Physics Envy: Pervasive, But Not Incurable

Everywhere you look, it seems, people are talking about “physics envy”.  This derisive term mocks the attempt of economists and other social sciences practitioners to imbue their disciplines with the equations and mathematical rigor of physics – a rigor that many believe fails when applied to the messy environments of disciplines like sociology or economics.  It’s not a new term – economist Philip Mirowski contributed to the Finnish Economic Papers series way back in 1992 with a piece entitled “Do Economists Suffer from Physics Envy?”

kinetic energy, not supply & demand

Eighteen years later the answer from many observation posts along the byways of public discourse appears to be: yes, they most certainly do, and so do their fellow travelers, business and financial markets experts.  After all, we just barely survived the most devastating economic event of our times, deeper and more far-reaching than any downturn since the Great Depression, and all the high priests of the field can do is shake their heads and say “wow, I sure didn’t see that coming.”  Distrust of fancy math is rampant in all walks of business life.  That presents a real problem for enterprise decision-makers at a time when they need smart quantitative tools – yes, fancy math and all – more than ever.  Markets are more complex than at any time in human history.  Giant waves of transactional data inundate marketing managers with new information every day.  Managers need science to help them gain valuable insights into the markets for their products and services – but how do they know that the growing number and variety of scientific marketing tools out there aren’t infected with the nasty symptoms of physics envy? Read the rest of this entry »

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Red Beads, Management Tools and the Elusive Quest for Strategic Advantage

Management tools do not automatically confer strategic advantage.  In principle any commercially available modern management tool from Total Quality Management to Lean Six Sigma, from Supply Chain Management to Price Optimization Models, is available to any and all paying customers on equal terms.  Two competitors in the same industry space may employ the exact same suite of management tools, but it is a good bet that their relative performance will vary considerably over time.  I don’t find this particularly surprising: generally speaking I subscribe to the view of competitive strategy vis a vis productivity enhancement tools eloquently expressed by Michael Porter in his 1996 Harvard Business Review article “What is Strategy?”  To wit: “Competitive strategy is about being different.  It means deliberately choosing a different set of activities to deliver a unique mix of value”.  That is to say, the act of hiring a Process Re-engineering implementation team or reinventing oneself overnight as a Learning Corporation will not automatically confer sustainable advantage.  Rather it is how (and if) those tools are integrated into a portfolio of aligned, mutually reinforcing organizational activities distinctive from those of competitors that will most likely make the advantage difference.

This makes sense to me.  Nonetheless I am often astonished by the frequent tendency among many corporate decision-makers to conflate the application of some management tool with a fabulous consultant-ese moniker into a “magic bullet” that will effortlessly change the organization overnight from a laggard to a market driving leader.  Then, as egregiously as they confer magic powers on the tools, after a few fiscal quarters the decision-makers realize they are not getting sustainable performance improvement, decide in their infinite wisdom that the inherent inadequacy of the tools is at fault, and consign them to the trash heap of unrealized expectations.

meaningful tools or random noise?

This misguided tendency – to ascribe awesome powers to something and then discard it for the wrong reasons – brings to mind one of my favorite management lessons: a timeless exercise developed by W. Edwards Deming called the Red Beads Experiment (actually, what I call “timeless” Deming himself calls “a stupid experiment you will never forget”).  Deming was one of the founding fathers of Statistical Process Control, itself a prototype of the management tools that abound in our age, and something of an iconic hero for several generations of Japanese business leaders dating back to the 1950s.  The phrase “you can’t improve what you can’t measure” is often attributed to Deming, though not always in the right context.  A more accurate reflection of his philosophy would perhaps be “measuring the wrong thing is much worse than not measuring at all”, and that brings us back to the Red Bead Experiment and its lessons for managers of today in the use and misuse of performance management tools.

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A Beer on the Beach, and Other Mysteries of Fair Pricing

Businesses want us to view them as fair – there is arguably nothing more important than a reputation for fairness in the daily marketplace of commercial transactions. As business managers what can we do to ensure that decisions we make – about pricing or other actions that are clearly visible at the point of the customer-product interaction – will be seen as fair? Is fairness something absolute, immutable and precisely quantifiable?  Or is it situational, capricious and ever-changing?  The bad news, perhaps, is that ‘fairness’ is a very elusive notion to pin down with certainty – it’s hard to put fairness in a bottle and label it as such.  The good news is that fairness more than anything else is about perception and the relative judgments of your customers and potential customers in varying demand situations.  That’s good news because the better you understand the granular contours of your demand environment and the precise needs and propensities of your customers, the more likely you are to understand how to make decisions in that environment that are both fair to the customer and profit-optimizing to your business.

thirst-quenching - but is it fairly priced?

