This is a presentation by Julien Girard at ISS Seminar: Supply Chain Analytics on 20 Nov 2013.

1. Managing Supply Chain from the Front: Demand Planning Excellence
Speaker
Julien GIRARD

2. Introduction

3. FuturMaster – Company
Worldwide representation
20 years of excellence
450 customers
50 countries
20,000 users
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4. FuturMaster – Competencies
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5. Why forecast?

6. Demand Planning – Why forecast ?
Service Level and profit
Respond to market growth successfully
Reduce loss of sales opportunities from Shortages
Increase sales turnover, market share and margins
Stock Optimization
Decrease inventory level (20-60%!)
Decrease obsolete, slow moving and wastages
Reduce working capital requirement
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7. Demand Planning – Why forecast ?
Costs reduction
Minimize material and component purchasing costs
Reduce manufacturing / supply costs
Optimize Supply Chain performance
Collaboration between departments
Collaboration with customers & suppliers
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8. Common Business Challenges?

9. Common business chalenges
Increase Market Complexity - Emerging and fast growing markets
Globalization of trade
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Local  National  Regional  International
Increase of specialized markets
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General & Traditional Trade  Modern Trade
Complexity of distribution network
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10. Common business chalenges
Increase of competition
Increased Competition & Pressure on Margins and Costs
Increased promotional activity
Shortened product lifetimes
Expanded product range
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11. Business Challenges
No effective collaboration between different Supply Chain entities
Greater number of Players - From Suppliers to Partners
Purchasing
Production
Distribution
Demand
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12. How to forecast & Improve Accuracy?

13. Forecasting Concepts
How is the forecast build?
Total forecast
Baseline Forecast
Promotion/launch
Cannibalization
BOM Component
Bundle
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14. Forecasting Concepts – Baseline Forecast
How is the Baseline forecast built
Quantitative approach
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Usage of sales history to anticipate the future demand
Calculation of statistical forecast
The main components of the baseline forecast
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A trend
A seasonality
Y1
Y2
Y3
Y4
Build a forecast free from non-recurrent activity (cleansed historical sales)
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These cleansed historical sales are calculated by removing the exceptional (non recurrent)
events from the historical sales
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15. Forecasting Concepts – Baseline Forecast
Past
Future
Sales history
History statistical model
Baseline forecast
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16. Forecasting Concepts – Cannibalization concept (promotion period)
Baseline Demand
Promotion plan
Cannibalization
Total demand
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17. Organization to support a sustainable
forecast process

18. Forecasting Concepts – Collaborative process
Who is involve in the Demand planning validation process?
The Demand planners: Baseline forecast proposal
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Usage of cleansed sales history
With statistical model for forecasting
Central in reaching the right forecast decision
The Sales: Sales forecast proposal
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Initialize and define the short term promotion plan
Input their knowledge of the market
Adjust the short term forecast plan
The Marketing: Marketing plan
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Input the long term promotion plan
Provide a long term view of the forecast
Initialize the launch plan (new product)
The Finance: The budget
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Budget for Y & Y+1
Last estimated
Target
Purpose of the collaborative process
The Committed Forecast (one single figure should drive the entire company)
A consensus forecast agreed through the Demand review and the S&OP meeting
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19. What is the key success factors?

20. Key Success Factors – The Organization
What action to be taken?
Build a collaborative and cross-functional process that ultimately drive to an aligned
operational plan
Harmonize and Simplify processes
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Clarify Roles & Responsibilities
Processes improvement
Change management
Enforce Collaboration and Accountability
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Inter-departments
Build the Right organization
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People
Process
A sustainable tool to support the Demand Planning process
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21. Key Success Factors – The Tool
Advanced Planning solution is no longer nice to have but mandatory to
support the processes and improve the performances against the competition
Ability to improve forecast accuracy
Support modeling of trend using Statistical Analysis
Improve efficiency and productivity
One tool / source
Easy to maintain
Easy to check gaps and discrepancies
80% of time in data analysis rather than data entry and trouble shooting and
20% in analysis (Low productivity)
Management by exception
Facilitate learning from historical data and activities towards improvement
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22. Key Success Factors – The Tool
Improve sustainability tool
Track changes and updates
Retain knowledge with Staff turnover
Easy to share information for collaboration
Sales, Marketing, Purchasing, Logistics, Warehouse, Production and Finance
Support workflow management
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Prepare Forecast by owner
Review Forecast by relevant department personnel
Entry of relevant information by relevant department personnel
Verify by owner of Forecast
Approve by department in charge
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23. Thank you