• Motion – physical layouts that are not optimized require significant movement of people in order to complete the process. Examples include movements in an assembly operation to obtain parts or tools; or movement required to transmit or receive orders, faxes, approvals etc.
• Waiting – in operations where work is done in batches, process participants along the chain will inevitably be waiting for while upstream work is completed. This creates uneven workflow and uneven workloads that result in bottlenecks. The typical solution here is to add resources to the bottleneck, rather than addressing the root cause.
• Overproduction – when work processes are not fully integrated, and are instead done in isolated silos, overproduction is typically the result. One department might be busy processing applications, without regard to a downstream department’s processing capacity. The result is a buildup in ‘inventory.’
• Overprocessing – this is another artifact of non-integrated processes done in silos.Examples are multiple reviews, unnecessarily complex work steps, redundancies(two different departments doing essentially the same work), logs and reports on the amount of work that has been done.
• Defects – any outcome that doesn’t meet the customer’s requirement is a defect and is therefore waste; i.e. time, effort, and resources were consumed but the outcome was not a saleable product or service.
• Inventory –In Lean thinking, work should be done in a continuous flow in response to customer pull. A demand pull system strives to minimize in-process and finished goods inventory, thereby reducing the waste associated with inventory storage, theft, and obsolescence.
• Transportation – when unfinished work has to be transported to different locations, there is opportunity for delay and error. On a shop floor, an inadequate layout might mean that unfinished products must be transported from stamping, to welding, to painting. Unfinished pieces accumulate at each station waiting for material handlers to move them to the next station.

Tools
The observed problem – errors, delays, bottlenecks, risk, high cost, low productivity – is really only a symptom of a deeper root cause. Addressing the symptom is ineffective (because the problem does not go away), and costly (because you’ll need to continually fix the problem). Six sigma provides a comprehensive set of tools and techniques for isolating root causes, including process mapping, cause & effect diagram, fish bone diagram, data sampling, regression analysis, hypothesis testing, and advanced statistical analysis. But the power of Six Sigma is the framework itself: Define the problem, gather and analyze data to link observed problem (symptom) to root causes, implement solutions that address root causes not symptoms, and manage root causes so the problem does not recur. 

Comprehensive
Six Sigma is different from TQM and BPR. While these two approaches have merit in certain situations, they fundamentally lack the rigorous data analysis which links cause to effect. Process re-engineering focuses on changing the process; i.e. how work is done. Six Sigma is far more comprehensive, combining process analysis with rigorous analysis of process and input data to permanently reduce variation in outputs.

The term sigma comes from the normal distribution (aka the Gauss curve or the bell curve). The normal distribution is used to describe many different types of numerical information. Using just two numbers (theaverage, which is the typical value or in statistical terms the most likely value to occur at random; and thestandard deviation aka Sigma, which quantifies the amount by which any data point could vary from the average) we can make statements about likely values (average) in a set of numbers and quantify how much the likely value could vary. For example, we can talk about the average (most likely) cost to process a transaction. Yet this cost will vary. The standard deviation tells us by how much it can vary. This gives us a range of possible values which can be helpful in decision-making.

With these two values (average and standard deviation), we can estimate where any data point is likely to fall. In the curve below, for example, we know that there is a 68.26% chance of a value falling between -1 and 1 standard deviation (sigma) from the average. Similarly, we know that there is a 95.44% chance of any data value falling between -2 and +2 sigmas from the average, a 99.7%chance of any data value falling between -3 and +3 sigmas and so on. Put another way, in any normally distributed set of numbers, 99.7% of the values will fall between -3 and +3 sigmas from the average. So if 6-month old babies in the U.S. weigh 13 lbs, on average, with a standard deviation of 1 lb, we can say that most 6-month old babies (i.e. 99.7%) will weigh between 10 and 16 lbs.

Management Philosophy
The lasting power of six sigma is the discipline and mindset it brings to execute flawlessly. As a management philosophy that continually strives for “zero defects”, six sigma engenders process discipline, employee engagement, metrics that foster excellence, and continuous innovation.

What are the measureable results you get from BPM?

• Better services delivered at lower costs
• More satisfied customers
• Engaged employees

In addition to these measureable benefits, organizations that embrace BPM as the "way they work" are naturally more agile and therefore better able to adapt to increasingly challenging internal and external forces.

