Page 11 - CIMA OCS Workbook February 2019 - Day 2 Suggested Solutions

SUGGESTED SOLUTIONS

Conclusion

In order to choose the most suitable approach to capacity planning a number of issues would
need further analysis.

1. The choice of capacity planning technique depends on how accurately Trigg Adventure can
forecast its sales and how far ahead these forecasts can be made. This may require investment in
suitable systems. If we are successful in pulling together relatively accurate forecasts then chase
demand planning would work well. It would mean some changes though, for example, staff may
be required to work additional shifts or short-term rentals may be required for equipment.

2. Equally the choice of approach depends on the variability of demand and whilst it is clear that
there is some variability further research would be needed.

It is therefore difficult to recommend at this stage which method is appropriate but as a potential
solution to the high inventory, it merits further investigation.

Forecasting demand

Being able to forecast demand is very important to a business such as ours, as it is so changeable
throughout the year. It helps when matching production with demand (chase demand plan) as
well as assisting in workforce scheduling and production planning. In addition, it helps us with
decision making and control.

There are two broad techniques for demand forecasting: expert opinions and surveys whereby
information is gathered on the likely purchase behaviour of the buyer and also statistical
techniques which use past demand as a guide to the future.

In terms of the expert opinions and surveys, one technique would be for us to conduct an expert
opinion poll. Outdoor play equipment experts would be asked to give their opinion about likely
demand for our range of products in future periods. This can be very subjective and experts may
have a range of opinions.

Alternatively, we could use the Delphi technique which is a variation on the expert opinion poll. A
group of experts would be questioned repeatedly until the responses are the same/ similar.

Participants are supplied with responses to previous questions and such feedback may result in
the expert revising their opinion. In addition to these expert opinions we could make use of
customer surveys. Customers would be surveyed in order to ascertain their demand in the future
period. All customers may be surveyed or a sample taken (less costly but also less accurate).

I also mentioned statistical techniques to help forecast demand. Time series analysis would be
one suggestion. Past data would be analysed to determine the trend in demand and any seasonal
variations. This information can then be used to predict future demand. To provide an indication
of trends in demand, an idea would be to look to competitor data. How useful this exercise is will
depend on the availability of competitor data.

Another suggestion would be regression analysis whereby a graph would be plotted of past
demand against time and the line of best fit is found. This is then used to predict demand in
future periods. This would only really be effective if there is a strong correlation between
demand and time.

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