Introduction to Simulation- Predictive Analytics
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The goal of analysis should provide leadership with insight into risk and uncertainty and guidance on actions that can be taken. However, common analysis methods of using point estimates to generate forward-looking business plans disregard uncertainty and ignore risk. In this presentation, you will learn how to incorporate uncertainty directly into a decision support application. The results is a range estimate with likelihoods of exceeding thresholds based on assumption values, providing leadership with the insight into uncertainty and actions that can be taken to reduce risk.
![Introduction to Simulation:
The Athematic of Uncertainty
May 15th, 2014
We
will
get
started
3
–
5
minutes
past
the
hour
“Our
culture
encodes
a
strong
bias
either
to
neglect
or
ignore
VARIATION.
We
tend
to
focus
instead
on
measures
of
central
tendency,
and
as
a
result
we
make
some
terrible
mistakes,
o>en
with
considerable
prac?cal
import[ance].”
-‐Stephen
Jay
Gould,
naturalist,
1941-‐2002
Presented by:
Andrew Pulvermacher
Director | Decision Sciences](https://image.slidesharecdn.com/pawebinar305-140515122216-phpapp01/85/Introduction-to-Simulation-Predictive-Analytics-1-320.jpg)
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Introduction to Simulation- Predictive Analytics
- 1. Introduction to Simulation: The Athematic of Uncertainty May 15th, 2014 We will get started 3 – 5 minutes past the hour “Our culture encodes a strong bias either to neglect or ignore VARIATION. We tend to focus instead on measures of central tendency, and as a result we make some terrible mistakes, o>en with considerable prac?cal import[ance].” -‐Stephen Jay Gould, naturalist, 1941-‐2002 Presented by: Andrew Pulvermacher Director | Decision Sciences
- 2. in/drewpulvermacher Agenda Value of Simula?on Modeling • What is it… • Why you need it… • When would you us it… • How to use it… • Which Sim Product to use… • Who uses it…
- 3. in/drewpulvermacher REASON FOR BEING 1: Cure for the Flaw of Averages 2: Embed UNCERTAINTY 3: Enable Risk Management MEANINGFUL INFORMATION
- 5. 5 Drew@PerformanceG2.com Simulation Modeling Why use it….
- 6. What-‐If What Utilization Rate should we maintain to maximize profit? Profit per Unit: 10.00$ Missed Order Cost (5.00)$ Plant Capacity: 100 Utilization Rate: 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Units Produced -‐ 10 20 30 40 50 60 70 80 90 100 Product Profit -‐$ 100$ 200$ 300$ 400$ 500$ 600$ 700$ 800$ 900$ 1,000$ Cost of Missed Orders -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ Profit -‐$ 100$ 200$ 300$ 400$ 500$ 600$ 700$ 800$ 900$ 1,000$ 6 What-‐If Analysis on Steroids *With beneficial side effects Input Variable Target TradiHonal What-‐If SimulaHon Input: # to
- 7. 7 What-‐If Analysis on Steroids *With beneficial side effects TradiHonal What-‐If SimulaHon Outputs = Meaningless Inputs = Misleading Inputs = ‘Mimic’ Real-‐World Outputs = StaHsHcally Meaningful • Talk in terms of Probability • Terms of Achieving • Likelihood of Failure • BeRer idea of what to EXPECT $#&!
- 8. 8 SCENARIO Today: May 15, 2014 Submit Sales Forecast for Black Friday Event Why don’t we use simulaHon…
- 9. WHY SIMULATION? What will Black Friday sales volume be? $5.5 B 80% Confidence Level $8.2 B $3.9 B Which es?mate do we use? (6 months from now….) POINT ESTIMATE RANGE trying to hold people accountable? establishing a budget? defending an audit of how it was generated? Leadership does not have permission to be uncertain!
