An exploratory case study on the use of data and analytics to drive managerial decision-making in a large organisation

Abstract

In a business environment, decision-making is considered to be the major function of management. Effective decision-making is vital, particularly due to the competitive and dynamic environment in which most businesses operate. Data has been used to support day-to-day operations ever since organisations started collecting it, although the utilisation of data and analytics in managerial decision making is not always consistent. The purpose of this study was to investigate how a large local organisation enables access to the use of data and adopts analytics in managerial decision-making. To this end, this research project took the form of an exploratory case study. The organisation being studied was investigated through a set of qualitative interviews with two groups of participants namely, four Data Professionals and eleven Managers, all of which were employed with the organisation under study. Data from the data professionals were gathered through a focus group while in-depth one-on-one interviews were held with each manager. The information gathered from the focus group and interviews was complimented with data gathered from two of the company’s reports. The participant’s responses together with the company reports provided insight into the access and use of data and analytics in managerial decision-making. The findings indicated that managers across the organisation recognise the value of using data and analytics in decision-making. The main themes which emerged in relation to their use were to enable effective planning, to improve competitiveness and to mitigate risk and uncertainty. The findings also showed that apart from data, intuition and experience were also important factors for effective decision-making, with the importance of each of these factors being very much dependent on the experience of the individual making the decision and the situation at hand. When analysing the pillars of an analytics ecosystem (People, Processes and Technology), it was evident that a number of organisational shortcomings exist which potentially hinder the use of data and analytics in decision making. These shortcomings provided insight into the organisational changes required to make data and analytics more central and critical in the decision-making process which, in turn, allowed for a number of recommendations to be suggested.