Having trouble forecasting isn't something new. In fact, it's the single most common problem shared by every company, large or small, in manufacturing and distribution. Though the problem is not new, it often worsens as time goes by. Why? Because of the increasing volatility of markets and the shortening life cycle of products. In addition, as competition grows more aggressive and customers more demanding, the potential impact of inaccurate forecasts becomes more significant.
Are there new solutions to this worsening problem? If you would believe the software community, the answer is yes. The improved solutions are often called "advanced forecasting" systems. How are they advanced? Usually with more complex and sophisticated mathematics and linear programming. Is this a real solution? The answer lies in the reality of the demand patterns of the given company. No matter how sophisticated and mathematically ingenious, the accuracy of future forecasts is inevitably dependent on the historical demand data upon which it is based. If tomorrow will look like yesterday, then it's possible for a mathematical projection to forecast more accurately. But the more tomorrow will differ from yesterday (and isn't this the reality in virtually every market across the world), the less one can rely on inere statistical projections of past history, no matter how sophisticated and ingenious.
What is the real solution? It lies in a deeper and better understanding of the forces that cause the demand to vary and forecasts to be inaccurate. Based on this understanding, it's vital to use both old and new tools in the proper combination to limit the inaccuracy of the forecast.
WHY NO ONE CAN FORECAST "GOOD ENOUGH"
A marketing professional in a public seminar responded to my question that he really didn't want to be responsible for the forecast. When I asked why, he responded that he couldn't do it "good enough." Why did he (and why do virtually all other sales and marketing professionals) feel this way? The major reasons are listed below:
• Uncontrollable forces: What causes demand to vary? Customers, customers' customers, distributors, dealers, competitors, economic forces, regulatory impacts, the weather, market trends, new technologies, etc., etc., etc. The list is virtually endless. Though the average sales and marketing professional tries to keep abreast of all
these situations, in most cases they cannot control them, but only react to them, and often they cannot predict them or anticipate them, but only notice them after they've already affected the demand patterns. Unlike factors that affect how well we can schedule and execute production rates, which are within the control of people within the company, many of these demand factors are very hard to influence or predict.
• Naturally "lumpy" demand patterns: Unfortunately, customers don't buy the same amount of ever}' product they need, every day. Often they don't even do it every week or every month. Why? Inconvenience, cost, and irregular demand patterns from their customers or the ul
timate consumer. Ordering, transportation, receiving,
handling, setup, and manufacturing, and other related
costs trigger lot sizing decisions at every link in the supply chain. For example, though the ultimate consumer of a pharmaceutical may consume in an even pattern, say one or two tablets a day, there is much lot sizing between them and the manufacturer. The consumer may buy a 30-day, 60-day, or even 90-day supply at a time, based on
a doctor's prescription, medical insurance rules, deductibles and prices, etc. Likewise, the pharmacy, distributors, and ultimate manufacturers of the pharmaceutical may also replenish their supplies in inconsistent quantities based on varying demand patterns, marketing promotions, pricing protocols, cash flow considerations, and the response to sales targets and agreements.
To Be Continued
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