SCMA 320 – Exam #2 Topical Coverage**
1. Forecasting
a) What is a forecast? What is the cardinal rule about forecasts? How does a forecast
potentially affect performance? What is good/bad about forecasting? What are
trends/cycles/etc.? What is the effect of random variation?
b) How can the quality of a forecast be measured? What is the difference between the
quality measures? What are the methods used in forecasting? What are the good/bad
things about each method?
c) How do I calculate the different quality measures and forecast methods?
2. Process Analysis
a) Design/analysis tools – what is a flow chart/service blueprint/; how are they used; what
can they tell?
b) Process - what are the relevant terms (e.g., bottleneck, capacity, etc.); how are these items
calculated; how are process measures related to costs? Profits?; how can firms use these
concepts?
c) Process-Flow – what is the relationship between flow rate of a system, capacity, demand,
and supply? How we can change the process to improve the capacity?
3. Quality Management
a) Philosophy – How should quality be defined? What are the core principles of quality
management?
b) Relevant dimensions – What are the main dimensions of quality (product and
service)?
c) Quality effect – How does quality affect organizational performance?
d) How do the concepts discussed by Deming and Six Sigma relate to effective quality
management? What is a Six Sigma Process?
e) Cost of quality – What are the different costs of quality and which type(s) are the best
to focus on for long term success?
f) Why is supplier quality important?
g) Lean systems – What is a lean system? What is waste? What are the seven sources of
production waste? What is Toyota Production System? What is a Kanban and a
Kanban system?
** Note: This is just an outline of the topics that were stressed. By no means is it inclusive of all the topics that could appear on
the exam. In other words, do not limit the scope of your preparation to what is listed on this page.
Exam 2 Equations
Forecast Error = Actual Demand – Forecasted Demand
𝐸𝑡 = 𝐷𝑡 − 𝐹𝑡
Cumulative sum of forecast errors (Bias)
𝐶𝐹𝐸 = ∑ 𝐸𝑡
Average forecast error
𝐸̅ =
𝐶𝐹𝐸
𝑛
Mean Absolute Deviation
𝑀𝐴𝐷 =
∑ | 𝐸𝑡 |
𝑛
Mean Absolute Percent Error
(∑
𝑀𝐴𝑃𝐸 =
| 𝐸𝑡 |
) (100)
𝐷𝑡
𝑛
Simple Moving Average Forecast
𝐹𝑡+1 =
𝑆𝑢𝑚 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑛 𝑑𝑒𝑚𝑎𝑛𝑑𝑠 𝐷𝑡 + 𝐷𝑡−1 + 𝐷𝑡−2 + ⋯ + 𝐷𝑡−𝑛+1
=
𝑛
𝑛
Weighted Moving Average Forecast
Ft+1 = W1D1 + W2D2 + … + WnDt-n+1
Exponential Smoothing Forecast
Ft+1= α(Demand this period) + (1 – α)(Forecast calculated last period)
= 𝛼𝐷𝑡 + (1– 𝛼)𝐹𝑡
Trend Patterns: Using Regression
Y = a + b1X1 + + b2X2 + b3X3 + b4X4+ … + bnXn
a = Intercept of the regression line
bi = slope of regression line, with respect to predictor i
Cycle Time = 1/Capacity
Average Direct Labor Unitization: 𝐷𝐿𝑈
𝑊𝑎𝑔𝑒𝑠
) ∗ 𝑇𝑖𝑚𝑒 ∗ #𝑤𝑜𝑟𝑘𝑒𝑟𝑠
𝐶𝐷𝐿 = 𝑇𝑖𝑚𝑒
(𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦) ∗ 𝑇𝑖𝑚𝑒
(
=
𝑇𝑜𝑡𝑎𝑙 𝐷𝑖𝑟𝑒𝑐𝑡 𝐿𝑎𝑏𝑜𝑟 𝐶𝑜𝑛𝑡𝑒𝑛𝑡
(𝑇𝐷𝐿𝐶)+(∑𝐼𝑑𝑙𝑒 𝑇𝑖𝑚𝑒𝑠)
𝐿𝑎𝑏𝑜𝑟 𝑇𝑖𝑚𝑒 𝑝𝑒𝑟 𝑈𝑛𝑖𝑡
= (𝐶𝑦𝑐𝑙𝑒 𝑇𝑖𝑚𝑒)(# 𝑜𝑓 𝑤𝑜𝑟𝑘𝑒𝑟𝑠)