Despite similarities to network design and project management models born of the 1950s as well as those from decades earlier (think Toyota Production System (TPS) here), Six Sigma is actually a methodology all its own, what, with its conception more closely associated with the 1980s and the advent of mobile phone technology. The following article will take a far less historic approach to describing Six σ and, instead, focus on why this oft controversial management methodology is here to stay and what you (starting today) can do about it!
Introduction
Less than two centuries ago, or 141 years to be exact (you’ll get that pun soon enough, trust us), mankind was still performing work either with the help of the sun or when candles and lanterns were prolific enough to make them economical for use in factories, warehouses, and the means of transportation at the time (here, read: horse, buggy, and boat).
That all changed, of course, with the invention and adoption of the light bulb, which was largely credited to Thomas Edison and, more to the point, his willingness to experiment with exacting precision.
But what does any of that have to do with present day manufacturing, warehousing, and distribution?
Two words: Six Sigma.
Now, before you roll your eyes and mumble, not this statistical stuff again, hear us out since there are very good reasons, which will be discussed post-haste, that Six Sigma has had such staying power in industry and spurned off attempts at making it redundant or replaceable with the hybrid Lean Six Sigma.
But quickly, and back to the light bulb, it is critical to note that Edison did not invent the first electric means of indoor or outdoor illumination so much as fanatically attempt to improve on what had already started to transform how mankind lived and worked. He and his team were then able to systematically create a more reliable, duplicable, and timely product that, in a twist of historic irony, would become commercially viable under General Electric and the second ‘founding father’ of Six Sigma: Jack Welch.
So, how is it that today Six Sigma is so misunderstood and, not unsurprisingly, loathed by GMs and ops managers the world over? And is it really here to stay, especially in the world of logistics and supply chain management?
In short? Yes, but here’s what you need to know about the past, present, and future of Six Sigma and why you will want to start implementing the methodologies tonight!
What is Six Sigma?
Now, and before you start nodding off at the mere thought of ‘Stats 101’ or ‘Statistical Analysis and Probability 410’, Six Sigma is more than just sample sizes and bell curves, it is an entire methodology.
This is critical to note since its counterpart, and oft confused cousin, Lean, is a philosophy. In other words, the latter is the warm, fuzzy, and difficult to measure focus on waste reduction and employee empowerment. Not that Six Sigma is not those things so much as it is the science-based data-driven approach toward eliminating defects…
for good.
Six Sigma carries with it a poor reputation mostly for this ‘hard’ approach when root causing an issue, which requires practitioners to conduct still more statistical ‘experiments’ in order to measure what is broken and how to fix it at the lowest cost and in the least amount of time.
Oh, right, and ninjas.
But more on those later; here’s what you need to know:
- Six Sigma gets its name from the belief that a customer should get a reliable product that works as advertised every time
- It is believed that in order to deliver just such a product, the manufacturing, warehousing, and logistics value stream must produce no more than 3.4 defects per million opportunities
- NOTE: this is where the statistical bell curve comes in the further a process performs away from the mean, or the thickest portion of the curve, the more likely it is to produce the right product, in the right quantity, and at the right time
- AS AN ASIDE: and in other words, one sigma from the mean, on either side, indicates an extremely poor-performing process with 691,462 mistakes for every one million opportunities
- BOTTOM-LINE: would you trust a warehouse with a 30% pass rate to keep track of your products and see to it that they got to the right customer on time? Doubtful.
- Ideally no manufacturer or shipper wants to produce even one defect, but processes can become unstable over time or, worse, overengineered
- Six Sigma then is the ‘toolkit’ that all managers, regardless of level, can use in order to ferret out defects and which range from the highly technical (e.g., ANOVA Gauge R&R, analysis of variance, regression, chi-squared, et al.) to the more visual in nature (e.g., fishbone, value stream mapping, SIPOC, et al.)
Why should I care?
Though many may think that Six Sigma is as dated as the first multinational corporation to bring it to the forefront of manufacturing, warehousing, and distribution (here, read: Motorola), few can argue with its results.
Mathematically speaking, of course.
Even if this ‘hard’ approach to defect reduction is anathema to your logistics or supply chain vision, the principles behind the methodology are powerful in that they provide a solid foundation for any warehouse, ‘soft’ or otherwise, to build and maintain reliable, timely, and accurate processes. In short:
- Customer-centric: no matter the location of a firm within a supply chain or value stream, the end user is still chief among why a business exists in the first place, which is to say that warehouses, DCs, and 3PLs all exist so as to provide the customer with the right item in the right quantity at a time and place of their (the recipient’s!) choosing
- Value-chaining: there are few ‘true’ monopolies that still exist in the world today and, so, warehouses and transport companies act as the conduits within extremely complex networks of manufacturers and customers; being able to visualize what the entire chain, or stream, looks like empowers a business to better position itself within that vast array of processes and to reduce, based on data, the probability of passing defects down the line
- KISS: being able to ‘see’ into a process with the help of statistics allows warehouse general managers and 3PL owners and operators to elimination not only variation in how the same products or services are rendered (remember, variation is bad while standardization is good!), but also keep their processes simple and reliable
- Momentum: once practitioners start to see hard results, then the softer side of Six Sigma takes over in that employees see their jobs become less frustrating and with bottom line profits on the rise, they are far more likely to see their paychecks or end-of-year bonuses benefit as well
- Firm, but flexible: in creating just such a virtuous cycle, firms can more easily guide their employees to not only adopt new smarter, better, and faster processes, but also contribute their own ideas toward continuous process improvement
literally.
