An overseas car manufacturer had an order from a government agency of a European country about 1000 cars with very peculiar equipment (at least for this type of car):

• manual gearbox
• white
• no air conditioning
• with 4 doors

Under adverse conditions this deal could not be closed, but the cars had already been produced…

These cars had been assigned to the German market with the task to merchandise them quickly. To manage this a lot of work and many concessions from the dealers were necessary.

In the reporting this process certainly led to some statistical inferences:

• These types of cars are sought after in white and with 4 doors.
• German cars don’t seem to need air conditioning.
• etc.

The persons getting these reports do not know all commercial transactions and have to rely on the data they have.

In every quarter the customer gets bonuses, if he reaches a certain target.

This target is measured by means of invoices and possible credit notes.

Now it can happen that by accident an invoice is not made out before the reporting date, what would lead to the fact that the customer had not reached the bonus.

Nevertheless, the bonus will certainly be granted to the customer.

How is this now displayed in BI?

Sales’ point of view, accountings’ point of view, customer’s point of view?

In the course of a reorganization the company decides to newly assign the areas of the sales staff.

So customers are shifted from area A to area B, from C to A etc.

When considering the development of the sales staff within the last years, what is the reporting supposed to provide:

• Consider the area on the basis of the restructuring?
• Or according to the customers that have been in this area at the time of the respective year?

What will the sales staff claim?
Those who lose a good customer, want to consider the sales figures as before the restructuring, the others will more likely be silent :-)

A dashboard indicating succintly the development of the customers’ sales figures showed unusual decreases for several customers.

This was justified by the fact that a top-selling product could not be delivered and therefore many customers canceled the order already placed. But nobody could actually see or explain this.

• How can one find out for which customers the decreases can be interpreted that way?
• How can these reasons be explained?

A classification figure that very often is missing in BI solutions concerning sales is the recording of the orders placed.

In this case that would have led to much more clarity and would have better identified the customers that actually reported decreasing sales.