Guest Post: Six Sigma - A Splendid Waste of Time

Kanishk's Note: One of the foundation of any continuous improvement process is: Feedback. 
So, here is a very honest and direct feedback on Six Sigma from our guest author, James Lawther. 
I will address his points in a separate post.

 

I work in the service industry.  For my sins I am responsible for process improvement.

Six Sigma is widely regarded as the process improvement methodology of choice.  The logic is that as an industry we are data rich, so a process improvement methodology that is data led has to be a good thing.  Consequently there has been a huge investment in Six Sigma training over the past few years.  I have master black belts and black belts and green belts and yellow belts coming out of my ears.  Thousands, if not millions of pounds have been spent on Minitab licences, training manuals, and consultants.

And I guess that 99% of it has been a splendid waste of time, let me be stronger, Six Sigma has precisely no practical application in my industry at all (might as well be hung for a sheep as a lamb).  If that sounds a little strong let me explain why.

Six Sigma is a great tool for process improvement.  If you have a multimillion pound production line that makes light bulbs at 1,000 a minute and 1 of them fuses the instant it is plugged into the power there is really only one way to diagnose the problem.  Like it or not, it is going to involve a fishbone diagram and a bit of regression analysis.  When you have a problem like that you need all the surgical precision you can get to find the root cause and fix it.  You need a statistical scalpel.

The service industry doesn't work that way though.  We don't invest millions in dedicated production lines and supply chains.  We invest millions in databases and people.

Now here is the thing: databases and people are flexible, you can add bits, change bits, do extra stuff, provide bespoke outcomes for bespoke customers.  And as a consequence we do.  It sounds great but we end up with the curse of proliferation.

We end up with a production line that produces 1,000 shapes of light bulb in a thousand different colors at one every 3 minutes.  We don’t care how many of them work; we are too busy looking for the one our customer wants.

We don’t need statistical scalpels; we need common sense and a mop to clean up the mess.

James Lawther gets upset by operations that don’t work and apoplectic about poor customer service.  Visit his web site “The Squawk Point” to find out more about service improvement.

About Squawk Point: The Squawk Point is about the way large organizations work. The way in which organizational design, business processes, operational delivery and staff ambition and motivation interact.  It is about the myriad of ways in which clever people make life difficult for themselves, their colleagues and their customers.

Identification via Isolation

Recently I had an interesting conversation with a software developer who was particularly frustrated with the people complaining about the end results of her software program.  At a high level, this software process looked something like this:

These complaints were not her big problem. Taking every feedback seriously, she would delve into her code and later identify that the problems were not due to programming errors or “bugs”. Rather, these problems were originating further upstream from the inaccurate data records which were used as an input to her program. So, her main frustrations were:

1. Why do the database people keep providing incorrect data?
2. Why is programming first to be blamed at?

Issue #1 is a classic process issue known as “Garbage In, Garbage Out”.  And #2 is due to general human tendency. Whenever we see an erroneous result, we tend to dig (or even blame) the step which immediately precedes the final result. 

An ideal and easy way to resolve #1 is to establish the service level agreements (SLAs) among the internal supplier & customer. In this case, the programmer is the internal customer of the database analysts (DBA). So, she defined a clear set of requirements/expectations from the data streams which are the inputs to her programming process. And the DBAs were instructed to achieve those expectations before providing their outputs. The DBAs can develop their own internal quality checks to validate the data and provide those results along with the data-stream to the programmer. In manufacturing world, this is similar to suppliers providing completed inspection checklists and test results with their parts shipments to the next customer.

Issue #2 is a bit complex one to deal with. Here, programmer is up against the general human tendency rather than any logical argument. After some thought, she came up with her own solution. She created a controlled sample of the data-sets by validating them herself first. Then, every modified version of her program was first tested by using that “controlled sample” and the results were analyzed. Now if the new, current data-sets (which were also being modified in parallel) do not produce the same results as being produced by the controlled sample, it is easy to conclude that problem lies in the data integration and not system-level programming. This is what I call, “identification by isolation”.

