Topics
Finance and budgeting
- A Model for Return on Engineering Expenses
- Growth, Profitability, and the Stock Price
- Metrics for cyclical businesses
- Stock buybacks
Investing
Product development
- Queuing theory and product development
- A Model for Return on Engineering Expenses
- The Essential Product Investigation Phase Gate
- So you want to ship the product early?
General Management
- Customer Equity
- The best and worst job in the company
- Tricks of the trade
- Woe be the average man
- Magic elixirs for business
- What goes around
- How to get laid off
Research
Strategy
- Growth, Profitability, and the Stock Price
- But thinking makes it so
- The experience curve
- Mommy, it's not fair!
- Attacking the entrenched competitor
Marketing and sales
Operations and Manufacturing
People and culture
- Silicon Valley melting pot
- What goes around
- Tricks of the trade
- Thank you Japan
- Bah, humbug
- How to get laid off
© Lance A. Glasser 2007-2011
All Rights Reserved
When I originally wrote this essay I railed against averages. Since that time we have experienced the Great Recession and I have spent more time thinking about this topic. While before I never trusted averages, I must admit that for many things in business I no longer even trust standard deviations. It is not that either is mathematically wrong, it is that they lead one to qualitative conclusions that do not sufficiently presage dramatic or outlier events.
Though I had read Against the Gods: The Remarkable Story of Risk and When Genius Failed: The Rise and Fall of Long-Term Capital Management, I underestimated the impact of the fat probability tails. Trained as an engineer, I am facile with Gaussian or "Normal" distributions, stationary processes, correlations, linear systems, and so forth. This is knowledge is backed not just by training, but also by personal real-world experience over decades. I have lead teams that built some fantastically complex electro-opto-mechanical machines. It seemed a miracle that they worked, but they did. They wouldn't have stood a chance if the physical world in which engineers live had fat tails.
On the other hand, I have worked a lot with people. Unless you care about their weight or height, the affairs of men and women are decidedly not Normal. I also have personal experience here. As a General Manager and later as a Group VP managing a billion dollars of annual revenue, I confronted volumes of real-world data on bookings and, frustratingly, on project delays. I tried to apply the statistics I knew to these data. They emphatically did not fit Normal distributions. There were many too many outliers. As I read Taleb's book on The Black Swan: The Impact of the Highly Improbable, I could see his assertions in my own data. Gauss must have had great marketing to have his distribution called "Normal."
Averages lie.
And for the affairs of men and women so do Normal statistics.
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The opinions here do not necessarily represent the views of any past, present, or future employer.
I am particularly interested in comments and stories related to my business essays and on pointers to original or insightful references. Thank you.
