Yet, that’s exactly what happened leading up to the 2008 financial crisis where banks bundled shaky and suspect mortgage loans known as collateralized debt obligations (CDOs) and resold them to pension funds and other investors worldwide. And while some financial services companies have since settled with the United States Securities and Exchange Commission for their role in misleading investors, most have not admitted fault.

Which leads to a larger question—when is it acceptable to knowingly sell a substandard product?

Charles Morris, author of “The Two Trillion Dollar Meltdown” aptly describes the period leading up to the financial crisis of 2008 as “sheer idiocy”. To start with, he says, debt to equity—or leverage—by many financial firms was as high as 100:1. In addition, high risk mortgages were more than the flavor of the month, as CDOs in 2006 were created from “more than 40% of all mortgage originations.” And of course, we haven’t even mentioned derivatives such as credit default swaps (CDS) that tied global banks together in an intricate web of interdependency.

What is the end-result of the 2008 financial crisis? The International Money Fund (IMF) estimates losses from the financial crisis at $4.1 trillion, jobless rates still hover at 12.5% or more in some states, and 401K account’s are still recovering from losses of 30-50% and sometimes more! Indeed, if anything has been learned from this global meltdown it’s that —caveat emptor still reigns—otherwise known as “let the buyer beware”.

Let’s get back to CDOs for a minute. A collateralized debt obligation is simply a bundle of 100-200 mortgages that are sliced and diced into “tranches” and then priced and sold to investors based on a risk management formula. Investment banks engaged in buying mortgages from “mortgage mills” and then packaged and resold these CDOs to investors. Not a bad concept, unless you know beforehand that the package consists of fraudulent and dubious loans that will likely never be paid.

In fact, Carl Levin, chairman of the US Senate’s Permanent Subcommittee on the Financial Crisis scolded a row of investment bankers on the process of producing CDOs and other financial products saying, “You people think it’s a piece of crap, and go out and sell it!”

But here’s the rub—as the writer of the Financial Times Lex Column describes it; “…selling crap is no crime per se.” In fact, the writer goes on to say, “If the SEC is so against the practice, it should also prevent people from the buying of crap too.”

In fact, there are many businesses that profit greatly from the buying of distressed assets including foreclosed homes, flailing companies, and even tarnished brands. Obviously, these sales should continue. However, the writer of Lex must also remember that some US states do prohibit the “knowing” sale and re-sale of defective products; for a good example see lemon laws for pre-owned cars.

A Financial Times reader responds—tongue in cheek—to the Lex column by saying if it is indeed a legitimate business practice to sell substandard products that the Lex column author, should “bear this principle in mind (the next time he/she) visits a doctor, dentist, pharmacist, lawyer or accountant.”

With the advent of the internet, the Smartphone explosion and now social media, global companies cannot afford to take the risk of knowingly selling sub-standard products. This advice of course, only applies if companies care about brand perception, reputation and integrity.

For many companies—reputation is one of the last bastions of competitive advantage. Millions if not billions of dollars in brand equity and goodwill are at stake. And consumers have long memories. There are no real shortcuts when it comes to quality.

Questions:

• In an age of “asymmetric information”—where the seller often knows more than a buyer—why are brands so important?
• When is it OK to sell a substandard product?

In an article from “The Observer,” John Naughton wonders in amazement at how society ever managed without the Internet. Naughton ponders a world without Google, Skype, instant messaging, and online bank accounts. And while the Internet has created boom for most of us, the rise of social media hasn’t been sweet ambrosia for all companies. In fact, with social media and Internet technologies, now company decisions and actions are mostly public, including those of front-line employees. Now, actions that happened last week, last night, or 10 minutes ago can be broadcast across the globe in seconds, creating very dangerous challenges for company branding and reputation efforts.

In the Financial Times article “Perils of a Tarnished Brand,” authors Morgen Witzel and Ravi Mattu notice that even the most scripted and orchestrated product launches can go haywire. And even when “best-intented” marketing plans are well-executed, companies can be exposed to the ramifications of their daily operational and strategic decisions (e.g., Google in China and BP). “What affects reputations, in turn affects brands,” the authors point out.

