Unilever appointed Kubrick to reduce cost and increase reliability in their global supply chain through increased forecasting accuracy and informed, confident and fast decision-making.
Predicted Annual Savings
Time reduction in decision-making
Forecast Accuracy
In the face of wide-ranging socio-economic uncertainty and complexity, resilience, agility and responsiveness are critically important to effectively manage and optimize supply chains - improving efficiencies, controlling costs, ensuring availability and maintaining competitiveness.
KubrickSaving $30m with optimized buying
The challenge
Remove silos between data sources and reduce the need for manual analysis of suppliers to build an accurate forecast and decision-making process. With a need to enable faster, accurate responses to rapidly changing pricing, shipping constraints, product availability and storage the solution needed to not just save time and money, but also ensure increased confidence and accuracy across operations.
The solution
Harnessing advanced analytics and machine learning, we developed an Optimizer Engine to model and forecast scenarios.
- Working closely with the Purchasing team to understand the variables, limitations, and domain challenges, Kubrick’s data and AI specialists collated the largescale datasets from across ERP systems, commodity pricing, markets and geo-political data to create a comprehensive model.
- The Engine allows buyers to set custom parameters to test and compare scenarios to optimize purchasing decisions for cost, waste, and longevity of supply and storage requirements.
The results
The Optimizer Engine enables buyers to model a cost-optimised purchase in just 5 minutes, reducing decision-making time by 99% and saving 2,100+ hours a year of manual analysis time.
- For the supply of one critical chemical compound in Asia, the tool has already demonstrated annual savings of $2.4m+, with a 96% accuracy on forecasting logistics spend.
- The tool is projected to save up to $30m across just 4% of Unilever’s supply chain, targeting 6 key ingredients accounting for $1.5 billion of spend.
- The success of the solution has already generated a second phase of activity – building a roadmap for a comprehensive Competitive Buying tool suite. This tool suite will provide buyers 24/7 access to insight through a GenAI Virtual Assistant. The capabilities will enhance supplier risk and performance evaluation, rate card comparison and price forecasting, and resilience to shipping and logistics scenario modelling.
