1. Supply Chain Planning Demand Planning Excellence – Automotive Industry
May 2013

2. Planning Complexity for a Typical Mid-Market Company
Demand Planning Process Example
Planning Complexity for a Typical Mid-Market Company
More than 10,000 items to review on a monthly and/or weekly rolling planning horizon
Volatile and complex planning environment
Difficulty to hire and retain skilled specialists in supply chain or operations management
Often only one resource to manage the total puzzle
IT systems not connected and not integrated
Functions are not connected, centralized or integrated
Few or limited resources to invest on advanced IT systems
ERP system lack of functionalities to support decision making process
Extensive usage of Excel spreadsheets
Lack of operational performance measures (KPIs)
Limited business intelligence capabilities

3. Demand Planning Process Example
Automotive Industry
Asia
Industry : manufacturer and distributor of automotive parts (OEM and aftermarket)
Number of active items (skus)
 8000
Required service level (fill rate) : >= 96 %
17 warehouses located in North America (Canada and USA)
3 manufacturing plants located in Canada
Usage of domestic and offshore sources (Asia)
15 major national client accounts
Lead times require accurate 3-month forecast

4. Demand Planning Process Example
Business Objectives
Business Objectives : « Aftermarket » distribution channel
Increase forecast accuracies (1, 2 and 3 periods ahead (months))
Decrease inventory of finished goods in the network
Maintain and increase customer service
Reduce planning complexity

5. Demand Planning Process Example
Modules Deployed

6. Required Planning Technology Enablers
Demand Planning Process Example
Required Planning Technology Enablers
Hyper cube technology (RAM based cube)
Configurable environments & processes
Easy integration to any other tools
Library of algorithms – 300 indicators
Collaborative work flows – Excel integration
Usage and enablement of all of these features
The key is to integrate all the information into the same planning workspace (screen)
Planner shall see, by default, only the important elements on which he should focus on
Planner should have drill down capability to see components that create or influence the value’s behavior
Reaction time between the change of an input and the visualization of its impacts on a set of outputs should tend to be “real time“

7. Build and manage forecasts Excel files (non standard)
Demand Planning Process Example
Planning Environment Prior to the Implementation of nSkep Demand Planning
Build and manage forecasts
Excel files (non standard)
Consolidate files
Use forecasts
Product Line i
Procurement 2 …
Production 3
Product Line N
Finances – Budget tracking 2
Usage of diverse non standard Excel spreadsheets to build forecasts
Manual and labor intensive planning process
Each business unit had the responsibility to supply its sales forecasts
A team at headquarter had the responsibility of consolidating and formatting forecasts from all business units
Long response time (long planning cycle) and heavy usage of human resources

8. Supply Chain The Vision Suppliers + Control tower Manufacturing plants
Demand Planning Process Example
The Vision
Supply Chain
Suppliers +
Control tower
Collaborate
Control
Plan
Execute
Measure
Manufacturing plants
One planning tool
Integrated with the transactional systems
With BI capabilities
Configurable and flexible
Clients
Distribution
and transportation

9. Implementation Phases
Demand Planning Process Example
Implementation Phases
Phase 1
Phase 2
Install and deploy an integrated SCM planning technology
Focus on consolidated forecasts at the item levels
Centralized planning functions, integration of information flows and of functions
Manage by exception
Create planning clusters
Create alerts and alarms
Manage by exception. Automation and optimization
Reconcile financial trends with the operational forecasts
Forecasts at the item-hub (warehouse) levels
Forecasts at the item-spokes (warehouse) levels
Internal collaboration
Centralization and standardization
Optimization and Simplification

10. Centralized Demand Planning Function
Demand Planning Process Example
Centralized Demand Planning Function
Centralized Function
Step 1 Improvements
Statistical forecasts – automated process
Segmentation of the process by product line and by ABC classes
Measure and track forecast accuracies
Consolidation of data flows and planning processes on a centralized platform
Stabilize data flows
Reduce number of participants
Better visibility
S&OP Process
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (Category Managers)
Consensus forecasting process 1 2 5 #
Number of resources involved in the process

