Limitation & Future Directions

The most significant limitation of this research is the representativeness of the

coefficients. Although they show economic sense when explained, few of them actually show

statistic significance due to the constraint of limited observations. Therefore, one should be

careful when interpreting the size, relative scale of and . Instead using the model in this

research for future forecast, it would be safer to say that these models are examples of how

client features could be included and help the forecasting quality of the company.

On the other hand, the data of this research is collected from an existing company

which has yet to adjust their forecasting system to account for the different customer attribute.

Nor do they have very solid idea what are the crucial variables with highest explanatory power.

Therefore, when many of the variables contained in the original data do not show high

correlation with sales, there might be a great deal of other variables with the same relevancy

being left out. This is also a common mis-practice in firms adopting customer database where

database failed to collect the most relevant information and responsible personnel could not

produce optimal results without these crucial information and sometimes might even have to

compromise with currently available variables with small explanatory power. In the future, if

information about customer attributes can be further expanded to cover other aspects that might

also be relevant in explaining sales variation in individual account, forecast results should be

improved. For companies wish to implement this forecasting mechanism, this model

misspecification problem resulted from the gap between the forecast practitioners and

information collector should be eliminated. It would be more effective to have thorough

communication between the sales force composite responsible for collecting client information

and the intelligence department who actually do the final modeling. Understanding from each

party could assure the company with higher chance of collecting the “right” information that

would eventually contribute to better forecasting results.

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