Every employee is a brand ambassador, and brand management is no longer simply the purview of marketing managers. Even the best branding intentions can go awry when actions don’t back up corporate speak, say Witzel and Mattu.

Of larger concern however, is marketing cost-cutting trends in the name of efficiency that potentially leave brands and reputations exposed.

Robert Mabro, Honorary President of Oxford’s Institute for Energy, describes this problem in a letter to the Financial Times. He writes, “(Companies) no longer want to employ specialists in soft matters, such as political issues and the like. When an accident occurs, they find themselves hopelessly unprepared. This of course (ends up) destroying shareholder value!” Moreover, economist John Kay sums up the problem quite succinctly, “Yesterday’s cost-savings are so often today’s corporate crisis.”

One potential solution is for companies to invest more in “softer matters” like brand, reputation, crisis and risk management. Undoubtedly, some of these considerations are tough to justify in an age of narrow return on investment marketing calculations such as cost per lead.

However, Internet and social media technologies that transmit events, news and crisis accounts—at the speed of light—aren’t going away. To succeed in such an environment, companies must invest in the softer functions mentioned above even when “payback” doesn’t appear imminent.

It’s difficult to forecast all types of crises that could occur. A much better plan is preparedness. Is your company up for the challenge?

Related: Financial Times “It Pays to Expect the Unexpected“

Contagion takes many forms in our global economy. Some definitions for contagion include the “spread and transmission of disease, ideas, influence and emotions.” Another aspect of contagion is that it spreads in unimaginable ways. Thus, sometimes what seems like a tiny spark ends up as a full fledged forest fire.

Marketing professionals know that contagion can sometimes be extremely dangerous to our companies, brands and reputations. Therefore, it’s imperative to not only recognize early warning signs of contagion, but to react quickly when contagion spills over. Below are five strategies that can help us plan, prepare, manage and even seize the advantage when contagion strikes.

First, manage your risks. Author Nassim Taleb of Black Swan fame, says the essence of risk management, “lies in maximizing the areas where we have some control over the outcome while minimizing the areas where we have no control of the outcome.”

One method of risk management is to maintain a significant buffer against unforeseen forces. For example, in financial services, companies are required by regulations to maintain a liquid capital cushion to buffer financial losses. Financial services firms also measure their risk exposure via Value at Risk (VAR) modeling or other stress test methods. And while it can be intelligently argued such methods are flawed, for many companies they remain the best tools available for analytical risk management.

Second, calmer heads prevail. When the European debt crisis threatened to engulf nation states in the European Union, German Chancellor Angela Merkel did her very best to stay above the fray. While contagion swirled around Merkel, she maneuvered among constituents, political leaders and central bankers to find a solution that would benefit both Germany and the greater European Union. And though some pundits argued that Merkel perhaps made matters worse by delaying action for weeks, sometimes it pays to gather information and not make hasty decisions.

Third, have a plan. Suppose a crisis hits, have you considered the likely outcomes? This is where scenario planning can help. Scenario planning is the consideration of known facts with plausible alternatives. Think about a given a situation and the top five likely outcomes. Then prepare a plan of action. Afraid you won’t get scenario planning right? Author Bill Ziemba reminds us that it’s darn near impossible to get scenario planning exactly correct. “What is important,” he says, “is to cover the board of possible occurrences. Then you will make sound decisions with risk under control.”

Fourth, consider using overwhelming force to deal with contagion. Sometimes the only way to restore confidence is via “shock and awe” or the use of the “big guns”. Best practices include the recent response of forty-three children’s medicine manufacturers to remove all potentially tainted products from store shelves until contamination causes can be determined. In another example, facing fraud allegations by the Securities Exchange Commission, Goldman Sachs hired Greg Craig, the lawyer who “saved Bill Clinton from impeachment.” Instead of responding in piecemeal to contagion, often it is better to respond in force.

