Case study: Retail
The client is one of the largest networks of electronics and household appliances stores, which has been successfully operating in the market for over 25 years.
The client approached us to solve a number of problems:
Financial data was spread across multiple non synchronised systems and a particular indicator was calculated using the data convenient to a particular manager to demonstrate performance of the department.
All analytical reports were generated in the system supported by 3rd party vendor without documentation. It did not allow company specialists to manage data sources and formulas without formal change requests to the vendor which caused delays and additional costs.
As a result, this misled senior management about an objective picture of the company's key business parameters. Our task was to develop a comprehensive solution that would include:
At start we engaged our senior financial consultant to elaborate a unified set of key financial indicators. During the business consulting phase he discovered the existing reporting system and business demands.
To ensure mutual understanding, we developed a glossary, defining all the concepts and terms used in the reports.
Then we performed a formalisation and specifiction of the parameters: each one got a ‘passport’, namely: how it should be calculated, what data should be used for its calculation, and how to interpret the results. Finally our team created a comprehensive "Scorecard tree" which incorporated 200 input parameters. We have created passports for 65 of these parameters and have collected and calculated data for 50 of them. Additionally, we have successfully integrated 15 primary systems into a single information space.
During the implementation of the IT solution, we set up a data warehouse based on the open-source software Greenplum, which also allowed the client to replace previously used proprietary applications and reduced costs of licenses. We also discovered a vendor lock in the existing BI system and were able to eliminate significant data discrepancies, which helped the client reduce material losses.
The final results
As a result of the team's work:
Project implementation period: 9 months.
Currently, we are providing technical support for the solution.