Job Description

Overview :


Responsible for managing and overseeing the monthly cycle of demand planning activities. This includes demand pattern analysis, KPI reviews, upstream/ downstream management and commercial data intelligence support. Demonstrate high levels of engagement, collaboration and proactive communication with key stakeholders.



Main Accountabilities

Lead demand planning process for Malaysia, ensuring forecast accuracy and strategic alignment across commercial members from all sites. Partner with sales team of each region/category, to ensure the demand plan is well executed (mid and long term); ensure gaps and overlaps are addressed, scenarios are completed and issues appropriately resolved or escalated to meet business objectives. Drive sales success by proactively identifying demand-supply bottlenecks, closing gaps through agile collaboration with supply teams, and enabling faster responses to evolving market dynamics. Create and maintain demand forecast models comprise of statistical forecasts baseline, sales opportunities pipeline captured through Salesforce, and vulnerabilities assessment. Champion flexible planning forums to quickly capture short-term demand spike, new launches, or strategic products, minimizing lost sales and enhancing service levels. Act as a key contributor to the Integrated Business Planning (IBP) process by facilitating monthly consensus meetings, scenario modeling, and cross-functional alignment on mid- to long-term horizons. Actively shape data transformation in sales team by providing centralized sales database, PPT & dashboards--driving data-led discussions and continuous performance improvement.


Requirement

Minimum 8 years related supply chain management or business planning experience in a multi-site manufacturing environment Bachelor degree or above in Business, economic, finance, statistics or management, etc. Knowledge of SAP, Salesforce, data visualization tools such as Power BI, Tableau or other software related to demand planning is preferred. * Experience in statistical forecasting using forecasting models, trend analysis is a plus.