Dogs chasing cars: The value of accurate data analysis.

Taiichi Ohno used to say “Where there is no standard there can be no Kaizen”, which can be translated to “you can’t improve what you don’t measure.” However, these two sayings have a critical missing element... the term “accurate”. Many organizations fall victim to poor data interpretation and instead of improving their processes they do them more harm.


Good data analysis is an integral part of good idea management systems. Breaking down the raw data and identifying trends in idea quality, user participation, and aging of ideas can help program administrators improve the process, however, the wrong slicing and interpretation of the metrics can quickly hinder it.

This concept always brings me back to my love of golf and in particular one of my pet peeves… the “Putting Average Leaderboard”.

It has always struck me as odd that one of the statistics most used by sports analysts to measure a pro golfer’s performance is their putting average. Normally, when a golfer has a bad year following a good one, they will usually look at their putting average as the culprit for the fall from grace.

Needless to say, putting accounts for close to 50% of strokes on a golf course, and putting averages are mostly the result of a golfer’s ability to get the ball close to the hole with the other 13 clubs prior to using the putter to finesse the ball into the hole. When there is only a 0.10 average put per hole separating the top putter and the 80th on the list, and when you realize that 2010’s top two money leaders, Ernie Els and Phil Mickelson are ranked 54th and 53rd respectively on the average putts list, it is time that analysts realize that this list does not come close to predicting how good a golfer is.

It’s a matter a fact that the top golfers find themselves putting for birdie more often than the golfers at the top of the putting list. The golfers with the lower averages are usually the ones having to chip and putt for par, and these are precisely the ones we seldom hear winning a green jacket and the first ones in line to join the Nationwide tour.

For Phil and Ernie, if they were subject to ‘management decisions’ made by interpreting the data, they would probably be sent to ‘putting-re-certification’ class. Unfortunately this would cause them to spend time away from sustaining and developing their other skills, and would likely lead them to fall off the top of the money list.

The irony would be that they would likely climb up the putting charts, giving ‘management’ the impression that the re-certification classes were effective and failing to realize that they have hindered their ability to be top performers by placing them in a position to sink more ‘PAR’ putts.

Thus, from the analytical sense, the putting average list has no value and the data represents a red herring, that if followed as most analysts interpret it, would lead to good golfers losing their winning ways.

… and as the old saying goes… “There are two things that don’t last very long: dogs chasing cars and pros putting for pars”

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Blame the process and not the person: Quality, redundancy, and catastrophic failures in the sinking of BPs Gulf of Mexico platform.

Seeing that my natural vacation sanctuary, where I normally go to break from life’s stresses and enjoy time with my family is about to be permanently destroyed, I decided to break with the Idea Management and Lean tone of this blog in order to reflect a little on quality management. For many years, I helped Mercedes-Benz suppliers improve their quality through lean tools, but also through the use of statistics. Even though I was never formally trained as a Six-Sigma ‘grasshopper’ and much less a Sensei, I did use many of the statistical tools found in the Six Sigma toolbox.

The FMEA has always been a key tool in the auto industry to identify areas of product quality risks and thus planning how to mitigate them. Those components that can play a role in a potential catastrophic failure, loss of life or loss of property, get treated with extra care. To generalize, these components are ‘serialized, and data is recorded along the entire manufacturing chain. Every critical process is monitored, and equipment is designed to “inspect” its own quality, and in the case of critical characteristics, it’s designed to check the quality of preceding processes. Redundancy is so built that if one inspection process fails, the next one will catch the defect. These redundant checks are designed in layers and their ultimate goal is to ensure no bad parts exit the manufacturing process.

With that said, to put six sigma quality in perspective, aircraft are a good example of redundant systems at work. Critical systems in aircraft are designed with multiple backup systems. (Keeping math simple, and not using real life numbers) If a hydraulic system has a natural tendency to fail once in 100,000 uses, applying a backup system ensures that in a worst case scenario, a simultaneous failure will only occur once in 100 billion uses.

