Spreading Ideas by Exclusiveness and Secrecy

The heading may seem like a large contradiction, but I believe it is not.

The Tip from a Friend
Why does a tip from a friend mean so much to you compared to an ad in a magazine or on television? Well, friendship is strongly related to honesty and the ability to keep secrets between each other. When you break either of the two, the good relation is sacrificed. Hence, if you get a tip from a friend, you believe it because (1) he is not likely to lie and (2) this may be an important secret your friend tells you about.

In sources [1] and [2], the word-of-mouth-marketing (WOMM) idea is advised to be used more by companies. But, a WOM epidemic is hard to start. It is more art than science, but some references exist that may give some valuable advice. In "The Tipping Point" [3], a WOM-model is introduced, and I like it.

The main thesis of the book is that ideas, products and social phenomena may spread like epidemics. "The Tipping Point" happens when "the vital few" as apposed to the the trivial many starts to use, apply or advertise the idea and the "epidemic" spreads. Gladwell calls this group phenomenon the Law of the Few, and from my point of view it is simply another way of stating the Pareto Principle [3] (find the vital few that produce the impact).

To apply the Tipping Point insight, the key is how to select the vital few. Gladwell asserts that you need to find the "Connectors, Mavens, and Salesmen" that can cause the tip. Finding who those are again is still an art.

A great example of a product where the WOMM effect is seen, is Gmail. Yes, there has been considerable amounts of media coverage on the service, but the fact of the matter is that the service has never been advertised. Hence, the media coverage has only started by WOM. The service was originally also only accessible to those who have been invited. Hence, there became a sense of exclusiveness and secrecy in the service. The product then exploded!

Relationships of Trust

WOMM is great, but is not possible in all situations. The thing is that not all products can be marketed through your friends. Some products have the characteristics so that there is little interest for someone to tip a friend. Furthermore, there is for instance a lot of research that indicates that buyers do not tell about products or services they like, but they are very likely to tell their friends about the ones they do not like. There are some success stories of WOM-campaigns that spread by giving consumers incentives to spread the word - but there are in many markets legal challenges for these type of models.

So when WOMM does not work, you as a company often need to spread the word yourself. To be able to do that successfully you must build a relationship of trust with your customers [6]. In order to do that, why not look at the model for friendship and look for inspiration. Hence, giving a customer secret and good offers while keeping a sense of exclusiveness to the relationship is most likely what will attract and retain them.

[1] Word of Mouth Marketing - WOMM!
[2] Word-of-Mouth: The World's Best-Known Marketing Secret
[3] The Tipping Point

[4] The Pareto Principle
[5] GMail
[6] It's Not About Permission, It's About Trust

The Vital Few or the Trivial Many?

When the Pareto Principle [1] was popularized within business and engineering in the 1940s by Dr. Joseph Juran, he called his theory "The Vital Few and the Trivial Many" [3] : A few vital inputs produce most of the results. For many years now that has been how we are taught to prioritize ideas and activities in business. However, thanks to the Internet, the Pareto Principle is being falsified [4] in various domains.
The insight comes from power law theory [2]. As one can see in the figure to the right (from wikipedia) , a power law distribution can be split into a vital few (the green area) and the trivial many (the yellow). What is happening for many products and services sold via the Internet is that demand is shifting down the tail - making the tail fatter and the head slimmer! According to [5] there are 3 reasons for this:

1. Cost of production of many products from music and books to Internet services is falling, thereby creating more available products in the tail.
2. Cost of inventory and distribution is falling though JIT production, digital content and application hosting. The marginal cost of one more product ore product feature in the inventory is extremely small, making it profitable for low volume sales of one item.
3. The Internet and it's search engines and communities are creating new ways for consumers and businesses to find more specialized products and solutions that fit their exact tastes and needs.
   

This insight is rather extraordinary because it shows that lucrative business opportunities exist where there was said to be none. Furthermore, there are signs that the profit margin is larger and the competition smaller at the tail per unit than at the head. Sounds like faster money to me!

