Shaping the future of multidimensional project management in retail industry using statistical and big-data theories

Jennifer Hayes, Azizur Rahman, Rafiqul Islam

Research output: Book chapter/Published conference paperChapter (peer-reviewed)peer-review


IT projects are by nature, complex and chaotic with a significant proportion failing, assessed as ‘not meeting requirements’, experiencing overruns in time, budget or scope or not determined acceptable by sponsors and stakeholders. This paper presents a literature review, focused on defining a project initiation and governance framework rooted in complexity theory and bound to the Liminal Cynefin framework with the potential to transform IT project management by understanding projects from the intersection of chaos, complexity and constraints theories. The findings would assist decision makers in the project management industry to assess the potential complexity of a project in the Concept, Validate and Plan stages, matching these results with adaptive governance models and adaptive project management leadership in order to improve project outcomes. With the traditional hard paradigm of the project management industry advocating quantitative measures of project success criteria and projects still failing against these measures, an analysis of historical projects against an amalgamation of current developments in chaos, complexity and constraints theories, combined with alignment to the Cynefin framework is proposed.
Original languageEnglish
Title of host publicationStatistics for data science and policy analysis
EditorsAzizur Rahman
Place of PublicationSingapore
Number of pages14
ISBN (Electronic)9789811517358
ISBN (Print)9789811517341
Publication statusPublished - 2020
EventThe 2nd Applied Statistics and Policy Analysis Conference: ASPAC2019 - Charles Sturt University, Wagga Wagga, Australia
Duration: 05 Sept 201906 Sept 2019 (program) (book of abstracts) (proceedings)


ConferenceThe 2nd Applied Statistics and Policy Analysis Conference
Abbreviated titleEffective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling
CityWagga Wagga
OtherProceedings due for publication May 2020
Internet address


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