Company top management had a need for reporting and BI system for each of its divisions (new car sales, used car sales, service) with the ability to get detailed info per each brand (car manufacturer). Such system would allow transparency and quality of management decisions.

First phase was about building unified data model and automating creation of 7 financial reports. Total scope of work including various views and details was about 20 different forms. Development of those reports required integration of data from internal accountant databases.

Second phase was about moving all reports to new system based on internal SharePoint portal (free Foundation edition) and training finance department specialists in building their own complex reports with different slicing and data depth.

Third phase was about configuration of sales and costs forecasting and analysis tools and building tools for plan and actual analysis for past periods.

Pilot project achieved the following goals:

• Development of data model for the following areas: finance, sales, including data per division and per brand, HR (payroll)
• Connecting of the following data sources: 1C Accounting, 1C HR, internal sales databases for each brand division
• Development of unified procedures and business rules for data integration and aggregation
• Automation of document creation – periodical and on user request reporting and BI generation
• Implementation of costs forecasting module

Pilot module (its user layer) was developed as a component of SharePoint portal. However, technical implementation is platform-independent and this module can work as standalone Web application.

Project results are as follows:

• Development of 4 key analytical reports and 15 supporting forms with different data slicing and depth. These reports were put into pilot production;
• Before reports were generated once in a month at a certain date. Now company management has an analytical tool which is accessible on-line and allows building analytics for any data with any data slicing and depth (based on defined data model);
• Development of forecasting analytical tools for sales and costs of service;
• Time saving for report generation of about 80 man-hours of employees per month