While many organizations are well on their way to Operational Excellence, at least with respect to their Supply Chain, using Strategy Deployment, Balanced Scorecards, and Lean Six Sigma, and are enjoying the benefits of shorter response times, lower inventory levels, and reduced costs, others are still contemplating how to get started. One of the reasons for this is the lack of a comprehensive and systematic Supply Chain performance measurement system. This makes it difficult to establish an operational linkage between potential Lean Six Sigma initiatives and the high-level goals and objectives of the organization as a whole. 1. Inventory Investment
Figure 1 shows the top pressures causing supply chain organizations to consider implementing Operational Excellence and Lean Six Sigma. Figure 2 shows how Best-in-Class Lean Six Sigma Supply Chain organizations compare against their peers with respect to some key performance areas. In this article we will introduce 16 Supply Chain Performance Indicators an organization should consider when establishing a measurement system for their end-to-end Supply Chain processes. Inventory investment directly affects an organization’s profit and cash flow. Every organization needs to invest in raw material, work-in-process, and finished goods inventory to assure required Customer service targets due to long lead times, fluctuation in demand, inaccuracy in demand forecasting, and the lack of manufacturing capacity. Inventory investment, for example as a percentage of gross or net revenue, should be calculated by item and location, based on the item’s lead time, expected demand, and Customer service targets. An effective Sales & Operations Planning Process and Lean Six Sigma methods such as Value Stream Mapping, Quick Changeover, and Kanban Systems can help an organization to optimize its inventory investment and achieve a positive impact on its cash flow and overall profitability while assuring that Customer service targets are being met. 2. Inventory Efficiency High inventory investment by itself does not indicate an inventory problem, as inventory investment for a specific product correlates with the demand for that product. Therefore, it is important to determine the efficiency of that inventory investment by measuring inventory turns or days-of-supply. Inventory turns are calculated as the ratio of the annualized cost-of-goods-sold (COGS) and the monthly average inventory investment. Inventory turns measure how often the inventory “turns over” during a year. Days-of-Supply (DOS) is defined as the number of days required for the forecasted cost-of-goods-sold (COGS)to match the inventory investment on-hand at a given point in time. For example, if the inventory investment at the end of the month is equal to $10M and the current forecast predicts that it will take 15 days to accumulate a total of $10M in cost-of-goods sold, then the organization has 15 days-of-supply by the end of the month. Some organizations exclude excessive and obsolete inventory, for example, inventory that does not have any demand in the next 30, 60, or 90 days or inventory above a pre-defined optimum inventory level for that product, from their inventory efficiency metrics. An effective Sales & Operations Planning Process and Lean Six Sigma methods such as Value Stream Mapping, Quick Changeover, The Seven Wastes, and Kanban Systems can help an organization to improve the demand forecast and reduce lead times, resulting in higher inventory turns and lower days-of-supply, while assuring that Customer service targets are being met.
3. On-Time Supplier Delivery Supplier on-time delivery performance is calculated based on the agreed versus actual delivery time. This metric can be stated in terms of on-time percentage (attribute), which means the supplier delivered during the agreed delivery window or not, or in terms of actual hours late or early (variable). The latter method is more useful when initiating Lean Six Sigma projects to improve on-time supplier delivery performance. Supplier on-time delivery is important to measure, as late deliveries often negatively impact an organization’s manufacturing and delivery schedule and therefore operating costs and overall lead times. An effective Sales & Operations Planning Process and Supplier Collaboration Process, as well as Lean Six Sigma methods such as Value Stream Mapping and Kanban Systems, can help an organization to determine realistic supplier lead times, simplify replenishment processes and improve supplier on-time delivery performance. 4. Forecasting Accuracy Forecasting accuracy is an important supply chain metric as it estimates future demand and thus drives every aspect of an organization’s supply chain. There are many ways to define forecasting accuracy including the three defined below. Forecast accuracy should be calculated by product or product family and most organizations choose a 30-, 60- or 90-day outlook, depending on their industry and forecasting maturity, to determine the accuracy of their demand forecasting and planning process. Figure 3 shows some of the most commonly used forecasting accuracy calculations.
