Integrated Multi-Income Stream Performance Dashboard: a Japanese Corporate Banking Case

Krisnhu Hananta Rachansa; Wasesa Meditya

doi:10.59395/ijadis.v5i1.1313

Authors

Krisnhu Hananta Rachansa School of Business and Management, Institut Teknologi Bandung
Wasesa Meditya School of Business and Management, Institut Teknologi Bandung

DOI:

https://doi.org/10.59395/ijadis.v5i1.1313

Keywords:

Marketing Performance Dashboard, Executive Dashboard, Business Analytics, Corporate Banking, CRISP DM

Abstract

In response to the complex operational challenges faced by Japanese Corporate Banking (JCB), arising from the coexistence of disparate core banking systems post-merger, this study aims to address inherent issues affecting marketing performance monitoring. The existing condition at JCB is characterized by data inconsistency, limited system interoperability, and fragmented income tracking through multiple Excel reports and management systems. Recognizing the gaps in the current setup, the research question revolves around how to enhance marketing performance monitoring effectively. The research objectives, therefore, encompass the development and implementation of a tailored integrated report utilizing the CRISP-DM methodology. This innovative performance dashboard harmoniously consolidates data from diverse sources, presenting a cohesive representation crucial for comprehensive marketing performance assessment. Leveraging advanced methodologies like data normalization and cross-platform integration, the research approach ensures streamlined income tracking, mitigating existing limitations. The data, drawn from various product applications, undergoes meticulous processing to facilitate a unified view on the integrated dashboard. The anticipated result is a significant improvement in monitoring efficiency, heightened data accuracy, and an empowered decision-making process within JCB's operations. The business implication of this initiative is the tangible enhancement of the bank's ability to comprehensively assess income performance, thereby elevating the quality of strategic decision-making and reinforcing JCB's competitive positioning in the banking sector.

Downloads

Download data is not yet available.

Author Biography

Wasesa Meditya, School of Business and Management, Institut Teknologi Bandung

Meditya is an assistant professor at the School of Business and Management, Institut Teknologi Bandung. He holds a Ph.D. in Management Information Systems from Rotterdam School of Management, Erasmus University, Netherlands, an M.Sc. in Logistics Engineering from Duisburg-Essen University, Germany, and a Bachelor of Mechanical Engineering (S.T.) from Institut Teknologi Bandung. His career spans work with international companies, including General Motors Europe - Germany and Rotterdam School of Management - the Netherlands. In Indonesia, he has served as an executive and consultant for a diverse range of organizations, from private companies and state-owned enterprises (BUMN) to notable start-up unicorns and ministries. His primary research and teaching areas revolve around leveraging advanced information systems to enhance business decisions, with a particular emphasis on business analytics. His work has been featured in renowned publications like IEEE Access, Journal of Enterprise Information Management, Decision Support Systems, Journal of Cleaner Production, etc.

References

C. G. Baicu, I. P. Gârdan, D. A. Gârdan, and G. Epuran, "The impact of COVID-19 on consumer behavior in retail banking. Evidence from Romania," Management and Marketing, vol. 15, no. s1, pp. 534-556, 2020, doi: 10.2478/mmcks-2020-0031. https://doi.org/10.2478/mmcks-2020-0031

PWC, "Digital Banking in Indonesia 2018," PwC Survey, no. July, 2018.

J. K. Davis and D. A. Thilagaraj, "Transformational Leadership Theory-A Critical Analysis with reference to Banking Sector," Webology, vol. 19, no. 2, 2022.

T. Wen Ni, "Factors Influencing Behavioural Intention towards Adoption of Digital Banking Services in Malaysia," International Journal of Asian Social Science, vol. 10, no. 8, 2020, doi: 10.18488/journal.1.2020.108.450.457. https://doi.org/10.18488/journal.1.2020.108.450.457

W. W. Eckerson, "Beyond the Basics?: Accelerating BI Maturity," TDWI Research, 2007.

A. Bris et al., "KNIGHTS, RAIDERS, AND TARGETS - THE IMPACT OF THE HOSTILE TAKEOVER - COFFEE,JC, LOWENSTEIN,L, ROSEACKERMAN,S," J Bank Financ, vol. 37, no. 1, 2021.

