This document discusses how companies can improve their sales and operations planning (S&OP) processes through predictive analytics, scenario planning, and risk management. It recommends that companies use digital modeling, simulation, and probabilistic predictive analytics to evaluate different scenarios and supply chain designs without experimenting on live operations. Incorporating risk management into S&OP allows companies to develop response plans for uncertain events and improve long-term sustainability and competitive advantage.

1. Enablers for Maturing your S&OP Processes
Gregory L. Schlegel CPIM, CSP, Jonah
VP Business Development
gschlegel@shertrack.com
January 27, 2011

2. NEXT GEN S&OP Solution Platform
Lehigh University G 2

3. We Solve Complex S&OP Enterprise Issues... subject to Conflicting Objectives
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Multivariate digital models are recognized as the methodology of choice for analyzing
complex manufacturing environments..
Financial Metrics
 Revenue & Earnings
 Working Capital
 Contribution Margin / Profit
 Return on Assets
Production Metrics
 Overall Equipment Efficiency
(OEE)
 Effective Capacity & Yield
 Agility (responsiveness)
 Variable Expenses
Market Metrics
 On-time Delivery (OTD)
 Order Policies:
 Lead times
 Minimum order size
 Product Mix
 Contribution Margin / Profit

4. WHAT is Predictive Analytics??
 Predictive analytics… encompasses a variety of techniques from
statistics, data mining and game theory that analyze current and
historical facts to make predictions about future events.
In business, predictive models exploit patterns found in historical
and transactional data to identify risks and opportunities. Models
capture relationships among many factors to allow assessment of
risk or potential associated with a particular set of conditions,
guiding decision making for candidate transactions.
Predictive analytics is used in actuarial science, financial services,
insurance, telecommunications, retail, travel, healthcare,
pharmaceuticals and other fields. But NOT Manufacturing or
Supply Chain!
One of the most well-known applications is credit scoring, which is used
throughout financial services. Scoring models process a customer’s
credit history, loan application, customer data, etc., in order to rank-
order individuals by their likelihood of making future credit payments on
time. A well-known example would be the FICO Score.
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5. Stochastic & Probabilistic Modeling
 Stochastic models:
 Models where uncertainty is explicitly considered in the analysis
 Probabilistic demand models:
 Statistical procedures that represent the uncertainty of demand by
a set of possible outcomes (i.e., a probability distribution) and that
suggest inventory management strategies under probabilistic
demands

6. Past & Present Clients (partial))
ROHM & HAAS A Wholly Owned Subsidiary of

7. S&OP Scenario Planning
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Probabilistic
Simulation
Enough
Information?
Risk
Response
Plan
Supply chain
Flow model
Base case
data
Decision
Logic
Probability
Distributions
of uncertain factors
Probability of
occurrence &
magnitude of
disturbing
events
Design of
Experiments
Performance
Measures
Feasible
Tactical Plans
No Yes Determine
“most appropriate”
values of
decision variables

8. Our Scenario Outcomes/Dashboard

9. Scenario/Risk Response Planning
Scenario Probabilities of Occurrence
HIGH
LOW
Risk Associated with Occurrence
LOW
HIGH
Take Scenarios & Build A Risk Response Plan
Scenario 1…..

10. 1. Internal Environment
2. Objective Setting
3. Event Identification
4. Risk Assessment…….
1. Type of risk &
2. Magnitude
5. Risk Response Plan…..
1. WHAT to do
2. WHO is responsible &
3. HOW to manage the risk
6. Control Activities
7. Information & Communication
8. Monitoring
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We Inject an ERM, Enterprise-wide Risk Framework into the S&OP
Process: What”

11. Defining How To Bring Scenario Planning To An Actionable Level
Application – Clarity on how to apply and the level of planning capability
needed to support.
Define as future “what if” not variations on plans
Control Plan – How to maintain scenario integrity, ensure they are
executable, and there is a continuous improvement process.
Probability of Plans and Assumptions
Scenarios for uncertain future
conditions
Plan Variation What IF

12. This New Sophisticated Methodology Leveraged at Bayer
 Combining Design of Experiments (DOE) methodology with
Digital Modeling leveraged the power of both methods.
 Bayer utilized SherTrack’s innovative predictive manufacturing
technology to support Scenario Planning
 A cross-functional team, in collaboration with SherTrack,
configured a SNAPPS™ digital model to simulate customer
demand, scheduling and production output of a very
complex compounding facility
Validate
Shertrack
Model
Design
DOE
Run
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Scenarios
Evaluate
Model
Predictions
Business
Leader
Review
Modify
Supply
Chain

13. Demand-Driven SC Execution Delivers Greater Operating
Performance (Service, Capacity and Production Efficiency)
Better Service, Less Inventory, Fewer Setups
Source: Connie Conboy, Bayer MaterialScience, ISSSP
Leadership Conference, May 2008
Bayer MaterialScience
262 products across 5
production lines
Improved OTD% & OEE% with Less Inventory
Variability Reduced & Operated close to Optimum
Basell Advanced Polyolefins
Source: Larry Maynard, Basell NA, SPE Polyolefin
Conference, 2/26/2006, Houston

14. Inventory – Service Exchange Curve
Green Shaded area contains feasible operating set-points
DOE Scenario
Live Performance
SNAPPS with
capacity increase

15. 15
Managing Uncertainty & Complexity’s Impact on Inventory

16. ROHM & HAAS A Wholly Owned Subsidiary of

17.  WHY RISK MANAGEMENT in S&OP?
 Competitive advantage
 Reputation & Branding
 Rating agencies & positive analyst
commentary
 Ability to reduce cost of capital

18. Scenario Planning & Risk Management Conclusions
 The combination of digital modeling, discrete event simulation
and predictive analytics is a very powerful technique for Scenario
Planning in the S&OP arena.
 Very compelling improvements are possible, especially in
complex operations.
 Identifying, codifying and prioritizing risk within the S&OP
enterprise process becomes a critical competitive advantage
 Developing a Risk Response Plan ensures long term
sustainability of Operational Excellence
A powerful environment to evaluate alternatives without
experimenting on customers & the bottom line!

19. SUMMARY……
 Companies NEED to evaluate their supply chain designs,
policies & practices on a continuous basis rather than
periodically
 Companies SHOULD segment/or Tier their customers and
develop efficient and effective supply chains based on
Total-Cost-to-Serve models
 Companies NEED to incorporate Risk Management tactics
and methods into their S&OP processes
 Companies SHOULD support S&OP Scenario Planning
leveraging Probabilistic Predictive Analytics
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20. Enablers for Maturing your S&OP Processes
Gregory L. Schlegel CPIM, CSP, Jonah
VP Business Development
gschlegel@shertrack.com
January 27, 2011