Blizzards and the Birth of the ATM

March 31, 2008

“Build it and they will come.” We hear that mantra a lot. But with innovation, it is often more like, “Solve a pain and they will come.” The ultimate success of the automated teller machine (ATM) is a great example of this.

The other night I was having dinner with someone who in the mid-1970’s worked with Citibank, the second largest bank at the time. He shared with me the story of the birth of the ATM, at least from his perspective.

In 1977, after investing hundreds of millions of dollars in ATM technology research and development, Citibank decided to install machines across all of New York City. But at first, they were not very popular. The technology was confusing to first-time users, the machines were not always accurate (they sometimes dispensed the wrong amount of money), and they were impersonal. I was told that customers who used ATM machines were so frustrated that many closed their accounts.

The ATM may never have been an instant hit if it weren’t for a natural disaster.

January 1978 will always be remembered for a blizzard that dumped as much as 4 feet of snow in the Northeast. In New York City, nearly 2 feet of snow brought the city to a halt. Banks didn’t open. Instead, people got their money from supermarkets. But most of those quickly ran out of money.

This created a massive “pain.”

Where did people turn? The ATMs. It is estimated that during the storms, use of the machines increased by over 20%. Soon after, Citibank started running TV ads showing people trudging through the snow drifts in New York City. That’s when the company introduced their wildly popular slogan, “The Citi Never Sleeps.” This was the real birth of the automated teller machine.

I found an interesting Fortune article that corroborates his story. The article claims that by 1981, Citibank’s market share of New York deposits had doubled. A lot of this growth could be attributed to the ATM.

This story illustrates an innovators dilemma. Brilliant innovations are not necessarily taken up by the masses. Some ideas just need time to incubate and gain acceptance. But can your business survive long enough to see the success? Too many ideas, like Webvan, could not endure the incubation period. Sometimes your innovations need a little boost.

As I have pointed out in previous blog entries, people take massive risks to eliminate their pains, but play is safe when it comes to adding convenience. ATMs were primarily about convenience. What did it take for them to become a success? A pain caused by a natural disaster.

Are your new ideas solving a pain? Or are they just a nice to have? If they are just a convenience, what can you do to create a pain – without having to rely on a natural disaster?

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“21 The Movie” and Innovation

March 28, 2008

[youtube]http://www.youtube.com/watch?v=PsK1c9ZBpuw[/youtube] 

“21: The Movie” is in theaters today in the United States.  Last week I wrote a blog entry on what innovators could learn from blackjack card counters. 

Today, to celebrate the formal release of the movie, I am including a downloadable pdf with a full article on the topic of statistics, probability, card counting and innovation.  This is an expanded version of the blog entry.

Download the article (pdf) – to save the file, right click and “save target as”

Feel free to email the article to all of your friends, colleagues, and anyone else who is interested in innovation.

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Analogy-Driven Innovation and Pavlov’s Fish

March 26, 2008

What if you could train a fish like you train a dog?  What if you could create a Pavlov’s fish? And why would you want to?

According to an Associated Press article, “The idea is to train fish to return to a feeding source when they hear a particular sound.  Scientists are testing a plan to train fish to catch themselves by swimming into a net when they hear a tone that signals feeding time. If it works, the system could eventually allow black sea bass to be released into the open ocean, where they would grow to market size, then swim into an underwater cage to be harvested when they hear the signal.”

This is an interesting example of analogy-driven innovation; taking a concept from one area and applying it to another.  This idea must be gaining popularity.  Just last week I was interviewed by a major national newspaper on the topic of analogy-driven innovation.  This can be an incredible source of new ideas – without needing to reinvent the wheel.

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What Innovators Can Learn From Vegas Card Counters

March 21, 2008

Which will help your business be more successful: statistics or probability?

Underwriters at insurance companies use statistics to assess future risks. This is based on years of collected data.

Probability is what card counters in Vegas use to increase their odds of success. This is based on real-time, real-life experience.

If you want to play it safe, use statistics. If you want to win big, use probability.

