Business Intelligence Success in Selected Organizations in the EnergySector in India: An Analysis

Ms. Rekha Mishra; Prof. A. K. Saini

doi:10.65301/dias.2021.18.1.1

Articles 35th Edition of DTR Apr 2021 – Sep 2021

DOI 10.65301/dias.2021.18.1.1

Business Intelligence Success in Selected Organizations in the EnergySector in India: An Analysis

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Published 2021-09-30

Abstract

A report by the International Energy Agency (IEA), 2020, has indicated that India should make energy data efforts to ensure its management, monitoring and data reporting to accomplish energy demand and sustainability targets. The energy sector organizations address these concerns using Business Intelligence (BD to gain insight for their various operations and support decision making. However, BI project's low success rate has been raising a question about its adoption; hence, there is a need to re look at the current BI Success model. In this study, we aimed to find the constituents of the Business Intelligence success model under different decision environments in organizations in the energy sector, using a survey of business intelligence users in the managerial positions. The study results found that interaction of systems, quality of data, user access to BI and risk level of the organization have a significant role to place in business intelligence success in organizations. This study's findings will be valuable for managers, policymakers, and researchers in the domain of business intelligence and energy sector and allied organizations.

Keywords

Business Intelligence Success Model Energy Sector Organizations

References

i. S. Adamala and L. Cidrin (2011). “Key Success Factors in Business Intelligence.”
ii. J. Almeida, M. J. Barros, and S. Maravilhas-Lopes (2020). “A Business Intelligence Maturity Evaluation Model for Management Information Systems Departments.” In Handbook of Research on Emerging Technologies for Effective Project Management (pp. 255–270). IGI Global.
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iv. J. W. Clark (2010). Business Intelligence and Decision Making: Understanding BI as a Theory-Performing Discipline of Decision Improvement.
v. John Dawes (2008). “Do Data Characteristics Change According to the Number of Scale Points Used? An Experiment Using 5-Point, 7-Point and 10-Point Scales.” International Journal of Market Research, 50(1), 61–104.
vi. Howard Dresner (1989). Business Intelligence. Gartner.
vii. M. Ghazanfari, M. Jafari, and S. Rouhani (2011). “A Tool to Evaluate the Business Intelligence of Enterprise Systems.” Scientia Iranica, 18(6), 1579–1590.
viii. Wayne Eckerson (2003). “The Rise and Fall of Spreadmarts.” Information Management, 13(9), 28.
ix. International Energy Agency (2020). India 2020. Paris: IEA. Retrieved from IEA India 2020 Report
x. E. Harison (2012). “Critical Success Factors of Business Intelligence System Implementations: Evidence from the Energy Sector.” International Journal of Enterprise Information Systems, 8(2), 1–13.
xi. P. Hawking and C. Sellitto (2015). “Business Intelligence Strategy: A Utilities Company Case Study.” International Journal of Enterprise Information Systems, 11(1), 1–12.
xii. B. Hostmann, A. Bitterer, and B. Burton (2007). Magic Quadrant for Business Intelligence Platforms, 1Q07. Gartner Research Note G145507.
xiii. O. Isik (2009). “Business Intelligence Success: An Empirical Evaluation of the Role of BI Capabilities and Organisation's Decision Environment.” AMCIS 2009 Doctoral Consortium, 13.
xiv. O. Isik, M. C. Jones, and A. Sidorova (2013). “Business Intelligence Success: The Roles of BI Capabilities and Decision Environments.” Information & Management, 50(1), 13–23.
xv. Z. Jourdan, R. K. Rainer, and T. E. Marshall (2008). “Business Intelligence: An Analysis of the Literature.” Information Systems Management, 25(2), 121–131.
xvi. S. Kokin and T. Wang (2013). “Development of Business Intelligence Success Evaluation Framework.” JAPSC, 13(9), 1657–1660.
xvii. H. Lee, J. Long, and L. Visinescu (2016). “The Relationship between a Business Simulator, Constructivist Practices, and Motivation toward Developing Business Intelligence Skills.” Journal of Information Technology Education: Research, 15, 593–609.
xviii. C. M. Olszak (2016). “Toward a Better Understanding and Use of Business Intelligence in Organisations.” Information Systems Management, 33(2), 105–123.
xix. A. Popovic, R. Hackney, P. S. Coelho, and J. Jaklic (2012). “Towards Business Intelligence Systems Success: Effects of Maturity and Culture on Analytical Decision Making.” Decision Support Systems, 54(1), 729–739.
xx. A. J. Pretorius and J. J. van Wijk (2009). “What Does the User Want to See? What Do the Data Want to Be?” Information Visualization, 8(3), 153–166.
xxi. M. Radenkovic, J. Lukic, M. Despotovic-Zrakic, A. Labus, and Z. Bogdanovic (2018). “Harnessing Business Intelligence in Smart Grids: A Case of the Electricity Market.” Computers in Industry, 96, 40–53.
xxii. T. Ramakrishnan, M. C. Jones, and A. Sidorova (2012). “Factors Influencing Business Intelligence (BI) Data Collection Strategies: An Empirical Investigation.” Decision Support Systems, 52(2), 486–496.
xxiii. A. B. Sangar (2014). “Measurement Metrics for Measuring Success of Business Intelligence System.”
xxiv. A. B. Sangar and N. B. A. Ilahad (2013). “Critical Factors That Affect the Success of Business Intelligence Systems (BIS) Implementation in an Organisation.” Intelligence, 12(2), 14–16.
xxv. M. Seah, M. H. Hsieh, and P. Weng (2010). “A Case Analysis of SaveCom: The Role of Indigenous Leadership in Implementing a Business Intelligence System.” International Journal of Information Management, 30(4), 368–373.
xxvi. N. Solomon and G. Paul (2004). “Business Intelligence.” Communications of the Association for Information Systems, 13, 450.
xxvii. B. H. Sparks and J. T. McCann (2015). “Factors Influencing Business Intelligence System Use in Decision Making and Organisational Performance.” International Journal of Sustainable Strategic Management, 5(1), 31–54.
xxviii. G. Varghese and L. M. Eapen (2016). “Power Sector in India—Recent Challenges and Measures Undertaken.” Asian Journal of Research in Business Economics and Management, 6(1), 33–46.
xxix. V. Vashisht, S. Kamya, and M. Vashisht (2020). “Defect Prediction Framework Using Neural Networks for Business Intelligence Technology-Based Projects.” Paper presented at the 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), 1–5.
xxx. Hugh J. Watson (2009). “Tutorial: Business Intelligence—Past, Present, and Future.” Communications of the Association for Information Systems, 25(1), 39.
xxxi. W. Yeoh, J. Gao, and A. Koronios (2009). “Empirical Investigation of CSFs for Implementing Business Intelligence Systems in Multiple Engineering Asset Management Organisations.” In Information Systems Research Methods, Epistemology, and Applications (pp. 247–271).