Situations like these keep reminding me of the importance of root-cause analysis in our daily lives. We don’t need a fancy formal training or certificate in order to become an effective problem-solver. In fact, being humans, this skill is hard-wired in our brain. We need to recognize and sharpen it by using common sense and a focus on resolving the issue, and not just whining about it.

How to Measure Anything

About an year and a half ago, I was struggling with a measurement problem. Being a Six Sigma Black Belt it was clear that in order to make sustainable process improvements, I need to quantify process performance and establish a sound measurement system around it. In a continuous physical process, where you are making a product or part, it can be done relatively easily. But in a transactional environment it is not easy to normalize a measurement and establish a simple, yet sound metric.

Then, I came across this great book, "How to Measure Anything: Finding the Value of Intangibles in Business". And no wonder this became one of my favorite books. A few important things which I learned about measurement are:

Concept of Measurement:
Measurement is a set of observations that reduce uncertainty where the result is expressed as quantity. Note that the uncertainty has to be quantified, but the subject of observation might not be a quantity itself.

Object of Measurement:
Using a short series of connections, called Clarification Chain, we can see intangibles becoming tangibles:
1. If it matters at all, it is detectable/observable.
2. If it is detectable, it can be detected as an amount (or range of possible amounts)
3. It it can be detected as a range of possible amounts, it can be measured.

Four Useful Assumptions:
1. Your problem is not as unique as you think.
2. You have more data than you think.
3. You need less data than you think.
4. There is a useful measurement that is much simpler than you think.

These concepts sound very theoretical, but will become more clear in the context, once you read the book and the accompanied text. Whenever, I get into the measurement quandary I think of these things and it helps me to look at my problem in an entirely new light. In my experience, most important of these are the four useful assumptions. In a normal day-to-day business operation, I come across so many situations, where "we have no data" is the "root cause" of the "problem" we are seeing. Come on, that can't be possible. Look at all the data/IT systems we have built around us in last 10 years. I force my thinking as "we gotta have this data somewhere"!

And this is how I now look at my measurement related problems.

Customer Service: 2009 Hall of Shame

Earlier, I have posted about Customer Service Hall of Shame survey in 2008. Recently, I found that 2009 survey results were released in June. Somehow, I missed the article that time, but nonetheless found it very interesting when I read it eventually. Providing an efficient and reliable Customer Service is of utmost importance to run a successful business. And surprisingly, so many companies fail to do so, again & again & again.

"How a company handles adversity can tell you a lot about its character. Does it stick to its guns, keeping the customer first? Or does it stick it to customers, raising prices and cutting service?

The recent economic turmoil has given companies a chance to prove their mettle. But many, particularly in the hard-hit financial-services industry, have failed to do so."

9 of these companies have featured in the top 10 listing of this survey in 2008. And despite their efforts to improve their customer service in reaction to such surveys, they still make it there. Now what is so challenging about improving customer service.

In my opinion, customer service is actually a very complex process to improve. Inherently, it is intangible and difficult to quantify issue. One can certainly weave a problem statement around "issue resolution time", "time of hold", "number of calls", "number of issues resolved in a certain amount of time", or what not. But the problem is that none of these measurements directly correlate to "customer satisfaction".

An efficient and great customer service is not just limited to "politely talking", "logging the issue", or "directing the call to a department". It is in fact, a function of a set of good communication skills, technical knowledge of product/service, an understanding of people's feelings, & the dynamics which come into play when an irate customer calls the customer service.

Cash for Clunkers

The recent "Cash for Clunkers" program from US government to augment the car sales was a great success, at least, for the auto companies which were craving for sales. Per the official website, www.cars.gov:

"The CARS program ended sales on the Monday night with nearly 700,000 clunkers taken off the roads, replaced by far more fuel efficient vehicles. Rebate applications worth $2.877 billion were submitted by the 8 p.m. deadline, under the $3 billion provided by Congress to run the program."

