A Framework for Building Mature Business Intelligence and Analytics in Organizations

George, Amrita; Schmitz, Kurt

doi:10.4018/jdm.2020070102

Cited by 13 publications

(11 citation statements)

References 56 publications

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“…The evolution of AI lately and its advancement in numerous fields is because of three main factors: huge volume of data, better algorithms, and considerably improved computational hardware [2,55]. This advancement has pulled in the consideration of enormous technology-oriented businesses to AI technologies.…”

Section: Artificial Intelligence and Machine Learning In Organizationsmentioning

confidence: 99%

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Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

2021

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In the past decade, current literature and businesses have drawn attention to Artificial Intelligence (AI) tools and in particular to the advances in machine learning techniques. Nevertheless, while the AI technology offers great potential to solve difficulties, challenges remain implicated in practical implementation and lack of expertise in the strategic usage of AI to create business value. This paper aims to implement a systematic literature review analyzing convergence of the AI and corporate strategy and develop a theoretical model incorporating issues based on the existing research in this field. Eighty-one peer-reviewed articles were discussed on the basis of research methodology from Webster and Watson (2002). In addition to gaps in future research, a theoretical model is developed, discussing the four sources of value creation: AI and Machine Learning in organizations; alignment of AI tools and Information Technology (IT) with organizational strategy; AI, knowledge management and decision-making process; and AI, service innovation and value. These outcomes lead to both theoretical and managerial viewpoints, with extensive possibilities to generate new methods and types of management practices.

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Section: Artificial Intelligence and Machine Learning In Organizationsmentioning

confidence: 99%

“…Refs. [22,24,55] developed theoretical frameworks that incorporate AI advancements, representation learning and machine learning tools to implement classification and prediction tasks with the guarantee of aligning analytics requirements with the organizational strategy. Ref.…”

Section: Ai Knowledge Management and Decision-making Processmentioning

confidence: 99%

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

2021

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“…Carvalho et al. (2019) develop a maturity model using literature review and George et al. (2020) use the Delphi method to find the maturity levels.…”

Section: Literature Reviewmentioning

confidence: 99%

“…, 2016, 2018; Carvalho et al. , 2019; George et al. , 2020), comprising 10% of readiness literature, have used methodologies prescribed for designing systems (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing organizational health-analytics readiness: artifacts based on elaborated action design method

Venkatraman

Sundarraj

2022

JEIM

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PurposeWhile the adoption of health-analytics (HA) is expanding, not every healthcare organization understands the factors impacting its readiness for HA. An assessment of HA-readiness helps guide organizational strategy and the realization of business value. Past research on HA has not included a comprehensive set of readiness-factors and assessment methods. This study’s objective is to design artifacts to assess the HA-readiness of hospitals.Design/methodology/approachThe information-systems (IS) theory and methodology entail the iterative Elaborated Action Design Research (EADR)method, combined with cross-sectional field studies involving 14 healthcare organizations and 27 participants. The researchers determine factors and leverage multi-criteria decision-making techniques to assess HA-readiness.FindingsThe artifacts emerging from this research include: (1) a map of readiness factors, (2) multi-criteria decision-making techniques that assess the readiness levels on the factors, the varying levels of factor-importance and the inter-factor relationships and (3) an instantiated system. The in-situ evaluation shows how these artifacts can provide insights and strategic direction to an organization through collective knowledge from stakeholders.Originality/valueThis study finds new factors influencing HA-readiness, validates the well-known and details their industry-specific nuances. The methods used in this research yield a well-rounded HA readiness-assessment (HARA) approach and offer practical insights to hospitals.

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“…In order for a manufacturing enterprise to function effectively not only must it have an effectively functioning manufacturing system, but also (and above all) efficient information flow as well as fast and correct decision making (George, Schmitz & Storey, 2020;Gola, 2014;Świć & Gola 2013). One of the basic tools for planning and realisation of production utilized in Polish enterprises is ERP class.…”

Section: Introductionmentioning

confidence: 99%

Computer-Aided Material Demand Planning Using Erp Systems and Business Intelligence Technology

Danilczuk

Gola

2020

acs

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Effective decision-making in industry conditions requires access and proper presentation of manufacturing data on the realised manufacturing process. Although the frequently applied ERP systems allow for recording economic events, their potential for decision support is limited. The article presents an original system for reporting manufacturing data based on Business Intelligence technology as a support for junior and middle management. As an example a possibility of utilising data from ERP systems to support decision-making in the field of purchases and logistics in small and medium enterprises.

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A Framework for Building Mature Business Intelligence and Analytics in Organizations

Cited by 13 publications

References 56 publications

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

Assessing organizational health-analytics readiness: artifacts based on elaborated action design method

Computer-Aided Material Demand Planning Using Erp Systems and Business Intelligence Technology

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