[1] The Pareto Principle
[2] Power Laws and Long Tails
[3] The Vital Few and the Trivial Many (external)
[4] Falsifiability (external)
[5] The Long tail (exteral)

The Pareto Principle - After 101 Years

The Pareto Principle or the 80/20 [1] rule as it has often been called, was first noted in 1906 by economist Wilfredo Pareto while he was studying the wealth distributions of people. Apparently, 80% of a nations wealth was in the early 1900s controlled by 20% of the population. Since then, the Principle has been popularized in management theory and is applied in all sorts of domains. Take for instance blog entries such as this [3].

It seems that 100 years later the relationship has become even more differentiated. According to [2] 10% of the worlds population control 85% of the wealth. Hence, if Pareto had lived today, the Pareto principle would have been called the 85/10 rule.

[1] Pareto Principle - an explanation of the Pareto principle and further reads.

[2] UN study of the wealth distribution in the world - ppt of some very interesting figures.

[3] Notes to Self blog entry about 80/20 in your daily life

The Medici Effect

The Medici's were a very influential family empire in Florence from the 1300s to the 1600s. An amazing number of scientific discoveries were made during their era - Leonard Da Vinci being one of the most famous and influential of the discoverers. The accepted theory for why this era was so productive is that the culture was very open and cross disciplinarian. That again made innovation more plausible.

The Medici Effect [1] is a book that looks at the innovation from such inhomogeneous processes and how you can accelerate the process. The main thesis of the book is very much in line with what the notes on this blog is about : Innovation comes nowadays from the intersection between disciplines. You take ideas and concepts from different disciplines and combine them into new concepts.

The big question is how you or an organization can step into this intersection. According to the book there are 3 key elements that are important driving factors:

1. By diversifying occupations.
2. By interacting with diverse groups of people.
3. By going intersection hunting.

1 and 2 are fairly obvious. Being in a culture of diversification, curiosity and open mindedness are key factors for innovation. 3 is mostly based in the idea of creating directed randomness in your thought process. One method is to go for a stroll and purchase or pick up objects that are not related to your current problem. Look at these and let your thought roll.

I won't say that the book is very revolutionary, and the fact of the matter is that you need to have a mind that is creative and curious in order to create this effect. Most ideas are created/formulated by a few people compared to the population. These few people make up many ideas - many which never make the test of reality. Still, the thesis of the book is important to remember, so if you want to create an innovative culture it would not be so silly to study the Medici's.

[1] Medici Effect: What Elephants and Epidemics Can Teach Us About Innovation

The Currency of Influence and Authority

Talking to a colleague senior project leader the other day, I learned a very valuable lesson. "Watch up so you do not 'spend' all your authority! It will be valuable to have later down the line", he said. He was talking about the currency of influence and authority.

His statement was the answer he gave after I asked him how he was so successful at reaching agreements in disputes with contractors and conflicting organizational units. He continued to tell me how he tries to delegate various negotiations and discussions to subordinates as much as possible. The obvious reasons for this was motivating his subordinates and more importantly to increase effectiveness by decentralizing authority.

His last reason however, is the key learning point for me. When you meet in negotiations yourself it means that you can never be the man that the issue is escalated to - you have already 'spent' your authority by being there. He told me that if he did not sit in on the negotiations, but instead only appeared if there was a dispute, his natural authority (and the authority he got from his position) was more effective.

So influence and authority not matter what its source is not infinite. Spend it with care, and be serious about where you invest it. The currency of influence and authority can give you big payoffs, but is very often spent on invaluable situations.

Occam's Razor Shows the Immature State of Quantitative Economics

"In physics, it takes three laws to Explain 99% of the data; in finance, it takes more than 99 laws to explain about 3%". According to an article [1] in HBR, the source of this statement from MIT finance professor Andrew Lo. He followed up by saying: "Economists consequently suffer from physics envy".