In general there are two major reasons for quality failures: The first is the failure to identify a potential failure mode and thus not guarding against it and is normally due to lack of historical reference or a lesson learned. The second is by far the worst, and it’s the failure of people to follow established procedures. This is critical because it is not a reflection of the actual workers, but rather a reflection on management.

Bunji Tozawa said “Blame the process and not the person”. What he eludes to is that management is responsible for the processes and thus a failure is essentially their fault.

Like the auto industry, big oil relies on suppliers, and it’s extremely critical to ensure these suppliers manage and maintain their internal procedures. In the auto industry we don’t only measure and rate suppliers by their ability to supply good parts, but we also audit their adherence to their quality systems and have different means of flagging potential problems before they occur. The proactive approach is taken to ensure that human lives are not lost driving cars.

Having a deep understanding of quality systems, redundancy, and personal ties inside the oil industry, putting my head around the sinking of the BP platform and BPs overall safety and environmental record (Pipeline 2006, Refinery explosion 2005) is almost impossible to think that it all happened because of ‘bad luck’ or failed equipment! This wasn’t a failure as in case one: Not identifying a potential failure mode, but instead a failure to follow procedures and adhering to best practices.

A reason why in general the global oil safety record is good is because of strict processes and procedures (I also wrote about managing safety and how Schlumberger uses idea management systems to manage identified safety risks.) Keep in mind that there are more oil wells in operation than there are aircraft in the air on any given day, and the number of catastrophic incidents pale in comparison to the aeronautical industry. (Here’s an old CNN article showing the worse accidents through 2001)

The bottom line, when the dust clears, a thorough investigation will likely yield a lack of self auditing and supplier auditing practices inside BP, and management’s inability or unwillingness to ensure that the entire corporate culture is driven by adherence to established procedures. A good indicator here will be BP’s response. As they start to blame Transocean (the operator of the rig), “a faulty blow-out” control system, a missed maintenance step, or operator error, what they really will be saying is that management has been incompetent and unable to drive a corporate culture that adheres to strict safety and environmentally relevant procedures.

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Lean Idea Management: Balancing the idea assembly line.

People have asked me in the past year what Lean Idea Management meant. They assumed it had to do with managing Kaizen in lean organizations. Although in reality our Idea Management tool would bring value to Lean organizations, it also applies well in all organizations.

The reason I named the blog Lean Idea Management, and really what drove the design of EurekaTool was the need to eliminate the non-value added steps often associated with that assembly line called “ideation-to-implementation”. There are many areas of waste in a typical continuous improvement process, even in lean companies.

For one, most ideas are recorded on paper, or perhaps a Kaizen Card. The idea has to be communicated to several individuals in order to align needed resources or get buy-in. Typically this happens in meetings. Ideas, and supporting documentation are put in manila folders and passed around for evaluation and eventually if the idea is good, it is handed over to someone or a team of implementers. Ultimately, most organizations I have seen, also have a coordinator or team of coordinators that walk these folders around, hand them over, retrieve them and even coordinate the meetings. Most of the time these coordinators, or gatekeepers, become bottle necks under the extreme load of keeping the idea assembly line moving, and at times have been known to make ideas ‘accidentally’ disappear.

If you try to picture this ‘idea assembly line’ you can envision a lot of people walking to and from these ideas, instead of the ideas coming to them. All this walking back-and-forth is non value-add. Then you have the bottle neck; the gatekeepers sifting through tons of paperwork, and trying to coordinate the whole thing. They try to chase down individuals who have sat on ideas for weeks (if not months). Imagine this process for 120,000 ideas?

Essentially, the manual process boils down to an assembly line that is not balanced – too much work on few individuals - , and no concept of Kanban – there is no natural method of pulling the idea through the process, and constantly has to be pulled and pushed by the coordinators (literally walking back and forth with the folders). Ultimately there are no Poka Yokes and visual flags alerting individuals and management that a good idea has not been evaluated on time, implemented, or perhaps lost… (which is common in these manual systems.)

So in general, as lean organizations engage in continuous improvement, very often they fail to improve that continuous improvement process itself, and this is where idea management software can truly solve many of the problems, add-value, and eliminate the waste encountered in this most necessary process (if you’re going to sustain Lean).

