#4: Data-driven process improvement
Data-driven process improvement
How do you react to problems that appear in your day-to-day routine? Do you fix them and forget? Is there any place for reflection and subsequent improvement? One of the most popular approaches nowadays is data-driven decision. In this weekly issue, we cover the 6-sigma approach to maintain continuous improvement of your activities.
A super short brief in statistics before we continue
A few words about statistics before we jump into the 6-sigma idea.
Sigma (σ) symbolizes “standard deviation” in statistics. In simple words, the standard deviation is a measure of the amount of variation. The lower the number, the closer set of values to the mean (μ). 68–95–99.7 empirical rule tells us that 66% of values lie within 2σ interval, 95% within 4σ, 99.7 within 6σ. Works only for a large amount of values, and the process of getting is more or less random in the natural world.
Six Sigma process quality
Let’s say that we have a process and there are items as an output of this process. That might be sold pies in a bakery or stumped discs on manufacturing. The 6 sigma says that items that we produce should follow their specification within 6σ cases (less than 0.3% of ones are out of their spec). The idea was originally introduced in Motorolla in 1986.
Continuous efforts to achieve stable and predictable process results (e.g., by reducing process variation) are of vital importance to business success.
Manufacturing and business processes have characteristics that can be defined, measured, analyzed, improved, and controlled.
Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.
Methodologies that ensure 6-Sigma:
DMAIC (Define, Measure, Analyze, Improve, Control): used for projects aimed at improving an existing business process
DMADV (Define, Measure, Analyze, Design, Verify): used for projects aimed at creating new product or process designs
The structured approach saves a ton of thinking resources. Even awareness about measurement → improvement might improve your results.
In the next weekly issue, we will discuss three vital principles you must consider in your API design. Subscribe below to not miss
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