Guest Post: Smoking– Forecasting and Product Life Cycle

Today’s Guest Post comes from Prof. Howard Weiss, the developer of the Excel OM and POM software that comes free with our text.

Forecasting: For the past 40 years, cigarette smoking has been declining at a rate of 3% to 4%. The
drop can be seen in the figure below and it clearly is following an almost straight line, which makes
forecasting very easy using the trend projection method discussed in Chapter 4.

Some of the more recent decline can be attributed to the introduction of e-cigarettes and vapes. However, smoking is on the rise again during this current pandemic which means that time-series forecasting methods, which rely on past data, would not be very useful for forecasting sales of cigarettes in the foreseeable future.

Product Life Cycle: Below is a figure that displays sales of cigarettes from 1900 to 2015 for 8 different countries on 3 different continents.

What is interesting about the figure is that while smoking started and peaked at different years, for all of
these countries, the pattern is identical for each country to Figure 2.5 in the text, which displays the 4 phases of the life cycle – Introduction, Growth, Maturity, and Decline. It is also interesting to note that the life cycle for cigarettes has been over 100 years.

Classroom Discussion Questions:

  1. Cite another product or service with a life cycle as long as a century.
  2. Do you think you can trust all of the data in the figure?

 

OM in the News: The Company That Makes 11-Month Forecasts

Sorry about that White Christmas, Philadelphia. It’s not looking good; temperatures are going to be at least in the 40s. Looking further ahead and afield: Come March, warm weather will boost shorts sales 28% in Chicago over last year, but the shorts business will be off a cool 15% in Tokyo. Oh, and good news for travelers: Flight delays at Philadelphia International Airport will be down 42% next year, compared with 2019, thanks to considerably less precipitation.

That is all according to  Weather Trends International, a Pennsylvania-based company that sells long-range — as in 11 months in advance — forecasts to retailers and investors, writes The Philadelphia Inquirer (Dec. 9, 2019). Home Depot, Target and Walmart,  JP Morgan, and Coca-Cola have all been customers. Reliable year-ahead forecasts would be invaluable to retailers. “Once merchandise has been put out for the season,” said an exec, “the cake is baked.” (Once a customer purchases an 11-month outlook, by the way, the company doesn’t change or update them).

Weather Trend’s formula is about two-thirds statistical analysis and the rest an analytical blend that includes weather “cycles,” primarily slow-occurring shifts in ocean temperatures and air pressure patterns, including the El Niño/Southern Oscillation and the Pacific Decadal Oscillation–plus 417 trillion bits of data. Temperature forecasts can be calibrated to retail sales: A one-degree difference makes a 15% change in air-conditioner sales and a 7% difference in the sunscreen business. A study by two climatologists concluded that for temperatures, the Weather Trends’ year-a-head forecast outperformed the U.S. Climate Prediction Center’s 3 month forecasts, which are updated monthly, four out of five times.

This is an interesting variation from the 3 types of forecasts (i.e., economic, technological, and demand) that we discuss in Chapter 4.

Classroom discussion questions:
1. Referring to “Forecasting Time Horizons” in your Heizer/Render/Munson text, how do short term forecasts differ from longer ones?

2.  Why is a weather forecast an OM tool?