Follow Us:

Home Data and Measurements
Data and Measurements


Supporting Business, Improving Productivity

Lean Six sigma process improvement

Are you measuring the right things in the right way?
Do you want to reduce the number of product defects and rework?
Do you want to improve the control of your process?

At the heart of the drive towards operational excellence is the ability to deliver world class customer satisfaction both in terms of quality, delivery and cost. This requires a business strategy which focusses on maximising efficiencies, minimising defects and reducing costs of the process. Six Sigma is about evidence-based decision making with the aim of preventing defects not just detecting them. Key to its philosophy is data, understanding how data is generated and processed, then using it to drive through improvement projects.


The ultimate goal of six sigma is to deliver a process which is capable of producing near zero defects. In Six Sigma terminology, this is defined as 3.4 defects per million opportunities. The application of Six Sigma to drive process excellence is best illustrated by the US postal service who initially had a measured quality of 99% with 20,000 lost mail articles per hour, a sigma level of 3.8. After implementing a Six Sigma improvement strategy, the process quality measured at 99.9997% with 7 lost articles per hour achieving a sigma level of 6.


Production Support 56 have a wealth of experience in using Six Sigma methodology for business and process improvement. Utilising the traditional DMAIC framework of Define, Measure, Analyse, Implement and Control, we can help to identify and quantify inefficiencies, wastes and variation in your process, formulate data driven solutions and implement cost effective sustainable solutions.

We can offer either singular evaluative and analytical services or full DMAIC improvement projects using the following six sigma tools:

  • Value stream mapping (VSM)
  • Cause & Effect analysis (CE)
  • Capability analysis
  • Failure mode & effects analysis (FMEA)
  • Measurement systems analysis (MSA)

  • Hypothesis testing
  • Design of experiments (DOE)
  • Response surface methodology (RSM)
  • Evolutionary operations (EVOP)
  • Statistical process control (SPC)


  • Reduced operating costs.
  • Improved process control.
  • Improved process efficiency – improved on time delivery.
  • More robust processes.
  • Improve regulatory compliance.

  • Increased customer satisfaction.
  • Reduction in defects and errors.
  • Motivated and engaged employees.

Data and Measurements


Data and Measurements

Take a look at the latest case study.

Drop us an email or call on 07843 879614