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906D06 WILKINS, A ZURN COMPANY: DEMAND FORECASTING
Professors Carol Prahinski and Eric O. Oln prepared this ca solely to provide material for class discussion.
The authors do not intend to illustrate either effective or ineffective handling of a managerial situation. The
authors may have disguid certain names and other identifying information to protect confidentiality.
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Copyright © 2005, Ivey Management Services Version: (A) 2006-09-13
On Monday, January 10, 2005, as Bernie Barge, the newly promoted inventory manager at the Wilkins plant in Paso Robles, California, prepared for the forecasting meeting scheduled for the following day, he wondered if he could find
an easier and possibly more reliable means of forecasting the sales demand.
BACKGROUND
Wilkins Regulator Company had built its strength on high-quality products for the plumbing, municipal waterworks, fire production and irrigation customer markets,
ranging from water pressure reducing valves and backflow preventers to anti-scald
国际学校有哪些shower valves. The general plumbing customer market reprented approximately
half of its sales revenue and the irrigation customer market reprented approximately a quarter of its sales revenue. Chris Connors, the plant’s general manager and Barge’s supervisor, had targeted the fire protection and municipal waterworks customers as opportunities for growth.四级成绩什么时候出
Zurn Industries acquired Wilkins in 1971. In 1998, Zurn merged with U.S. Industries Bath & Plumbing Products Co., and changed its name to Jacuzzi Brands
in 2003. From the most recent Jacuzzi Brands 2004 Annual Report, Barge read: Demand for our products is primarily driven by new home starts,
remodeling and construction activity. Accordingly, many external
factors affect our business including weather and the impact of the
broader economy on our end markets. Weather is an important
variable for us as it significantly impacts construction. Spring and
summer months in the U.S. and Europe reprent the main
construction ason for . . . commercial and industrial markets. As
a result, sales in our bath products and plumbing products gments
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increa significantly in our third and fourth fiscal quarters as
compared to the first two quarters of our fiscal year. The autumn
and winter months generally impede construction and installation
activity.
Our plumbing products business is dependent upon commercial and
institutional construction activities and is, therefore, affected by
macroeconomic factors, such as the unemployment rate and the
availability of financing. Despite the cyclical nature of the U.S.
commercial and institutional construction market, which
experienced declines in revenue of approximately 14 per cent in
fiscal 2002, approximately six per cent in fiscal 2003 and a slight
rebound in fiscal 2004, sales of our commercial and institutional
products have continued to grow at a rate that exceeds that of the
industry. We have achieved this growth through favorable pricing,
product innovation and targeted marketing programs.
Connors provided Barge with additional insight into the complexities involved in forecasting demand:shorter
There are lots of uncontrollables. Uncontrollables included the
weather, competitors’ product introductions and our own product
introduction. Sometimes, we cannibalize our own sales —
intentionally — and, sometimes, unintentionally. Other influences
on the demand include marketing strategies, such as price
promotions and, in the irrigation market gment, an early-buy
program that encourages customers to place their orders in the early
spring.
CURRENT FORECASTING PROCESS: THE FORECAST MASTER
Each quarter, Connors and Rick Fields, the sales/marketing manager, developed the quarterly demand forecasts for each product family. Barge, in his newly created position, would also participate in the forecast development. Bad on their knowledge of industry trends, competitive strategies and sales history, they would estimate the sales for the next five or six quarters. Barge commented: Rather than forecast the total quarterly sales volume for a product
family, we forecast the average anticipated sales per week for the
quarter for each product family. We have about 25 different
product families and each product family has what we call a
planning bill. To start the process, however, we start with what we
call the forecast master. The forecast master is a spreadsheet that
lists the average weekly sales history for each product family by
quarter and year since 1999. For each product family, we divide
the total quarter’s actual sales by 13 weeks per quarter to determine
the average weekly sales per quarter. Then, we plug in our
expected demand for the next five or six quarters. The numbers
reprent our best estimate. This information is then ud to
calculate the average dollars per unit and average gross profit per
quanlideyouxiunit, which is ud by our accounting and finance group to develop
various budgets.
A portion of last quarter’s forecast master is shown in Exhibit 1 for two product families: Pressure Vacuum Breakers (PVBs) and Fire Valves. PVBs were a type of backflow prevention device, which was designed to prevent the rever flow of water and other substances into the water source. PVBs were ud predominantly by the irrigation market gment.