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Ms. Rekha Mishra, Prof. A. K. Saini . (2021). Business Intelligence Success in Selected Organizations in the EnergySector in India: An Analysis. DIAS Technology Review, 18(1).

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[1] i. S. Adamala and L. Cidrin (2011). “Key Success Factors in Business Intelligence.”

[2] ii. J. Almeida, M. J. Barros, and S. Maravilhas-Lopes (2020). “A Business Intelligence Maturity Evaluation Model for Management Information Systems Departments.” In Handbook of Research on Emerging Technologies for Effective Project Management (pp. 255–270). IGI Global.

[3] iii. Richard P. Bagozzi and Youjae Yi (1988). “On the Evaluation of Structural Equation Models.” Journal of the Academy of Marketing Science, 16(1), 74–94.

[4] iv. J. W. Clark (2010). Business Intelligence and Decision Making: Understanding BI as a Theory-Performing Discipline of Decision Improvement.

[5] v. John Dawes (2008). “Do Data Characteristics Change According to the Number of Scale Points Used? An Experiment Using 5-Point, 7-Point and 10-Point Scales.” International Journal of Market Research, 50(1), 61–104.

[6] vi. Howard Dresner (1989). Business Intelligence. Gartner.

[7] vii. M. Ghazanfari, M. Jafari, and S. Rouhani (2011). “A Tool to Evaluate the Business Intelligence of Enterprise Systems.” Scientia Iranica, 18(6), 1579–1590.

[8] viii. Wayne Eckerson (2003). “The Rise and Fall of Spreadmarts.” Information Management, 13(9), 28.

[9] ix. International Energy Agency (2020). India 2020. Paris: IEA. Retrieved from IEA India 2020 Report

[10] x. E. Harison (2012). “Critical Success Factors of Business Intelligence System Implementations: Evidence from the Energy Sector.” International Journal of Enterprise Information Systems, 8(2), 1–13.