Here’s a test of fairness.  Imagine you are lying on the beach on a hot summer day and find yourself craving a cold, satisfying beer.  What price would you be willing to pay to quench your thirst?  Now imagine two alternative scenarios.  In one, the only place within walking distance to buy a beer is the poolside bar of a swanky five-star beachfront hotel.  In the other, there is a rather run-down beachfront grocery store that sells beer.  Imagine further that both the hotel and the grocery store sell the exact same brand and type of beer.  Does your maximum price point change depending on whether you think you are getting the beer from the hotel or the store?  Do you think it is fair for two different establishments to sell the same commodity for a different price? Read the rest of this entry »

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Fair Price, Optimal Price

Businesses seek to maximize the value they can obtain from their revenue models.  Price is the key lever decision-makers can operate to influence revenue, and in recent years a growing number of businesses have sought to implement strategies for actively managing the price lever – strategies such as demand management and revenue optimization.  However businesses are also highly sensitive to the perception by individual consumers and the society at large that their prices are fair, in other words that they do not violate widely held individual or societal norms.  Fair pricing matters – it matters to me, and to you, and perhaps ever more so in a climate characterized by economic uncertainty, downward pressure on demand and a perceptible decrease in the citizenry’s trust of public and private institutions.

Fortunately for business decision-makers, fair pricing and optimal pricing are not at odds with each other but can comfortably coexist.  Over the course of the coming weeks my colleagues at Sentrana and I will be approaching the rich topic of fair pricing in a series of exchanges on this blog.

debating the age-old question of fair price

What is a fair price?  This question has perplexed humanity throughout history.  Leading thought output of the ages, from Aristotle’s Nicomachean Ethics to the Summa Theologicae of  Thomas Aquinas, Pierre de Fermat’s probability proofs and Adam Smith’s classsical economics, have all weighed in with considered opinions on the fairness and justness of alternative ways to price economic goods and services, and the debate continues today.  A series of letters exchanged between Blaise Pascal and Pierre de Fermat in 1654 is often regarded as a primal cause of the development of modern probability theory: this exchange was actually an attempt to establish a scientific basis for the notion of fair price.  In his paper “The Unity and Diversity of Probability” Rutgers professor Glenn Shafer shows how these letters created hypothetical games of value that we today can recognize as the application of probability methods to defend a price as ‘fair’ under conditions of uncertainty. Read the rest of this entry »

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From 1.0 to 4.0 in 130,000 Years: Pricing’s Extraordinary Adventure from Haggling to Scientific Micromarketing

Pricing has evolved from the ancient art of haggling to the application of scientific methods to the micromarket.  In a sense we are going back to the unique knowledge of individual customers and products that existed in the old bazaars and town squares – but we’re armed with powerful technological tools of the 21st century.  The world of Pricing 4.0 is upon us.

But let’s start at the beginning.  In the beginning there was the trade, and the trade saved humanity.  Seriously.

Homo neanderthalensis – Neanderthal man – had been occupying the planet for about 200,000 years when our ancestral gene pool, Homo sapiens, showed up on the scene (both species evolved from a common ancestor Homo habilis that had begun to make and use basic tools about 2.5 Ma (million years ago), but their evolutionary paths diverged some 600,000 Ma).  Despite what would seem to be a solid first-mover advantage thriving in the harsh Ice Age climate of Europe and Western Asia, Neanderthal man vanished from the face of the earth sometime around 30,000 years ago while the progeny of H. sapiens went on to give the world the Hanging Gardens of Babylon, Magna Carta and How I Met Your Mother.  In 2005 academicians Richard Horan, Erwin Bulte and Jason Shogren presented a well-researched argument for why this happened: trade.  According to their paper “How Trade Saved Humanity from Biological Extinction: An Economic Theory of Neanderthal Extinction” it appears that our ancestors had particularly honed skills in organizing specialized activities such as tool-making, and trading their goods between different social organizations.  As the Ice Age melted and populations grew and migrated, the skills of free trade became an evolutionary competitive edge. Read the rest of this entry »

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Why Pricing Must Be a Continuous Process (Part 1)

At some point, every homeowner learns an important lesson about how to save money on air conditioning during the hottest part of the summer. Generally speaking, it costs less to keep your house at a relatively even, tolerable temperature, then to turn off the unit entirely during the day and blast the A/C in the evening when you are home. The process of re-cooling the entire house each time wastes a lot of energy to get to a comfortable temperature again.

Multiple optimal prices can exist for a product, even in transparent markets. Note that all of the prices in this image apply to the exact same HP printer.

