Our client is one of the largest hypermarket chains in the world and had been using an outsourced service to calculate sales forecast. In order to improve inventory accuracy and optimise sales forecasts, they decided to bring forecasting systems and processes in-house using Oracle RDF. We ran a project to implement the system and create a new centralised forecasting team.
Our client is one of the largest hypermarket chains in the world, the second largest retail group in the world in terms of revenue, and the third largest in profit. They operate mainly in Europe, Argentina, Brazil, China, Dominican Republic, United Arab Emirates, Qatar and Saudi Arabia, but also has shops in North Africa and other parts of Asia.
The client had been using an outsourced service to calculate sales forecast and these figures were then manually manipulated by teams in other systems. In order to improve inventory accuracy, standardise processed and optimise sales forecasts, they decided to bring forecasting systems and processes in-house.
There were a number of different cultural and working dynamics to manage since the client/CMG working team comprised a number of different nationalities. CMG staff stationed overseas had to quickly learn local business customs and expectations to be able to integrate with both management and users.
The client selected Oracle Retail Demand Forecasting (RDF) and set up a project to implement the system and create a new centralised forecasting team.
Initially the implementation of RDF was going to cover FMCG, hardlines, textiles and electronics and complete within one year. The scope and roll-out approach, however, changed several times during the project.
The client asked for our support to manage the change, including: Process Design, Organisation Design (Roles & Responsibilities, workload planning), Communications Management, UAT, PMO, Training Design and Delivery.
During the project the client made the decision to build two additional systems to work alongside the RDF. This meant that a parallel development stream started slightly late into the project and also was approached in an “agile” way, causing challenges with integration testing and UAT testing. This meant that we had to be flexible and gather information wherever possible to compile process maps, in order to define a UAT schedule and approach.
Via extensive communications, engagement and training we managed a disparate user community through to a positive place by the end of the project.
We created a bigger, more defined role for the client forecasting team and introduced clearer common processes so that the team worked more effectively.
By bringing together information from the many working parts of the team to create joined up communications, we improved control of forecast product and created cost reductions.