Both bloggers make the case that intangibles are important but very difficult to measure. I agree that they are important but think it is unfortunate that they are seen as so hard to measure. The field of intangibles and intellectual capital provide a number of important ideas that can be applied in IT business cases. Here are a few.

IT is Intangible: To start with, it is important to recognize that IT is itself a (mostly) intangible investment. I say this because much of IT spending is not capitalized on the balance sheet but, rather, expensed on the income statement. Any analysis of the costs of a project ends up happening outside the accounting system because so much of the spending simply gets expensed.

The only reason for mentioning this is to remind those in IT that intangibles are not something to be ignored or dismissed. They are actually at the heart of almost every business today. Roughly 80% of the value of companies today is intangible, that is, not on the balance sheet. IT is a big part of that. So IT should embrace the study of intangibles.

Intangibles Gain Value From a System: Another important point is that intangibles do not have much stand-alone value. Their value comes as part of a system. Most IT implementations cannot be picked up and moved to another company without a lot of work. This is because they exist in a larger context of the work patterns and skill of the workers that use them.

Yet most examinations of IT spending tend to focus on a specific project. It is much more informative to understand IT in terms of its role as the platform for automation of underlying business processes, literally providing the machines a company uses to “manufacture” value for its customers. Taking this broader perspective leads you to focus on all of the three basic types of intangibles:

• People (incl. competencies, experience, capabilities)
• Structural knowledge (incl. processes, software, intellectual property)
• Networks (incl. customers, partners, suppliers, brands)

An IT implementation needs all three kinds of IC to succeed. To evaluate IT, you need to understand the business process, the people who run it, the partners that contribute to it and then, yes, the IT itself. So measurement should not just look at one part of the system—an attempt should be made to understand how all the parts work together. I have a friend in charge of a $100 million implementation of a new governmental IT system. She tells me her greatest worry is whether the people that are supposed to use it will actually be willing to and capable of adapting to the new system. That is such a fundamental issue that she and others in her position ignore at their own peril. And one that requires looking beyond hardware and software for a resolution.

Intangibles Can Be Measured: How to measure this kind of implementation? Both Ritchie and Kahn suggest a preference for tangible measurements. I agree but it’s not enough. When dollars are invested in an intangible, the path from dollars spent to dollars earned or saved on the backend is usually intangible. If you insist on ignoring intangibles, you are basically consigned to measuring money going in a black box and hoping that money comes out the other side.

It’s much more powerful to ask the question, “when we invest in this system, what do we expect to happen?” and then try to create measurements around this.

A basic principle of measurement should be that you take a baseline measurement, identify the desired change and allow for a follow up measurement. This is no different for intangibles. But what often happens is that people identify the desired change and then try to measure it. Without a baseline, however, measuring the “change” is basically impossible and people conclude that “it’s all too soft to rely on.”

How to take a baseline measurement? If the intangible cannot be measured through dollars (such as the cost of an investment) or numbers (such as transaction throughput or a similar numerical measure), you will have to try some new approaches. One approach is an assessment. An assessment involves creating or using a standardized survey to analyze something. Assessments can be made by the project team but, ideally, they will include feedback from internal and external stakeholders. The tool we use asks stakeholders to rate the effectiveness of specific processes on a scale from 1-8. If you do this kind of assessment in a disciplined way, you get some pretty powerful information.

Asking stakeholders to assess the state of intangibles before beginning a project has the added benefit of identifying strengths upon which you can build and weaknesses that need to be addressed to ensure the success of the implementation. It will also make it easier to identify the right metrics to monitor as the implementation progresses.

But Intervention delivers a much broader message, about how the human propensity for hamartia isn’t miraculously expunged by mathematics, statistics, or the scientific method.

In proving her point about assessing the risks of genetic engineering, Denise calls into question the seemingly unassailable position of science in our culture. The book suggests we desperately need “a new kind of science” (to borrow Steven Wolfram’s phrase) — one that accounts for the nature of the beings (i.e., us) who are wielding its increasingly powerful tools. Try as we might, whatever model we create to try and describe reality, our scientific models inescapably say much more about human beings than they do about some objective reality. In the book, Denise exposes our lapses in rationality due to cognitive, social, and technological realities. Such lapses are everywhere in the areas I cover (technology, social trust, and privacy).

