Transforming Supply Chain Management for a Global Cosmetics Manufacturer
Technology Category
- Functional Applications - Manufacturing Execution Systems (MES)
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Life Sciences
Applicable Functions
- Logistics & Transportation
Use Cases
- Additive Manufacturing
- Demand Planning & Forecasting
About The Customer
The customer is a multibillion-dollar global manufacturer of skin care, makeup, fragrance, and hair care products. They serve 150 markets worldwide and are known for their iconic brands. Their supply and demand planning activities were previously heavily reliant on manual processes and Excel, with no master production planning capabilities focusing on operational and strategic horizons. The company faced difficulties in consolidating a demand picture due to the frequent need for manual interventions to estimate the impact of promotions, marketing, and new product introductions.
The Challenge
The customer, a multibillion-dollar global manufacturer of skin care, makeup, fragrance, and hair care products, was facing significant challenges in its supply and demand planning activities. These activities were heavily reliant on Excel and manual processes, which depended largely on the personal knowledge of each planner. The company lacked master production planning capabilities focusing on operational and strategic horizons. The process of pulling a consolidated demand picture was difficult and time-consuming due to the frequent need for manual interventions to estimate the impact of promotions, marketing, and new product introductions. The supply planning/scheduling was primarily a sequential planning process where each stage of the manufacturing network was planned one after the other, and material constraints were not integrated. Furthermore, there was a lack of inclusion of promotions and product launches in the demand forecasting process.
The Solution
The company adopted o9's cloud-native platform to overcome these challenges. The platform provided full visibility over their demand picture, automating the process and reducing the need for manual interventions. It enabled a concurrent material and capacity constrained plan for both manufacturing and distribution, ensuring an integrated, more feasible, and better-executed plan. The platform also allowed for the inclusion of new product launch calendars directly on it, providing a 360-degree view of the forecast in units and dollars, considering internal and external drivers of demand. The Enterprise Knowledge Graph was used to build demand and supply-knowledge models with master production scheduling. This allowed for running all key planning processes across operational time horizons between 2 and 12 months in a single integrated and responsive platform, replacing the previous system, SAP APO.
Operational Impact
Quantitative Benefit
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