Neil Ward-Dutton has a great post about BPM vendor results that moves into a discussion of process improvement approaches:

The distinction between “old school” and “new wave” process improvement approaches (I’ve called these “high church” and “low church” before) is just continuing to get stronger. 10 years ago, the vast bulk of process improvement activity used to be driven by the “high church” crowd: lots of ceremony, burning of incense, and so on. Scientific improvement efforts driven by highly-qualified specialists are essential in situations where there’s a lot at stake (for example when you’re reengineering an auto manufacturing line: get it wrong and it’s going to cost you a lot to put it right). And don’t get me wrong: there’s definitely a place for this.

This description and the ensuing thoughts reminded me of our early experiences with BPM at Lombardi.  Lance and I (and others at Lombardi) were often running into process improvement experts with a grounding in Six Sigma or Lean (or less often, IDS Scheer, or Enterprise Architecture modeling).  We were sometimes supported by these folks, and sometimes they resisted our approach (and “BPM” in general).  On the whole, there was a lot of resistance, as our approach to process improvement was somewhat heretical.

So Lance (now CEO of BP3), embarked on a journey to get behind the curtain, to understand the vestments of the Six Sigma and process improvement community so that we could better work with these folks.  After going through the first rounds of training at the Green Belt level, he started to get others of us to go through the training as well.  And what we found was that you didn’t have to adopt the religion of Six Sigma to get the value.  The statistical tools are just that :  great tools you can use.  The “high church” trappings are wholly unnecessary but they do create an aura of authority for those who exercise them.  Lance went on to become a certified Master Black Belt, but we continued to apply what we learned from Six Sigma in an eminently practical way.  The point isn’t to be “pure” – the point is to get to value faster.  If statistics can do that for your business, then you use them.  In our mind, if a BPMS can do that for your business, then you use it.  Make the best of the tools at your disposal to get the maximum benefit.

Still, there are those whose self-interest is aligned with keeping the “high church” ceremonies and orthodoxy firmly in place.  The challenge is to keep it in perspective – scientific approaches can inform the “new wave” way of thinking without slowing things down.

One of the ironies now is that some of the newer entrants to the Business Process space now see BPM as the high church (old school) and their own approach as the new wave.

Interesting article in the MIT Sloan Review on “Where Process-Improvement Projects Go Wrong“.  It compares process improvement projects to the behavior of a metal spring, by dividing into three phases:

1. Stretching – at the beginning, a small team is motivated to succeed, and has support of executives.  A six sigma or process improvement coach helps them navigate some of the harder issues to make sure they stay on target and achieve early success, which causes additional initiatives to be kicked off.
2. Yielding – As the process improvement coach is removed, teams begin to revert back to prior behavior, or lose the ability to get the team objectively past some of the harder sticking points.  Executive attention, and perhaps some of the best team members, has moved to other projects.  Performance starts to retreat, though not necessarily to pre-improvement levels.
3. Failing – the vicious cycle begins “With the improvement expert long gone and no additional training in Six Sigma or other improvement strategies provided by the aerospace company, team members became increasingly discouraged by their failure to build on earlier success. They eventually stopped caring about the improvement project, partly because it wasn’t tied to their performance reviews.”

Well, I feel motivated, how about you? Luckily we are not springs, we’re people, and we can be a bit more creative about avoiding this inglorious “failing” phase than the author imagines.

The article author proposes 4 lessons learned from the many companies they studied for this report:

1. Keep the improvement expert around longer – or share this expert among more than one team to spread the cost – but the recommended term was 2 years, augmented by training managers to pick up these responsibilities.
2. Performance appraisals tied to improvement.
3. Keep teams small (less than 10).
4. Executives need to directly participate in the projects, not just receive reports from someone who has incentive to focus on only the good news.

This isn’t bad advice, it is good advice to start.  But it is insufficient and unlikely to cause organizations to suddenly get higher success rates with process improvement.

What did they miss?  Well, they missed BPM, is what they missed.  One of the reasons BPM is a “killer app” for process improvement is that when you discover the most effective changes to make for your process, you can put them into software, not just into a book of Standard Operating Procedures that your team will quickly forget about.  And your improvements aren’t just things that people on the team learn and practice, nor just things that they pass on to others on adjacent teams – they are things that get encoded into your process.  The software gives you:

• Some resistance to the “yielding” phenomenon described in the study results.
• Accurate measurement over time – no dependence on manual measurement techniques that may degrade as team members lose interest in the stop watch and other manual measurement techniques.
• The ability to “bake in” an improvement and move on to the next thing, rather than get stuck in a high-cost maintenance of the first improvement.
• A “control” baked into the software.  (Six Sigma has standard approach called DMAIC – define, measure, analyze, improve, control… and BPM software directly addresses D, M, and C, and supports the A and I activities…)  So often the “failing” phase is because the organization loses focus.  Software doesn’t lose focus – it just keeps running.