What does it mean if Lo's statement is true ? In my experience I believe he is, and I see two alternatives:
(1) Economics and its mental world is not at all as amendable to the power of mathematics as physics in the physical world. This is the conclusion in [1].
(2) Economics is simply too immature, and totally new approaches to its understanding is needed in order to build predictive models. If this is the case, the emergence of such a theory will be through the collaboration from other fields.

According to alt. (2), Occam's Razor will force a new and radically simpler quantitative economic theory with greater accuracy. It might be you who finds this theory?

[1] Article in Harvard Business Review.

The Balanced Simplicity in a Classical Music Recording

The goal of a classical recording is of course to create a sound in a stereo that gives the listener the impression that he is sitting in that concert hall. The process goes though several steps, the major ones being recording, editing and mastering. I was talking to a Classical Music Master yesterday, and among other things he explained the ultimate recording setup: 2 microphones!

Apparently, one studio uses one microphone in each seat in a concert hall to make the recording and the result is terrible. The sound arrives in each seat at different times and in that way it becomes distorted. Furthermore, the mastering becomes really complicated due to all the channels the Music Master needs to work with. By having two microphones, you receive

Occam's Razor strikes again: "A solution to a problem should be as simple as possible, but no simpler." In the mastering process, the master reworks the analog recording to a digital piece. This is apparently a balanced analytical process and intuitive art. The master looks at the musical digital profile and listens to the sounds for impressions in an iterative manner. The master also needs to take into account that most listeners are using simple stereos that do not bring out the full quality of the music. So to summarize, a digital musical masterpiece is a product of fine balance of simple building blocks.

Power Laws and Long Tails

The standard normal distribution (bell curve) is today dominant when we model phenomena. It often works out quite nicely with reality, but it has one easily to forget limitation : It assumes that the occurrences are independent. In many cases independence is very limiting. Interdependence needs to be taken in account. In these cases power laws are more accurate (For a definition of a power law see [1]). The result is that extreme events become much more probable.

Look at the diagram below from [3] (also a great overview of power laws). As you can see, a bell curve will predict that unlikely events are very rare. In cases of independence of phenomena that is likely. A power law distribution looks similar, but has a "fat tail". The implication is that it predicts that rare events are much more likely (you may say that the interdependence creates a possible "butterfly effect").





An example from [2] (a brilliant book by the way) is illustrative. In the book business, the largest brick and mortar shops can keep an inventory of maximum 100.000 books. After that the business of keeping them in store becomes unprofitable. A site like Amazon.com has an inventory of over 1.5 million books and growing. Even though it sells only a a few copies of the millionth popular book, it still makes a profit on it. That's due to the low costs of storage, distribution and sales.

An example from [3] is another illustration : "In the case of market fluctuations, for example, the bell curve predicts a one-day drop of 10 percent in the valuation of a stock just about once every 500 years. The empirical power law gives a very different and more reliable estimate: about once every five years." As the reader may know, we see 10 percent drops fairly often!

[1] Wikipedia - Power Law
[2] The Long tail
[3] Power Laws & the New Science of Complexity Management

Principles of the Greatest Companies

What makes a company truly great?

The research by Jim Collins presented in his book Good to Great [1] from 2000 gives me a lot of inspiration. Collins researched the stock market and found the companies that had beat their market segment by 7 to 15 times over a 15 year period. The team then found the common qualities the great companies shared. Some of the results were really surprising. Interestingly, the list did not include companies like GE, Coca Cola and Microsoft. These did not qualify.

Below are the qualities :

1. Level five leadership
2. First Who, Then What. Pick the right leadership team
3. Confront the brutal facts - Murphy's Law
4. Hedgehog Concept (Strategy)
5. Discipline in culture
6. Use technology to accelerate

See [2] for a thorough walk through of the complete set of ideas that were introduced in the book. The book is also a very good read.

