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DEMAND DATA SPECIALIST ( Fluent English )Company: AkzoNobel
The main objective is to monthly generate the best fit statistical forecast model possible for the company's main business units globally, providing this Baseline to be data-driven for building the Demand Plan (DMR) within the IBP cycle.
Purpose/Key Objectives of the Job
Statistical Forecast is the base across Akzo's Nobel business units for the development of the IBP's Demand Plan.
Demand Hub must keep generating the Statistical Forecast for 58 Commercial Units within 8 Business Units from Decorative Paints and Coatings.
Focusing on Automation and KPI's Results: Forecast Accuracy, Forecast BIAS, Forecast Value Added.
Identifying, aligning, raising, implementing, and monitoring opportunities for improvements in KPIs.
Alignment with BPOs when required actions needed developments in our current statistical forecast tool (OMP).
Alignment with the Business on the different demand scenarios (e.g. headwind/ tailwind) to be included and centralized in OMP and alignments with the Demand Data Scientist on the realization of the Continuous Improvement projects.
Responsibilities Specialist role: 25% Managing Decorative Paints, being a focal point to the business, 25% Specialist Hands-On (managing 5 Commercial Units). 50% Focus on CI: Automation and Results. Managing the projects, getting support from the team, delegating the tasks, and defining the priorities. Managing Paints/Coatings, and as a focal point for CI Projects: Ensure the connection between the technical world and the operation or business. Defining/Deploying the process/guidelines with COE connection (functional profiles). Generate statistical forecast: Ensure the data quality that will be used as a Statistical Base Forecast, identifying, and flagging data anomalies. Reviewing and applying guided corrections whenever necessary. Ensure the flow of activities and execution of established procedures for generating the monthly statistical forecast. Execute some operational procedures based on guided interactions. Connecting and Interacting with Demand Planners: Identifying and removing Outliers together with the demand planning areas, ensuring it will be uploaded in our main tool and the historical base will be cleaned up. Analysis of Outliers automatically identified by the statistical engine system. Mapping of Phase In/Out items, aligning with the demand areas to upload in the system. Forecast performance analysis: Focus on statistical forecasts of the most representative and most critical items based on the ABC/XYZ curve. Focus on the long term, m3 onwards. Evaluate whether the results of the main KPIs meet expectations, Accuracy, BIAS, and FVA (Forecast Value Added), in Lag-1, Lag-3, and Lag-6. If they are below the expected results, understand the reasons and propose and implement solutions to achieve the goals. Conduct monthly meetings to align statistical forecasts with business units, results and outlook, seasonality, trends, and levels. Explaining in detail the reasons for what is changing between cycles, updates considering the most recent results, or regarding improvements. Evaluate and test different methods and statistical models at different calculation levels to obtain the best results, aligning with the demand team of each business unit. The statistical tool currently used is OMP. Continuous Improvement Mindset: Explore alternatives on how we can achieve better results in terms of Accuracy and BIAS (reducing forecast error). Proactively seek means and methods or auxiliary tools to enhance the forecast performance and overwrite the statistical forecast in OMP whenever necessary. Follow up on improvements already mapped to ensure the effectiveness of actions and conclusion of developments in Quality and Production environments. Consistent communication with internal customers (demand planners, demand managers), to understand their needs, identify opportunities for improvement, propose solutions, monitor their effectiveness, and align expectations considering our restrictions, which is making them aware of what is viable, always with transparency. Achieve credibility of our internal customers, demonstrating the value our area adds to the demand plan consensus. time on analysis and results. Align with Demand Planners and Managers on potential leading indicators (exogenous variables) containing high correlation with sales history and how could influence the forecast. Job Requirements Bachelor's degrees in Math, Statistics, Engineering, or Data Science. Solid experience as a Statistician and Data Scientist with a focus on demand forecasting (sales/consumption). Experience with Demand Planning and Supply Chain (competitive advantage). High level of experience in Data Analysis tools and languages. Experience with the tools and technology below: Advanced Excel: ability to handle data, knowledge of statistical resources within Data Analysis, Solver, Macros, VBA (Desired) Alteryx (Desired) Python R SQL Management Studio (Desired) Azure Data Platform: Databricks, Data factory Power BI Desired knowledge of OMP forecasting tool ( It's nice to have) Experience and understanding of statistical modeling. Analytical profile, resilience, flexible, problem-solving attitude. Excellent communication and interpersonal skills Fluency in English: BU support on a global level, constant communication with several countries.
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