Green belt and black belt projects

Both green and black belt initiatives are process centric and driven towards process optimization. Green belt projects cover a single functional area, whereas black belt projects are cross-functional.

Green belt and black belt projects are taken up to achieve the process goals as demanded by business objectives. Identify the internal tasks where the variation can be controlled. Take them up as green belt projects…for example, the time lag between a “ready pizza” and its “pick up” can be focused and management techniques applied to optimize it.

USL/LSL & UCL/LCL

USL is the upper specification limit, while LSL is the lower specification limit. USL and LSL are dictated by / based on customer expectations. Some processes have only USL, some others have only LSL, and still others have both USL and LSL. (for example, the pizza example has only USL). Software processes have both USL and LSL.

Companies may have different kinds of processes for different customers, or may have the same processes for different customers. The types of processes to be followed are dictated by business demands, as customers have varying expectations.

UCL is the upper control limit, LCL the lower control limit. Control limits are three times the standard deviations (3Sigma always) on either side of the mean.

Pizza Delivery Example

Imagine there are two companies delivering pizzas in a city. Their average delivery times (in minutes) are seen in the table. Say, the upper specification limit is 30. That is the pizza has to be delivered within 30 minutes no matter where the client resides (within the city). (This limit is self-defined by the pizza outlets)

The Average for both the outlets is 20. But, as can be perceived by looking at the values, Outlet A seems to be more consistent, and shows less variability in cooking & delivering pizzas compared to Outlet B. Mean therefore is not a proper measure for comparing variations. A better way is thru standard deviation.

Instead of comparing process variability thru Mean, compare the sigma levels, which give a better insight into the process variability.

For Outlet B to better its process performance, it can target these: 1. Mean. 2. Standard Deviation 3. Sigma Level. Note that the specification limits cannot be changed as they are derived from customer expectations. By focusing on internal processes that are responsible for delays (such as cooking time, time lapse in dished out pizza and its pick up for delivery, etc.), Outlet B can improve on variability in delivery time.

Sigma Level = Diff bet'n mean & spec limit / Sigma

Note: In this example, the Simga Level we get is Zlt. To get Zst, add 1.5. So, as per Zst, the process of outlet A is at (7.91+1.5), and that of outlet B is (1.41+1.5).

Variability and Bell-shaped Curves

Every human activity has variability. Natural patterns of data of any process are bell-shaped curves. Most of the human processes follow a bell shaped curve. Take for example, the internet connectivity speed. Even though the connectivity speed may be 64kpbs, it is not at that speed at every point of time. It keeps on varying. At some time it may be overshoot the specified speed, and at others, remains below that. On an average, however, the connectivity is 64kbps.

Mean is the area around which most of the data points tend to cluster. Going away from the mean on either sides of the curve, values the clustering gradually come down.

Six Sigma - Green & Black Belts

Green & Black Belts: Green belts can handle most of the common situations, while black belts can address even the complex situations.