[1] Good to Great - cool study of the greatest business transformations.
[2] Jim Collins' web site

The Spooky Explanation for Pretty Girls

According to [1], beautiful parents are 36 percent more likely to have a daughter than a son. Hence, beautiful women are easier to find than attractive men. The hypothesized reason for this statistical result is that "evolutionarily speaking, beauty is a trait that is more valuable for women than for men". Selection pressure hence gives the beautiful parents pretty girls.

Similar results apply to parents working in "empathic" occupations such as nurses, social workers and kindergarten teachers. On the other hand scientists, mathematicians and engineers are more likely to have sons than daughters.

Did anyone say politically incorrect?

[1] Why Do Beautiful Women Sometimes Marry Unattractive Men?

Being Orthogonal and DRY through McKinsey's MECE

Two of the important lessons that many software engineers have learned through experience is so brilliantly explained in the book Pragmatic Programmer:

• Orthogonality - "Things that are not related conceptually should not be related in the system."
• DRY (Don't Repeat Yourself) - "Every piece of system knowledge should have one authoritative, unambiguous representation. Every piece of knowledge in the development of something should have a single representation. A system's knowledge is far broader than just its code. It refers to database schemas, test plans, the build system, even documentation."

While skimming through the book The McKinsey Mind (a follow up of another very similar book called the McKinsey Way) I suddenly found the same principle being present in the Firm's analysis methodology. The principle is called MECE and stands for:

• (ME) Mutually Exclusive - "must ensure that a list of items is mutually exclusive, or that every item is separate and distinct"
  
• (CE) Collectively Exhaustive - "it must also be collectively exhaustive, that it includes every issue relevant to the problem"
  

According to the source, the MECE principle is used by the associates in the Firm to analyse different scenarios or to develop a list of questions concerning a particular issue. It is funny to see that the same principle is applied by both successful software designers and successful business analysts. The principles are just coined differently. DRY and orthogonality covers ME. You can say that CE is supported by any working software system in that it works.

Ability Quotients

For many years, IQ was the main measure of a person's capacity. Logical capacity was how you valued the candidate's mind. During the 80s and 90s that view started evolving, and today the way of evaluating a person is more wide and balanced. Below I give 3 major measures.

IQ - Intellectual Quotient:
Measures a person's cognitive abilities. Research shows "IQ is correlated with academic success; it can also predict important life outcomes such as job performance and socioeconomic advancement."

EQ - Emotional Quotient:
Measures a persons "ability, capacity, or skill to perceive, assess, and manage the emotions of one's self, of others, and of groups." Some researchers have found that emotional intelligence is an important predictor of grades, promotions, health, and relationship quality.

AQ - Adversity Quotient:
Measures a person's resilience to adversity. Case studies indicate that AQ is a good predictor of performance, promotions and sales resilience in the candidate. AQ has been studied on a total workforce scale and found correlated with business success. An important finding is that AQ is a factor that can be rewired and increased for most people through training. Due to the simple measures needed to get better and the direct business implications, AQ has become very popular in the business world.

Notice that when it comes to effects, these quotients overlap. From my perspective these measures are not MECE. The measures are correlated (as studies show) - hence not being Mutually Exclusive (ME). Furthermore, I believe they far from convey the whole picture, hence not being Collectively Exhaustive (CE). Quotients on our abilities offer a lot of (r)evaluational potential if someone takes a holistic focus on improving them.

Little's Law

It strikes me that Little's Law [1] is a wonderful little equation that balances usefulness and simplicity. I wonder how many business cases and capacity evaluations I have made and evaluated that could have been done so much simpler! Two definitions:

a. For the business:

"The average number of customers in a stable system (over some time interval) is equal to their average arrival rate, multiplied by their average time in the system."

b. For the technical:

"The average number of objects in a queue is the product of the entry rate and the average holding time.'' [2]

[1] Little's Law (Wikipedia)

[2] Little's Law (Bell Labs)