During this time, the auto dealers came up with some creative marketing strategies to allure the customers to buy automobiles from their piled up inventories and full lots. The Fuccillo Automotive Group in New York state is known for it's aggressive marketing and "It's Huge" campaign. One day got a mailer in my mailbox with a car key, followed by an invitation and offer number next day. It was pretty enticing offer, except for the fact that I was not looking to replace my 2007 Scion TC. But if I'd be driving a clunker, and spending an awful amount of money on gas, Fuccillo's marketing strategy would have certainly worked on me.

Risk Analysis in Process Design

Any good process improvement project, will have a slide with the before & after process map. The "before" process map depicts the process as-is, ideally at the project/initiative kick-off. The "after" process map shows the future state of the new, improved process. The hypothesis here is that the new, improved process, if implemented, will result in waste-elimination, reduced cycle-time, higher efficiency, increased output etc. depending on the scope of project.

Now, when the project leader, who is usually the Black Belt or Master Black Belt, presents this proposed process to either the leadership team, champion, or key stakeholders to get their buy-in, one question is usually asked.

"What are the risks involved with this new process? What can we potentially miss if we implement this process? What will fall apart if we stop following the current process?"

In my opinion, a very simple tool can be used to address these valid concerns. I call it Risk-Opportunity chart. I am not sure if it is a part of the standard Lean/Six-Sigma tool-set, but found it to be very useful. In the form of a classic four-blocker, this tool provides an excellent visual of not only the risks involved, but the opportunities associated along with. Remember that with every risk, comes an opportunity.

The Risk-Opportunity matrix will look like this. This is definitely a team-based tool. The Black Belt or project leader will facilitate this tool with the project team members, consisting of the process-owner and key experts of current process.

Steps:

1. Assemble the team in a room. Post the "before" and "after" process maps posted on a side-wall (on flip charts). Draw the four-blocker on a flip-chart.

2. Start going over the "after" process map step by step while asking the question: what are the potential risks involved here? You may refer to the "before" process-map whenever needed. (Having a high-level SIPOC of current process will immensely help)

3. Quantify every risk as Low or High per team consensus. For every risk, ask what is the associated opportunity. Quantify the opportunity as Low or High per team consensus.

4. Write the risk/opportunity pair in appropriate block of the four-blocker.

After finishing the data-collection, chart a strategy to address these risks involved in the priority shown as 1-2-3-4 . This tool will greatly enhance your understanding of the new process and its potential impact on other processes as well. Also, the visual created will come as a handy tool to communicate the analysis to others.

Let me know if you have questions or feedback regarding this.

Process-Mapping on YouTube

Sometimes, the wealth of real knowledge freely available on WWW just amazes me. It just depends on us, how we choose to spend our time and utilize the power of Web 2.0 in enhancing our knowledge base and honing our skill-set. For instance check this video on "Process-Mapping in Lean Six Sigma". Gone are those days, when companies had to higher highly paid consultants to train their work-force in process improvement tools, when the good quality stuff is available online...free. However, it does a lot of motivation and focus to do such things online. Maybe that's why the classroom training still exists. Anyway, enjoy the video:

Think Process!!! ....But how?

In those rare cases, where an explanation of Process & Process Management (per my previous post) is able to generate the other person's interest, the conversation usually goes this way:

Him: "Interesting! So, you are a process improvement professional."
Me" "Yeah! sounds like fun ..isn't it?"
Him: "Maybe for yourself..... So, tell me one thing.."
Me: "Sure"
Him: "What is your general approach when you are doing problem-solving and/or process-improvement?"
Me: " Well...The mantra of success is always: Think Process!. One has to develop his process-based thinking and the ability to visualize a process, no matter how complicated the problem is."
Him:"Hmmm.....but how do you do that?"
Me: "Well, maybe it just comes naturally...or ...aaaannn...I don't know. Seriously!"