There Are Lies, Damned Lies, and Statistics – Mark Twain

Businesses are increasingly using statistics to manage decision making, as evidenced by popular books like Tom Davenport’s Competing on Analytics and the boom in CRM system usage.

The belief is that if we gather more data we can make better decisions. But this may not be true when it comes to innovation.

If you are crunching numbers, you are probably gathering information from existing customers. This will give you insight into their buying habits, usability behaviors, and other patterns. But most likely you are only gathering data on YOUR customers.  This represents the middle of the bell curve or the norm. This information may be useful in “incremental” improvement, but it will rarely lead to significant innovations.

When you move beyond the norm to the far ends of the bell curve, you will find the real interesting ideas.

Being normal is not a virtue; it denotes a lack of courage

On the far right-hand side of the curve are the market leaders; the advanced users. They may not be your customers because you can’t meet their high-end needs. Or maybe they were once your customers and they left. When someone is not a customer it is difficult to gain insights into their wants and needs. If you could somehow understand their perspectives, you may find opportunities for “advanced” innovation and insights on where the industry may be going in the near future. These innovations would be more radical, yet continuous in nature. Think of this as the Blu-ray improvement on the standard DVD (we’ll save a discussion on the demise of HD DVD for another time).

On the far left-hand side of the curve are the laggards; the less sophisticated users. Your products/services may be too advanced, too complicated, or too expensive for their needs. Again, you are probably not gathering statistics on these individuals or organizations. But here lies the greatest opportunity for discontinuous innovation.  Or as Clayton Christensen would call it, disruptive innovation.  If you can find a way of “dumbing down” your offering, you might find new and untapped sources of revenue. Quite often these products become the de facto standard, much like when PCs replaced the more sophisticated mainframes and mini-computers.

The problem is, it is very difficult to get data about the ends of the bell curve. Focus groups, surveys, and other traditional data gathering techniques are useless. I love this quote from Scott Cook at Intuit: “For every one of our failures, we had spreadsheets that looked awesome.” We can use numbers to justify anything we want. But quite often they justify the wrong actions.

The Probable is What Usually Happens – Aristotle

If a statistics-driven innovation model does not work, what would a probability-based model look? Probability tells me that if everything is equal, the more bets I have, the more likely one will be successful. The odds of 1 success out of 200 are greater than 1 success out of 20.

But how can you have more bets without diluting your effort and potential returns? The key is to learn as you go. This is exactly what card counters to.

Let’s contrast a more statistics-driven model with a probability-based model. To do so, we will use two exceedingly simplistic examples. With innovation model #1, you make a few “big bets” based on analytics you gathered from your customers (a statistics-driven model). Innovation model #2 is a more experiential “learn as you go” model (a probability-based model).

In both examples, let’s assume you have $100 million to bet, woops, I mean invest in innovation.

[Read more]

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Simplification is Innovation

March 20, 2008

Antoine de Saint-Exupery, author of The Little Prince, once said, “Perfection is finally attained not when there is no longer anything to add but when there is no longer anything to take away.”

This is a brilliant quote because it describes the challenge many innovators face.  Too often, new products are overly complex and end up “over-serving” their customers.   

My new computer with Vista and Office 2007 is a perfect example of that.  99% of the software’s functionality goes unused, yet these complexities slow down my computer and reduce ease of use.  Being able to do everything for everyone is not perfection.

Next time you are designing a process, a product, or a service, ask yourself, “What can I remove?” For most consumers, simplicity is more important than comprehensiveness (and complexity).

The concept of “taking away” is also a great time management technique.  In addition to your “to do” list, be sure to create a “don’t do” list.  Become masterful at killing products, eliminating non-value adding tasks, and removing old/pointless habits.

Or, as Michelangelo once said, “In every block of marble I see a statue as plain as though it stood before me, shaped and perfect in attitude and action. I have only to hew away the rough walls that imprison the lovely apparition to reveal it to the other eyes as mine see it.”

What are you doing that is imprisoning your perfection?

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