The reason? Variance is what the customer feels. Recall the earlier example of only ever getting what you want 30% of the time. What’s more, however, is that customers do not judge a company or distributor based on an average so much as that one, single transaction that was less than satisfactory.
As a final, and friendly reminder, variation, in a warehouse or distribution center process is to be avoided at all cost…
So, and before you shelve Six Sigma as a methodology for good, think about the true cost of losing a long-term contract or value-stream partner based on sloppy processes that result in quality escapes that, in hindsight, could have been standardized and easily duplicable day in, day out.
Where and when to stop?
Now, if you have been following along, then you might now be wondering, well, if the point of Six Sigma is defect reduction and the achievement of 100% process reliability, won’t there come a time when either the process is perfect or so close to being so that you reach a point of diminishing returns?
And you would be absolutely correct! So, where and when do you deploy a Six Sigma methodology or create an entire project, when should you stop that initiative, and what are some of tools, tips, techniques, and procedures to accomplish your goals?
Glad you asked, here are but a few top-line considerations:
- Getting started: it is critical to note which process (NOTE: not person or department) your firm believes is breaking down and resulting in substandard customer service; from there, practitioners need to define the problem, measure the outputs of that process, analyze the data and make sense of the variations, improve the system by controlling the variables, one at a time, until, finally, they achieve a standardization rate close to 99.99966% accuracy in which they control for the long-term
- Timing: Six Sigma, like its Lean cousin [hyperlink to internal piece here], are resource intensive and can reduce warehouse operations and throughput if not carefully monitored. What’s more, and this is why clearly defining a goal is critical, they can run on to infinity since perfection is at the very end of a long, long tail.
- Tools: as previously mentioned, Six Sigma is the ‘hard’ statistical methodology to Lean’s more philosophical approach to process improve. That said, it should come as no surprise that the tools, techniques, and tactics are number ‘heavy’ and designed to produce a great deal of data. Just a few include the 5 Whys, analysis of variance, linear modeling, regression analyses, scatter diagramming, axiomatic designing, mapping, run charting, value stream mapping, SIPOC modeling, root cause analyses, quality function deployments and houses, histograms, and more!
As an aside or side-bar discussion: while each of these tools requires an article in and of itself, there are still more tools that you can use within your warehouse or supply chain that are automated, which is to say:
HAVE NO FEAR, MINITAB IS HERE!
Like most software and hardware ‘solutions’, however, Minitab is but another tool at the hands of a practitioner, consultant, warehouse GM, or operations manager out on the floor. It does not do the ‘hard’ work of identifying a potentially off-kilter process so much as help to collect, analyze, and suggest improvements based on inputs. That said, and like all computer-based solutions, what you put into the machine is a huge factor of what you get out.
Bottom line? Consider Minitab, but only after you understand the methodology and principles (see above) of Six Sigma writ large!
So, what can I do starting right now?
Right. Now you’re probably wondering what you can do starting right now since you are not in the business of making or shipping lightbulbs and are pretty certain that your processes are ‘in check’.
Great. Why not, then, start by asking some of those five whys out on the shop floor and solving issues together with your ops lead and employees. Next, reflect on the progress of any minor adjustments you may or may not have made to an input variable and what the subsequent output was within the system. Measure this and continue to do so by taking daily ‘gemba’ walks, which is a Japanese term that will see you out on the floor asking, and seeing, where a problem is occurring—real time!
As a friendly reminder, always, always, always look for the root cause in the process and not the person and try to get everyone on the team involved in finding a suitable, cost-effective solution.
If you’re already doing this, even better as you can start a full-on Six Sigma program complete with those ninjas from earlier!
All kidding aside, and in creating that virtuous cycle of continuous process improvement vis-à-vis employee engagement, Six Sigma comes with a tiered system that allows participants to become practitioners by starting as white belts (those with a basic understanding of the history of the methodology) and climbing the ladder so as to become black belts or master black belts (transforming entire businesses and value streams).
Lastly, and getting back to the foundation of Six Sigma, any process or value stream can benefit from its own standardization in the form of DMAIC, or: defining, measuring, analyzing, improving, and controlling.
This step-by-step construct can also be reengineered to fit with warehousing, distribution, or transportation, though, many of the concepts are the same. Consider, then, the following:
- Design for Six Sigma (DFSS)
- Design for X (DFX)
- Define, measure, analyze, design, and validate (DMADV)
- Define, measure, analyze, design, optimize, and validate (DMADOV)
- Identify, define, develop/design, optimize, and verify/validate (IDDOV)
Those five, and in combination with DMAIC, account for your six methodologies along with a slew of other Six Sigma knowledge, but, and probably, a little outside of the six-minute mark…
but we’ll get right on controlling for that quality escape; you can trust us on that!