On a global scale, for all Paints & Coatings:
- Leads technical design and deployment of IBP Reporting & Analytics (DART/SMART for Demand/Supply). Supports IBP Data Science Manager & Business Process Managers (BPMs) in process design and deployment of IBP Reporting & Analytics (DART/SMART for Demand/Supply).
- Supports deployment of IBP & Demand/Supply by supporting Data Science manager and users to improve master data (product, customer, region, supply hierarchy, and for critical sites: production data, MRP views) and supports automation initiatives such as master data profiles.
- Technically design and deploy end-to-end reporting and analytics processes to optimize key end-to-end KPIs being Service, Cost-to-Serve and Inventory (Incl Slobs). Thus, supports Data Science manager in process design and deployment, e.g. in matching demand segmentation (ABC-XYZ) with supply policies (MTO/MTS), and setting order quantities/lot sizes to optimize all 3 KPIs.
- To keep data up to date and operate as efficiently as possible, design and deploys automation of all data management through rules. Once there is a solid foundation, explore opportunities to apply machine learning (e.g. in Alteryx) and utilize functionality of Advanced Planning Systems (APS).
- Develops materials to build capability in the supply planning community including trainings and set-up of Knowledge Management System (KMS) for Reporting & Analytics, as well as Master data management for the above mentioned scope.
For DART/SMART, Master data, optimization of key end-to-end KPIs, automation, KMS:
- Effectively partner within the data science team, operational users and senior stakeholders in other COEs and IM, to make data accurate and to make the process to manage data efficient.
- PMO of technical progress while balancing agile working to deliver rapid prototyping and further incremental development of the technical product, with good communication to sponsors and key stakeholders.
- Conduct advanced data analyses, develop rules & mathematical models to promote efficiency, and translate these into a usable tool/system which supports the process.
- Extract relevant information from available data sources for further analytical processing, e.g. data mining
- Process, cleanse, and verify the integrity of data used for analysis; where possible collaborate and guide the junior Data scientist to perform this task.
- Interpret results in a business context, discuss with business partners, and incorporate data-driven decision-making in operations
- Serve as interface between business and IT departments. E.g. alignment with Global PRISM project on Master data.
- Validate achieved process performance with meaningful KPIs
- Ideation: Identify new strategic application areas and use cases
- Leads Onboarding and Training of junior Data scientists.