1) Elimination of paperwork and eventual transcriptions into a database or spreadsheet. Ideas are entered by idea generators via the web (typically an on-site kiosk)
2) Routing of ideas to multiple champions, depending on area or idea type, thus eliminating the overloading of the coordinator.
3) Electronic notifications of task assignments and full transparency (to everyone) where the idea is on the ‘assembly line’
4) Alarms and escalation of tasks which are overdue.
5) And last but not least, the metrics and visual communication tools needed to keep everyone informed of how well the process is performing: Idea Quality, throughput time at different stages, participation, and (of-course) cost savings or process savings generated.

Bottom line, the software becomes the virtual assembly line, and the resources needed to evaluate and implement only get engaged when necessary. The notifications and alerts keep the line moving, and the administrator no longer becomes a full time resource assigned to keep the process moving, but instead a part time maintenance worker that can spend time on other value-add processes throughout the organization.

Ultimately, when the system is inefficient, it leads to individuals who have great ideas to lose faith in the system and cease their contributions - there is absolutely no value in ideas, only in their implementation.

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Managing ideas that save lives - Can you afford not to do it effectively?

If there is anything to learn from the Toyota accelerator fiasco is that there is a vast disconnect in the reporting systems that currently exist in organizations to stay abreast of safety situations which could be deemed ‘catastrophic’ (loss of life impact).

Part of the reason that Toyota did not address the accelerator problem more decisively was the fact that the external sensors (data collection points) that they were utilizing were not well integrated and collected a lot of erroneous or misleading data. NHTSA was perhaps one of the biggest contributors to this problem by not feeding all accelerator issues back to Toyota, or providing collateral data indicating the problem may have been driver error and thus adding ‘noise’ to the data needed to fully understand the extent and the root of the problem.

Now in no way am I saying Toyota was innocent in this matter, but I do want to defend them in their methodic ways of not jumping to conclusions without letting the data speak first. One of the core teachings of Lean is that “you cannot improve what you cannot measure” however measuring also has to be accurate. If data is inaccurate, as was the case with the acceleration problem, then it is understandable that there was a delay before Toyota clearly saw that there was a major problem to be addressed.

The dilemma stems from the fact that this dirty data cannot be used as a defense. To a degree most auto manufacturers, and to that extent, most organizations are using sensors that are potentially flawed and inaccurate, let alone internal sensors. When it comes to safety matters there really is no room for error since bad data is as good as no data, and people’s lives are worth the extra time and effort to ensure data is accurate and the handling of the data is treated with priority.

Recently I had the opportunity to speak with someone at Schlumberger regarding their QUEST program. The quest program is an idea management system focused on safety issues and based on the DuPont STOP methodology. (For those not aware of the STOP methodology, essentially it’s every employee’s responsibility to identify and report all areas of safety risk.) Schlumberger realized that in the oil services arena risks are plentiful and thus decided to bring some solid structure behind their process. Their QUEST system manages all global incidents and keeps every Schlumberger employee abreast of the latest incidents and risks, and provides them with an immediate ability to record risks they detect and possible solutions. However, the key component is the escalation… top management is advised of risks which have not been addressed promptly or catastrophic incidents (loss of life, environmental damage, etc).

As I learned more about Schlumberger’s process I also learned that in the oil services industry, Safety (and the environment) are so important that not having solid processes to manage these points can cost contractors their business with big oil (Exxon, Shell, Chevron, etc).

Applying this lesson to Toyota, and all the other Toyotas out there, at the first indication that an accelerator pedal was involved in a loss of life incident, Mr. Toyoda should have been notified. Was he? Probably not, and perhaps it was after several losses that someone, perhaps a data clerk sifting through warranty data noticed there was a possible problem.

In conclusion, with the kind of technologies and applications available on the market, there is no reason why any company should not adopt an idea management software system to streamline their continuous improvement initiatives, but more importantly, keep their workers and customers safe. Companies spend billions of dollars each year on software to keep their inventory and orders under control, why not spend some of that on keeping loss of life and lost time incidents under control? After all, as we learned with Ford and Firestone, and now with Toyota, loss of life can be costly and especially for those that fail to take all measures necessary to protect it.

