Data analytics competency for improving firm decision making performance

Ghasemaghaei, Maryam; Ebrahimi, Sepideh; Hassanein, Khaled

doi:10.1016/j.jsis.2017.10.001

Cited by 246 publications

(193 citation statements)

References 63 publications

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“…Thirathon, Wieder, Matolcsy and Ossimitz (2017) concluded in their study that firms that were more successful were those that had a higher analytical culture which they used as the main driver in analytical decision-making. Ghasemaghaei, Ebrahimi and Hassanein (2018) argue that firm resources play a critical role in ensuring that BI leads to improved organisational decision-making. The resource-based view suggests that the qualities and arrangement of resources makes the firm distinct from a competitive perspective.…”

Section: Factors Influencing the Quality Of Decision-makingmentioning

confidence: 99%

“…Another study by (Ghasemaghaei et al 2018) surveyed 151 IT managers and data analysts in order to understand how data analytics competency affected decision-making performance in organisations. The study (see Figure 1) found that all factors positively affected the quality of decision making in organisations.…”

Section: Factors Influencing the Quality Of Decision-makingmentioning

confidence: 99%

“…Employee domain knowledge is defined as the deep understanding about the internal procedures and processes of the business functions and their impacts. Analytical skills is the capability of being able to analyse and interpret data to gain insights (Ghasemaghaei et al 2018). Raghunathan (1999) found that the decision-maker's understanding of the relationships between entities was paramount and recommended that the decision-makers be included in the analytics process.…”

Section: Information Qualitymentioning

confidence: 99%

“…A data clean-up improved the quality of decisions for the first round, but deteriorated as data grew stale. The study suggested that a continuous improvement approach is required to the maintenance and assessment of the quality of data Figure 1: BI impact on decision making performance -adapted (Ghasemaghaei et al 2018). Wang (1998) argued that firms must put some effort to ensure data quality in as much as they work towards ensuring product quality.…”

Section: Information Qualitymentioning

confidence: 99%

See 3 more Smart Citations

Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal

Chummun¹,

Singh²

2019

J. Rev. Global Econ.

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The current study sought to investigate the factors which influence the quality of decision-making using business intelligence (BI) in a metal rolling plant in KwaZulu-Natal. Specifically, the study was focused on information quality, system quality and BI service quality. The study used a self-administered survey sent out to participants having sufficient report runs which made up the population of the study. The collected data came from different levels of employees, namely; managers (47%) and non-managers (53%) with varying levels of BI experience, and the data was imported into SPSS for analysis. The results showed that information quality had a positive significant impact on the quality of decision-making; system quality had a positive significant impact on the quality of decision-making; and BI service quality had a positive significant impact on the quality of decision-making. Multiple linear regression analysis was conducted to determine the strength of these variances in influencing decision-making. It was found that the three variables explained 65.7% of the variance in the quality of decision-making. Overall, the study found that high quality information, coupled with a high-quality system and good BI service, leads to a higher quality of decision-making, and that the impact of BI on decision-making is positive. The study recommends that the company implement data quality management focusing on data cleansing, it should also implement more sophisticated analysis techniques to get insights and have strategies to upskill both technical and business workers.

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Section: Factors Influencing the Quality Of Decision-makingmentioning

confidence: 99%

Section: Factors Influencing the Quality Of Decision-makingmentioning

confidence: 99%

Section: Information Qualitymentioning

confidence: 99%

Section: Information Qualitymentioning

confidence: 99%

See 2 more Smart Citations

Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal

Chummun¹,

Singh²

2019

J. Rev. Global Econ.

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“…In making decisions with uncertainty, enterprises should be able to classify the data collected to build a suitable model for mitigating the risk of misinterpreting the data [10]. The collected data must be in accordance with the objectives to be achieved by the enterprise, therefore increasing the reliance that can be placed on the data analytics models derived [11]. The act of basing decisions on the analysis of data rather than purely on intuition is referred to as Data-Driven Decision-Making (DDDM) [12].…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Decision-Making Model for the Third-Party Logistics (3PL) Industry

Moyo¹,

Scholtz²,

Mohammed³

Kalpa Publications in Computing

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The evolution of the supply chain has resulted in a growth in the usage of technology and data generated and distributed within the industry. Third-party logistics (3PL) companies operating within the supply chain industry are not maximising the capabilities of data to make well- informed decisions. The purpose of this paper is to address this gap and to develop a prescriptive, theoretical model for data-driven decision-making (DDDM). To address the gap, a literature review of DDDM in 3PL industry and in other contexts was conducted. The proposed model is built based on the consideration of existing DDDM models and frameworks; data and data analytics principles to collect, store, manage and analyse data; and the Cynefin framework. Existing models and frameworks for DDDM do not provide explicit guidelines on how to apply DDDM in a 3PL and supply chain context. The proposed DDDM model constitutes of three phases, namely: (1) the setup phase, that considers data knowledge and decision-making knowledge; (2) execution phase; and (3) the learning phase. The application of the model in 3PL companies can support the decision- making process in these companies, with a consideration of the challenges and opportunities that exist in the supply chain. The decision-makers in 3PLs can thus make better-informed decisions that positively impact their enterprises and the supply chain.

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Advanced Sensing Systems in Automobiles

Savadatti,

Bale

2024

Computational Intelligent Techniques in Mechatronics

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Data analytics competency for improving firm decision making performance

Cited by 246 publications

References 63 publications

Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal

Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal

A Data-Driven Decision-Making Model for the Third-Party Logistics (3PL) Industry

Advanced Sensing Systems in Automobiles

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