The client’s Consumer Devices and Services Division had lots of data available. But it was struggling to exploit it commercially. The information including internal systems data, retail partner data and purchased third-party data was taking too long to pull together. There was also a lack of consistent business processes for generating numbers and reports. Teams were wasting time during meetings arguing over which metrics mattered. On top of all that, the client found it difficult matching different data sets because of inconsistent product codes.

Key stakeholders were interviewed and an audit of all the data and information sources was completed. The process allowed us to also identify any gaps in the information and create a strategy to fill them. We identified a need to increase the coverage and consistency of the sell-out data received from retail partners. We advised the client that it needed to stipulate in contracts that this data should always be provided by retail partners on a timely basis.
The next stage was to design and build an AWS based data lake and data warehouse platform to consume all the data coming from internal systems, retail partners and third-party data vendors. This platform needed to process the information in a way that standardised all product correct codes. We bulit business intelligence dashboards and self service reports that could be run off the data warehouse and be customised to the specific needs of different groups within the organisation, such as senior leadership teams, individual account sales teams, product category teams, marketing and finance. In addition, we suggested that the client share a sub set of this processed data in BI dashboards to its retail partners. That way, it could encourage transparency and facilitate more constructive commercial conversations. Finally, we proposed putting in place a small team of dedicated analysts to maintain the solution correctly and continually improve accuracy and consistency.

When the client implemented our proposed strategy, good things started to happen. Soon, all the internal teams were working from master data that was processed quickly and consistently. People had virtually real-time access to the latest numbers in a format that met their specific needs. They also now spent more time on their core duties rather than data processing. Most satisfying of all, we put an end to arguments between departments over numbers. We were told by a grateful management team that the productivity of its internal and client meetings increased significantly as a result!