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Innovation is about adding value.

I am guilty of making the same mistake many make about innovation – believing it’s usually about state-of-the-art inventions. I recently blogged about the Apple iPAD and did a good job of criticizing the lack of new technology. After all, the iPAD is essentially something between a large iPhone or a small laptop that most companies will be able to emulate. From the outside this doesn’t look like a great invention, however, leave it to Chuck Frey to set me straight.

I came across his recent blogpost “Seth Godin on the power of remarkable ideas” and realized that I had failed to acknowledge what Apple does best. They historically have not been a technology leader. (The Mac (1984) was not the first computer to have a mouse or have a user friendly GUI. The iPod was not the first mp3 music player.) However, Apple has always had the ability to perfect a product or service and continually improve it until it shines. They are able, better than any other company, to determine what people really want, and deliver value to them… after all, innovation is about delivering VALUE!

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The big challenge in Open Innovation (Part II)

What’s in it for me? This is the very first question most of the participants in an open innovation initiative will ask. One of the aspects often overlooked with OI is what will the process or organization give back to the participants. It is very easy to give out cash prizes for winning ideas or participation, but is what is the formula for ensuring participants keep coming back in an open Innovation scenario?

Creativity and The Performance Paradox, by Steve Shapiro, is perhaps one of the best explanations I have seen in trying to understand the right balance of motivation that has to be provided in order to get the desired performance. It reflects on the Yerkes-Dodson law, where performance increases with motivation up to a certain point after which performance drops. (I want to credit Stefan Lindegaard who suggested I look up some of Steve’s contributions in this subject, and thus saving me a long dissertation on this topic.)

Keeping this in mind, there is one more element that is sometimes forgotten when implementing the motivation structure in an open innovation culture. The ‘Learning’ element is sometimes forgotten, but one of the most valuable weapons in ensuring that the OI culture matures and becomes highly effective towards the expected goals of the OI initiative. Many participants in an OI activity join because of the rewards, but as they engage the process they find that they also find a reward in what they are learning from the activity and from other’s involvement. (This could perhaps make a case for continued participation without rewards, however, at a given point, as their experience and knowledge grows their ‘learning’ reward begins to diminish.)

From the OI side it’s critical to keep these ‘learned’ individuals coming back. They are no different than employees who you’ve spent significant resources on, and the OI initiative benefits each time they return. These individuals are more adept at the process, and with each return their ideas increase in quality and they become more adept at making those critical ‘idea connections’ that need to occur as multiple individuals from different walks of life collaborate on a particular problem (see Innovation: Collaboration has a multiplier effect.)

In the attempt to ensure the participants return, I usually like to take a page from the Airline Industry’s handbook… frequent flier miles. Making a flight on a particular airline will get you nothing but points, but continuing to loyally fly the airline can eventually get you free tickets. What this means is that there has to be a motivation transition or connection from one OI initiative to the next in order to maintain participant loyalty.

In OI there really is no need to provide a large ‘home-run’ prize, after all, as Steve Shapiro clearly explained, participants will be engaged for the wrong reasons and their creativity, which is essential to OI, will likely be diminished. The learning experience is a significant reward in itself and coupling it with a structure that allows participants to incrementally build towards a reward (like in the frequent flyer case) can be a powerful weapon at securing their loyalty to the process while in return they increase their ability to add-value with each subsequent open innovation challenge.

The big challenge in Open Innovation (Part I)

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The big challenge in Open Innovation (Part I)

I started investigating stats regarding open innovation to see what I could find regarding the idea quality ratio. In simple mathematical terms this ratio is the number of approved (or implemented) ideas divided by the total submitted ideas.

Over the years, data from most idea management processes has shown that programs where this ratio is high, participation, and more importantly return participation, runs high and tends to increase. However, when this ratio is low, participation tends to decline. The reason for this is simple; most people don’t take rejection very well.