This conversation sent me through the thinking path: How do you develop the process based thinking? And the answer came in the form of a SIPOC, an acronym for Supplier, Inputs, Process, Outputs, and Customers. In Six-Sigma DMAIC roadmap, SIPOC analysis is used the Define phase to map the high-level process and the relationships among suppliers, process, & customer via respective inputs & outputs. A quick search over Google brought this excellent link on SIPOC Analysis and the steps needed to perform one. A typical SIPOC diagram for a project looks like this:

Now coming back to the point, how does SIPOC help to generate process based thinking? Whenever you are trying to understand a problem symptoms, try to identify what is the main process involved here and what are it's inputs and outputs. Next, think about who is supplying the inputs and how can they impact the quality (in either positive or negative way) of the process and it's outputs. Next, identify the outputs and whom and what they impact, i.e. the customers or other processes. Let me give a simple example:

Say, one fine morning, your coffee doesn't taste good, or rather let's say it tastes real bad. Now the Process here is coffee-making. The equipment used is the coffee-maker and the process parameters are temperature, length of time for brewing, etc. The Inputs of the process are coffee beans, and water (and sugar, creamer, etc.). Suppliers are coffee-bean company, & water supply (or bottled water company). Output is off-course the coffee (which is of bad quality) and the Customer is the coffee-drinker (in this case, is yourself).

I agree that this is a very simple example compared to the processes we deal with in a business or organization, but the idea is that one's thought process has to be aligned in a SIPOC way. This will help you a lot in ....guess what...."thinking process".

Data.gov

Recently, I found this cool website, which is essentially a huge data-dump. It has all kinds of data-sets to play around and hone your statistical tool skills. From my six-Sigma training and the subsequent trainings I have given to Green-Belts, I found that the data-sets used in the examples, and practice sessions are very boring and manufacturing oriented. This website, www.data.gov, has some really cool data which can be more meaningful in teaching the analytical & statistical tools to the Green/Black Belts. The website introduction is:

"The purpose of Data.gov is to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government. Although the initial launch of Data.gov provides a limited portion of the rich variety of Federal datasets presently available, we invite you to actively participate in shaping the future of Data.gov by suggesting additional datasets and site enhancements to provide seamless access and use of your Federal data."

"Data.gov includes searchable data catalogs providing access to data in three ways: through the "raw" data catalog, the tool catalog and the geodata catalog. "

I downloaded the "Airline On-Time Performance and Causes of Flight Delays" data-set and started playing around with it. It has all kinds of data, which can be used to make interesting and more engaging case-studies, than the standard age-old examples from manufacturing, cycle-time, etc. still being used in the trainings, where a good majority of people are from transactional backgrounds. Well, I'm working on making something from these enormous data-sets and will put them here soon.

Enjoy playing with the data!!!

Process Management

For last few days, I have been thinking that what should be the first post on this redesigned blog. And after some thought, I decided to post on the concept of "Process Management". Time and again, people ask me what do I do? Merely saying that I am a "Six Sigma Black Belt" actually doesn't help much. It is usually followed by a "What do you actually do?" look. Then I try to explain my job further by talking about quality, continuous improvement, and process management. So, what exactly is process management? What is a process? What is process improvement?

Based on my experiential learning, I have made a visual to explain these terms and their inter-relationships. And now I will try to explain them.

Process: A series of steps, or tasks which add value to their inputs and result in an output. An input can be in the form of information or a physical material. Similarly, the output of a process can be in the form of a material, product, or information.

Process Improvement: It includes a series of tasks with the sole objective of improving the process. The improvement can be in terms of improving the quality of the output, increasing the efficiency of the process, or reducing the operating cost of the process itself. The data generated from process-monitoring and the feedback on the output need to be analyzed properly to identify the improvements needed in the process, or in the process-monitoring to get a better picture of the process. The last but not the least is the execution of those improvements leading to process management.

Process Management: Process Management means the ability to manage processes efficiently and improving them continuously. It encompasses an expertise in utilizing the tools-set of Six-Sigma, Lean, Project Management, Systems Thinking etc., the art of devising right strategy, and the ability to drive change in the system & among the people. It is the efficient process management which results in a sustainable change/improvement in the process.

Now, processes exists at each and every layer in the hierarchy of an organization. Those at the high level are termed as business processed, while the ones in the subsequent layers are called functional processes. And never forget that no matter what your process is, it needs to be improved!