Six Sigma to distinguish patterns in COVID-19 approaches

Willem Salentijn, Jiju Antony, Jacqueline Douglas

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Purpose: COVID-19 has changed life as we know. Data are scarce and necessary for making decisions on fighting COVID-19. The purpose of this paper is to apply Six Sigma techniques on the current COVID-19 pandemic to distinguish between special cause and common cause variation. In the DMAIC structure, different approaches applied in three countries are compared. Design/methodology/approach: For three countries the mortality is compared to the population to distinguish between special cause variation and common cause variation. This variation and the patterns in it are assessed to the countries' different approaches to COVID-19. Findings: In the DMAIC problem-solving approach, patterns in the data are distinguished. The special cause variation is assessed to the special causes and approaches. The moment on which measures were taken has been essential, as well as policies on testing and distancing. Research limitations/implications: Cross-national data comparisons are a challenge as countries have different moments on which they register data on their population. Furthermore, different intervals are taken, varying from registering weekly to registering yearly. For the research, three countries with similar data registration and different approaches in fighting COVID-19 were taken. Originality/value: This is the first study with Master Black Belts from different countries on the application of Six Sigma techniques and the DMAIC from the viewpoint of special cause variation on COVID-19.

Original languageBritish English
Pages (from-to)1633-1646
Number of pages14
JournalTQM Journal
Volume33
Issue number8
DOIs
StatePublished - 2021

Keywords

  • Attribute charts
  • Corona
  • COVID-19
  • DMAIC
  • Pandemic
  • Six sigma

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