Fifth, when contagion strikes look for opportunities in chaos. When the Wall Street “flash crash” occurred on May 6th 2010, liquidity evaporated from the market and bellwether companies like P&G saw their stock drop 35%, while global consulting firm Accenture’s stock traded briefly for one penny! Meanwhile, on financial news network CNBC, the normally hyperactive and boorish Jim Cramer calmly announced that anyone with modicum of common sense should buy those two stocks. Ultimately, the market corrected itself within a twenty-minute time frame and those who listened and immediately acted on Mr. Cramer’s advice made a mint. Where there’s panic, nervousness or irrational behavior, there’s also likely opportunity for gain—if you’re paying attention!

With today’s global economy tightly linked by capital, labor, and information flows at the speed of light, it’s not uncommon for bad news, nervousness, or outright panic to spill across borders and disrupt even the most stable of companies and industries. Moreover, what may seem like a non-event can quickly transform into a full blown crisis.

Listed above are five strategies when contagion swirls. Do you have others?

Now if you didn’t, please don’t feel too bad. Most economists also missed the signs of contagion.

What is contagion? Some dictionaries call contagion the “spread and transmission of disease, ideas, influence and emotions.” Other financial dictionaries cite contagion as “the likelihood of significant economic changes in one country spreading to other countries.”

What the dictionary definitions omit, however, is the rapid speed of transmission in contagion.

With today’s global economy tightly linked by capital, labor, and information flows at the speed of light, it’s not uncommon for bad news, nervousness, or outright panic to spill across borders and disrupt even the most stable of companies and industries. Indeed, everything’s connected, and sometimes in ways that we can’t quite see under the surface.

With just a few recent examples, the concept of contagion is quite prevalent in today’s periodicals:

• A European official recently compared the growing European debt crisis to the Ebola virus.
• To stop the debt crisis contagion, Eurozone finance ministers rolled out a rescue package designed to “shock and awe” investors with a whopping “$644B emergency facility to protect the Euro area from potential disaster.”
• Researchers at Kellogg School of Management at Northwestern University have found that if your neighbor strategically defaults on their home mortgage, the odds increase that you will choose to do the same.
• The Financial Times writes regarding Kyrgyzstan, “When demonstrators took to the streets … few, if any, foresaw that what started as a protest against a rise in electricity prices in the remote copper and gold belt of Kyrgyzstan would develop into a full-blown revolution that toppled a central Asian government.”

Whether it’s financial default of countries, companies or persons, government upheaval, or the decision to walk away from a mortgage because “everyone’s doing it,” small ripples of contagion tend to cause big waves elsewhere. And once those waves start rolling, it’s hard for marketing executives with their best laid plans to get out of the way.

The warning signs aren’t really hard to spot. In fact, they’re everywhere. What’s difficult to extrapolate is whether a rock thrown in the pond lands with a thud, or causes a full-blown title wave. And that’s the difficult part of understanding contagion, because in complex systems the next crisis could come from the smallest of beginnings.

With this in mind, how can a marketer separate signal from noise?

The first step is to read and listen. Pay close attention to global media for disruptions, trending topics, and events gaining critical mass. Reach out to peers for their perspective on today’s events (the more cross-industry perspective the better). Also, talk to customers for their point of view.

Second, watch your own company key performance indicators. In times like these, a strong analytical infrastructure with near real-time data feeds can help alert you to coming challenges. Use analytics to identify variances, strengths, softness, and project trend lines.

Third, leverage internal and external expertise to help distinguish matter from mania. Providing you have access to or have already hired the smartest brains, learn from PIMCO on how they hold weekly meetings to “square off in hours-long debates that are a cross between Socratic dialogue and bare-knuckled slugfest.” Challenge, debate, and try to project outcomes from today’s events.

The next crisis could come from left field, right field or drop from the sky. However, armed with the above processes, the probability of being blindsided is greatly reduced.

Leading up to World War I, it wasn’t uncommon for critical information to take hours if not days to reach its destination. Author Liaquat Ahamed cites in Lords of Finance that despite the advent of railroads, steamships and telephone, mail service was the norm for important dispatch, and it took a person five days to cross the Atlantic via ocean liner.

Oceans aren’t much of an obstruction anymore. With transoceanic internet cabling made possible through the birth and death of dot.com businesses, global markets are durably connected. Today, information flows at the speed of light across supply chains, and project work “follows the sun” shifting across various time zones. In addition, velocity is the new normal as the speed of decision making accelerates, and executives must analyze and act faster.