So while reading the book, I decided present my views on these issues in a blog post. Admittedly, going into some depth on Denise’s book on the Hybrid Vigor blog (which is Denise’s creation) seems almost self-congratulatory. But I think the larger themes in Intervention are relevant to most of the really difficult problems we’re trying to solve globally today, and understanding these issues will help focus our discussion at Hybrid Vigor.

Softening the Hard Sciences: The Triple Threat to Rationality

1. The Limits of Human Cognition

On the cognitive level, scientists may subconsciously fall in love with logical fallacies they create, without realizing that any theory they concoct is inseparable from their cultural conditioning. Models and theories are as much expressions of a person’s worldview as an expression of scientific truths. On this point, Denise quotes Paul Thurman, a Columbia professor of statistics and data analysis, who puts it rhetorically: “If I’ve built a model based on certain assumptions, that’s what I believe.” (p. 63)

Any assumptions built into the model are virtually undetectable to its creator and patrons; the model becomes a Matrix: “a prison that you cannot taste or see or touch. A prison for your mind.” Mike Walter, whose blog I follow from time to time, calls this brand of irrationality the “Wizard of Oz Syndrome.” The problem here is more than simple self-delusion; it’s the cognitive disability in human beings to view their work and their environment with true objectivity.

In theory, science is based on empiricism, so logical fallacies are supposed to be weeded out by peer reviews. To believe that model of the scientific method only illustrates my point. In practice, reliance on empiricism is the crux of the problem, because in most cases not enough data exist to form an effective model. To do good science, you need good data.

But as Denise puts it, “How do you know what to measure … when you’re looking for the risks in something completely new?” (p. 76)

2. The Effects of Sociality on Scientists

On the social level, we have learned that logical fallacies elicit cultish behavior. Once a fallacy attracts believers, it becomes a shibboleth to distinguish the intellectual elites from the ignorant masses — or “innumerates,” as the math nerds call us. Denise skillfully refutes their case against the innumerates with several examples, including the Long Term Capital Management debacle.

The problem with innumerates isn’t only that we lack perspective about numbers. … What’s more, [we are told,] we tend to personalize things — to be misled by our own experiences rather than being objective and rational and informed by the facts, an error in judgment that apparently no mathematician or scientist ever makes. … [But] to conclude that “innumerate” people cannot understand risk because they don’t understand sophisticated mathematical concepts is inaccurate at best and it certainly isn’t an objective truth. Thurman’s Nobel-winning economists doomed Long Term Capital Management by building their models on faulty assumptions, which they then relied on to make decisions.

Denise’s argument here reminds me of a hilarious episode of Zefrank on the role of consciousness. It’s good comic relief if you want to go check it out before continuing with the rest of this post!

Once a group of like-minded people isolate themselves from independent thinkers, groupthink sets in, and group members can be made to believe almost anything.

3. The Psychological Effects of Technology on Scientists

The introduction of technology into a social setting has demonstrable psychological effects on human beings, including scientists. An intervening technology may change people’s perception of a problem so they come to rely on the technology (a structural solution) and accept its authority. The result is blind deference to the intervening technology. Denise again allows Paul Thurman to make the point:

Many researchers simply believe the numbers that come out of the computer…. They say, ‘I have a model; that’s the right thing to believe. If there’s anything out of pattern, then I must have done something wrong.’ They rarely think that the model itself could be wrong. People don’t do the simple sniff tests anymore … they immediately cut to a quantitative explanation…. They infer a scientific precision that isn’t there…. But obviously even Nobel winners can build erroneous models. (p. 63)

The Absurdity of Certainty

Epistemology is the term philosophers use to describe the ways of knowing. Rather than try to define it, I’ll offer a small thought experiment. Answer these questions in your mind:

• How good-looking are you?
• How intelligent are you?
• How do you smell?
• How sure are you about your answers and how do you know?

