Demand Planner - Westville at RCL Foods

Job Description

The purpose of the role is to drive and facilitate the demand planning and where applicable, demand management process, in order to enable visibility of expected demand to the business and in particular to the supply chain. This forward forecast will be used to improve the business decision making process around product mix, product prioritisation and cost / profitability choices; and to drive up customer service levels by enabling the supply planners to plan out unnecessary operational costs and supply risks. The role will require a strong working relationship with customer, marketing, supply planning, distribution, and commercial teams.

Minimum Requirements    

• 2 Years Demand Planning experience ideal
• 2-3 previous Supply Chain experience would be an advantage, particularly in Supply Planning or Distribution Planning; or Customer Marketing experience
• Bachelor of Commerce/Economics Degree, or related Supply Chain National Diploma (e.g.: SAPICS CPIM)

Duties & Responsibilities    

Functional Strategy into Action Operationalisation

• Work closely with customer, marketing, and commercial teams along with other senior managers in the Supply Chain and Customer teams to cocreate the forward demand plan based on a 1-2 year's view of requirements. This will be used as key input into the business volume plans to be used for budget and quarterly planning
• Facilitate integrated supply chain delivery by managing relationships and interaction within the extended supply chain, distribution and customer teams.
• Collaborate with the supply chain and customer teams to drive up customer service levels and volumes sold.

Demand Analysis:

• On a weekly and monthly basis analyse actual demand to generate the forward forecast, make recommendations, and drive continuous improvements in order to gain concensus with cross functional teams on the forward forecast (including base & event)
• Understand what is causing differences between what was forecasted vs what was actually ordered, and use this to drive discussions with the front-end team, challenging their assumptions and making suggestions on how to improve accuracy of the forecast
• For price sensitive product groups (like value chicken and sugar) ensure that pricing information and competitor information is gathered as part of understanding gaps to forecast, as well as impact on stock builds or stock shortages.
• For Make to Order production (Beverages, Fresh Chicken), closely watch the forward forecast vs historical demand to ensure that there is a good correlation between the two. In chicken particularly, where fresh demand does not materialise, the impact can be significant as the raw chicken portions may then end up being packed into products like single portions or IQF, where it was not intended to go. This could impact stock builds or pricing that can be achieved

Generating Base Demand:

• Analyse historical demand and remove anomalies (including outliers) from the norm using historical information, knowledge of the category and by getting input from the customer teams, in order to generate a sound base demand forecast
• Identify the most appropriate statistical forecasting model for each product group in order to generate an accurate base forecast, 12 months rolling forward.
• Generate the base demand plan using the most appropriate statistical forecasting algorithm and make adjustments where necessary
• Understand any variance between actual customer demand and the statistical forecast and make appropriate challenges, changes and recommendations to the base forecast

Events/Promotions:

• Use the promotions grid and related discussion that are provided by the customer team as input into the event forecast
• Work closely with the customer team to document the assumptions for each promotion, driving clarity on volume, price and customers
• Challenge all promotional volume increases when history shows that these have not been achieved before; or if historical the promotions have delivered higher volumes, also challenge to get the volumes increased.
• Present the proposed forecast along with assumptions to get a consensus forecast to be used by the business. This will be done at the monthly Demand Planning meeting.

Publishing and Reporting on the Forecast

• Publish the agreed forecast in the appropriate format to ensure transparency and one set of numbers. This includes ensuring that the Demand Planning tool (Barton) is correct and that these numbers are correctly interfaced to the Group Reporting Cube. The Fixed Forecast will be used by the business to measure the effectiveness of the Demand Planning Process, while the Operational Forecast may be changed more regularly to enable the Supply Planning teams to make better priority decisions should the actual demand be significantly different to what was initially thought.
• Using the agreed forecasting KPI’s (Forecast Bias, Forecast Sku Compliance and Customer Service level) to drive improvement in the forecasts and to minimise volatility. Use these KPI’s to assist when analysing the historical data while generating the forecast
• Publish the forecasting KPI’s in the agreed format, in line with the agreed timeline for weekly reports and monthly scorecards