Our Solution

Our technical solution was built on the Microsoft Azure stack. The first stage was to create a suite of procedures using a combination of Python and APIs to automatically import data from the siloed data sources. These sources ranged from emailed spreadsheets to system feeds.

Once this data had been consumed, we automated processes for transforming and loading the data into a structured relational dataset in SQL Server.  The main aim of the processing was to make sure all variables such as product codes, date and time were standardised. We also wanted to make sure that all data was classified and grouped in the same way.  This would ensure the data could be analysed in relation to one another for the first time.

To make the clean data accessible we also built a suite of Power BI and Excel dashboards.  Each dashboard was designed with the specific needs of different groups in mind. We built dedicated dashboards for senior leadership team, individual account teams, product category teams, marketing and finance. 

Our Impact

As a result of our work, all the internal teams can now work from master data that has been processed quickly and consistently. The teams have virtually real-time access to the latest numbers in a format that meets their specific needs.  This results in employees spending more time on their core duties rather than data processing.  Most importantly, the productivity of internal and client meetings has increased significantly.  Specifically, account teams can build better business strategies with their customers and the organisation is able to measure the relative success