- 10. 10 “If a man will begin in certain1es he shall end in doubts; but if he will be content to begin in doubts he shall end in certain1es.” -‐Sir Francis Bacon
- 11. Es?mate $5.5 B Combine a point esHmate with a likelihood esHmate Chance of Missing | 35% WHY SIMULATION? What will Black Friday sales volume be?
- 12. ASK YOURSELF… MENTAL BREAK Blackjack Dealer HIT 70% of busHng Stay 65% of busHng
- 13. ASK YOURSELF… 401(k) Return: Return: 25% 15% RiskP(<0%) 15% 5% Risk Tolerance Uncertainty <> Risk RiskP(<0%)
- 14. CORE CONCEPT Uncertainty <> Risk UNCERTAINTY does not equal RISK. By recognizing uncertainty exists and by modeling uncertainty (simula8on), you know enable decision makers to bejer manage RISK.
- 15. Es?mate $5.5 B Chance of Missing | 35% WHY SIMULATION? Combine a point esHmate with a likelihood esHmate $3.9B $5.5B $8.2B 10% 35% 90% Black Friday Sales Forecast
- 16. 16 What-‐If Analysis on Steroids *With beneficial side effects What-‐If What Utilization Rate should we maintain to maximize profit? Profit per Unit: 10.00$ Missed Order Cost (5.00)$ Plant Capacity: 100 Utilization Rate: 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Units Produced -‐ 10 20 30 40 50 60 70 80 90 100 Product Profit -‐$ 100$ 200$ 300$ 400$ 500$ 600$ 700$ 800$ 900$ 1,000$ Cost of Missed Orders -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ -‐$ Profit -‐$ 100$ 200$ 300$ 400$ 500$ 600$ 700$ 800$ 900$ 1,000$ Input Variable TradiHonal What-‐If SimulaHon 75% chance producHon will be less than 100 units.
- 17. in/drewpulvermacher REAL WORLD RISKS Pa?ent Flow Mee?ng an Order Due Date Tampering with a Stable Process Modeling Customer Loyalty Long-‐Term Value of a Customer Reducing Churn Inventory Modeling Es?ma?ng Dynamic Market Share Warranty Costs for a Product When would you use SimulaHon Modeling… Corporate FP&A
- 20. 20 DEMO Office of Finance
- 21. 21 Pa?ent Flow
- 22. 22 Why SPSS…
- 23. 23 Why SPSS… Black Friday…. $65M $67M 2012 2013 Black Friday….
- 24. Black Friday…. $65M $67M 2012 2013 24 Why SPSS…
- 25. 25 Drew@PerformanceG2.com Who is using it… REAL WORLD RESULTS
- 26. 26 26 SimulaHon Modeling: TODAY Building Risk Management at Lego August 5, 2013 Today, the sophis?ca?on of LEGO’s Enterprise Risk Management (ERM) framework is widely recognized. It is one of the foremost companies to use Monte Carlo simula?on to quan?fy risk and present key risk informa?on to its board of directors for decision-‐making purposes. This gives the company a true understanding of the vola?lity that it believes is inherent in its ac?vi?es, in order that it can act to pre-‐empt it.
- 27. in/drewpulvermacher YOU CAN DO THIS & PerformanceG2 WILL HELP Regression Mul?variate Analysis Forecas?ng Op?miza?on Modeling Markov Chains Queuing Theory War Gaming Neural Networks Linear Networks Decision Trees Bayesian Networks ANALYTICS
- 29. Thank you for attending our webinar 29 Drew@PerformanceG2.com " Call us: 877.742.4276 " Email us: info@performanceg2.com or drew@performanceg2.com " Visit our web site: performanceg2.com " Read our Analytics blog: performanceg2.com/blog " Follow us: " (Twitter) @performanceg2 " (Facebook) /performanceg2 " (YouTube) /performanceg2 " (LinkedIn) /performanceg2-inc
- 30. Predictive Analytics Series 1. Execu?ve Introduc?on 2. Data Modeling 3. Simula?on 4. Op?miza?on – June 2014 5. Data-‐Driven Leadership