How to Measure the Success and ROI of Demand Planning

Four key business process areas that manufacturers must focus on to continuously improve their demand planning process

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When a manufacturer needs to measure the success and associated return on investment (ROI) of a demand planning process, the key is to identify the business process areas that need to be improved and then define the associated metrics that can then be measured and ultimately translated into ROI. While there are many process areas associated with demand planning, there are several key areas where manufacturers should focus that will derive the greatest process improvement for their demand planning. These focus areas require careful consideration before embarking on a project — a manufacturer must insure that it can adequately calculate value and ROI based on the economics of the portion of the process being improved.

Business Process Focus Areas

Forecast Accuracy: In any demand planning process improvement project, forecast accuracy is the most important starting point. Forecast accuracy is the key business metric that drives the effectiveness of the rest of the demand planning process at every manufacturer, and a forecast is only as good as the data you are relying upon to commit to and generate the forecast. If you are capturing only a portion of the data, then your forecast is susceptible to errors and fluctuations.

One of the most common mistakes is to rely on a historical perspective for forecasting and not have adequate reach into the demand side of the business. For this reason, the first step in improving forecast accuracy is to improve the reach of the demand planning process. For most manufactures, this means the demand forecasting process should be extended as far out to the point of sale as practical so that a more complete demand signal can be captured. All stakeholders in the forecasting process should be brought into the demand planning process, including internal sales teams, outside rep firms, distributors and key customers.

In order to avoid overwhelming the process participants with too much data, SKU granularity can be used to focus on specific products using a "key products" program. This is a simple way to get the process participants started. Then, as they get accustomed to the process, you can expand the number of SKUs to eventually capture a complete forecast for all products.

Forecast Cycle Times: An area where companies can greatly benefit and realize immediate and significant ROI is in changing their forecast cycle times. By doing this, manufactures can develop better visibility into changes in the forecast as those changes occur, which enables better exception handling responses. The fact is, companies that develop a forecast and commit to a plan on a quarterly basis risk having too much inventory. So much can change in just one week that a quarterly review and forecast just does not work anymore.

As a matter of practice, most companies are committing to a forecast and plan on a monthly basis. The reason for this is simple: capturing the necessary data, having the requisite meeting, and making the final decision is an arduous process at best. It just takes time to get all of the information together to allow decisions to be made.

However, with new technologies on the market today, companies are able to gather in real time the data that allow them to make decisions based upon events occurring that day versus having to wait a month to consolidate and review the information. Companies that employ technology that allows them to capture the data in a near real-time environment have been able to move their planning and forecasting timing from monthly to weekly. By making this change, enormous ROI can be realized because the data are relevant now versus reviewing data that are already one month old. Experience has shown that companies moving to weekly versus monthly forecasting will realize higher inventory turns, more streamlined and optimized inventory levels, higher customer satisfaction rates and higher margins.

Inventory Management: Improvement in forecast accuracy will have an immediate effect on another process area that requires close measurement — inventory management. Of course, there are many aspects to inventory management, but we're focusing this discussion not only on what is common to most manufacturers but also on what is used to measure the financial health of a company — on-hand inventory and inventory turns.

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Having an accurate demand planning system that everyone trusts will provide the confidence for demand planners and inventory managers to tighten up weeks-on-hand and safety stock requirements for inventory across products. It's essential to put in place an ability to tie current inventory data to the demand forecast data, which means delivering up-to-date backlog and shipment data in-line in the forecast data to enable more accurate forecasting. This also establishes a behavior linkage between forecast and shipments which, as with forecast participation from the field, increases accountability.

The measurement for this area is a reduction of inventory buffers at all points in the supply chain, which in turn shrinks the costs associated with inventory carry and write-offs. By closely measuring inventory performance, you will gain the ability to control critical resource allocation per division and product lead times.

Customer Satisfaction: The final key area of process focus and the value that comes from improving demand planning is customer satisfaction through service levels. In a cascading relationship, forecast accuracy supports better inventory management, which supports better management of lead times, which can make or break a customer relationship.

The measurement areas for customer satisfaction include reducing shortages and stockouts, increasing order fill rates and optimizing supply/demand matching so that the highest priority customers, based on profit, competitive situations or other business relationship drivers, are always maintained at the highest level of customer satisfaction. By touching your customers more often and more closely, and by understanding their demand requirements more accurately, you can build a more meaningful relationship, which ultimately benefits both companies.

Measuring Success and Calculating ROI

Manufacturers that have established measurement metrics in forecast accuracy, inventory management and customer satisfaction have seen significant improvements, based on my company's experience working with a variety of companies on such projects. For example, a $2 billion semiconductor firm focused their demand planning process around key products and extended the reach to include all key stakeholders, while also enabling an informal "on-demand" update capability for their forecasting process. The results included an increase in forecast accuracy by 13 percent, a reduction in inventory days by 25 percent, and an increase in customer satisfaction rates by 33 percent.

Another company, a $2 billion consumer electronics manufacturer, also focused on these areas and drove significant measureable improvements. For their top retail accounts, they were able to increase inventory in-stock, on-time delivery and fill rate all to the high 90th percentile, while revenue growth was up 20 percent during the same period. They also were able to reduce inventory for a key distributor by 59 percent. These inventory management improvements were coupled with increased forecast accuracy of about 20 percent on sell-through and 10 percent on sell-in across all customers.

The final step in the process is to calculate ROI by translating performance metric measurements into dollars based on the economics of your company. Of course, every company has different material costs, different forecast accuracy improvements when translated into the associated revenue/margin impact, and variable costs associated with inventory throughout their extended supply chain. This means that the finance teams at manufacturers need to establish the relationships between process metrics and the company's operating costs.

Inventory carrying costs are typically the most direct areas to measure ROI since, as an asset, they have a material impact on the financial situation of a manufacturing company. For example, if a company were able to achieve a 15 percent improvement in forecast accuracy, this would certainly lead to an immediate reduction of inventory. In a specific case, one manufacturer that my company worked with was able to reduce inventory by $14 million on an annual basis. Since the industry average carry cost for inventory is 6 percent per year (which includes interest on the goods, cost to warehouse, etc.), the cost savings added up to $840,000 annually. Applying savings calculations against the cost of the tools, the internal cost to improve the demand planning process and implementation or consulting services, the hard dollar ROI in this case was over 300 percent in the first year alone. Over a five-year period, of course, the ROI will be much higher.

The other area that is often difficult to measure, but that can provide a substantial ROI, is improvement in customer satisfaction. Getting the product to the customer on time in the right quantities can not only keep the customer happy but may drive additional sales and revenue from that customer simply because you are able to demonstrate that you can deliver on your commitments on time.

Measuring the Success and ROI of Demand Planning

By improving and measuring business process improvements in these key areas, manufacturers can continuously improve their demand planning process. This allows these companies to make more profitable economic decisions while still within the lead time to profit from those decisions. This also means revenue and margin may now be predicted with confidence thanks to a more comprehensive demand planning process. This is critical because bottom line measurement pressure is very high, leading to "misses" that can greatly affect the valuation of the company.