MBA Lecture:A BETTER APPROACH toSupply Chain RiskManagementPaul BarschMarketing Director
Modern Day SCM Assumptions                 •   Signal based  JIT… is good   •   Inventory is waste                 •   Rig...
Modern Day SCM Assumptions                   •   Cost reduction via elimination  Lean … is good       of waste (non-value ...
Modern Day SCM Assumptions                   •   Statistical forecasting using Forecasts … are       historical data mostl...
Problems with PredictionsWhat’s This?
Problems with Predictions“In all my experience I have neverbeen in any accident of any sortworth speaking about. I have se...
Problems with Predictions"I think there is a worldmarket for maybe fivecomputers."    - Thomas Watson, chairman of IBM, 1943
Problems with Predictions• “We’ve never had a decline in  house prices on a nationwide  basis. So, what I think what is  m...
More Problems with Predictions• In the early 1990s, JK  Rowling’s Harry Potter and  the Philosopher’s Stone was  rejected ...
So much for Conventional Thinking…
Assumption 1: Normal Distribution  – “Known Knowns”• Assumes  normality• Independence  (i.e. coin flips)• Randomness• Unli...
Assumption #2- Bayes for “Unknown Knowns”• Bayes is subjective probability – a  measure of belief.• Not precise, not objec...
Assumption 3: Fat Tails – the “Unknown,Unknowns”• Non “normal”  distribution• Outliers• Black Swans:  1 in 100 year  event...
Belief vs. Reality     What we assume                           What happens very                      infrequently – but ...
Beware Mickey Mouse Probabilities                   • Before the -23% drop in the 1987                     crash, the wors...
Fat Tails Happen!• Watch the PBS Frontline video on  Fukushima Daiichi nuclear disaster• http://video.pbs.org/video/220284...
Who Needs a Microcontroller Anyway?• 40% of world’s embedded microcontrollers (for cars)  made at factory disrupted by Fuk...
Drastic Changes in Past 20 Years•   Dot.com/Y2K•   World is Flat Phenomenon•   New Characteristics:    –   Technology Adva...
Are We Sitting on Dynamite?•    “Globalization creates interlocking fragility,     while reducing volatility and giving th...
Implications • Humans mostly think   linearly – tomorrow will be   like today • World was loosely coupled   and less compl...
Solutions• Near shoring – bringing work  back home• Examine risks up and down  supply chain   – Beyond Tier 1 suppliers• R...
Food for Thought•   Remember – things that haven’t happened before will happen.    Things that have happened, will happen ...
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MBA Lecture: Supply Chain Risk Management

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The world is getting more complex and interdependent, leaving the old supply chain management assumptions out in the cold. Executives need a new way of thinking when it comes to supply chain risk and better options on dealing with volatility. This presentation discusses problems with predictions, a new framework for risk management, and potential solutions for more effectively countering the effects of globalization.

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  • Thank you very much
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  • Hi Paul - Great presentation. Can you please share o my email at gery.nurit1@gmail.com?
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  • Joseph, thanks so much for viewing and commenting. Real time monitoring helps - no doubt. However, better than monitoring (as is), or response (after the fact), I'm a huge advocate of prevention and/or adding robustness where possible.
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  • I enjoyed your presentation. As you imply, we need to have a greater degree of attention to real time monitoring of supply chain risk in order to help mitigate the impacts of the types of events you mention in your presentation.
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MBA Lecture: Supply Chain Risk Management