In a tightly connected world, there are the inter-dependencies we can see and document, and those not so transparent.

For example, Morgan Stanley Chief Economist, Stephen Roach, in his book The New Asia comments on how “this new connectivity (has) been amplified by increasingly complex financial instruments (such as derivatives).” Indeed, Roach cites Fed Chairman Alan Greenspan’s belief that the sub-prime contagion of 2005-2008 could be “walled off.” Unfortunately, as Roach points out, it’s only now that the global economy is picking up the pieces from this misconception and economists now understand the deep linkages between the U.S. consumer and the rest of the world.

In a tightly connected world, we live in a complex system that is composed of multiple sub systems. While some may argue the world isn’t quite “chaotic,” it is becoming clear that perturbations (even quite small) can cause quite a ripple in the global pond.

Take for instance, an event that happened nearly one hundred years ago: the powder keg eruption in Europe with the assassination of Arch Duke Ferdinand of the Austrian-Hungarian Empire. Indeed, this one event (momentous in the eyes of those in the Balkans) was thought to be “contained” by European and Asian powers. And it was—for a month. However the linkages and alliances among various countries sitting on the sidelines eventually brought major and minor global powers into the World War I.

Indeed, the world is more complex today than in the second decade of the 20th century. If it is to believed that one shot from Serbian nationalist Gavrilo Princip started a chain reaction leading to the loss of 37 million lives, it’s conceivable that in today’s more tightly coupled world, a single “spark” could have blinding consequences.

Author James Gleik reminds us, “(In complex systems) points of crisis are everywhere—small scales intertwine with the large.”

Today’s marketer is not immune to contagion. Events in the global market rarely happen in a vacuum anymore (much like this domino video). We must account and plan for the things we can control, and prepare for events we cannot.

Questions:

• What is the next global flashpoint that could choke your sales and marketing forecasts?
• What small event—seemingly innocuous—could give rise to massive global turbulence?

First, let’s start with a fun exercise courtesy of Wilmott Magazine. Let’s look at damage estimates of earthquakes in California from 1970 to 1993 in the table below. Can you make an educated calculation of losses due to earthquakes in 1994?

Taking a look at the distribution of data, notice the low end is “0″ and at high end, the most damage caused was “129″. So what’s your guess?

If you’re like me, you probably guessed wrong. Using the above numbers as an “anchor“, most people would reasonably assume that 1994’s earthquake was either an average of the above numbers or perhaps a bit higher than 129. Maybe you even threw out “129″ as an outlier in the dataset. To be honest, I guessed around “200″.

The correct answer is “2217.2″! FEMA estimates that every year earthquake losses in the United States add up to $4.4 billion a year. But then, some extreme outliers can really skew that number, especially years like 1994 where just the Northridge Earthquake in California alone tallied $20B in damage!

Let’s get back to talking turkeys via a parable from Nassim Taleb, author of the “Black Swan“. Dr. Taleb reminds us that fat, dumb and happy is probably the best way to describe the life of a turkey. They’re fed and nurtured for three years straight. Day after day, they expect the same thing. But then, one fateful day arrives and the “life” of a turkey ends quite abruptly.

Can we accurately predict the future based on reviewing and analyzing historical data? Sometimes, but we have to make assumptions of similar conditions, a normal distribution, and event independence. Complex systems will have none of these characteristics. Dr. Taleb says as much; “Real life isn’t a casino.”

Indeed, the parable of the turkey and the earthquake loss estimation exercise show us that predicting the future in complex systems can be a futile exercise because there are so many unknowns, changing conditions, and inter-connecting relationships. Extreme events that carry a huge impact happen, and some would argue they’re happening a whole lot more often as interlocking financial markets and globalization become commonplace.

Should prediction exercises be avoided? Nassim Taleb would argue otherwise; “We need to start thinking of the inconceivable,” he says. And while we cannot determine the exact probability of tomorrow’s events, we can “get a general idea about the possibility of their occurrence.”

And that’s where scenario planning comes into play. Bill Ziemba, author of the aforementioned Wilmott Magazine article says, “Getting all the scenarios and their probabilities right is impossible and doesn’t matter much anyway. What is important is to cover the board of possible occurrences. Then you will make sound decisions with risk under control.”