A. Medina, Rolf; Medina, "The competence loop Competence management in knowledge-intensive, project-intensive organizations," International Journal of Managing Projects in Business, vol. 1, no. 1, pp. 125-130, 2014, [Online]. Available: http://www.emeraldinsight.com/journals.htm?issn=1753-8378&volume=2&issue=2&articleid=1781094&show=abstract

K. M. Cyrus and N. N. Kojal, "Implementing business intelligence's performance management system in strategy base corporations (BI logic)," in Proceedings - CIE 45: 2015 International Conference on Computers and Industrial Engineering, 2015. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963644346&partnerID=40&md5=661b58c62944549ac7aeaf99f698b859

C. A. Tavera Romero, J. H. Ortiz, O. I. Khalaf, and A. R. Prado, "Business intelligence: business evolution after industry 4.0," Sustainability (Switzerland), vol. 13, no. 18. 2021. doi: 10.3390/su131810026. https://doi.org/10.3390/su131810026

C. S. Lee, P. Y. S. Cheang, and M. Moslehpour, "Predictive Analytics in Business Analytics: Decision Tree," Advances in Decision Sciences, vol. 26, no. 1, 2022, doi: 10.47654/V26Y2022I1P1-30. https://doi.org/10.47654/v26y2022i1p1-30

W. Raghupathi and V. Raghupathi, "Contemporary business analytics: An overview," Data, vol. 6, no. 8. 2021. doi: 10.3390/data6080086. https://doi.org/10.3390/data6080086

S. Liu, O. Liu, and J. Chen, "A Review on Business Analytics: Definitions, Techniques, Applications and Challenges," Mathematics, vol. 11, no. 4. 2023. doi: 10.3390/math11040899. https://doi.org/10.3390/math11040899

D. Delen and S. Ram, "Research challenges and opportunities in business analytics," Journal of Business Analytics, vol. 1, no. 1, 2018, doi: 10.1080/2573234X.2018.1507324. https://doi.org/10.1080/2573234X.2018.1507324

A. A. de Waal, "Performance-driven behavior as the key to improved organizational performance," Measuring Business Excellence, vol. 14, no. 1, pp. 79-95, 2010, doi: 10.1108/13683041011027472. https://doi.org/10.1108/13683041011027472

J. Brix, "The performance-improving benefits of a radical innovation initiative," International Journal of Productivity and Performance Management, vol. 64, no. 3, pp. 356-376, 2015, doi: 10.1108/IJPPM-10-2014-0153. https://doi.org/10.1108/IJPPM-10-2014-0153

S. S. Alam, V. Arumugam, N. G. Mohd Nor, P. Kaliappan, and L. S. Fang, "Relationships between Innovation Capabilities, Business Performance, Marketing Performance and Financial Performance: A Literature Review," Business and Management Horizons, vol. 1, no. 1, 2013, doi: 10.5296/bmh.v1i1.3415. https://doi.org/10.5296/bmh.v1i1.3415

M. Anwar, "Business model innovation and SMEs performance-Does competitive advantage mediate?," International Journal of Innovation Management, vol. 22, no. 7, 2018, doi: 10.1142/S1363919618500573. https://doi.org/10.1142/S1363919618500573

M. L. P. Moreno and T. Duarte-Atoche, "Relationship between sustainable disclosure and performance-An extension of Ullmann's model," Sustainability (Switzerland), vol. 11, no. 16, 2019, doi: 10.3390/su11164411. https://doi.org/10.3390/su11164411

C. Alberti and I. Durand-Zaleski, "ICUs: From performance appraisal to executive dashboard?," Intensive Care Medicine, vol. 33, no. 8. 2007. doi: 10.1007/s00134-007-0697-9. https://doi.org/10.1007/s00134-007-0697-9

