The Role Of Automation in Retailing Business

One of the problems that many companies face is whether to use a single metric system or use a combination of systems when developing and maintaining a metric system for a metric application. Many companies have made the decision to use a single metric system, such as STATA, to be used throughout their operations. Others have chosen to use a combination of systems, such as the U.S. dollar indicator (USDI) or multi-metric product indicators (MMI). Still others use a combination of both, particularly when dealing with financial data and financial services data. Regardless of which metric system a company chooses to use, however, it is important that all employees, management, and customers are trained how to use this new system and that all metric applications are documented accordingly.

One way that companies can teach employees how to use the fact measure in a data cube is to have each person to perform the task on his or her own and then compare the results of their calculations against the spreadsheet that the metric system provides. This approach allows a company to train its employees on the basics of converting the raw data into a meaningful, standardized measurement. Companies can also use the spreadsheet to compare their employee’s results against those of other employees, to identify patterns that may be of interest to management, and to develop and implement appropriate training strategies.

• The fact measure in a data cube is an excellent training tool because it enables one employee to quickly and accurately perform a wide variety of tasks related to the business.
• Since the data cubes are standardized, there is no need to develop different systems for employees who perform very different tasks.
• The fact measures can be used to analyze any data set, regardless of its format and the number of factors involved.
• Another great advantage of using a fact measure in a data cube is that it assists managers in their decision making process.
• A manager must consider many things before making any decision.
• One of these is whether or not the investment will create a significant return on investment (ROI).
• Using a standardized data cube, managers can easily determine if the investment will be worthwhile, and if so, how much should be invested in order to get the greatest ROI.

How does a fact measure in a data cube help a manager to make an effective decision?

First, all factors must be equal to create a meaningful result. If one factor is greater than the others, then the result will also be negative. For instance, a purchase of fifty cents on a particular product represents one fact, while a purchase of one and a half cents represents another fact. Therefore, a purchase of fifty cents versus a purchase of two cents will always result in a negative fact. However, a fact measure can be calculated by adding up the individual values of each fact to calculate a single overall positive fact.

The truth about a fact measure in a data cube used at a retail chain business is that it is only helpful when it is the sole determining factor used to make a decision. For instance, if a customer enters the store and sees only one item, he/she may assume that all items are the same. Therefore, he/she will spend only half as much as she would if all items displayed were the same as well. By using a standard fact measure in a data cube, all items in the cube will then be factored in. Once the results come out, the manager will have a single statistic to work with, thus giving him/her the ability to make a more informed decision regarding the investment he/she is making in his/her business.