A key aspect to making improvements in your business process is to understand the data that you are measuring when assessing process performance.

Assuming that you have already started collecting data on your process performance metric, the questions and examples outlined below will help you understand the data you are collecting.

  • Why did you choose this metric to improve your process?
    • Measure of efficiency – volume and cost of resources consumed in your process
    • Measure of effectiveness – focuses on what your product or service looks like to the customer
    • Measure of predictability – looks at the relationship between process inputs and output

  • What is your data type? (Continuous v/s Discrete)
    • Continuous – only those things that can be measured on an infinitely divisible continuum or scale
      • Time – hour
      • Money – dollar
      • Temperature – degree
    • Discrete – count measures that you can sort into non-overlapping categories
      • Type of vehicle – truck, car, SUV
      • Product rating – fair, good, very good, superior or 1, 2, 3, 4, 5 scale
      • Type of shoe – Nike, Reebok, Adidas

  • What are the descriptive statistics for your data?
    • Central tendency
      • Mean – the average of a set of value
      • Median – the midpoint in a string of sorted data
      • the most frequently occurring value in a data set
    • Spread or dispersion
      • Range – the difference between the largest and smallest observations in a data set
      • Deviation – the distance between a data point and the mean
      • Variance – the average squared deviation about the mean
      • Standard Deviation – the square root of the average squared deviation about the measure
    • Symmetry and skewness
      • Histograms are graphical displays of the data that can allow you to see its general shape

Next Steps

  • Once you have a basic understanding of your data, more advanced techniques can be used to assess your measurement system, determine if your process is stable, and determine your process capability.
  • In addition, statistical data analysis can be used to identify root causes. Finally, once improvements are implemented, you can compare before and after analyses to assess progress and monitor controls on your key performance metric.

Branner Consulting, LLC can help you at any stage along your journey from process documentation to implementing process improvement projects. We also provide coaching and training in Six Sigma and Lean methodologies.