August 1997, Volume 3, No. 8 How to Improve Service with Better Forecasting

Faced with the reality that sales forecasts are frequently wide of the mark, some manufacturers respond by building up inventories to meet any possible contingency &endash; but at a high cost. Those companies following this "Overstock Everything" approach are paying too much for this level of preparedness and, worse, the customer service they are trying to achieve will likely not be met. Other companies respond by trying to forecast future demand, but because their forecasting tools are inadequate, they wind up with an unbalanced inventory, which can be just as expensive in terms of high investment and low service. This is the "Crystal Ball" approach. However, these companies usually find themselves saddled with inventory excesses in finished goods as well as raw materials and work-in-process. When it comes to forecasting products with many possible options and then developing a master production schedule, "There's no such thing as completing 99% of a product for a customer's order, simply because you have 99 of the 100 parts needed to assemble and ship," observed Mike Donovan, president of R. Michael Donovan & Co. (Natick, Mass.), a management consulting firm. Stock-outs from poor inventory planning and deployment lead to frantic calls to suppliers, while work-in-process queues build up, cycle time increases and customer service goes down. Production is thrown into turmoil and attempts to solve the problem are usually more expediting instead of doing the needed business process redesign. As the expediting activity level increases, profit margins start shrinking as the company's overhead and variable costs increase. Worse, when the expedited material finally arrives and the delivery promised to the customer has already been missed, the situation can prompt customers to jump ship and order from a supplier with the consistent capability for short cycle, on-time deliveries. There are substantial, and often hidden, costs to manufacturers who rely on flawed sales forecasts and poor inventory deployment strategies. "If the company's fill rate is, say, 90%, that means 10% is left unfilled on the first pass," Donovan explained. "This condition will reduce revenue in most industries a lot more than management may realize. The revenue is lost on the orders you didn't fill, but a very important consideration is the lost revenue on future orders that go to a more reliable competitor for them to fill." Manufacturers with more complex products, especially with many different options, usually have the greatest difficulty forecasting demand for optimum inventory deployment and plant scheduling. Because of this difficulty, some build very sizable inventory excesses in an attempt to insure against a stock out that could prevent a late shipment. "Some will say that they don't bother with forecasting because demand in their business is too unpredictable," Donovan said. "The fact is that any company with inventory on hand in anticipation of customer orders is forecasting. In many cases, though, the forecasting is being done in the wrong way by the wrong people." Effective forecasting tools exist, and they can help manufacturers achieve lean and well-balanced inventory deployment - with materials and components going through production based on much better projections of customer orders rather than "just in case" contingencies and other guesstimates. There are some very good sales forecasting and finished goods inventory deployment tools and techniques available to help manufacturers effectively work out their inventory planning and plant scheduling, including the capability for making fast adjustments in near real time as order patterns change. Reducing Unpredictability Is the Key The quality of the numbers at the front end of the process is important for successful finished goods deployment. According to Donovan, the real issue is to reduce unpredictability &endash; rather than trying to get a perfect number. The mathematical techniques for dealing with predictability and variation have been around for decades, yet have been ignored by many manufacturers. The same logic used in statistical process control (SPC) can be very helpful in monitoring the sales forecasting and inventory deployment planning process. It's important to understand the probable range in variation of a forecast extending out over a period of weeks or months. Since variation often increases as the time span for a sales forecast lengthens, manufacturers need much less inventory when they are able to cut their order-to-delivery cycle time and have higher velocity throughput. For materials with short cycle times, customer demand can drive material and parts requirements, but as soon as the cycle times to acquire and manufacture products exceed the lead times quote to customers you must forecast. Manufacturers should develop a good forecasting process so they have good numbers driving the front end of their planning system. Getting cycle time reduced is key to developing better forecast quality and eliminating the need for excessive inventory buffers. This will require substantial work on business process issues and improving flow and balance throughout the order-to-delivery cycle. A well-implemented modern enterprise resource planning (ERP) system can be valuable in delivering high quality information to exactly where it is needed at the time it is needed for planning and execution. For example, most manufacturers can compress a 40-day cycle down to 10 days or less, which can result in on-time delivery predictability of 98% or better to the day. Oftentimes sales revenue starts to increase, thanks to the customer service improvement, and operating margins improve dramatically with more volume to cover fixed costs in addition to lower operating expenses. "Actually, there's a double payoff," Donovan said, "and this is the avoidance of the highest potential cost of poor sales forecasting and inventory deployment, which companies should never lose sight of, and that is customer retention. That can mean dramatic savings in the company's selling expense used to appease and retain current customers. Also, this can result in increased revenue from new customers because of improved sales force productivity." Donovan recalled the case of a midwestern manufacturer that had been relying on seat-of-the-pants forecasting and inventory deployment methods in a production environment with 10,000 inventory items sold from stock. "Initial refinements in their forecasting, inventory deployment and master scheduling began to improve balance and flow in the supply chain. As a result, the company's fill rate rose from 80% to 92% rather quickly. After 12 months, this company was at a 96% service level with inventory levels down by 30%. With more work, they will get their service level to 99%+ and have overall lead-times reduced by 80% with a significant reduction in inventories as a fringe benefit," Donovan said. When it comes to cycle time reduction, the first 50% reduction in cycle time is usually easy to achieve, Donovan observed. The next 50% is harder, but driving cycle time down to the bare minimum with further process improvements is well worth the payoff in service, customer retention, lower operating expense and reduced inventories. The most successful companies manage to effectively combine a number of best practices methods, including using appropriate forecasting and inventory deployment methods, realistic information systems, cross-functional integration, and the elimination of wasteful and error-prone business processes. Avoid Patchwork Companies that tend to do a little of this and a little of that in trying to improve operating performance can never quite pull it all together to achieve what they really need. It's essential to first work out the issues of how best to redesign your supply chain as well as other key business processes that tie in with production. A low-risk strategy for near-term results, while waiting for the supply chain to be redesigned, is to initiate a short-term sales forecasting and inventory deployment process improvement effort as a first step or concurrent with supply chain redesign. The benefits in customer service and overall operating performance can be very compelling.

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