BUT: a need for innovative tools to analyze its KPIs

But is a french retailer specializing in home goods, including furniture, large and small appliances, and consumer electronics. They operate more than 300 stores in France.

Challenges

To better leverage their data , But wanted to have innovative tools to analyze key sales performance indicators with more depth. The organization was facing several challenges:

Évolution du Système d'Information :
Complexité à Surmonter

Their data architecture was complex, with data scattered across several systems. Some pieces of data were hosted by commercial partners operating on their marketplace, which was making quick access to this data complex for But.

Urgent action and limited skills:
Meeting business needs

But’s operations teams couldn’t allocate the time necessary to best answer the various business needs emerging from the organization.

Furthermore, they lacked skills in data science and data engineering, which prevented them from addressing all the projects they wanted.

Artisanal Approach :
Data Access Complexities

Initiatives launched by data teams were often using a handcrafted approach, which was caused both by difficult access to data and inadequate tools.

Solutions

But adopted Saagie’s DataOps Platform to address their data use cases and analyze commercial performance.

Methodical IS improvement:
Accessible Data Lake

Constitution of a single data foundation to centralize all their data inside a data lake, some of which were hard to access up until now.

Personalized coaching:
Rapid development of business value

But’s business teams are supported by Saagie’s Professional Services teams to develop business value quickly and enable the group to develop internal skills on data technologies and best practices.

Methodical, orderly construction:
successive stages of expansion

Validation of Saagie’s technical solution and project methodologies through a first use case of data centralization before broadening the scope of the partnership with the adoption of new projects based on Business Intelligence and predictive analysis.

You want to go into production and launch your data projects?