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OM4 C11 IM
14.* Two experienced managers at Wilson Boat, Inc. are resisting the introduction of a
computerized exponential smoothing system, claiming that their judgmental forecasts
are much better than any computer could do. Their past record of predictions is as
follows (these data can also be found on the worksheet C11P14 in the OM4 Data
Workbook):
Week Actual Demand Manager’s Forecast
1 4,000 4,500
2 4,200 5,000
a. How would the manager’s forecast compare to a single exponential smoothing
forecast using = 0.4?
Manager’s forecast:
Exponential smoothing:
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OM4 C11 IM
b. Based on whatever calculations you think appropriate, are the manager’s
judgmental forecasts performing satisfactory?
With experimentation, you will find that the MSE for the manager’s forecast is
better than any exponential smoothing forecast (see the table below). Thus, you
can conclude that the manager’s forecast is rather good.
Alpha MSE
0.1 637725.2747
0.2 592564.5051
c. What other criteria should be used to select a forecasting method for this
company?
Students might consider issues such as how much time or other information must be
15. Research and write a short paper (2 pages maximum) that summarizes the capabilities
of commercial software available for forecasting. How does such software compare
with using Excel?
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OM4 C11 IM
A Google search reveals 24 million hits on the topic of “forecasting software.” SAS
(www.sas.com) is a popular commercial software that does business analytics and
Case Teaching Note: BankUSA: Forecasting Help Desk Demand by Day
Overview
The case describes a telephone call center (contact center) where 98% of the call volume
is internal customers (i.e., the bank's sales force, trust administrators, branch managers,
wealth advisors, etc.). Accurate and quick answers are expected from the customer
service representatives (CSRs). Staff call center scheduling is critical to maximizing
service and minimizing costs. Of course, the first step is an accurate short-term forecast
of call volume by day. A small sample of call volume data is presented in the case and
the student or student team is ask to determine the best method or methods to forecast
these data. This data can be evaluated using simple graphs, time series, or regression
analysis. Although the focus is forecasting there are several other OM issues.
The four-step demand-capacity-schedule framework is (1) Demand Analysis, (2) Set
Service Standards, (3) Compute Capacity Requirements to Meet Demand (Using
Equation 7.2 or queuing models), and (4) Develop a Resource (Staff) Schedule” and
associated issues. This case focuses only on the forecasting step but you might want to
frame in what happens after a good forecast of demand is generated.
Note: The case data in OM4 is changed from all previous versions of the case.
Case Questions and Brief Answers
1. What are the service management characteristics of the CSR job?
The best way to answer this question is to ask students, especially ones who have
worked in a call center. Make sure students realize when they are interacting with a
Typical CSR job characteristics include: service management skills (i.e., simultaneous
technical (operational), marketing, and human interactions skills), job is electronically
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OM4 C11 IM
2. Define the mission statement and strategy of the Help Desk contact center? Why is
the Help desk important? Who are its customers?
The Help Desk's mission is "to provide accurate and timely resolution of customer
problems and inquires for the bank." The Help Desk is the gateway to problem
3. How would you handle the customer affected by the inaccurate stock price in the
banks trust account system? Passive or pro-active approach? Justify your answer.
Two options exist as follows: (1) If the stock price is in error correct this customers
account statement, call them and apologize, and immediately mail a corrected account
What this real bank actually does is briefly described as follows: Call a Priority 1
meeting with the appropriate systems, product support, retail, and backroom support
After the error is acknowledged and fixed do a root cause analysis and try to fix the
source of the error, if at all possible. Write-up a report summarizing what happened
3. Using the data on Call Volume in the accompanying table, how would you
forecast short-term demand?
Given the OM template your students may do some of the following analysis.
Moving Average Forecasting BankUSA Forct Help Desk
Enter data only in yellow cells. The template is designed for up to 20 observations and k = 2, 3, or 4.
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OM4 C11 IM
Periods in moving average, k (2, 3, or
4) 2
Time Period Observation Forecast Error Error^2
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OM4 C11 IM
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0
100
2 00
300
400
500
600
Moving Average Forecast
Observa tion Foreca st
Time Pe rio d
Exponential Smoothing Forecasting
Enter data only in yellow cells. The template is designed for up to 20 observations.
Smoothing constant 0.3
Time Period
Observatio
n Forecast Error Error^2
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OM4 C11 IM
The simple exponential smoothing model with alpha = 0.3 provides another good forecast
If students use MA and ES methods this is often a good time to briefly discuss Equation
Teaching Plan
(1) What are the service management characteristics of the CSRs job?
(2) Define the mission statement and strategy of the Help Desk contact center? Why is
the Help desk important?
(3) How would you handle the customer affected by the inaccurate stock price in the
banks trust account system? Passive or pro-active approach? Justify.
(4) How would you forecast short-term demand? Method? Approach?
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