1. Build and end-to-end planning framework
To overcome fragmented planning processes and limited accountability, one end-to-end planning framework was implemented, integrating business processes and IT across all relevant functions and regions. This also included alignment of the organisational setup, governance and incentives in order to facilitate quick decision-making.
2. Create end-to-end visibility
The next step was to map and interlink all supply chain data from across the network: inventory, capacity, requirement forecasts, orders, shipments, etc. One major part was ditching Excel spreadsheets for a connected planning platform as a single point of truth, and making it accessible to all parties involved.
3. Leverage AI/ML to increase level of automation
One of the key objectives was to automate most of the daily activities of the planners, to make more time to collaborate with other functions and make more tactical decisions.
Two good examples are the application of AI/ML techniques in the area of forecasting and replenishment. While this technology’s already proven to have a positive impact on forecast accuracy, the real benefit was the automation of the data cleansing and updating the parameters, which took the planners almost a day per week to do this manually. Within replenishment, the client was able to move towards a low-touch ordering process and focus on order proposals that needed extra attention.
4. Establish a solid project management office that stimulates innovation
Bringing structure to all the initiatives with clear feedback loops to senior management is crucial. Equally important is providing a high degree of organisational freedom and flexibility to enable rapid cycles of development, testing and implementation of solutions. This requires a culture that develops and/or acquires talent to enable transformation and encourages new learning, while also gaining scale by sharing standardised and proven practices.