Six Sigma is a quality improvement program that gets its name from the concept of 99.9997% quality. In statistics, each sigma represents the statistical measure of 1 standard deviation from the mean in a range of outcomes. Six sigma translates into no more than 3.4 defects per million opportunities.
It is often related to (and sometimes conflated with) the concept of “Lean”, which was coined to describe Toyota’s manufacturing practices during the late 1980s, when their level of consistent quality was noticeably superior to much of what was coming out of Detroit at the time. Lean focuses on improving efficiencies by reducing waste through standardization and elimination of non-value-added efforts. Six Sigma, developed by Motorola and widely popularized by GE and others, focuses on improving quality by reducing process variation and using detailed measurement and statistical analysis. The two are often used in tandem in Lean Six Sigma programs.
Striving for this kind of consistent quality can save lives in healthcare procedures and plant safety. It is what we have come to expect today from our personal electronic devices and even from lower priced automobiles, and this is the kind of uptime we expect from computer and communications networks.
In financial services, it’s what we strive for in our transaction processing, statement production, compliance programs, and reliability of our ATMs and core systems.
What’s not to like?
Quality, consistency, efficiency, defect reduction, what’s not to like?
Lean and Six Sigma programs work well when there are identical operations and repeatable processes in large volumes, particularly when those operations can generate a lot of accurately measured data. When administered properly, they also focus on creating real value by improving quality, cost and customer satisfaction.
But what happens when you perfectly execute the wrong priorities?
Kodak was arguably the best manufacturer of celluloid film in the world (although Fuji Film might argue that one). Nokia was the world’s leading maker of mobile phones, with 48.7% market share in 2007. Sony’s Walkman was the leader in portable music for a decade. The quality of their operations was admirable, and not what turned out to be the achilles heel for those companies.
New technologies and new business models regularly disrupt the status quo. Blockbuster beat all comers in the business of operating video rental stores. They executed the standard business model of their industry better than anyone else. Netflix didn’t beat them at their own game, they changed the game.
Blockbuster is an especially good example for financial services. For most of the industry’s history, success has been about executing the same business model better than largely similar competitors. The winners of the consolidation wars over the past three decades have been those who executed with the efficiency that created operating leverage.
“There is nothing so useless as doing efficiently that which should not be done at all” – Peter Drucker
Efficiency and positive operating leverage are important ways to win the standard game in financial services, but they aren’t necessarily enough to counteract the new technologies and new business models that are changing the game now and in coming years. Nor will simply blindly going all-in on the latest in fintech hype. How can we balance operational excellence and efficiency with flexibility and innovation?
The power of One Sigma
One of the drivers of the dot com boom and bust of late 1990s was the notion of ‘build it and they will come’. Billions of dollars of equity was invested in new technologies that were promising, yet unproven in the marketplace. Valuations got unreasonably optimistic, money flowed too freely, and millions of dollars of advertising was spent hawking products that not enough people wanted.
Eventually reality set in, valuations came back to earth, and the weakest value propositions died off. New wisdom prevailed from Geoffrey Moore, Steve Blank, and others, including Eric Ries who offered a better formula for testing ideas before making big bets. This process of Build, Measure, and Learn is a twist on “lean” methodologies that Ries detailed in his bestselling book The Lean Startup. But this ‘nail it then scale it’ approach is not just for startups.
In financial services we tend to think that if we can just get all of our smartest people in a conference room, perhaps supplemented with the best consulting minds we can rent from the outside, we can perfectly plan out all of our strategies and “roadmaps” down to the last detail. Then, all we need to do is execute them perfectly. Plan your work and work your plan. Simple, right?
But the marketplace has a way of making us look stupid when we make think we can plan for every contingency up front. Market conditions change, customer preferences evolve, and the competitive landscape shifts, so our plans have to be flexible and responsive to these changing conditions.
One Sigma in a normal distribution covers more than two-thirds (68.27% to be exact) of the outcomes. That’s not nearly good enough for heart surgery or network reliability, but it’s a pretty good indication that you’re on to something worth testing further.
The answers are outside the building, not inside the boardroom. The sooner we can test our ideas, the sooner we’ll know whether we should increase our bets or iterate to something better. That’s stacking the odds in your favor in the strategic planning process.
By all means keep those Lean and Six Sigma programs going where they’re working, but navigating these uncharted waters in our rapidly changing industry takes a new approach. It’s time to embrace the power of One Sigma.