11. Centralized Demand Planning Function
Demand Planning Process Example
Centralized Demand Planning Function
Centralized Function
Step 1 Challenges
A large quantity of information to review
Difficulty to trust the system (change management challenge)
Wrong interpretation of the outputs
Improper or weak understanding of statistical models and how they manipulate information
Long time required to review all forecasts
Difficulty to properly interpret risks
Bias caused by human factors
S&OP Process
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (Category Managers)
Consensus forecasting process

12. Manage by Exception  Automation and Optimization
Demand Planning Process Example
Manage by Exception  Automation and Optimization
Segmentation of the Complexity and Processes 
Strong Positive Trend 
Strong Negative Trend 
Stable Trend
Risks - Variability
Sort by importance
Alerts
Reviews achieved by the planner
Seasonal
3 130 items (40 %) to review
Non Seasonal
Discrete
Automated reviews by the system
4 717 items (60 %) reviewed by the system
New

13. Manage by Exception  Automation and Optimization
Demand Planning Process Example
Manage by Exception  Automation and Optimization
Segmentation of the Complexity and Processes – Second Level of Segmentation
Non Seasonal
Seasonal
Reviews achieved by the planner
Automated reviews by the system
1845 items (23.50 %)
6002 items (76.50 %)
Sales Forecasts

14. Manage by Exception  Automation and Optimization
Demand Planning Process Example
Manage by Exception  Automation and Optimization
Manage by Exception - Automation and Optimization
Step 2 Improvements
Reduce by 76% the number of items reviewed on a monthly basis
Increase the users’ trust with the planning system
Help focus on the most important elements
Reduce complexity
Quickly identify problems and suspicious behaviors
Reduce planning cycle time
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (Category Managers)
Consensus forecasting process
Seasonal
Non Seasonal
Discrete
New

15. Manage by Exception  Automation and Optimization
Demand Planning Process Example
Manage by Exception  Automation and Optimization
Manage by Exception - Automation and Optimization
Step 2 Challenges
Difficulty to reconcile operational forecasts with financial trends
Gaps between the two forecast flows
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (Category Managers)
Consensus forecasting process
Seasonal
Non Seasonal
Discrete
New

16. Internal Collaboration
Demand Planning Process Example
Internal Collaboration
Sales + Supply Chain + Finances (Complete Internal Collaboration)
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (category managers)
Consensus forecasting process
Consensus and alignment of financial trends with operational plans
Sales and Supply Chain
Finances
Flex Budget
« bottom-up & top-down »
Product Line
Item
Item –  HUB (Warehouses)
Item –  Spokes (Warehouses)
consensus
Production & Procurement
Supply Chain

17. Internal Collaboration
Demand Planning Process Example
Internal Collaboration
Sales + Supply Chain + Finances (Complete Internal Collaboration)
Step 3 Improvements
Alignment of operational forecasts and financial trends
Better forecast at the Item-Hub levels and at the Item-DC levels
Coherent communication of the demand plan to all actors within the company (one version of the truth)
S&OP Process
Sales Forecasts
Statistical forecasts built and managed by the demand planner
Sales forecasts built by the CMs (category managers)
Consensus forecasting process
Consensus and alignment of the financial trend with the operational plan
Product Line
Items
Combinaisons « Item – HUB (warehouses) »

18. Demand Planning Process Example
Tangible Benefits
Business Objectives : « Aftermarket » distribution channel
Increase forecast accuracies (1, 2 and 3 periods ahead (months))
Increase forecast accuracies by more than 5 points
Decrease finished good inventory in the overall network
For only ten items, inventory value reduced by more than $50,000
Maintain and increase customer service
Reduce planning complexity
Centralized demand planning function
Standardized processes
Reduced number of actors
Reduced planning cycle time

19. Demand Planning Process Example
Key Takeaways
Divide planning complexity and processes based on a set of business rules, alerts and classification parameters
Automate and optimize decision making process whenever possible. Identify which cluster can be treated.
Use the right management alerts and key performance indicators for each decision making process
Adapt decision making methodologies for each cluster and each process
Identify decisions and parameters that have been overridden by the user
Automate creation and classification of planning clusters
Prioritize and identify planning clusters that should be reviewed by the planner or by the group
Within each planning cluster, prioritize items to review based on other sorting criteria
Allow decision maker to create and maintain his own planning clusters
Measure quality of decision (likelihood corridor) and send alerts if decision is not acceptable based on tolerance corridor

20. Thank You!