I came across this blog entry from Stefan Lindegaard regarding my old employer’s (Daimler) attempt on open innovation. There was a very telling line that he quotes from Daimler’s “Style your Smart” contest where 50,000 design ideas were received from over 100 countries and only six prizes given out. (3 for design and 3 for active participation in the contest by evaluating, uploading and commenting on designs)

The obvious result of this was that for those that came out winners, this was a great experience, and in a heartbeat they would probably participate in the next Daimler open innovation initiative. But what about the thousands of non-winners who entered ideas and helped evaluate and rate the designs? Will they spend the time and effort to do this again?

Daimler’s attempt, to a degree, recognized that engaging individuals required more than declaring a design winner. “Style your Smart” cleverly gave out prizes for participation, thus giving individuals a little more hope that they could win something, but for the most part it was a marketing gimmick that lacked a clear vision of how to re-engage the original participants in Daimler’s next OI initiative.

What is clear is that in the development of an open innovation culture one of the most important questions that has to be answered is... how do you guard against the inherent erosion of contributors?

The big challenge in Open Innovation (Part II)

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Something Different

A new book by Youngme Moon promises to be “Different”. In this age of bigger, better, faster, it’s time for companies and people to be different. Organizations are beginning to realize that they need to instill the innovation culture in their organizations in order to stand out. Whether it’s on the shop floor continually innovating improved processes to eliminate non-value-added steps, to online communities of customers and employees brainstorming the next product breakthrough, managers in today’s business world will need to challenge their teams to break with paradigms and go against the grain in order lead.

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Kaizen Teams = Innovation Teams

The common recommendation by TPS experts is that Kaizen teams must be cross-functional. The common rule is to form the team with 1/3 target area members, 1/3 from upstream and downstream areas, and 1/3 from external areas (i.e.: Finance, engineering, HR).

This makes sense, and sounds reasonable, however I found that perhaps the best way to explain the benefit of the cross-functional structure of the Kaizen team is to look into the ‘science’ of innovation. After all, Kaizen IS Innovation… albeit most people associate the latter, by default, with radical innovation (i.e.: iPODs, blackberrys, NASA, etc.). On the other hand, Kaizen (in 99% of the cases), is about incremental innovation, but the best practices for achieving incremental or radical innovation are the same.

Perhaps one of the best articles I’ve read about innovation was in the New Yorker (see this blog post), and clearly shows how great inventions come from the sharing of the right information at the right time. It goes into detail of how a company, Intellectual Ventures, was founded and how it became one of the greatest inventing organizations of our time. (IV, as it’s known for short, is 100% dedicated to the business of inventing, patenting, and licensing their inventions.) So how do they do it? While most organizations load up their R&D departments with engineers, doctors, chemists, and technical gurus, IV loads up with, lawyers, doctors, pilots, musicians, paleontologists, chemical engineers, programmers, teachers, and everyone you can think of, and launches brainstorming sessions to tackle myriads of problems. What they realized is that inventions seldom come from one individual and instead come from a set of circumstances that bring multiple experiences and information together in one place to help solve a problem.

That’s why a Kaizen team benefits from being cross-functional, and why the ‘thirds’ rule makes good sense. The more varied the experiences, the greater will be the chance to succeed with a solution.

So as I like to say when emphasizing the benefits of teamwork… Nobody has the answer, but everybody has the answer.

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Open Innovation: Corporate citizenship redefined.

One thing that I was taught when I was young was that sharing information with others and not keeping secrets could make you friends with a lot of people. In today’s market, it looks like major corporations are starting to leverage that axiom to further expand their corporate dominance.

Being a good corporate citizen no longer means charitable giving to local communities, and hiring interns from local schools. The definition has been transformed by some of the top corporate citizens to include direct participation from the community in identifying the next products, services and trends. In the case of IBM’s 2006 Innovation Jam, they allowed their corporate crème-de-la-crème to openly collaborate and share ideas with common citizens, and the result was an impressive 46,000 ideas from employees, family, friends, and partners, of which 10 were identified for further funding.

What has become clear is that cloud-based idea management platforms, which are configured for open innovation, are quickly becoming the tool of choice for these modern age corporate citizens to proactively engage their communities.

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