Too often, the proponents of Lean and Six Sigma ignore technology because they view it as an impediment, failing to understand that there is more to technology than MiniTab or SAS/SPSS or Excel.  And if technology allows you to do something at lower cost, such as a process improvement project, or maintaining an improvement over time, then it shouldn’t be dismissed out of hand.  But it is easy to understand why they sometimes see tech as an impediment – deploying software takes time – and during the initial phases of improvement the improvement guys just want to move fast.  My take is – don’t let the tech get in the way, but don’t pretend it can’t dramatically improve the efficiency of your business – in fact, technology, and specifically BPM software, is likely the key to locking in the gains you seek to establish a “new normal” that is a more efficient and effective process.

All too often I see conclusions based on observable data, where the conclusion does not necessarily follow the data presented.  This doesn’t mean that the conclusion is wrong on the face of it, but that it can’t be made based on the facts presented thus far.  Sometimes the conclusion is presented as causal when it is only correlated, sometimes it is extrapolating from a really small sample to describe the whole population (over generalizing).

I recently read Theo Priestley’s post on why Six Sigma doesn’t work in the real world.  In it, he relates a LinkedIn posting from someone attempting to do six sigma analysis on a call center process.  From reading the LinkedIn posting, it is clear that the person posting is not experienced in Six Sigma or other  related process improvement technologies that would be helpful to the cause.  This person is trying to figure out how to get a bell curve from a formula related to rate of defects in the call center process, where a defect is defined as a call response being over 60 seconds.  Theo extrapolates from this that it is an example of why Six Sigma doesn’t work in the real world, and why black belts are not needed (all that is really needed, he says, is a pragmatic approach).  And he quotes a response he advocates:

“…at the end of the day if you produce a bell curve telling me the USL and LSL for my call centre, along with the number of defects per million and a sigma value of 1.727, is this really a useful measure? More to the point, what can I – as a business person – do with it?”

Well, look. The response (quoted) asks the right question – is this a really useful measure, and what can I, as a business person, do with it?  In other words, are you wasting our time trying to figure this out in the first place?

But here’s the rub.  A good Six Sigma practitioner would not need to post to linkedIn (hardly the font of six sigma knowledge in the first place) to ask how to plot a bell curve to show USL and LSL.  So the poster hardly represents the “failure of Six Sigma in the real world”.  And a good six sigma practitioner could tell the respondent quite nicely:

If we can plot the response times of your call center, we can understand whether the process is “in control” or not – by which we mean, is it predictable and does it vary in a “normal” way from the median behavior.  If it *is* in control, then we can endeavor to improve the process by decreasing overall response time if too great a percentage of responses are exceeding your 60s window.  However, if your process is *not* under control, then this means that there are one or more special cause conditions causing the process to be more volatile. Therefore your first effort has to be on stabilization before you effectively focus on ratcheting down the long-term variation (i.e. drop the average of the process down as a whole).

Not that Six Sigma is the only tool available.  Lean has several tools that are well suited for call-center style efficiencies, and so does 5s (the Japanese concepts of organizing the workplace to keep things consistent and orderly in order to keep the process consistent as well) and keep in mind just like BPM, Six Sigma is continuously evolving with new tools and techniques and while the statistics is certainly an important part it’s not the alpha-omega that many who haven’t learned Six Sigma believe it to be; certainly not the Six Sigma of the 1980′s.

My problem with the post:  using one example of someone struggling with the concept of Six Sigma, to challenge the whole notion of using Six Sigma – a bit like challenging the concept of a 100-meter dash after watching me run it, instead of Carl Lewis – at least look at how experts apply the techniques!  Six Sigma is not a religion (or at least it doesn’t have to be!)- it is simply a set of tools that can be used to pragmatically improve your process by focusing on unemotional data rather than exposition based on anecdotes.  Not all the tools are even statistical, which was a surprise to me when I first studied material at the green belt level -but even those tools are very practical process improvement tools.  The biggest problem with Six Sigma in the past has been the C in the DMAIC moniker (Define, Measure, Analyze, Improve, Control).  BPM really helps address C by putting the controls in software (call center software can help with this as well), and it helps with the M by helping measure the process even when no Six Sigma blackbelts are paying attention.  This makes it a lot easier for them to drop in, interpret the data, and devise new improvements based on the data, rather than spending so much time collecting hand measurements.

Here’s a great post by Jason Cohen (of Smart Bear software) that illustrates that humans are terrible at making gut decisions that can be disproved with statistics, and how to help yourself avoid sample size errors at least when dealing with A/B tests (as in, which is better, A or B?).  Better yet, it has a cute video of Hammy the Hamster to assist.  It cuts to the point about how much data you need to get a reasonable sample size to draw conclusions, and I think it makes clear why data sets of less than 10 are just generally problematic.  Um, also, there are formulas involved, so if you don’t put much faith in mathematics, Mr. Cohen’s article may not be much comfort to you, but I promise the math required to evaluate your sample size will be easy to do!

In my view, the real problem with applying Six Sigma is usually people.  Turns out it takes skill and  judgment to apply Six Sigma tools in a way that helps the business answer questions the business cares about.  This isn’t that much different than the kind of challenge one confronts getting a business to adopt BPM, or a software package.  Let’s not condemn a whole professional practice with proven successes just because we have one example of someone who doesn’t understand how to apply it (or even 10 examples of such people).