Improving Forecasts with Integrated Business Planning, 1st ed. 2019
From Short-Term to Long-Term Demand Planning Enabled by SAP IBP
Management for Professionals Series

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Language: English
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421 p. · 15.5x23.5 cm · Hardback

This book provides both a broad overview of the forecasting process, covering technological and human aspects alike, and deep insights into algorithms and platform functionalities in the IBP toolbox required to maximize forecast accuracy. Rich in technical and business explanations, it addresses short-, medium- and long-term forecasting processes using functionalities available in demand planning and demand sensing.

There are also several theoretical concepts underpinning the algorithms discussed; these are explained with numerical examples to help demystify the IBP forecasting toolbox. Beyond standard procedures, the book also discusses custom approaches (e.g. new segmentation criteria, new outlier detection and correction methods) and new methods (e.g. the use of Markov chains for forecasting sporadic demands), etc. It subsequently benchmarks common practices using these innovative approaches and discusses the results. As measurement is an important precondition for improvement, an entire chapter is devoted to discussing process improvement and value using the Six Sigma methodology. In closing, the book provides several useful tips and tricks that should come in handy during project implementation. 

Introduction.- Building Demand Planning Organization and Competencies.- Efficient and Effective Usage of Out of the Box Statistical Forecasting.- Custom Method to Forecast Seasonal Products.- Custom Method to Forecast Intermittent Products.- Value of Forecasting with Custom Methods.- Improving Short Term Forecast with Demand Sensing.- How to Measure and Improve Forecasting.

Ganesh Sankaran has been consulting large multi-national companies for over 11 years on their supply chain processes and IT solutions and helping them solve business problems and generate value from their investments. Ganesh possesses a skillset that combines theoretical insights in SCM and implementation experience in SAP solutions further supplemented by around seven years of software development experience. He is passionate about teaching and research and continues to engage closely with his alma mater to pursue these interests.

Federico Sasso is a consultant with a solid background in Logistics and Supply Chain Management. He is specialized in SAP Integrated Business Planning especially in demand planning, developing new algorithms and processes for forecasting seasonal and intermittent products. He disposes of an interdisciplinary expertise in engineering and economics. He is a ISCEA Certified Demand Driven Planner (CDDP), leveraging the concepts of the Demand Driven Methodology (DDMRP - DDI).

Robert Kepczynski has more than 20 years’ experience in supply chain management and technology. Robert took business roles in plant supply / production planning, inventory and materials management, costing and budgeting, then moved to in market IBP, S&OP, distribution and inventory planning, then made impact in regional & global S&OP, forecasting, demand planning. Robert led x-functional transformation programs delivering supply chain optimization and differentiation e.g. in Demand Management. His experience was valued in 2nd worldwide SAP IBP implementation, which has started in 2013 and proved that Robert has heart, head and hands for IBP.

Alessandro Chiaraviglio has MSc Degree in Aeronautical Engineering at the Polytechnic of Turin. Since 1998 he is a lecturer in the field of Industrial Plant & Safety, he has taught the course of Basics of the Engineering Economics. He provides consulting for technology innovation in the industrial production secto

Describes out of the box forecasting methods for SAP IBP practitioners

Provides guidance on organizational structure, roles, responsibilities and skills for demand planning teams

Presents SAP IBP custom use cases for forecasting seasonal and intermittent products

Outlines demand planning and forecasting process improvement, executed using the Six Sigma methodology