A. Kruglov, D. Strugar, and G. Succi, "Tailored performance dashboards-an evaluation of the state of the art," PeerJ Comput Sci, vol. 7, 2021, doi: 10.7717/peerj-cs.625. https://doi.org/10.7717/peerj-cs.625

T. Mauritsius, A. S. Braza, and Fransisca, "Bank marketing data mining using CRISP-DM approach," International Journal of Advanced Trends in Computer Science and Engineering, vol. 8, no. 5, 2019, doi: 10.30534/ijatcse/2019/71852019. https://doi.org/10.30534/ijatcse/2019/71852019

B. Carneiro da Rocha and R. Timoteo de Sousa Junior, "Identifying Bank Frauds Using CRISP-DM and Decision Trees," International Journal of Computer Science and Information Technology, vol. 2, no. 5, 2010, doi: 10.5121/ijcsit.2010.2512. https://doi.org/10.5121/ijcsit.2010.2512

T. Darmawan, "Credit Classification Using CRISP-DM Method On Bank ABC Customers," International Journal of Emerging Trends in Engineering Research, vol. 8, no. 6, 2020, doi: 10.30534/ijeter/2020/28862020. https://doi.org/10.30534/ijeter/2020/28862020

M. Ghasemaghaei, "Understanding the impact of big data on firm performance: The necessity of conceptually differentiating among big data characteristics," Int J Inf Manage, vol. 57, 2021, doi: 10.1016/j.ijinfomgt.2019.102055. https://doi.org/10.1016/j.ijinfomgt.2019.102055

P. Childerhouse, M. Al Aqqad, Q. Zhou, and C. Bezuidenhout, "Network resilience modelling: a New Zealand forestry supply chain case," International Journal of Logistics Management, vol. 31, no. 2, pp. 291-311, 2020, doi: 10.1108/IJLM-12-2018-0316. https://doi.org/10.1108/IJLM-12-2018-0316

B. Jaffar, T. Oreszczyn, and R. Raslan, "Empirical and modelled energy performance in Kuwaiti villas: Understanding the social and physical factors that influence energy use," Energy Build, vol. 188-189, 2019, doi: 10.1016/j.enbuild.2019.02.011. https://doi.org/10.1016/j.enbuild.2019.02.011

D. Clayson, "The student evaluation of teaching and likability: what the evaluations actually measure," Assess Eval High Educ, vol. 47, no. 2, 2022, doi: 10.1080/02602938.2021.1909702. https://doi.org/10.1080/02602938.2021.1909702

I. G. Sudirtha, "Program evaluation: implementation of tourism village development," International Journal of Social Sciences and Humanities, 2019, doi: 10.29332/ijssh.v3n3.356. https://doi.org/10.29332/ijssh.v3n3.356

J. S. L. Lam and X. Bai, "A quality function deployment approach to improve maritime supply chain resilience," Transp Res E Logist Transp Rev, vol. 92, pp. 16-27, 2016, doi: 10.1016/j.tre.2016.01.012. https://doi.org/10.1016/j.tre.2016.01.012

R. Gupta et al., "Spatial analysis of distribution grid capacity and costs to enable massive deployment of PV, electric mobility and electric heating," Appl Energy, vol. 287, 2021, doi: 10.1016/j.apenergy.2021.116504. https://doi.org/10.1016/j.apenergy.2021.116504

D. Matheson and J. E. Matheson, "Smart organizations perform better," Research Technology Management, vol. 44, no. 4, pp. 49-54, 2001, doi: 10.1080/08956308.2001.11671442. https://doi.org/10.1080/08956308.2001.11671442

D. Alonso-Martinez, V. De Marchi, and E. Di Maria, "The sustainability performances of sustainable business models," J Clean Prod, vol. 323, 2021, doi: 10.1016/j.jclepro.2021.129145. https://doi.org/10.1016/j.jclepro.2021.129145

P. Velte, "Environmental performance, carbon performance and earnings management: Empirical evidence for the European capital market," Corp Soc Responsib Environ Manag, vol. 28, no. 1, 2021, doi: 10.1002/csr.2030. https://doi.org/10.1002/csr.2030