The fact is, like the turkey, we just don’t know what tomorrow will bring. So, plan for the five to seven most likely occurrences and then develop contingencies based on those scenarios. French microbiologist Louis Pasteur says it best, “In the fields of observation chance favors only the prepared mind.”

For a turkey, today may appear like any other “normal” day. However, tomorrow could be the chopping block.

Questions:

• Nassim Taleb says, “It is only in very rare circumstances that probability (by itself) is a guide to decision making.” Does this mean that historical data analysis isn’t worth the effort?
• If chance favors the prepared mind, what’s the “next unexpected twist” that marketers should be looking for?

Almost every consultant hates the phrase “paradigm shift.” And in effect, because of the recent global financial crisis, it is easy to see how consumer and business sentiments have changed quite radically. At least for now, the days of freewheeling risk taking, unabashed materialism and wanton spending have been replaced with frugality, caution and spending cutbacks.

PIMCO bond king Bill Gross, would agree that “thrift” is a new mainstay. In an Atlantic article, Mr. Gross suggests that as a result of the global financial crisis there’s something different regarding investor outlook:

“Risk taking went over the edge. We are inventing something new. We’re very afraid. We know from the Depression that people who lived through it didn’t change their mentality for the rest of their lives. They were sewing their socks. My sense is that it will take 10-20 years to find that kind of risk taking in people again.”

A recent survey conducted by Money Magazine validates Mr. Gross’ positions. Polling over 1,200 Americans, the survey discovered:

* 54% report they are worse off now than a year ago
* 89% say they’ve changed how they manage money
* The top three new habits are: eating at home more often, looking for discounts and cutting back on luxury purchases
* New attitudes are emerging with 88% surveyed saying they will be more frugal, 81% playing it safer with investments and 74% ignoring advice from Wall Street
* Men seem more pessimistic about the economy than women
* 73% said in the future they will play it safer with money and focus less on materialistic gain

To be sure, the results of the survey–at least for Americans–present a new prototypical consumer who is less trusting, a bit more conscious of his or her finances, and one that is getting “back to basics.”

Whether we are permanently in a new paradigm–or not–these statistics paint a new reality that marketers must take into account. Most companies have accepted this new reality and are baking marketing strategies accordingly. But many company executives anxiously sit on the sideline, hoping that market conditions get “back to normal” so they can raise prices, increase capacity and worry less about operational efficiencies.

In statistics, reversion to the mean indicates there are driving forces towards the average, and that outliers will eventually join the “normal”. Perhaps however these changes in consumer and business sentiments are permanent–and in effect, the mean has moved.

Questions:
* Longer term (in the next four years) will you be better off than today? What’s your outlook–optimistic or pessimistic?
* Target commercials show your home patio deck as the new vacation spot, a “Slip and Slide” as the new water park, and playing with a Wii as the new dance club. What do you think of these commercials? Does Target have their messaging right?
* Do new attitudes of frugality and safety have staying power? Once the recession ends–and it will–is it back to the past, or is this the new reality for consumers and businesses?
Related post: Advice on Altering Your Message, Product, Brand

Forecasting sales and inventory levels is probably one of the most difficult jobs of a product and/or supply chain manager as companies need to marry demand signals with supply. Adding more complexity to the mix is global supply chains that span weeks, multiple countries and sometimes oceans. Lots of hand-offs, tons of data to track, and lots of points for things to go wrong.

For many product managers (and the marketing/brand managers that support them) inventory management is a critical task. By not carrying enough inventory, companies can not only lose out on sales but also suffer reputation damage by not meeting customer needs.

Nonetheless, with companies hoarding cash–it seems the last thing companies need is to be stuck with unsold finished goods or piecemeal parts.

Apple’s Chief Operating Officer Tim Cook agrees. In a recent Fortune article, Cook says inventory is “fundamentally evil.” And Cook should know, as he’s in the very fickle consumer electronics business. “You kind of want to manage it like you are in the dairy business,” he says. “If it gets past its fresh date you have a problem.”

