Good document to get Pull systems to work

1. Mary Côté, CPIM
H‐1 Using Forecast Performance to Set Safety Stocks
What is Supply Chain Management?
“Supply chain management (SCM) is the process of planning, implementing, and
controlling the operations of the supply chain with the purpose to satisfy customer
requirements as efficiently as possible.” (Anteneh Yilma, Wikipedia.)
It could also be characterized as the correlation and understanding of the departments of
a company. It is being able to know what to do if anything or anyone in the company
does not go according to the plan; it is about knowing which dominos are side by side.
Being a supply chain manager, demand planner, or inventory manager is like having an
ongoing six sigma project, and your purpose is reduce variation in the company’s
business processes.
Why Safety Stock?
To prevent our customers from feeling the effects of the variations in plans, whether it is
a raw material, production, quality, or shipping deviation, companies will carry safety
stock. If safety stock levels are adequately set, although variations in the plan will occur,
the service levels should remain very high.
The role of the supply chain is to determine the correct amount of safety stock to service
customers, keeping in mind that too little could risk shortages and too much will
increase warehouse and carrying costs, which will lead to reduced profitability.
Based on sales forecast variability, different market segments require different levels of
safety stock. The less predictable a segment’s sales pattern is, the more safety stock you
should carry to be able to sustain your service levels. Generally speaking, the larger the
sales level is, the lower the sales volatility will be. Per the illustration below, when
throwing the arrow, you are much more likely to miss Object #1 than you are to miss
Object #2, assuming similar circumstances.
Object # 1 Object # 2
2007 APICS International Conference Proceedings, © 2007 APICS

2. Using Forecast Performance to Set Safety Stocks
The easier an item is to forecast, the need for a company to hold safety stock decreases.
As companies enhance their planning efficiencies in hopes of reducing costs and
increasing return on investment (ROI), they frequently look at automating most
repetitive and/or highly mathematical planning processes. Companies are tempted to
implement small changes, such as a more reactive safety stock target, that are also less
time consuming for the inventory planner. Originally, several companies would have a
set safety stock target in units. To increase the target’s correlation with the actual sales
forecast volume for that period, companies are regularly persuaded to change their
target based on their equivalence in days of forecast (DOF). Concept shows that as the
forecast is changed during the period based on new sales information, the safety stock
target would also change accordingly without any manual intervention.
For example, if an item has a forecast of 1,000 units per 30‐day‐period, and the safety
stock target for that item in a particular location is set to 10 days, the target would be set
to 333 units (1,000/30 x 10). As the forecast is adjusted to 1,500 for the same period, the
target would then automatically be increased to 500 units (1,500/30 x 10). The concept is
simple, fast, and very reactive to forecast changing with minimal manual intervention.
However, there are some drawbacks.
Highly Intermittent Sales
In some market segments such as a smaller scale of export sales, sales can be
significantly intermittent. Considerable transportation costs often lead to sizable
shipments, which then lead to more sporadic orders. As Table 1 shows, a forecast may
very well include some null forecast quantities. Consequently, the safety stock target
based on DOF would also generate a target of zero.
In reality, it is at the time when the forecast is zero and the sales are expected to be null
that the company requires the most safety stock. If the company’s forecast turns out to
be inaccurate and sales orders actually come in, the company would then be required to
dip into safety stock. In this particular scenario, the company risks not having safety
stocks and shorting the customers. If a planner had to choose between having safety
stock on‐hand either when forecast is null or when forecast is there, the planner should
choose to hold inventory during null periods of an intermittent sales item to avoid
having to once again “fight fires.”
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2007 APICS International Conference Proceedings, © 2007 APICS

3. Using Forecast Performance to Set Safety Stocks
Forecast per period SS Target
2,500
2,000
1,500
Units
1,000
500
-
1 2 3 4 5 6
Time
1 2 3 4 5 6
Forecast per period 1,500 ‐ ‐ 1,500 ‐ 2,000
Target in days 15 15 15 15 15 15
SS Target 750 ‐ ‐ 750 ‐ 1,000
* based on 30‐day period
Table 1.
Promotional Activity
The area of forecasting in which companies continuously struggle with accuracy is with
promotions. With limited historical information on promotional types, lifts, and
competitive information, promotional forecast are often the greater source of inaccuracy.
To prevent shortages, companies will set the promotional volume to decidedly
optimistic levels. Consequently, if a promotional forecast is potentially overstated, the
target will also be grossly exaggerated in the event that a safety stock target is set based
on the forecast (including promotional activity).
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2007 APICS International Conference Proceedings, © 2007 APICS

4. Using Forecast Performance to Set Safety Stocks
Forecast per period SS Target
5,000
4,500
4,000
3,500
3,000
Units
2,500
2,000
1,500
1,000
500
-
1 2 3 4 5 6
Time
1 2 3 4 5 6
Forecast per period 1,000 1,200 800 4,500 800 1,200
Target in days 15 15 15 15 15 15
SS Target 500 600 400 2,250 400 600
* based on 30‐day period
Table 2.
If a company continues to overstate promotions by fear of shorting customers, an
ongoing outcome would be excess inventory, aging, and incurring warehousing cost.
Having a target based on DOF will most likely further increase the quantity of excess
inventory and add to the cost of the promotional activity.
Likewise, manufacturing companies collaborating with customers on promotional
activity planning are at the end of the chain. Consequently, the forecast and safety stock
target at the manufacturer’s level may be high, and it may also be that the recipient of
information was already slightly overstated by the retailer, customer, and distributor
(bullwhip effect).
Conclusion
The use of setting an automated process for safety stock targets clearly has its benefits.
The use of a target based on the fluctuation of a normal forecast also most likely
outweighs the drawbacks. When an item is in the growth or decline stage of its life cycle,
a DOF safety stock target will set a very reactive and extremely beneficial level of
inventory. However, it is important to understand that this highly reactive method may
create a new type of anomaly for which the inventory planners need to be ready. A
hybrid method where the items most likely to be exceptions would be set with a fixed
quantity target and the rest of them based on DOF will reap the most efficiencies, and
consequently the most profit, for the company.
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2007 APICS International Conference Proceedings, © 2007 APICS

5. Using Forecast Performance to Set Safety Stocks
About the Author
Mary Cote, CPIM, worked for seven years as the supply chain planning manager for a
frozen potato product manufacturer. She managed the forecasting, inventory planning,
and master scheduling of three plants. She is currently a business consultant with
Deltaware Systems, Inc. Cote is a frequent speaker at forecasting events around the
world. She has a degree in business, with a major in accounting, from Dalhousie
University in Halifax, Nova Scotia, Canada.
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2007 APICS International Conference Proceedings, © 2007 APICS