Making Sense of Time Series Forecasting

It is a common scenario: A practitioner has sales data for the past several months and wants to forecast next month’s sales volume. This type of forecasting can help manufacturers and distributors ensure they have enough product to meet customer demands. But how is this forecasting done? Statistical analysis software offers two ways to plot…


Pareto Principle (80/20 Rule)

Vilfredo Pareto was an economist who is credited with establishing what is now widely known as the Pareto Principle or 80/20 rule. When he discovered the principle, it established that 80 percent of the land in Italy was owned by 20 percent of the population. Later, he discovered that the pareto principle was valid in other parts…

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Rounding and Round-off Rules

When performing statistical data analyses, quality professionals are always challenged to maintain data integrity. When should you round up the answer; when should you round down? How many significant figures are appropriate for the data set that has been taken? Below are a set of simple rules that should help you traverse the perils of…


Actionable Information from Soft Data

Engineers, Six Sigma practitioners and other researchers often work with “hard” data – discrete data that can be counted and legitimately expressed as ratios. But what of “soft” data, things like opinions, attitudes and satisfaction? Can statistical process controls (SPC) be applied here? Can process variation in customer satisfaction, for example, be measured and then reported to…


Are You Sure Your Data Is Normal?

Most processes, particularly those involving life data and reliability, are not normally distributed. Most Six Sigma and process capability tools, however, assume normality. Only through verifying data normality and selecting the appropriate data analysis method will the results be accurate. This article discusses the non-normality issue and helps the reader understand some options for analyzing…


Minimize the Risk of the Unknown in Six Sigma Projects

“You don’t know what you don’t know.” That phrase has been taught in Black Belt training for many years, and it continues to be relevant today. When combined with a related phrase, “What you don’t know can hurt you,” these words illustrate a common challenge: Sometimes, the events that hurt us are unknown and unexpected….

Attribute Agreement Analysis for Defect Databases

A defect database that tracks errors in processes (or even products) – a database that is so sophisticated that it actually tracks where the defect occurred in addition to the type of defect – can provide powerful information. It can be quite helpful in scoping and prioritizing potential improvement opportunities. But is the data trustworthy?…

A Parallel Process View for Information Technology

The value and impact that a solid Design for Six Sigma (DFSS) approach can bring to an IT business is well known. While many organizations understand the relationship between DFSS and their own project management approach, what they often miss is attention to the foundational concepts of Lean and DMAIC (Define, Measure, Analyze, Improve, Control)…


Discriminant Analysis Can Minimize Returned Products

Accurate predictions, optimal decisions, and an explanation of root cause and its effects on a process are just a few of the many types of solutions managers are expected to deliver when complex problems appear. Yet, discriminant analysis, one of the most powerful tools used to solve problems in a process, is often neglected in…


Analytical Treatment of Discrete Ordered Category Data

Ordered category data is discrete data representing appraiser or client perception against a rating scale such as a survey or questionnaire. Black Belts learning to apply the Six Sigma methodology to ordered category data are traditionally taught analytical methods that include normal and Poisson distributions. This is probably due to Six Sigma’s beginnings in manufacturing….

Simulation Modeling Best Addition to Analysis Toolkit

Because of the rapid growth and increased competition in information technology (IT), business process outsourcing (BPO) and other service sector industries in India, quality and cost of operations have become the major distinguishing factors among such companies. Survival, growth and profits depend on how an organization controls its costs and satisfies its clients or customers….


Connecting Six Sigma to CMMI Measurement and Analysis

Measurement and analysis (MA) is a Level 2 support process area within the Capability Maturity Model Integration (CMMI) process. The purpose of MA is to provide management information necessary to implement monitoring and control of various required processes. Source: Ahern, Clouse and Turner, CMMI Distilled: A Practical Introduction to Integrated Process Improvement, second edition, Addison…

Implications of Analyses of Software Inspections Data

A variety of analyses can be done during the Analyze phase of a Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) software project with data from Fagan-style inspections. These analyses suggest possible implications when considering Improve activities. Analyses used here are based on a real situation and the conclusions drawn are valid in that situation,…