Here’s the rub, however. Forces of globalization and tight coupling are magnifying the complexity, impact and frequency of events. Once steady suppliers are going bankrupt, some suppliers cannot get loans in the credit crunch, and disruptions in the supply chain are becoming more commonplace. Your product launch date doesn’t matter much if your suppliers cannot deliver.

But can’t analytical modeling save us? After all, most companies are using advanced planning applications to predict future trends and behaviors, right?

While statistical forecasting techniques can help extrapolate future trends, these methods rely on building models based on historical data. And some executives say in volatile times, historical data can no longer be trusted to accurately model and predict the future.

So what’s the solution? Should we build more redundancy into our supply chains to better manage the risk of suppliers, or stay the course with the trend towards information management and just-in time supply chains that are well optimized and thin?

Better communication is a potential answer says Camille Schuster, President of Global Collaborations. What is needed, she says is, “Proactive contact with suppliers on a regular basis to determine how supplies are doing, what issues are coming up, whether any shortages are foreseen, whether there is any softness in any product area, what changes and/or rumors are floating about.”

For many companies, effective inventory management is a critical component of financial health. With “cash” at a premium in this global financial pandemic, inventory decisions can literally make or break your company.

When it comes to inventory, what level of risk are you comfortable with?

Questions for DailyFix readers:

* Is a little inventory cushion warranted as risks (environmental, political, criminal, financial, reputation, terrorism etc) seem to be increasing in intensity, complexity and frequency?
* In volatile times, should forecasting and inventory management be more focused on “gut” decision making rather than mathematical models?
* Stockouts leave “money on the table” and ultimately reduce customer satisfaction. What is your marketing advice to supply chain, operations and/or engineering executives in these volatile times? Hedge their bets with a little more inventory, or continue to operate “thin”?
* Is inventory still evil? Should it be avoided at all costs?

It’s that wonderful time of the year where leaves turn bright amber, apples hang from trees, tempting smells waft from the kitchen and families across the United States gather for the Thanksgiving holiday. To be sure, of all holiday staples for Thanksgiving, most in-home chefs won’t forget the turkey.

However, this particular Thanksgiving, I’d like to bring up the parable of the turkey as told by Nassim Nicholas Taleb as a constant reminder that all business executives should always plan for the unexpected …. no matter how remote the possibility.

As detailed in “The Black Swan“, Taleb asks us to consider the life of a turkey. You see, the lifecycle of most turkeys is well known to the outside observer. A turkey is born, and then fed generously everyday. For 1,000 days straight the turkey expects its morning shovel of grain, grass, acorns or shoots.
A monumental event happens to that turkey on day 1001–and we all know what that event is. Until that point of course, everything is considered “normal” by the turkey. In fact most days deviate only slightly from the norm, with maybe a few minor exceptions.

Getting back to day 1001, Taleb points out, “A turkey cannot figure out what is in store for it tomorrow based on the events of today.” And Taleb notes that this is one of the key challenges with assuming tomorrow or even next year will be much like today.

Author Peter L. Bernstein often asks, “What is ‘normal’ anyway?” Good question.

Quantitative financial analysts, attempting to model the stock market, took heavy losses in 2008 as they assumed the past would be a relevant predictor of the future. Automobile manufacturers forecasted that demand would be similar to last year (maybe a bit less), and now many are frantically leasing space outside of key US ports to store unsold cars.

This year has seen the DOW index range between 13,000 and 8,000. And Mr. Greenspan, former Federal Reserve Chairman, said in testimony to the United States Congress in October 2008, “This crisis–has turned out to be much broader than anything I could have imagined.”

What’s a business executive to do?
Don’t throw out the models–just yet. I have previously mentioned that modeling can be a very valuable tool for companies assessing future scenarios, determining cause and effect, and allocating scarce resources. But use caution; models are support tools that should be combined with good judgment, experience, and the input of others to effectively drive decisions.

Another avenue is to pay attention to outliers via analysis. Alberto Roldan, mentions in a post that, “(Outlier analysis) uses concepts like average, standard deviation, and Z-scores to determine whether a determined data point is abnormal in the same classification or category.” Examine the outliers in your market. Are they occurring more frequently than your models predict?

