should be a detailed understanding of the service to be offered, particularly concerning lead time, minimum order quantity, and stock holding requirements. It should also articulate the parameters that define exceptional demand (e.g., a promotion) from normal fluctuations in demand that can be accommodated as “business as usual”
2. There should be a robust, regular channel of communication with your customer, to measure and improve performance levels defined in the SLA
Most enlightened businesses now have some kind of Sales & Operations Planning (S&OP) processes. Many however, are very inwardly focused and don’t include sufficient or any direct input from the customer. This is the opportunity for the customer to communicate significant future demand changes for which the supply chain needs to be recalibrated
3. Proper supply chain planning must consider total business cost including demand, capacity, supply and inventory planning
Another common failing of many S&OP processes is that they do not cover all the elements of cost. Typically the debate can be around manufacturing efficiency and capacity and ignore the costs associated with poor customer service or resultant inventory. A good S&OP process understands the service model agreed and then determines the least cost way of delivering this.
4. Know when and when not to use a forecast
Forecasts, no matter how inaccurate, are the best tool that we have to determine future capacity requirements. Therefore we should have a toolset that enables us to access this information easily. Forecasts are typically not bad at determining how much of something we will need, i.e., is demand increasing or decreasing, but very poor at predicting exactly when the demand will occur. Therefore never use a forecast for order generation to do so flies in the face of any demand driven lean-approach.
“A common mistake here is to confuse demand variability calculated entirely from the historical demand pattern with forecast variability, which is the variance between history and forecast. The former is correct the later is meaningless.
5. Segment SKUs based upon their demand volume and variability and then select the appropriate replenishment rule for each segment
The same service level and/or replenishment rule is rarely appropriate for all SKUs. Normally there is a range of items from high volume. These low variability items require a highly repetitive supply plan, through to those with sporadic requirements that should ideally be ‘make to order.’ This segmentation fits closely with the principles of lean manufacturing. A common mistake here is to confuse demand variability calculated entirely from the historical demand pattern with forecast variability, which is the variance between history and forecast. The former is correct, the later is meaningless.
6. Use the correct replenishment rule to calculate the correct stock level for each SKU level, to satisfy the agreed customer service level in the SLA
Once all the levers of cost are understood and the appropriate replenishment rule selected for each SKU, an inventory and production plan can be built that delivers the desired customer service levels. In order to get the correct balance of inventory and manufacturing cost, a new way of calculating inventory holding is required that flies in the face of much of the conventional inventory planning wisdom. The traditional approach is to calculate a moving safety stock based upon several weeks forecast, sometimes ‘refined’ by using forecast variability against historical usage (in APS systems). This method is fatally flawed in two ways; it relies exclusively on forecasts to calculate the amount of safety stock required, and it actively plans in a level of ‘dead’ stock, with the anticipated on-hand levels moving between the safety stock level and safety stock plus the minimum order quantity.
The new approach to inventory target calculation sets a maximum target level of inventory for each SKU. This is made up of an element of inventory for the replenishment time plus an element for demand variability, which is statistically related to the required service level from the stocked item. This approach makes the entire inventory available for use, with on-hand levels fluctuating between the inventory target and zero. It also builds in some sound statistical probability of material availability based on historical demand variability. As long as your S&OP process flags up demand that falls outside of this agreed variability, you will have a lean level of stock that supports your customer SLA at least cost.
7. Completely separate planning activity from execution activity
Another curse of MRP is its ability to blur the line between planning and execution. A planner is being asked to replan and chase orders daily, or even hourly as the MRP “shuffles the order pack” each time it runs, requiring their constant attention. It is vital to separate the activity associated with planning from that of daily order raising and execution. Best practice requires that a plan is set, normally for a month, in line with the frequency of the S&OP or forecasting cycle. Then execution happens daily against this plan, enabling a set of lower-skilled or automated actions to be taken daily. This normally means a key change to the skills required by a planner, meaning considerably fewer but more highly skilled individuals.
8. Execution tools that allow orders to be raised in line with appropriate replenishment rule
There will invariably be the need to cater for a range of replenishment rules when placing manufacturing or purchase orders, from fixed repeating schedules, through kanbans and reorder cycle items, spares requirements, to pure make to order. Most ERP/DRP systems support some but not all of the required techniques. Therefore you will either need a new order generation tool that uses the required execution technique to compliment the chosen replenishment rule, or you will need to imaginatively configure your ERP/DRP systems to behave and raise orders differently.
9. Forecasts must be completely eliminated from the ordering/execution process
Inaccurate forecasts are the major cause of cost in all supply chains, and forecasts are always inaccurate! The aim should never be to execute an order against a forecast. Forecasts can, however, be used as an indicator of forward demand volumes and linked correctly with actual demand variability from history can be used to set appropriate inventory policies and targets. “Inaccurate forecasts are the major cause of cost in all supply chains, and forecasts are always inaccurate!”
10. When planning, use the shortest possible planning horizon to minimize the likelihood of plan change and to minimize the number of orders that need to be controlled
There is a belief that by extending lead-times, you increase your available capacity. This is a myth. Extending lead-times will upset your customers, particularly if this violates an agreed SLA, and increase the level of activity and cost required to plan. Wherever possible, drive down lead-time, which will, in turn, drive cost out of the supply chain. This approach fits exactly with the requirements of lean manufacturing.