Lean Six Sigma basics

Peter Strempel

The principles of Lean Six Sigma were initially developed to improve manufacturing processes, but they can be effectively applied to any kind of business process to streamline and trim waste.  This is why it’s commonly combined with business process analysis.

I combine these principles with business process management, especially processes mapped out in BPMN diagram, to gain help maximise efficiency and value in the processes I am tasked to analyse and improve.

How that works is explained here first by looking at the terminology and guiding frameworks, and then by how these might be applied in practice.

The terminology

Lean, as in lean manufacturing or enterprise, refers to the waste-reduction efforts pioneered most successfully in the Toyota Production System (TPS).  Six Sigma, or 6σ, refers to a target of producing 99.99966% defect free products where six refers to decimal places and sigma is the symbol for standard deviations from the norm.  The target need not be reached in practice, but every step towards it substantially reduces defects.  See Figure 1 and Table 1 below for a visualisation.

Deviations
FIGURE 1: the distribution of occurrences of what is being measured over standard deviations in a normal distribution curve.

 

TABLE 1: occurrences of whatever is measured drop of sharply with increasing standard deviations.
σ level Defects per million Defect free
1 690,000 30.85%
2 308,000 69.15%
3 66,800 93.32%
4 6,210 99.38%
5 230 99.977%
6 3.4 99.99966%

What this tells us is that Six Sigma was intended as a scientifically measurable improvement target.

DMAIC and DMADV

Lean Six Sigma works within two frameworks, derived from the Deming continuous improvement cycle–DMAIC and DMADV (see Figure 2 below).  The acronyms stand for Define-Measure-Analyse-Improve-Control, and Define-Measure-Analyse-Design-Verify.

The first is best for improving existing processes, the second for planning entirely new processes.  Both centre on the concept of critical-to-quality customer requirements (CTQ).

Two frameworks
FIGURE 2: the two Lean Six Sigma frameworks as continuous improvement cycles.

CTQ in this context really means understanding whether the client or customer would regard any step in any process as adding value.  If not, that step should be changed or removed, except: if it is an ethical or regulatory requirement, like workplace health and safety rules, fiduciary duties, or consumer protection legislation requirements.

Targets for efficiency

Lean Six Sigma is based on some fundamental principles that may be summarised as follows–

  1. Never lose focus on the client or customer. This can be easy to do when getting too distracted by the process itself.
  2. Identify and understand how value is created at each step in the process. That is, make the process a value stream, and remove any step that does not add value or meet a governance requirement.
  3. Continuously manage the process flow to ensure no waste or inefficiency creeps in.
  4. Manage by measurable fact and reduce variation as a source of defects and inefficiency.
  5. Harness and empower people involved in the process to improve it.
  6. Pursue improvements in systematic, documented, measurable ways.

Keeping these in mind, I can target the principal sources of inefficiency and waste in any process using a variety of methods and targets.  I generally keep in mind the factors referenced in the acronym DOWNTIME:

  • Defects
  • Overproduction
  • Waiting
  • Not using skills or talent
  • Transportation
  • Inventory surplus to demand
  • Motion waste
  • Excess processing

Each of these factors can introduce waste and inefficiency.  And each factor has a wider than literal scope.

  1. Defects can apply to service process failures as much as product flaws
  2. Overproduction might apply as much to making too many widgets as employing too many people or using too many resources.
  3. Waiting means the interval between one part of the manufacturing or supply chain process and the next, but can also mean the interval between a service request and fulfilment.
  4. Not using skills or talent in manufacturing is much the same as in services: know your people and take best advantage of their skills and experience. This can also mean train them to upskill or cross-skill.
  5. Transportation of goods costs money and adds expense in manufacturing. The same is true for any travel a customer has to undertake to access a product or service; ordering from the internet involves zero travel, and only the cost of the internet connection.
  6. Inventory excess is a companion to overproduction. It means the organisation is paying to store goods it cannot sell, or a retail outlet devotes too much shelf space to items that are not selling at the expense of items that do sell well.  In services it could also again indicate too many people doing too little to add value.
  7. Motion waste is similar to transportation but more localised, meaning time and effort it takes to move resources between manufacturing processes, or the number of steps in a service fulfilment process.
  8. Excess processing is like motion waste but focused more on double-handling—two or more people involved in the same process step unnecessarily, or a process loop of unnecessarily repeated steps.
CTQ diagram
FIGURE 3: CTQ diagrams can suggest problem areas that deserve attention.