Average Deviation – The Average Deviation or Forecasting Error simply calculates the monthly average deviation (difference) between the forecasted and the actual demand. While this is a very easy way to calculate forecasting accuracy, the disadvantage is that positive and negative forecasting errors will cancel each other out. Average Absolute Deviation – To overcome the above-mentioned disadvantage of the average deviation calculation, some organizations use the average absolute deviation to calculate their forecasting accuracy. The difference in the calculation is that negative deviations, e.g. as for the month of April in Table 3, will be changed to a positive deviation. Root Mean Squared Deviation – The Root Mean Squared Deviation calculation is very useful as it is also used to determine the safety stock for specific products or product families. Here the monthly deviations will first be multiplied by themselves (squared), then the average of the squared deviations will be calculated, and finally, the square root will be calculated of the average. An effective Sales & Operations Planning Process, Customer Collaboration Process, and Postponed Product Customization, as well as Lean Six Sigma methods such as Time Series Analysis and Multiple Regression Analysis, can help an organization to better understand its demand patterns and as a result, improve its forecasting accuracy. 5. Lead Time Lead Time is defined as the time required to perform a specific task or process. Measuring the lead time of critical supply chain and other business processes, e.g. order-to-cash or order-to-ship, is important because lead times drive a significant portion of the overall supply chain costs and inventory investment. Individual lead time components include queue time (waiting), processing time, moving and transportation, receiving, shipping and inspection. Lean Six Sigma methods such as Value Stream Mapping, Quick Changeover, The Seven Wastes, 5S Visual Workplace Organization, and Mistake-Proofing can help an organization to reduce its lead times and as a result improve cost, inventory, and customer satisfaction. 6. Unplanned Orders Unplanned orders, measured for example as a percentage of total orders, are orders that are scheduled within the standard lead time or exceed their original capacity allocation, for example, based on the outcome of the monthly Sales and Operations Planning meeting. Isolated unplanned orders can normally be integrated quite seamlessly into the existing production schedule. However, poor management practices, inaccurate demand forecast, or internal process breakdowns often allow unplanned orders to become a chronic issue, resulting in significant time spend on re-scheduling, additional machine setups, possible delay of already scheduled orders, and raw material and capacity shortages. An effective Sales & Operations Planning Process, Customer Collaboration Process, and adherence to well-defined and documented Standard Operating Procedures can reduce the need for unplanned orders, resulting in improved productivity and customer satisfaction while reducing inventory investment. 7. Schedule Changes Schedule changes are different from unplanned orders as they are normally caused by process changes or unexpected events. Some of the major contributors to schedule changes include material shortages, equipment breakdowns, and staffing and quality issues. Lean Six Sigma projects and methods such as Total Productive Maintenance, 5S Visual Workplace Organization, and Mistake-Proofing can help an organization to reduce the number of schedule changes and as a result, improve operational efficiency. 8. Overdue Backlog While for some organizations a certain amount of backlog is normal, every organization should periodically reevaluate its assumption about the optimal level of its backlog. Excessive or overdue backlog, often measured as a percentage of revenue, can be caused by poor scheduling, quality problems, machine breakdowns, or production and material constraints. Lean Six Sigma projects and methods such as Total Productive Maintenance, 5S Visual Workplace Organization, and Mistake-Proofing can help an organization to optimize its overdue backlog and as a result, improve customer satisfaction. 9. Material Availability All resources required to manufacture an order need to be available at the scheduled time. Poor resource availability results in work stoppages, downtime, and rescheduling of orders. Common reasons for material availability issues include incorrect inventory information, lack of information, poor supplier performance, quality or personnel issues, and machine breakdowns. As a result of poor material availability, inventory investment, and work-in-process increase. An effective Inventory Management Process, Production Scheduling Process, and Supplier Collaboration Process, as well as Lean Six Sigma projects and methods such as Total Productive Maintenance, 5S Visual Workplace Organization, and Mistake-Proofing, can help an organization improve material availability and as a result, improve inventory investment and customer satisfaction. 