Whatever your answers, the only certainty about this exercise is that you’ll be wrong. But something in the human psyche allows us to guess and make up answers — and then to believe in what we just made up as if it were factual.

There’s a game called “blind man’s bluff” that illustrates this point rather well. Blind man’s bluff is a kind of reverse-poker, in which players can see everyone else’s hand, but not their own. Players then make bets on their hands, not knowing what cards they themselves hold. It’s a riot to play. (Note: if you watch the video in the link above, in my opinion the game is more fun if you force people to place bets and not allow anyone to fold.) If you haven’t ever played blind man’s bluff, you should stop reading this blog post, get a few friends together immediately, and play a round. Go ahead! I’ll wait.

When you understand blind-man’s bluff, you’ll begin to understand that we humans are much more socially aware than we are self-aware. In fact, without others to play the game with us, we have no way of knowing the cards we hold.

As social creatures, our need to belong makes us just conscious enough of “self” to sense aloneness. We’re not adapted to survive completely on our own, so we bond with others. One of the primary ways we bond is by concocting stories about ourselves and others. Good stories are ones that help people coordinate behaviors and improve cohesion within a social unit. So naturally, we are also willing to believe others’ stories.

Our ability to believe is a virtue, not a flaw. The human propensity to invent stories and believe others plays a key role in the survival of our species. But it also means that our survival instinct favors social cohesion over intellectual acumen. In my opinion, if scientists understood the relationship between belief and social instinct, there would be little tension between religion and science.

I was glad to find that Denise avoids the pitfalls she writes about in the book. She doesn’t fight science with science. Instead, she simply asks for greater caution, in light of human frailty that leads to irrationality–the scientific community not excluded. And so I’m rating this book a “must-read” for the rational being.

Edmans concluded that from 1998-2005, a stock portfolio of the companies listed on Fortune magazine’s “Best Companies to Work For in America” increased in value by an average of 13% per year–double the rate of the market as a whole. Empirical Finance outlines how to build an investment strategy based on this fact.

This looks like a fun blog. The post previous to this one gave rating of 5 (on a scale from 1 to 10) for a strategy that looks at CEO real estate purchases as an indicator of expected declines in stock prices. They gave a rating of 9 to strategy based on investing in Fortune’s Best Companies list as a simple way of targeting companies that create the most value in today’s “ideas-based service economy.”

I’m not an investment adviser. But I am a consultant that has seen a lot of winning (and losing) companies over the years. And I know that the winners understand that we live in a knowledge-based economy. Knowledge starts with people. Knowledge only grows with the input of people. People cannot be ordered to think better. They have to want to do it. So employee satisfaction is an important component of a winning strategy in any company.

This is a hard thing for organizations to swallow. They are accustomed to the command-and-control approach where making something a goal is the first step to getting it done. I’ve seen companies that have as a shared goal “to become more innovative.” This means that the personal goals of everyone in the organization include something about “being more innovative.”

But a manager cannot order someone to innovate! He or she has to create the environment where there is enough freedom and the right resources so that their employees can and will innovate. In this view, the manager’s role is to help frame the problem, convene the conversation and get the right people to the table.That’s why I think of innovation as the “new” strategy. It requires a completely different view of how to plan for the future of your company. It is not about identifying the right course and executing it flawlessly. It is about first deciding what problems need to be solved, then attracting the right resources, creating the right ecosystem and supporting a process of continuous learning. It is about leveraging the collective expertise of your employees, your customers and your partners to collectively solve the tough problems.

Contrast this with the recent New York Times editorial by songwriter and author Billy Bragg, The Royalty Scam. Bragg tells the story of Bebo, the social-networking site that grew to 40 million members in two years and, in Britain, apparently ranks with MySpace and Facebook in popularity.

A couple years ago, Bebo founder Michael Birch asked to meet Bragg after Bragg had lobbied MySpace on its proprietary rights clause. Birch assured him that Bebo would always put the interests of artists first—although this “support” never included any kind of royalty to the artists contributing content. Last week, when Bebo sold to AOL for $850 million, Bragg observed:

The musicians who posted their work on Bebo.com are no different from investors in a start-up enterprise. Their investment is the content provided for free while the site has no liquid assets. Now that the business has reaped huge benefits, surely they deserve a dividend.