There’s also a whole range of other analytical methods, including:

  • Value stream mapping (see my page on enterprise architecture)
  • Five whys analysis. Asking stakeholders five questions about why a problem occurred to drill down into a root cause.
  • CTQ tree diagramming. Showing branches from customer demand to the requirements necessary to fulfil that demand, from requirements to its measurable components.
  • Cause and effect (fishbone) diagramming to track potential causes to problem effects.
  • Pareto charting of problems by frequency of potential causes.

Precisely what combination of tools and methods I would apply to any particular assignment depends entirely on specific circumstances.

Lean Six Sigma as strategy

In some industrial organisations, Lean Six Sigma has approached quasi-religious status, being pursued with fanatical zeal to purse the full benefits of its methods and tools.

And there have been spectacular results, particularly in Japan.

I mention this because the application of Lean Six Sigma in problem situations is unlikely to work if organisational culture doesn’t embrace its application and pursuit whole-heartedly, or if management commitment is lukewarm.

I many cases adopting the Lean Six Sigma perspective is a radical shift in thinking, and involves a major, transformational change effort to re-frame or re-orient many strategic and operational objectives, goals, and targets in terms of Lean Six Sigma contexts.  Such an effort is the domain of strategic planning and change management rather than Lean Six Sigma itself.

Traps for players

Every significant perspective or skillset has its flaws and critics.

Lean Six Sigma is no exception, so I will outline some of the downsides I have seen personally.

Sometimes people who have invested themselves personally and financially in gaining Lean Six Sigma certifications can adopt a quasi-religious or ideological fanaticism about the overriding importance of only their particular skill-sets and perspectives.  This is not unusual.  I have seen the same apply to people promoting their ITIL and PRINCE2 certifications.

Such zeal may signal commendable passion about, and commitment to their specialty, but also comes with the risk that Lean Six Sigma ‘acolytes’ will overlook all other issues, skills, tools, and perspectives that might be relevant or useful in any particular organisational context.

Even when excessive zeal is not the issue, the Lean Six Sigma practice comes with some internal risks.  The most common one being forgetfulness that it is a scientific method originally aligned to manufacturing processes.  In other words, it is based on statistically sound measurement of results.  Not understanding the underlying mathematics and misapplying the metrics will deliver misleading results and questionable claims.

One of the biggest mistakes made by business analysts using Lean Six Sigma, it is about meaningful statistical measures for service processes.  For example, can you streamline a helpdesk process with lean six sigma methods and measure success by customer satisfaction?  The short answer is: with great difficulty.

Cochran's formula
FIGURE 4: Cochran’s formulae for statistically significant sample sizes.

You cannot take the number of ‘resolved’ calls as indications of customer satisfaction, as is often claimed by service desk managers trying to game unrealistic KPIs.  You would need to survey the customers directly to get close to any satisfaction rating.  And you cannot use a statistically insignificant sample and simply apply it to a total number of calls of disproportionate size.

So, for example, if you had a total of 1000 service calls in a given period, and conducted 150 surveys, of which 120 indicated they were not dissatisfied, you cannot confidently assert that this 80 per cent rate applies to your sample population of 1000 calls.  A version of Cochran’s formula adjusted for small samples (say under 10,000) tells us that a statistically significant sample rate for a total sample of 1000 is 278—almost twice the 150 actually sampled in the example above.

But even if you had sampled 280 customers, not being dissatisfied is not the same thing as being satisfied, and still does not justify a finding of 80 per cent satisfaction rate over the total call number of 1000.

So, yes, you can attempt to measure qualitative outcomes with statistical methods, but the complexity will be about getting an adequate sample size, and then also about survey questions and responses that actually mean something about customer satisfaction.  There is a whole statistical discipline built around framing questions for qualitative outcomes.

To misrepresent statistics may be common practice in politics, economics, business, and anyone else seeking to dishonestly justify a particular perspective, but in business process analysis it is evidence of incompetence or wilful deceit, either of which brings the entire discipline into disrepute.  To fall into bad practices like misrepresenting metrics is easier if Lean Six Sigma becomes a monomania to the exclusion of all other perspectives.

I understand these pitfalls and will not disappoint you by pretending I can achieve results I cannot, just by playing fast and loose with numbers.  My analytical perspective is always informed by a sufficient range of complementary but distinct professional practices not to let me fall into the trap of becoming too committed to any one way of doing things at the expense of doing it right.

Hopefully this brief discussion of what is a huge area of professional practice has shown you how you might benefit from examining your processes using Lean Six Sigma methods.

Contact me today to discuss your business process improvement needs.