Webinar - The "Flaw of Averages" How Our Methods Doom Our Estimates and What We Can Do About It
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Date: Tuesday, June 9th, 2020
Time: 7:00 PM ET/ 6:00 PM CT/ 5:00 PM MT/ 4:00 PM PT
Duration: 45-60 minutes         
Date & Time
Tuesday June 9th, 2020 6:00pm CDT
End Date & Time
Tuesday June 9th, 2020 7:00pm CDT
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Webinar Link / Meeting Instructions
Registration is required to join this event. If you have not registered, please do so now:
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Brief presentation outline:
  • Estimates are critical to most, if not all, businesses. Despite the critical nature of estimates, most of the techniques in use do not give good results. As a result, we jeopardize schedules, profits, customer relationships, and employee morale far too frequently. Why are our estimates so bad?
  • Many of the estimates that we rely upon are generated by using “average” assumptions to give expected outcomes. Average inputs should give average results, right? Wrong! In almost any system of reasonable complexity, average inputs will not generate average outputs. As a result, many of our estimates are overly optimistic and hence overly risky. Even in those rare situations where average inputs do generate average results, the actual outcome will almost never be at the average that was estimated. Therefore, it is critical for good decision making to generate estimates that include a view of the likely variability of the outcome. Decisions made without knowledge of likely variability are inherently risky and doomed to fail.
    The Discussion:
  • Why properly understanding historical data is critical for building good estimates
  • Why using averages and static analyses to produce estimates often leads to incorrect results and provides no insight into the range of possible outcomes
  • How relatively simple techniques such as Statistical Process Control and Monte Carlo Simulation can dramatically improve both our estimates and our insight
Dave Northcutt
President: Catskill Analytics
MS Computer Science, MA Economics, MS Statistics
Presenter Bio: Dave is a retired Industrial Statistician with over 35 years of experience driving improvements in the IT industry. Dave was most recently an IBM Distinguished Engineer specializing in data analysis, predictive modelling, and continual improvement in IBM’s services business.
Dave has worked with teams around the world to help them improve their businesses by helping them to understand their data. Throughout his career, Dave has always sought to make the teams he worked with self-sufficient, not simply give them the answers.
Dave holds Master’s degrees in the following fields: Economics (Northwestern), Computer Science (Univ. of Illinois at Chicago), and Statistics (Rutgers).
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Date & Time: 06/09/2020 06:00:00 PM CDT