[11] xi. P. Hawking and C. Sellitto (2015). “Business Intelligence Strategy: A Utilities Company Case Study.” International Journal of Enterprise Information Systems, 11(1), 1–12.

[12] xii. B. Hostmann, A. Bitterer, and B. Burton (2007). Magic Quadrant for Business Intelligence Platforms, 1Q07. Gartner Research Note G145507.

[13] xiii. O. Isik (2009). “Business Intelligence Success: An Empirical Evaluation of the Role of BI Capabilities and Organisation's Decision Environment.” AMCIS 2009 Doctoral Consortium, 13.

[14] xiv. O. Isik, M. C. Jones, and A. Sidorova (2013). “Business Intelligence Success: The Roles of BI Capabilities and Decision Environments.” Information & Management, 50(1), 13–23.

[15] xv. Z. Jourdan, R. K. Rainer, and T. E. Marshall (2008). “Business Intelligence: An Analysis of the Literature.” Information Systems Management, 25(2), 121–131.

[16] xvi. S. Kokin and T. Wang (2013). “Development of Business Intelligence Success Evaluation Framework.” JAPSC, 13(9), 1657–1660.

[17] xvii. H. Lee, J. Long, and L. Visinescu (2016). “The Relationship between a Business Simulator, Constructivist Practices, and Motivation toward Developing Business Intelligence Skills.” Journal of Information Technology Education: Research, 15, 593–609.

[18] xviii. C. M. Olszak (2016). “Toward a Better Understanding and Use of Business Intelligence in Organisations.” Information Systems Management, 33(2), 105–123.

[19] xix. A. Popovic, R. Hackney, P. S. Coelho, and J. Jaklic (2012). “Towards Business Intelligence Systems Success: Effects of Maturity and Culture on Analytical Decision Making.” Decision Support Systems, 54(1), 729–739.

[20] xx. A. J. Pretorius and J. J. van Wijk (2009). “What Does the User Want to See? What Do the Data Want to Be?” Information Visualization, 8(3), 153–166.

[21] xxi. M. Radenkovic, J. Lukic, M. Despotovic-Zrakic, A. Labus, and Z. Bogdanovic (2018). “Harnessing Business Intelligence in Smart Grids: A Case of the Electricity Market.” Computers in Industry, 96, 40–53.

[22] xxii. T. Ramakrishnan, M. C. Jones, and A. Sidorova (2012). “Factors Influencing Business Intelligence (BI) Data Collection Strategies: An Empirical Investigation.” Decision Support Systems, 52(2), 486–496.

[23] xxiii. A. B. Sangar (2014). “Measurement Metrics for Measuring Success of Business Intelligence System.”

[24] xxiv. A. B. Sangar and N. B. A. Ilahad (2013). “Critical Factors That Affect the Success of Business Intelligence Systems (BIS) Implementation in an Organisation.” Intelligence, 12(2), 14–16.

[25] xxv. M. Seah, M. H. Hsieh, and P. Weng (2010). “A Case Analysis of SaveCom: The Role of Indigenous Leadership in Implementing a Business Intelligence System.” International Journal of Information Management, 30(4), 368–373.

[26] xxvi. N. Solomon and G. Paul (2004). “Business Intelligence.” Communications of the Association for Information Systems, 13, 450.

[27] xxvii. B. H. Sparks and J. T. McCann (2015). “Factors Influencing Business Intelligence System Use in Decision Making and Organisational Performance.” International Journal of Sustainable Strategic Management, 5(1), 31–54.

[28] xxviii. G. Varghese and L. M. Eapen (2016). “Power Sector in India—Recent Challenges and Measures Undertaken.” Asian Journal of Research in Business Economics and Management, 6(1), 33–46.

[29] xxix. V. Vashisht, S. Kamya, and M. Vashisht (2020). “Defect Prediction Framework Using Neural Networks for Business Intelligence Technology-Based Projects.” Paper presented at the 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), 1–5.

[30] xxx. Hugh J. Watson (2009). “Tutorial: Business Intelligence—Past, Present, and Future.” Communications of the Association for Information Systems, 25(1), 39.

[31] xxxi. W. Yeoh, J. Gao, and A. Koronios (2009). “Empirical Investigation of CSFs for Implementing Business Intelligence Systems in Multiple Engineering Asset Management Organisations.” In Information Systems Research Methods, Epistemology, and Applications (pp. 247–271).