Demand Planning & Inventory Optimisation

Balance service levels and working capital with better forecasts

Fewer stock-outs: lower forecast error and higher DIFOT and service levels.
Less working capital: better stock turns and lower overall inventory.
Automated replenishment: across periods, categories, lines and SKUs with Demand Planner, replacing home-grown spreadsheets.

An ongoing challenge for modern-day demand planners and inventory managers is improving the accuracy of demand forecasts in order to simultaneously reduce stock-outs and working capital requirements. Besides the algorithmic challenge of minimising the forecast error, there is also the challenge of understanding and optimising the trade-off between working capital costs and service levels to customers. Most organisations manage this process through aggregated sales forecasts and subjective estimates, which are often based on home-grown spreadsheets and ad-hoc reports. This sub-optimal approach often results in:

High working capital requirements
Unrecoverable freight costs due to the wrong inventory being at the wrong place at the wrong time
Stock outs and reduced service levels to customers, especially on measures such as DIFOT and fill rates
High forecast error
Manual handling and manipulation of data from a variety of sources, leading to data integrity issues and substantial time inefficiencies
Significant time, expertise, and labour required to analyse just a few scenarios, making it impractical to conduct a comprehensive analysis to find a truly optimised replenishment plan or inventory allocation

Complexica can help you address these commonplace problems through our Demand Planner, which provides robust and easy-to-use demand planning, forecasting, analysis, and replenishment optimisation capabilities.

Based on advanced statistical models and machine learning techniques, Complexica can help your organisation move demand planning away from an anecdotal and “gut feel” approach, to a data-driven process. In particular, our Demand Planner can help you:

Reduce the forecast error associated with demand planning
Increase DIFOT and service levels to customers
Improve stock turns and decrease overall inventory levels
Improve reaction time and response to unexpected events (e.g. sudden change in demand requiring additional inventory)
Automate manual processes to eliminate human error and key man risk
Understand the impact of changes in business rules and constraints (such as lead times, capacity constraints, required inventory levels, etc.)
Replace home-grown spreadsheets, which are often opaque and convoluted
Optimise and automate the replenishment process across various time periods, product categories, lines, and individual SKUs
Understand customer sales trends and patterns