Six Sigma is a universally applicable approach for solving operational problems in any organization. In most organizations, problems arise and solutions are quickly implemented. For example, if processors make errors, a common solution is to implement an error checking step. But what happens when the error checkers make errors? Or what happens when work volumes increase? The obvious solution is to increase staff. If this is not an option,then new procedures are implemented, existing staff will be expected to work harder, and performance, along with customer satisfaction, tend to decline.
The observed problem –errors – is really only a symptom of a deeper root cause. Addressing the symptom is ineffective (because the problem does not go away), and costly (becauseyou’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 matrix, 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.
Six Sigma is different from TQM and process re-engineering. 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 results.
Lean Six Sigma
This is the fusion of two complementary business management philosophies, Lean and Six Sigma.Lean, as the name suggests, continually looks for ways to “trim the fat” in a business process. Trimming the fat reduces costs and speeds up the process. Lean uses a few tools (a Value Stream Map or VSM is the most commonly used Lean tool) and is best applied to reduce process cycle times and inventory. The central concept in Lean thinking is that work should be done in a continuous flow,rather than in batches. Batching creates ‘lumps of work’, generates inventory,and leads to bottlenecks. “Fat” or waste in Lean terminology is broadly defined. Lean defines 7 categories of waste:
- 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.
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.
The lasting power of six sigma is the discipline and mindset it brings to deliver flawless products and services. As a management philosophy that continually strives for “zero defects”, six sigma engenders process discipline,employee engagement, metrics that foster excellence, and continuous innovation.