Fire valves, a type of pressure reducing valve, were designed to reduce or regulate water pressure in residential, commercial and industrial applications. In addition to having just signed on a new customer, Connors anticipated high growth in the fire valve market since Wilkins was introducing a n
2012年12月1日umber of new product extensions designed to increa market share. One such product extension was the development of fixed-tting fire valves. Wilkins’ current fire valves had adjustable ttings, which were t by the installer. Some regulatory agencies, however, were concerned about improper installation or modification to the valves and were now requiring fixed tting valves to improve safety.
CURRENT FORECASTING PROCESS: THE PLANNING BILL
Each product family had its own planning bill. Barge described the planning bill: There are five important components to each planning bill. First,
the planning bill contains the sales history for each product within
the family. We have quarterly sales history that goes back to 1989.
If I dig into the old files, I can go back even further. Second, for
the last four quarters, the planning bill calculates the average
number of units sold within that product family each day withinbytheway
each quarter. For example, for our first fiscal quarter of 2005,
which started on October 1, 2004, we sold 48,159 units within the
PVB product family [as shown in Exhibit 2]. Since the quarter had
58 days, the planning bill will calculate that we sold a daily average
of 830 units. We will also calculate the average daily sales for the
last four quarters; for the PVBs, it was 1,205.
Third, the planning bill contains our projection on the average daily
sales for that family that we think we will ll in the next 12
months. This number came from the forecast master and is one of
the key determinants of the forecast by product. With the PVB
product family, for example, we think our sales will have a
大学四六级报名官网moderate growth rate predominantly due to industry growth and
some problems at one of our competitor’s manufacturing facilities.
Last quarter, we forecasted that we would ll an average of 1,400
units each business day in the next 12 months [as shown in the far
教育部雅思考试官网right column of Exhibit 3].
Fourth, we disaggregate the family forecast into each product bad
on the per cent of sales of the product family. To do this, we first
calculate the proportion of unit sales that each product currently
reprents within the family. We call this the “raw per cent.”
Then, we try to forecast the percent of family sales that the product
will reprent in the future, which we call the “planning bill per
cent.” It can get pretty complicated. If we have new products, we
have to factor in the effect that they may have on our existing
products. Plus, with new products, we also have to project growth
without any historical data.
The fifth key piece of information in the planning bill is the
calculation of the annual sales forecast for each product within the
family. We u a couple of key pieces of information: The
planning bill per cent is multiplied by 250 days in a year and by the
daily sales forecast for the family, which are 1,400 units in this
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situation.
The sales history for a lect group of products is shown in Exhibit 2. The planning bills for the PVB
s and fire valves, as of October 2004, which was the beginning of the 2005 fiscal year, are shown in Exhibit 3 and 4, respectively. FORECASTING PERFORMANCE
When contemplating the forecast accuracy, Barge said, “I don’t have a clue on how well we have been doing. I think we are doing OK at the aggregate level, but we probably have some swings in our accuracy level at the individual product level.” For the first quarter of 2005, Connors and Fields had forecasting sales of 53,560 PVB units and 559 five valve units. According to Exhibit 2, actual sales were 48,159 PVB units and 580 fire valve units.
IMPLEMENTATION CONCERNS
Barge wondered if he could u statistical forecasting methods to ea the forecasting process and perhaps improve the reliability of the sales forecast. If Barge was going to recommend a new forecasting method, he considered how he should gain buy-in from Connors and other managers at the plant. He knew that Connors considered it important to u judgment in developing the sales forecast. For example, if Connors believed that the industry was entering a mild recession, he wanted to make sure the demand forecast reflected the anticipated economic downturn.
Barge also wondered how to incorporate the occasional price promotions that were ud to ll off e
xcessive finished goods inventory. He knew that if management reduced the price, Wilkins was going to ll more units and be more competitive. Barge frequently joked that the fire valves were leading economic indicators. Although he said it jokingly, he wondered if there was some truth in it. Since the product was ud in new construction, an increa in product sales would indicate that the construction industry was in an upswing. To help determine the demand forecasts, he wondered if he could u the United States economic information, such as the unemployment rate data (e Exhibit 5), the bank prime loan rates (e Exhibit 6) or the number of new housing starts (e Exhibit 7). Barge knew that less than one per cent of the PVB sales were outside the United States and he didn’t remember any fire valves having been sold outside of the United States. Finally, he wondered how to forecast new products, such as the new fixed-pressure fire valves. Although he could u the historical sales of the adjustable-pressure fire valves, both he and Connors believed that the new fixed-pressure valves would have dramatic growth, which Barge did not think could be captured by the historical sales data of the older products.
As Barge reflected on his preparation for tomorrow’s meeting, he wondered what he should recommend to Connors and how to address any potential implementation concerns.