The lessons of efficiently cooling a home can be applied to many scenarios. In business, having a system in place for tweaking procedures continuously is easier to manage over time than are prolonged periods of stasis followed by dramatic transformations. Transformations are complicated. They are often expensive. If too much time passes between transformations, the organization’s inertia coefficient (a 100% made-up term) passes a critical threshold. After that point, two outcomes are the most likely, with a few shades of gray in between: (1) transformation projects mushroom from merely “expensive” to “expensive and painful”, or (2) the company is too lethargic to change, effectively dooming the business to eventual defeat or absorption by more innovative rivals. For the sake of comprehensiveness, I have to acknowledge that for a fortunate few, “federal bailout” must now be added to this list as a third possible outcome. However, in a few years we will see if my suspicion that outcome three eventually finds its way back to outcome two turns out to be correct. Read the rest of this entry »

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Revenue Optimization: Coming Soon to a Big Drug Company Near You

Large brand-name drug companies – Big Pharma in the common vernacular – are not exactly known for competitive pricing or razor-thin margins.  For 2008 the industry was ranked third most profitable in the U.S. according to Fortune magazine, with average profit-to-sales margins of 19.3%.  That’s a pretty fat comfort zone compared to the scorched-earth landscape of many other industries…or is it?  Until recently Big Pharma was pretty consistent at the #1 spot in those rankings. A look under the microscope reveals some troubles bubbling up in the hitherto happy world of magic molecules and blockbuster brands.  These days the whole country seems transfixed by the subject of healthcare, and no matter what does or does not come out of the legislative sausage factory this year, some major trends are afoot that have potentially far-reaching consequences for Big Pharma and may influence the normally lackadaisical approach drug makers have exhibited to the prices they charge for their brand-name drugs – in particular when those drugs reach the end of their exclusivity protection period and go off patent. Read the rest of this entry »

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How Major League Baseball Can Steal Profits Back From Ticket Scalpers Using the Right Pricing Solution

The National Baseball Hall of Fame recently inducted Ricky Henderson, one of baseball’s most prolific base stealers with a record 1,406 bases stolen in his career – yet, Major League Baseball has failed to deal with scalpers who steal millions in profits from their franchises every year. Scalpers have seized the lost opportunity where Baseball franchises lock in their ticket prices months before the season starts and choose not to adjust prices throughout the season. A more efficient secondary market thrives due to the scalpers’ ability to factor in several game variables (e.g. strength of opponent, seat type, starting lineup, weather conditions, etc.), as well as buyer-specific factors (e.g. age, attitude, clothing, jewelry, etc.) to determine the maximum (and therefore optimal from the seller’s perspective) price that each person is willing to pay. Another advantage for scalpers is their ability to immediately negotiate if the buyer doesn’t accept the first price, carefully moving the price down until both the buyer and seller agree upon a satisfactory price. To help reclaim these lost profits, the San Francisco Giants are now testing dynamic pricing software to help adjust ticket prices based on the expected consumer demand for each game. So what exactly is dynamic pricing, and is it powerful enough to replace the individualized pricing, negotiation, and sales effectiveness of ticket scalpers? Read the rest of this entry »

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Optimizing the Playing Field Where the Great Deleveraging Meets Freetopia

Two economic developments are currently having a profound effect on the playing field of consumer demand.  One is the Great Deleveraging: the painful scaling back of the household debt burden that reached a historical peak, at 133% of household income, in late 2007.  The Great Deleveraging means that household dollars that several years ago would have been earmarked for new discretionary spending are instead being diverted to pay down the hangover of old discretionary spending.  As fewer dollars chase the same supply of products we would expect some combination of lower prices and/or a reduction in the quantity of products supplied – a reversal of the SKU proliferation that has been a dominant feature of our consumer experience for the past several decades.

At the same time, though, a second major event appears to be unfolding:  the emergence of the economics of “free,” or “freeconomics” as provocatively described by Chris Anderson of Wired magazine in his recently published book “Free: The Future of a Radical Price.”  “Free” in Anderson’s formulation is the notion that the near-zero cost of doing business online turns upside down the conventional notion of economics as the science of parsimonious choices under conditions of scarcity.  The “economics of abundance” in Anderson’s phraseology may filter through the prism of our traditional understanding of markets as being good news for cash-strapped consumers (more stuff for which I don’t have to pay money) and bad news for suppliers of goods and services (“free” doesn’t sound like a price that will shore up my profit margins). Read the rest of this entry »

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Missing the Ocean for the Stream: What We Can and Cannot Learn from IBM’s New Breakthrough

As part of its perpetual quest to reinvent and perfect its business model, IBM has made an aggressive push into the analytics market in the last half-dozen or so years. The company’s slick, though occasionally confusing ad campaigns (remember those ads with the mysterious red box being unveiled?) often announce its new initiatives, though it is not always clear that a new announcement is indeed a major one. In the analytics space, however, Big Blue does mean business. The announcement of its sizable new business analytics and optimization division is clearly intended to prove as much. Shortly after its announcement, IBM also unveiled a new stream computing platform called “System S” to much fanfare. The breathless enthusiasm of business journalists, technology bloggers and investment analysts has been palpable. But what exactly does this technological advancement do, and what does it mean for your business?

To answer this question, let’s begin briefly by dissecting what IBM has introduced. Imagine that you are receiving a continuous stream of data, such as stock prices on the Nasdaq. These figures must be quickly analyzed so that the proper buy and sell orders can be placed. Suppose that you also need to base your decisions not just on the Nasdaq prices but also the numbers figures coming in from dozens of other exchanges. Read the rest of this entry »

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