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A microbrewery in Colorado is growing rapidly. There is a long lead time for the purchase of new equipment, so management must make a demand forecast for the next couple of years in order to ensure that it has the capacity it needs to continue expansion. There are constraints, however, in particular with respect to access to key inputs. This casts uncertainty on the demand forecasts, such that simple extrapolation of current growth rates is going to be insufficient. A decision tree is used to help with the demand forecasting, taking into account different scenarios with respect to the growth patterns and the growth constraints.
This paper is based on a real world situation. The situation at hand is that of a small microbrewery, operating in Colorado. The microbrewery is five years old and has expanded annually since its inception. The brewery produces five beers regularly, and these are available bottled for the packaged trade and in kegs for the hospitality trade. Several products are produced seasonally and these are only packaged in kegs. The company's sales have now increased to 10,000 barrels annually. The most popular product, the India Pale Ale (IPA), accounts for 50% of total sales by volume. The IPA accounts for roughly 40% of profits, because it has higher ingredient costs than some of the other products. The brewery uses a single brand for its different products, which are extensions of that brand. The IPA, because of its popularity, has been subject to further extensions in the seasonal range.
The signature ingredient of an IPA is hops, which are the flower of a vine. They are relatively difficult to grow, requiring specific conditions. They thrive only at certain latitudes in temperate regions. They are cultivated in all great brewing nations, their presence being a critical requirement for the development of beer-drinking culture in the Middle Ages. New world nations like the United States, New Zealand and Australia have cultivated the hop as well. The hop is relatively delicate, and can be susceptible to disease, in particular if growing conditions are wetter than expected. There are different types of hop, and each strain will produce flowers with different characteristics that impact the character of the end product (the beer).
Most hops used by the microbrewery are domestic varieties, produced in Washington State, with some from Oregon and Idaho as well. Hops available to microbreweries tend to come from a handful of major wholesalers, who source globally. They process the hops, usually into a pelletized form, for longer storage and easier distribution. Only the largest companies, like Anheuser-Busch, are vertically integrated to the point where they produce their own. Thus, almost the entire industry relies on these wholesalers, who dominate the North American trade.
The Operational Problem
The operational problem at hand occurred, when a confluence of factors resulted in a dramatic hop shortage across North America (Morgan, 2013; Welch, 2007). Adverse weather conditions resulted in poor harvests in two sequential years, reducing supply. Moreover, the growing popularity of microbreweries, and the hop-intensive IPA style in particular, resulted in rapidly increasing demand. The conditions of the wholesale industry favored larger breweries, who were locked into long-term contracts with the wholesalers. These breweries were allocated their hop needs. Smaller breweries, like ours, who tended to purchase hops on an ad hoc basis, found that their orders could not be fulfilled. Orders would either be unfilled entirely, or filled on a partial basis.
For the brewery, this represented a significant challenge. It had limited supplies of hops on hand -- for some varieties as little as 2 months' supply. It had growing demand for a flagship product that consumed 65% of total hop usage. With hop prices escalating due to supply issues, and in some cases supply being unavailable at any price, the brewery was faced with a challenge of forecasting. The supply chain disruption was going to require changes at the marketing end. Even if the brewery could maintain IPA production, it might be forced to lower production of other products as it would lack raw materials to make them. Marketing was going to have to reduce dependence on IPA for growth, and that meant new product introductions. However, marketing was also facing a tide of consumer demand that was not going to accept mildly-hopped beer, which for drinkers of microbrews is often equated with blandness.
Worse, the brewery needed to order equipment to facilitate its expanding business. If access to ingredients were not a problem, forecasting future demand would be relatively easy. However, since the brewery needs to order equipment now for delivery anywhere from six months to a year in the future, it needs to have a good quality forecast of sales, including the possibility that it will not be able to produce enough IPA to meet expected demand for that product. Thus, demand forecasting with a number of different scenarios is necessary to give management the insight it needs to make the capacity expansion decision.
Forecasting demand, therefore, had to take into account the trends of past sales growth, the industry trend towards IPA sales growth, and the effects of the marketing department's renewed emphasis on other products. These products would have to be scheduled, based on expected sales and expected availability of the raw material needed to produce them. Further complicating the issue is that the hops shortage constrained supply from other parts of the world, which could not be imported due to global supply shortage. Also, market response to new product introductions is unknown at this time. Forecasting is important not only because of the 2-4-week lead time to produce the beer, but for the 6-month to 1 year lead time for new equipment needed to maintain the brewery's pace of expansion.
Operations Management Principles
There are a number of different operations management principles that can be applied to this case. The most critical is forecasting. The brewery needs a means by which it can estimate future demand, in order to set production schedules. These schedules will determine inventory management as well. The constraints on the availability of raw materials represent a challenge for demand forecasting.
Demand forecasting relies on both qualitative and quantitative information. On the quantitative side, there are a number of techniques that can be used. These include simulation and extrapolation. For example, the company is currently on a growth trajectory and this can be extrapolated into the future. For example, if growth is currently at 25% per year across all brands, and the brands are not expected to change, then next year's demand forecast will simply be this year's production multiplied by 1.25. For the brewery, that is not the case however.
Most forecasting builds in some qualitative information as well. For example, the base forecast is built on current demand levels. To this, projected changes in demand are incorporated. For example, if IPA is expected to continue to be more popular, it will grow faster. The qualitative analysis that shows this type of beer increasing in popularity is then translated into a growth figure that is then added to the forecasting model. Similarly, if the hop shortage is going to constrain IPA production, then that can also be built into the model, where growth of that type of beer is capped, regardless of where the demand might otherwise be.
A decision tree is a technique that is used to help the company analyze the different possibilities. A basic decision tree might factor in, for example, low-growth, normal-growth and high-growth scenarios. The tree would then have three different demand forecasts. These can be weighted by probability as well, to further help the decision-making process. The brewery might then further build out the tree by adding in probabilities for hop availability, or demand probabilities for individual brands. In this case, it is introducing new brands and the differences in success for these can be high, giving wildly different demand forecasts depending on which scenario comes to pass. The decision tree, therefore, allows management to envision different possible futures and make better decisions as the result of this analysis.
Application of OM Concepts
The current production of 10,000 bbls is divided into IPA (50%), Pale Ale (10%), Brown Ale (15%), Porter (10%), Wheat (5%) and seasonal products (10%). Current growth is 25% per year, but IPA is growing at 40% per year, while Wheat is declining. Other products are growing at roughly 25%. This creates a base projection of Brewery Projections
Thus, the requirements for hops for the IPA are going to nearly double in the next two years. However, there is a 25% chance that the hop shortage is going to constrain availability, and thus IPA growth will only be 10% each of the next two years. This gives the following projection:
The average expected growth will…[continue]
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