Statistical thinking and its role for industrial engineers and managers in the 21st century

Abstract

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to demonstrate the vital linkage between six sigma and statistical thinking. The paper also explains the key characteristics required for statistical thinking and some of the common barriers in the implementation of the key principles of statistical thinking. Design/methodology/approach -The objectives of the paper have been achieved in several ways. The paper provides the key principles of statistical thinking and then discusses the possible reasons for lack of statistical thinking in modern organizations. The paper then illustrates the linkage between the statistical principles and six sigma. The tools and techniques of six sigma used within statistical thinking are also highlighted in the paper. Findings -The key findings of this work include the relationship between the two key powerful methodologies: six sigma and statistical thinking, reasons for lack of applications of statistical thinking in organizations, the future role of managers and engineers in companies with regard to statistical thinking era and the commonalities in the application of tools and techniques between these two methodologies.Research limitations/implications -The paper needs more justification through surveys and case examples and this will be the future step of this study. In fact, one of the co-authors is currently conducting a survey in the UK organizations to investigate the relationship between statistical thinking and six sigma. Practical implications -The paper is very practical in nature and it does yield a great value to those people who are currently embarking on six sigma program, especially at senior manager and executive levels. Originality/value -Very little is published in the field of statistical thinking in the UK academic world. In fact, there is a cognitive gap in this field and this paper certainly forms a good platform for further research that will enable to bridge the gap.

Measuring Efficiency of Statistical Methods Use in Enterprises: Development of an Initial System of Indicators

“…The frequency of statistical methods use is estimated in the same way as for the C 2 indicator. Consequently, the I 7 indicator is given as: 7 1…”

“…The main problems here refer to the fact that business surveys are very demanding and requesting special skills of the researcher [3] and that response rates could be very low [4]. Moreover, the second reason, the key one, why a system of statistical methods use indicators has not been formed yet is an unfavourable position of statistical methods use and of statistical thinking, in general, in enterprises [5][6][7][8][9][10][11]. The third reason of a scarce presence of statistical methods use 424 Measuring Efficiency of Statistical Methods Use in Enterprises: Development of an Initial System of Indicators indicators and their systems is that the process of forming a high quality system of indicators is a very demanding task.…”

Adoption and Benefits of Statistical Methods in Enterprises: Differences between Croatian Regions

“…Past research concerning statistical methods in enterprises was mainly oriented on inspecting whether enterprises use them (West 1994, Ahmed and Hassan 2003, Tanco et al 2008, or on defining the main barriers to their use (Deleryd 1998, Antony et al 2004, Makrymichalos et al 2005. The main reason for the scarce use of statistical methods is thought to be the insufficient familiarity of employees with statistical methods' abilities and benefits (Tanco et al, 2008).…”

“…Some efforts in additional statistical methods training for employees have been done (Vere-Jones 1995, Dransfield, Fisher and Vogel 1999, Wild and Pfannkuch, 1999, Grigg and Walls, 2007. Unfortunately, the aversion of employees is too high to change their attitudes towards statistical methods and to achieve better results in the short run (Hahn and Hoerl, 1998, Deleryd, Garvare and Klefsjö, 1999, Rungasamy, Antony and Ghosh, 2002, Makrymichalos et al, 2005. Some research has been done on the impact of statistical methods on small enterprise performance (Dumičić, Bregar andŽmuk 2014, Žmuk 2015).…”

Business Sample Survey Measurement on Statistical Thinking and Methods Adoption: the Case of Croatian Small Enterprises

“…According to Makrymichalos et al [33] the main reasons and barriers to further development and increase of the statistical methods usage level in enterprises are: different opinions on statistical methods of enterprises and their employees; inadequate education at universities in the field of statistical methods use; managers' fear of the statistical methods use. Deleryd [34] has formed four groups of reasons for seldom statistical methods application: problems in management; conservative personal employees' attitudes; practical problems; methodological problems.…”