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8 Tips for Implementing a Statistical Forecast in SAP Sales and Operations Planning

by Anjali Butley, Solution Architect, SCM and SAP, Tata Consultancy Services

January 29, 2015

The following is an excerpt from the SCM Expert article “Advanced Demand Planning with S&OP and SAP HANA.”

A very simple statistical forecast method, Time Series, is available in SAP Sales and Operations Planning (S&OP) 3.0 powered by SAP HANA, Support Package 01, which is required for an S&OP process. Based on my experience with S&OP powered by SAP HANA, I share the following tips for implementing a statistical forecast:

  1. For triple exponential smoothing, historical periods, and historical error period, select twice the number of seasonal periods.
  2. For single and double exponential smoothing, at least two historical periods are required.
  3. Historical error periods should be less than historical periods.
  4. In the statistical forecast job log, users face difficulty reading the error. To do the error analysis, they need help from an SAP HANA developer. To read the errors, an organization may need to develop custom-defined reports.
  5. S&OP powered by SAP HANA’s planning cycle performance has improved, and now the demand planning cycle time can be shortened.
  6. New product introduction’s impact on supply requirement, manufacturing, and profitability decisions can be taken in S&OP meetings quickly by collaborating with the demand planner, supply planner, and finance manager.
  7. SAP HANA PAL forecast methods can be integrated and made available in S&OP HANA by defining a planning operator.
  8. Integration testing and customer acceptance testing have to be done regressively.

 

 

         
         

SCM Expert author Anjali Butley has more than 20 years of strong functional, business, and IT experience with domain expertise in supply chain planning and logistics.

She is a business analyst with more than 15 years of SAP experience in design and development of integrated supply chain solutions for large-scale enterprises. Her expertise includes process modeling, business process analysis, application implementations, production support and presales across multiple client engagements in the SCM domain.

She has executed various types of SAP projects, such as implementations, global rollouts, enhancements, production support, business consulting, and program and project management in multicultural environments worldwide. Her industry exposure includes areas across major industry verticals, including IT consulting, consumer, high technology, and discrete manufacturing.

She is always interested in exploring new SAP SCM applications and products and sharing her learning experiences with the SCM community.

         
         

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