For sale industry


  • Analysis of implementation of the sales plan
  • Sales cross-statistics
  • Anomalies, budgeting, controlling
  • Indicators
  • What-if analyses?


A person holding the managerial position in the sales industry, when deciding on promotions, sales or orders, should base its decisions on the results of the analyses and the facts, and not on feelings or assumptions. Access to reliable and current information significantly allows for easy and quick implementation of the management tasks. Achieving this information can be very difficult due to several, listed below, reasons.

The larger the managed company is and the more customers and the offered products it has, the more difficult it is to obtain a consistent and transparent view of the whole activity of the company. The company uses different systems to record the various data: one system is to record sales, another one is used to manage contracts with the employees, and another one is to administer invoices and dictionary of contractors and suppliers. The level of complexity can also be increased if the company has some independent facilities located in different places.

The main problem in the process of developing high-quality management information is no data integration. No data integration between the systems means that the terms meaning in fact the same are described and identified differently in different systems. Whereas, the consequence of the above is impossibility to obtain the cross-sectional reports to reach the source of the diagnosed problem.

For example, the manager of the network of 3 traditional shops and 1 on-line shop faces the need to develop a set of analyses, within which inter alia the following will be presented: key factors, profitability of the individual facilities, comparison of the costs generated by the facilities located in different places, results of the promotion and discounts for the selected products etc.

The main challenges of the manager include integration of the data from the IT systems operating in one facility and integration of the data from different facilities. Regarding the level of complexity of the systems and the size of the stored data, this task can be difficult, if not impossible, to execute without the support of the relevant software.



The solution to the problem of integration of that data and thus obtaining a consistent and reliable source of the data for analyses and reports is to build the central repository for the data based on the idea of a data warehouse. In contrast to the database, the data warehouse stores the data so as to meet any reporting request the best and as soon as possible. The data from the field systems are transferred to the data warehouse through the ETL process, which cares about their accuracy, integrity and up-to-datedness. The ETL process can collect the data from any number of sources so that the concept of the data warehouse is not limited to the system or the location.

Integration of data between systems is not an easy task and, regarding the size of the data sets, it certainly cannot be executed manually. Within the works, it is necessary to establish the rules for integration, and often reversely complement the data in the field systems.

However, it is worth to spend time and resources to integrate. The possibility to analyse, on one summary, the data from different systems and even from different location provides, unreachable by integration, possibility to look at the company’s work as a whole, without division into the systems or the locations.


Establishing a central repository of the reporting data (the data warehouse) opens a very wide range of possibilities to develop credible, current and useful information based on the collected data.

The advantages of BI reporting based on the data warehouse are:

  • Possibility of connecting the data from different substantive areas,
  • Possibility of developing the cross-summaries,
  • Possibility of relating the data from the current time periods to the archive data.

The developed analyses should be properly presented, stressing the cases requiring immediate attention. With the development of the reporting system, the number of analyses increase, therefore they are grouped together in the form of the reporting desktops with varying levels of accessibility for the users.

The information presented in the analysis can be visualized in different ways, depending on the needs: table, pivot table, chart, measuring instrument etc. The information can be in one form or many forms. Each analysis can be exported to a spreadsheet to make changes.

For example, the set of the reporting desktops for the sales industry.

Main reporting desktop including the most important numerical indicators as well as charts and measuring instruments presenting the key information.

  • The numerical values of profitability, profit, revenues and costs, number of transactions, and number of customers.
  • Global status of the sales plan.
  • Summary of revenues and costs in a month.
  • Average number of transactions for the last 3 months.
  • The most and the least profitable Cost Centre (CC).
  • Top and down of 5 sold products, CC in terms of profit, customer in terms of revenue.

Efficiency analyses to check, which facilities are effective, and how the facility presents on the background of other selling facilities.

Profitability analyses to check, which facilities are profitable, and how their profitability changed over a year/several years. Comparison of profitability between the facilities.

Statistical analyses of any kind.

  • The most active distribution channels.
  • Employees generating the largest profits, and employees generating the largest number of transactions.
  • Percentage share of voivodeships/cities in sales.
  • Product statistics.

Anomalies analyses to check whether the data collected in the sales system are logically consistent and correct. The results of the analyses can be the basis to control and/or to take remedial actions. Examples of the analyses detecting anomalies:

  • Unprofitable sales, in which the costs exceed the revenue.
  • Too high, unrealistic number of sales transactions in a given period of time executed by the employee.
  • Execution of the sales plans exceed 75% or more.

If, despite having the finished reporting desktops, the operator needs its own analysis, it can create, visualize and save it on its own desktop by itself.

Specialist IT knowledge or programming skills are not required in order to execute these operations.