A final recommendation from Taleb, “We need to start thinking of the inconceivable.” Can a business executive plan and resource for every outcome? No, but Taleb reminds us while it is very difficult to discern the exact probability of significant events, “it is easy, however to get a general idea about the possibility of their occurrence.”

Complacency is not your friend. There are good chances that tomorrow will vary significantly from today. Don’t forget the parable of the turkey!

Questions:
* Are the global financial events of 2008 simply outliers? Should we assume that things will return to a level of “normalcy”?
* Should the “extremes” be considered as you budget and forecast for the next one to three years? How are you taking the possibility of “significant events” into account?
* As we close out the end of the year, most marketers have already turned in preliminary budget requests for their next fiscal year. What key assumptions are you using to plan for next year?
* Are global markets getting more risky or less? In an unpredictable world, how are you dealing with uncertainty?

Data, by itself is of little value. The real value lies in the capturing, cleansing, management and analysis of data thereby making it more useful for decision making.

One of the ways companies analyze data is to build or “program” models to simulate, test, learn and predict outcomes. Indeed, models built upon statistical techniques are helping companies identify fraud, predict next best offers, determine customer churn, and assess credit risk among other valuable applications.

But modeling isn’t a panacea, and a recent New York Times article, “How Wall Street Lied to Its Computers“, shows us how companies can get it wrong.

Writer Saul Hansell notes that Wall Street traders have long had very sophisticated models on market behavior–devised by quantitative analysts–that were supposed to help them hedge their positions and allow them to essentially manage their risks (or enable them to take bigger risks).

However a key challenge emerged when, “The people who ran the financial firms chose to program their risk management systems with overly optimistic assumptions and feed them oversimplified data.”
Even worse, many of the products (read: derivatives and derivatives of derivatives) weren’t understood by the creators of the products and thus it was near impossible to accurately assess the risk of these products with a mathematical model.

Modeling isn’t just for risk management, and can be a very valuable tool for companies assessing future scenarios, determining cause and effect, and allocating scarce resources. However the New York Times article highlights a great case study of pitfalls and key challenges when attempting to model a system, phenomenon or behavior.

First, understand that a model will only be as good as your assumptions. For example, in many risk management systems, models are designed to assume rational decision makers, a stable and relatively volatile-free marketplace, and that outliers generally have a limited effect on the entire population. Anyone who’s invested in a 401K and tracked their stock portfolio recently knows the futility of these assumptions (Nassim Nicholas Taleb explains why here).

Second, mathematical modeling is only as good as your data. Hansell’s article points out that it was in the best interest of traders to ensure the models didn’t warn them of impending danger, so they took efforts to smooth the data and manipulate the amount of historical data their risk management systems could analyze so as to take more aggressive trading positions.

Third, modeling is only as good as the design and designer of the model. “There was a willful designing of the systems to measure the risks in a certain way that would not necessarily pick up all the right risks,” says Gregg Berman of software company Risk Metrics. The design of an model should be checked for accuracy–not only of the accuracy statistical concepts used, but also that the model is not “tweaked” to produce desired results.

Last point: a model might be based on fair and accurate assumptions, sourcing clean and legitimate data, and designed properly–however it is of little use of politics stands in the way of recognizing and acting upon the output. All the analytical systems in the world are of little use if corporate politics dictate an outcome that is different than what the model prescribes.

No mathematical model is perfect–a model is just that–a model and not a silver bullet. Also such models are support tools that should be combined with good judgment, experience, and the input of others to effectively drive decisions.

That said, the time, energy, and investment dollars spent on mathematical modeling is close to worthless when poor assumptions, faulty/dirty data, bad design and corporate politics get in the way of good decision making.

Questions:
* Mathematical models are used by companies for customer segmentation, risk management, propensity to buy, loyalty management etc. Are you using models to help you make better decisions? If so, how?
* Do you think we often try to model things that are too complex–things that can’t be modeled effectively? What might be the ramifications when we get it wrong?
* In the business world, do you think the use of mathematics sometimes overrides “common sense”?
* Mathematical modeling–done right–can be a powerful business tool. How can we teach future generations of business leaders to use these tools ethically?