How to establish BPM in your organization

1. Define Your Objectives - Many organizations confuse their employees with too many initiatives, programs, and objectives. The best approach is simplicity. Three to four major objectives are what most people can handle. It also makes it easier to communicate to employees.
2. Clarify Your Strategy - With only 3 or 4 major objectives, it's easier to focus and to develop workable strategies. Your strategy should be clearly defined, over communicated, and have measureable milestones. Without objective measures, it's hard to know whether you're really making progress. Progress toward achieving objectives also keeps employees energized.
3. Communicate - Many organizations rely on email to communicate. But this is perhaps the least effective medium because our inboxes are already overflowing. Use email sparingly and reinforce messages with formal and informal presentations, webinars, and even phone calls. Strategy should be clearly communicated to unleash the power of all employees pulling together to achieve objectives.
4. Map Value Chain - Identify the parts of your organization's value chain that enfeeble rather than enable your strategy.
5. Reinforce Weak Links - Carve out specific projects to reinforce the weakest links in your Value Chain. These projects can be small or large in scope. The important point is to ensure focused effort to address vulnerabilities in the Value Chain.
6. Lean, Six Sigma, and BPR - These techniques are proven and when used appropriately, will yield meaningful results. Each has its place. BPR can be very useful for rationalizing dysfunctional processes, but is less useful with more complex problems of variability and defects. When variability is the challenge, Six Sigma techniques, with their reliance on data and statistical rigor, are a great way to drive to root cause. And if long cycle times are choking your organization's capacity, Lean Value Stream Maps are very useful for identifying waste in the system.

Field of dreams. The prevailing culture at a mortgage bank is "if you bring 'em in we'll close 'em". Anecdotal evidence suggests that underwriters are spending a lot of time on the phone dealing with applicants so they're not closing loans fast enough. The manager creates and staffs a customer service department to deal with customer calls. Customer calls are now answered promptly and courteously by trained CSRs. The problem is that the CSRs have limited information about the callers' status and therefore have to revert to the underwriters and call applicants back. The unintended consequence is that underwriters are now constantly in communication with the CSRs either by email or phone to respond to their queries. These responses are then relayed to the customer. The underlying problem is salespeople who are bringing in unqualified borrowers (of which we now know all too well the consequences). Underwriters, under pressure to achieve high close rates, spend time on the phone with dicey borrowers. Rather than take the time to gather facts and address deficiencies in the sales process, the manager sprung into action and created a bigger problem. The action did reduce the calls being handled by underwriters, but did not improve the effectiveness or speed of underwriting.

Let's go paperless! An organization that relies on paper originals to process applicant files decides that it's time to streamline and reduce paper. The manager decides to put the initial application form online. Now, rather than requesting a form online, waiting to receive it, filling it out and mailing it back, the entire process is completed by the applicant online. The applicant's initial perception of increased efficiency, however, is quickly shattered by the lengthy delays in the back-end processing of the applications. The unanticipated flood of applications creates a huge (and equally unanticipated) backlog which takes months to work down. Customer fury builds as the expectation of a streamlined process goes unmet and the "improved" process proves to be worse than the old paper-based process.

What these cases demonstrate is that a manager's bias for action can often have unintended consequences. Rather than resolving a problem, the action creates new problems. The pressure - real or perceived - to "do something" obscures the benefits of action based on well-reasoned analysis. In both cases, some fairly quick gathering of the facts would have led to better decision-making. A quick analysis of the types of calls being handled by the underwriters would have revealed that many calls were from applicants with spotty credit histories and low FICO scores. A more thorough qualification of applicants upfront would have weeded out unqualified borrowers that were consuming underwriters' time. A simple checklist and stricter guidelines for salespeople would have improved underwriter productivity. Instead, the action taken - creation of a customer service department - did not solve the problem, was costly to unravel, and created dissatisfied customers.

In the second case, doing nothing would have been preferable to the action taken. In the rush to automate one piece of a bigger process that remained dysfunctional, manual and paper-intensive, the company created an expectation that it could not fulfill. An analysis of historic application volumes, processing capacity, and peak volume processing times would have raised red flags. The manager could have then taken steps to free up processing capacity before initiating the change.

When operating managers identify problems, the urge to react can be strong. As these cases show, the managers would be well advised to stop, gather facts, and act based on a reasoned analysis of the facts. This delays action by a few weeks but will mitigate downstream pain.