  1. 1. MBA Lecture:A BETTER APPROACH toSupply Chain RiskManagementPaul BarschMarketing Director
  2. 2. Modern Day SCM Assumptions • Signal based JIT… is good • Inventory is waste • Right inventory, right place, right time
  3. 3. Modern Day SCM Assumptions • Cost reduction via elimination Lean … is good of waste (non-value adding work) • Improve the flow (smoothness)
  4. 4. Modern Day SCM Assumptions • Statistical forecasting using Forecasts … are historical data mostly accurate • Usually simple linear regression • Collaborative
  5. 5. Problems with PredictionsWhat’s This?
  6. 6. Problems with Predictions“In all my experience I have neverbeen in any accident of any sortworth speaking about. I have seenbut one vessel in distress in all myyears at sea…I never saw a wreckand have never been wrecked, norwas I ever in any predicament thatthreatened to end in disaster of anysort. -Edward John Smith- Captain, Titanic
  7. 7. Problems with Predictions"I think there is a worldmarket for maybe fivecomputers." - Thomas Watson, chairman of IBM, 1943
  8. 8. Problems with Predictions• “We’ve never had a decline in house prices on a nationwide basis. So, what I think what is more likely is that house prices will slow, maybe stabilize, might slow consumption spending a bit. I don’t think it’s gonna drive the economy too far from its full employment path, though.” -7/05
  9. 9. More Problems with Predictions• In the early 1990s, JK Rowling’s Harry Potter and the Philosopher’s Stone was rejected by 12 UK publishers.• “Not unique enough to stand out in the marketplace” – recording studios to Madonna in early 1980s
  10. 10. So much for Conventional Thinking…
  11. 11. Assumption 1: Normal Distribution – “Known Knowns”• Assumes normality• Independence (i.e. coin flips)• Randomness• Unlikely events are rare; many standard deviations from mean 66-95-99.7
  12. 12. Assumption #2- Bayes for “Unknown Knowns”• Bayes is subjective probability – a measure of belief.• Not precise, not objective. We can learn from approximations• Allows making of predications with no prior information at all• Infer where objects are based on learned experience; each new bit of information gets you closer to certitude, keep revising probabilities• Compute power helps• The hunt for U-Boats and Soviet Subs!
  13. 13. Assumption 3: Fat Tails – the “Unknown,Unknowns”• Non “normal” distribution• Outliers• Black Swans: 1 in 100 year events now happening every 2-3 yrs• “We need to start thinking about the inconceivable” – N.Taleb
  14. 14. Belief vs. Reality What we assume What happens very infrequently – but with large impact!
  15. 15. Beware Mickey Mouse Probabilities • Before the -23% drop in the 1987 crash, the worst previous in sample move was close to 10% • “Not in a million years would we have expected this gyration to be as vicious and enduring as it has been,” – Steven Solmonson, head of Park Place Capital Ltd. • “A turkey cannot figure out what is in store for it tomorrow based on the events of today.” – Nassim Nicholas Taleb
  16. 16. Fat Tails Happen!• Watch the PBS Frontline video on Fukushima Daiichi nuclear disaster• http://video.pbs.org/video/2202847024/ (start at 1:25 til 8:25)
  17. 17. Who Needs a Microcontroller Anyway?• 40% of world’s embedded microcontrollers (for cars) made at factory disrupted by Fukushima • Controls engine • Sensing systems for airbags • Dashboard display systems • GPS Navigation • Collision warning • Advanced features such as self parking systems, internet access Production of 370,000 cars delayed at Toyota
  18. 18. Drastic Changes in Past 20 Years• Dot.com/Y2K• World is Flat Phenomenon• New Characteristics: – Technology Advances – Speed and Zero Latency – Interconnectivity – Fewer buffers – Consolidated players• Now we live in a system – fewer islands• Is the World More dangerous?
  19. 19. Are We Sitting on Dynamite?• “Globalization creates interlocking fragility, while reducing volatility and giving the appearance of stability. In other words it creates devastating Black Swans”.• “Almost all banks are interrelated. The increased concentration among banks seems to have the effect of making financial crisis less likely, but when they happen they are more global in scale and hit us very hard.”• “(The Great Moderation). True, we now have fewer failures, but when they occur .... I shiver at the thought. The government-sponsored institution Fannie Mae, when I look at its risks, seems to be sitting on a barrel of dynamite, vulnerable to the slightest hiccup”. -Nassim Taleb, 2007
  20. 20. Implications • Humans mostly think linearly – tomorrow will be like today • World was loosely coupled and less complex (oceans as buffers) • Things that were once loosely coupled; now tightly correlated because of network effects and derivatives • Connectedness = Domino Effect, especially when there are errors
  21. 21. Solutions• Near shoring – bringing work back home• Examine risks up and down supply chain – Beyond Tier 1 suppliers• Redundancy• Disaster Planning for “known knowns” and “unknown knowns”• Doing Nothing – “It is difficult to motivate people in the prevention of Black Swans... Prevention is not easily perceived, measured, or rewarded; it is generally a silent and thankless activity. History books do not account for heroic preventive measures” – Taleb (2005)
  22. 22. Food for Thought• Remember – things that haven’t happened before will happen. Things that have happened, will happen again.• Your “worst case scenario” probably isn’t really the “worst case scenario” (think: Fukushima’s seawall).• With knowledge that things are fragile– better to be a little wrong (limited loss) than majorly wrong (out of business)• Don’t think of Black Swan’s as only negative (what I can avoid) – Think of them as “options”. Little investments with limited loss. Many have more upside than downside – Trial and error are options with small costs. There are huge pay-offs for being right such as big discoveries (positive Black Swan).

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