10. Excess & Obsolete Inventory Excess inventory, for example as a percentage of average cost-of-goods-sold (COGS), is often calculated based on a pre-defined optimum inventory level for that product. The optimal inventory level for a specific product is a function of lead time, demand quantity, and expected service targets. Excess is defined as the inventory on-hand minus the optimum inventory level. Some organizations start with a simpler method to determine excess inventory and define inventory that does not have any demand for example in the next 30, 60, or 90 days as excess. This can in many situations be an effective way to get started until appropriate product-specific inventory levels are determined based on the lead time, demand quantity, and expected service targets. Obsolete inventory started in most cases as excess inventory, but now has no longer demand in the sales forecast. This results in the loss of the COGS or book value of this obsolete inventory. Obsolete inventory is often the result of a poor New Product Introduction Process or Transition Planning Process used to manage the transition from an existing product to a new product. Obsolete inventory is difficult to eliminate without write-offs or price reductions that may impact the sales of newer products. An effective Sales & Operations Planning Process, New Product Introduction Process, and Transition Planning Process can help an organization to reduce excessive and obsolete inventory and result in fewer write-offs or the risk of cannibalizing the sales of newer higher-margin products. 11. Customer Service Targets Customer service targets are the foundation of a Lean Six Sigma supply chain since the end-to-end system needs to be designed and managed to provide an organization’s products and services based on its customers’ needs, expectations, and requirements. Service targets can be measured as a percentage of on-time delivery with respect to unit fill rate, order line fill rate, order fill rate, or in financial terms. Many organizations differentiate between on-time delivery based on the Customer’s request date and the organization’s promise or commit date based on resource availability and scheduling decisions. An effective Sales & Operations Planning Process, Production Scheduling Process, and Customer Collaboration Process, as well as Lean Six Sigma projects to identify the root causes of early or late deliveries can help an organization to improve its Customer service targets resulting in improved customer satisfaction and revenue. 12. Perfect Order The perfect order metric captures every step in the life of an order. It measures the number of errors per order line and is a valuable form of metric that points out the interrelationship between different parts of an organization’s end-to-end supply chain. Example:
In this example the perfect order measure would be 91.43% (0.995 X 0.994 X 0.950 X 0.975 X 0.998 = 0.9143 or 91.43%). Lean Six Sigma projects and methods such as Mistake-Proofing and Standard Work will help an organization to continuously improve its perfect order performance and result in increased customer satisfaction. 13. Gross Profit Margin Gross margin is obviously a key measure to determine an organization’s operational efficiency in converting inputs into outputs, as it is calculated as revenue minus cost-of-goods-sold (COGS). Lean Six Sigma projects can impact both revenue and COGS. 14. Asset Efficiency Measuring how effective an organization is managing its assets is critical to developing a supply chain based on Lean Six Sigma principles, methods, and tools. Supply chains that meet their financial and operational goals and objectives with fewer assets than their competitors need to be “leaner” by definition. Asset efficiency is calculated as the ratio of an organization’s sales and the average value of an organization’s assets. Depending on the scope or purpose of this metric, assets include accounts receivable, long-term investments, inventory investment, properties, plants, warehouses, and equipment. Lean Six Sigma projects focusing on productivity improvements and on the development of cost models to support make-buy or lease-buy decision making will help an organization to continuously improve its asset efficiency. 15. Return on Assets (ROA) Lean Six Sigma Supply Chains should have high ROA levels relative to their competitors and ROA levels should continuously improve as an organization’s Lean Six Sigma deployment impacts more and more parts of the supply chain organization and matures. ROA is calculated by multiplying the Net Profit Margin with asset efficiency. The net profit margin is calculated by dividing the net income by the total revenue, where the net income is defined as the total revenue Lean Six Sigma projects can help improve the ROA of an organization by increasing the net profit margin or improving asset efficiency. 16. Gross Margin Return on Investment (GMROI) The GMROI is an excellent operational metric that shows how much capital an organization should invest in inventory to increase its return on investment (ROI). GMROI is calculated as the ratio of gross margin and an organization’s average inventory investment cost. When used in conjunction with other financial metrics, the GMROI can be a very good metric for Lean Six Sigma projects to effectively utilize Inventory Investment to increase an organization's ROI. Lean Six Sigma projects can help improve the GMROI of an organization by optimizing inventory investment leading to an improved return on investment.
Figure 1, Figure 2 & Figure 4 - Source: Lean Manufacturing: Five Tips for Reducing Waste in the Supply Chain, Aberdeen Group 2009 Please Contact Us to discuss how we can support your Operational Excellence initiative, and visit our OpEx Academy for Training Materials, eLearning Modules, Online Courses, and Public Workshops. Experience. Passion. Results. |
What are the metrics used to measure improvements in supply chain management?
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