Business intelligence and big data’s role in decision making
There’s little doubt that the 21st century’s explosion of digital data has revolutionised the way we connect, communicate and operate.
Thanks to its unprecedented growth, digital technology has delivered new capabilities for gathering and analysing huge amounts of data and opening up endless – and exciting – possibilities for both society and business.
But with the continuous surge of information that’s pushed through ever-increasing pipelines, many organisations can find using huge amounts of data to make strategic decisions an overwhelming priority.
Dr Morteza Namvar has recently completed a PhD that investigates how business intelligence and big data help organisational leaders make sense of the business environment.
‘Business intelligence is mainly used in making operational decisions but its use in understanding complex situations, which can potentially lead to strategic decision making, was not investigated – neither in the literature of business intelligence nor sensemaking,’ he says.
Business intelligence is the process that organisations use to capture, store, integrate and analyse their data. By understanding the way business intelligence can be employed, an organisation is able to acquire genuine business insight.
‘My research investigates the opportunities in using business intelligence technologies to make sense of a business environment … I developed a theoretical framework which shows how sensemaking can be supported using business intelligence tools and techniques,’ says Morteza.
Completing an undergraduate science degree in Iran, Morteza added a master’s degree in science that majored in information technology (IT) engineering. It was this study that sparked his interest in big date and business intelligence.
‘During my master’s degree I worked on some research about using big data in predictive modelling. The findings of my research, which was published in several journals and conferences, proposed innovative approaches for predicting customer segmentation and customer churn prediction using predictive modelling and business intelligence,’ he says.
After two years’ of work in this field, Morteza soon realised that while many researchers were already developing predictive models, there was a clear gap in the research using predictive models.
‘For my PhD research, I employed a qualitative approach to investigate how the models which are developed by data scientists should be applied to real business problems,’ he explains.
Within the organisational environment, ‘sensemaking’ is a term that describes the approach – or sequence of business activities – that help an organisation to better understand its context and problems.
‘Sensemaking is an important prerequisite to reaching informed decisions and involving processes that current or future business intelligence technology could support,’ he says.
Bringing together the two distinct theoretical fields of sensemaking and business intelligence, Morteza says his research demonstrates how the two approaches can be put into practice with applications for business intelligence-based sensemaking.
‘It extends the theory of sensemaking by firmly grounding in a modern data-driven organisational environment, where tools such as business intelligence can assist decision-makers in making sense of ongoing changes in the business environment,’ he explains.
Morteza says he chose to undertake his doctoral studies at Deakin after searching a range of Australian universities in a quest to find one that matched his research interests of business intelligence and analytics.
‘When I discovered that Deakin had a new program in business analytics, and also academics with invaluable experience in this area, I contacted some of the staff whose research was closely related to my interests – fortunately I received very positive responses.’
He says one of the main challenges of his study was conducting qualitative research on a highly-quantitative topic.
‘As most of the studies in the area of business intelligence and analytics employ a quantitative method, it was difficult to publish in top-ranked information system journals. Had I done a quantitative study, I believe I could have published more,’ he says.
However, there were also many positive milestones in Morteza’s PhD journey including an opportunity to present his research abroad.
‘Deakin supported me to travel to New Zealand to present the outcome of my research at one of the world’s most prestigious conferences –the International Conference on Information Systems. Several well-known information systems’ researchers attended my presentation and provided me invaluable comments which I applied to my PhD thesis before its final submission,’ he says.
Morteza’s research is now an important contribution to the literature of business intelligence as it investigates what business intelligence can do before decision-making and actions occur.
‘From a practical perspective, my research clarifies that business intelligence can assist not only decision-making but also sensemaking. It identifies the elements needed for the sensemaking process to succeed in organisational settings and provides guidelines for creating business intelligence capacity.’
With his PhD complete, Morteza is now working as a lecturer in the Deakin Business School’s Department of Information Systems and Business Analytics and enjoys sharing his knowledge with students who are keen to learn about the tools, techniques and concepts of business intelligence and analytics.
‘During my research I became familiar with several analytics and business intelligence tools and learnt how to apply them for solving business problems. Knowing how to use these tools and apply them has prepared me for work in both academia and industry.’
Originally published on Deakin Business School Newsroom, 19 May 2017.