If Bebo owners had shared this purchase price equally (and kept nothing for themselves) each member would get $21. Is this they way it should work? Or are some members more equal than others? What is fair compensation for building a site versus providing content? Could content creators band together and share in the revenue from a marketplace they control? Or should they use sites like Bebo for advertising and create their own direct sales model on a dedicated site owned by the artist?

The fundamental question is whether a Web 2.0 world is ready to compensate content creators directly—and take the traditional media out of the picture entirely.

I believe that we have a lot of work to do to learn how to manage the intangibles that determine the winners and the losers in this “flat” world. And the American farmers are just the latest in the long line of businesspeople on the losing end of the intangibles game.

Fortunately, around the same time, I met Denise Caruso, who runs the Hybrid Vigor Institute and edits this blog. We became acquainted after she wrote a wonderful piece in the New York Times, “When Balance Sheets Collide With the New Economy” which highlighted the inadequacy of financial reporting to deal with the knowledge economy.

Denise explained how knowledge intangibles are invisible in financial and managerial reporting. They are also often passed over in decision making—in the assumption that “soft” issues cannot stand up to the rigor of traditional analysis.

But it is the soft issues that count. They help farmers in Brazil beat out their American competitors. They are at the heart of successful innovation. They create the competitive advantage of companies as diverse as Toyota and Google. We all need to get better at “seeing” and managing the soft, intangible side of our organizations.

So I was thrilled when Denise invited me to join in the budding, cross-disciplinary discussion at Hybrid Vigor. The challenges that we face in the “flat” world require new kinds of solutions—solutions that often lie beyond the ken of traditional economics, accounting and management. The topic of intangibles is no exception. I know that it will benefit from a broad diversity of perspectives. I look forward to joining in and bringing an “intangible” point of view to the conversation.

[Editor’s note: We are thrilled to have Mary on board here at hybridvigor.net. I was tremendously impressed by her in our conversations, and I believe the work she is doing on intangibles and intellectual capital is critically important to the future success of the global economy. I also loved her description of herself on the website of her consultancy, Trek Consulting: ‘Mary is a good listener, a studious thinker and an honest critic.’ Who could ask for more? You can read her full bio here. D.C.]

According to this USA Today article, financial institutions reported 17.6 million transactions to the Federal Crimes Enforcement Network in 2006. Does this fact imply that 17.6 million transactions in 2006 were criminal in nature? No, they were simply “transactions of interest” (my term). In addition, financial institutions filed about 1 million “suspicious activity” reports in 2006 (up from 413,000 in 2003) to government agencies. Allegedly, it was the suspicious activity reports that linked Spitzer to the prostitution ring.

But most of the people behind the other 17.59 million financial transactions aren’t accused of any crime. Still, their spending habits are monitored, and if anything sketchy turns up they’ll then be accused of a crime. This seems afoul of the Fourth Amendment, which guarantees:

The right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures, shall not be violated, and no Warrants shall issue, but upon probable cause, supported by Oath or affirmation, and particularly describing the place to be searched, and the persons or things to be seized.

I’m sure that money laundering laws make a lot of sense for the narrow purpose of tracking criminals and terrorists. But reporting millions of transactions a month feels like an exponential change of scope. What are all these people doing that is so suspicious? What exactly are the rules of this game?

Happily, Google’s got click interpretation down to a science, so we’re all off the hook (although the algorithm apparently still struggles with interpreting wit, sarcasm, irony, rhetoric, and French). So now I’m anxiously anticipating the beta of Google Intentions: an app for searching everyone’s click streams, categorized by intent!

(Free) registration is required to read the article online.

I am happy to report that in April 2002, Oliver Morton, Hybrid Vigor Fellow and the news and features editor for Nature (as well as the author of two books), wrote a terrific monograph for Hybrid Vigor on essentially the same subject, The Living Skies: Cloud Behavior and Its Role in Climate Change.