A Heatmap Approach for Master Data Management Programs

AnnMarie Ericsson, Mikael Berndtsson


Master data management programs are large by nature since the aim is to provide the entire enterprise with a shared trusted view of the organisation’s most critical data assets. In this paper, we present what dimensions and activities a master data management program in a large organisation should consider and how to monitor such a program once it is up and running. A heatmap approach is used to visualize the inherent complexity of a master data management program. Our approach is derived from participating in four different master data management programs in four different global organisations during 2007-2020.


data quality; master data; master data management; master data management programs; heatmap

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Allen, M., & Cervo, D. (2015). Multi-Domain Master Data Management : Advanced MDM and Data Governance in Practice (Vol. First edition). Waltham, Massachusetts: Morgan Kaufmann.

Berson, Alex, & Dubov, Lawrence. (2007). Master data management and customer data integration for a global enterprise. New York: McGraw-Hill.

Cadena-Vela, Susana, Mazón, Jose-Norberto, & Fuster-Guilló, Andrés. (2020). Defining a Master Data Management Approach for Increasing Open Data Understandability. Paper presented at the On the Move to Meaningful Internet Systems: OTM 2019 Workshops.

Cleven, A., & Wortmann, F. (2010). Uncovering Four Strategies to Approach Master Data Management. Paper presented at the 43rd Hawaii International Conference on System Sciences System Sciences (HICSS).

Haneem, Faizura, Kama, Nazri, Taskin, Nazim, Pauleen, David, & Abu Bakar, Nur Azaliah. (2019). Determinants of master data management adoption by local government organizations: An empirical study. International Journal of Information Management, 45, 25-43. doi: 10.1016/j.ijinfomgt.2018.10.007

Haug, Anders, Schlichter, Jakob, Stentoft Arlbjørn, Jan, & Zachariassen, Frederik. (2013). Master data quality barriers: an empirical investigation. Industrial Management & Data Systems, 113(2), 234-249. doi: 10.1108/02635571311303550

Haug, Anders, & Stentoft Arlbjørn, Jan. (2011). Barriers to master data quality. Journal of Enterprise Information Management, 24(3), 288-303. doi: 10.1108/17410391111122862

Iqbal, R., Yuda, P., Aditya, W., Hidayanto, A. N., Handayani, P. Wuri, & Harahap, N. C. (2019). Master Data Management Maturity Assessment: Case Study of XYZ Company. Paper presented at the 2019 2nd International Conference on Applied Information Technology and Innovation (ICAITI).

Ishizuka, Ryo, Washizaki, Hironori, Fukazawa, Yoshiaki, Saito, Shinobu, & Ouji, Saori. (2019). Categorizing and Visualizing Issue Tickets to Better Understand the Features Implemented in Existing Software Systems. Paper presented at the 10th International Workshop on Empirical Software Engineering in Practice (IWESEP).

Karia, J., Sundararajan, M., & Raghavan, G. Srinivasa. (2021). Distributed Ledger Systems to Improve Data Synchronization in Enterprise Processes. Paper presented at the 2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER).

Ko, Chielsin, Adywiratama, Andytias Dwi, & Hidayanto, Achmad Nizar. (2021). Master Data Management Maturity Model (MD3M) Assessment: A Case Study in Secretariat of Presidential Advisory Council. Paper presented at the 9th International Conference on Information and Communication Technology (ICoICT), Information and Communication Technology (ICoICT). Conference retrieved from

Krismawati, D., Ruldeviyani, Y., & Rusli, R. (2019). Master Data Management Maturity Model: A Case Study at Statistics Business Register in Statistics Indonesia. Paper presented at the 2019 International Conference on Information and Communications Technology (ICOIACT).

Loshin, David. (2009). Master data management. Amsterdam ; Boston: Elsevier/Morgan Kaufmann.

Radcliffe, J. (2004). Learn the Four Styles of Customer Data Integration: Gartner.

Rahman, A. Aditya, Dharma, P. Gusman, Fatchur, R. Mohamad, Freedrikson, A. Nala, Ari, B. Pranata, & Ruldeviyani, Y. (2019). Master Data Management Maturity Assessment: A Case Study of A Pasar Rebo Public Hospital. Paper presented at the 2019 International Conference on Advanced Computer Science and information Systems (ICACSIS).

Smith, Heather A., & McKeen, James D. (2008). Developments in Practice XXX: Master Data Management: Salvation Or Snake Oil? Communications of the Association for Information Systems, 23, 63-72. doi: 10.17705/1CAIS.02304

Spruit, Marco, & Pietzka, Katharina. (2015). MD3M: The master data management maturity model. Computers in Human Behavior, 51(Part B), 1068-1076. doi: 10.1016/j.chb.2014.09.030

White, A., Newman, D., Logan, D., & Radcliffe, J. (2006). Mastering Master Data Management: Gartner.

Wilkinson, Leland, & Friendly, Michael. (2009). The History of the Cluster Heat Map. American Statistician, 63(2), 179-184. doi: 10.1198/tas.2009.0033

Vilminko-Heikkinen, R., & Pekkola, S. (2013). Establishing an Organization's Master Data Management Function: A Stepwise Approach. Paper presented at the 2013 46th Hawaii International Conference on System Sciences.

Vilminko-Heikkinen, Riikka, & Pekkola, Samuli. (2017). Master data management and its organizational implementation. Journal of Enterprise Information Management, 30(3), 454-475. doi: 10.1108/JEIM-07-2015-0070

Vilminko-Heikkinen, Riikka, & Pekkola, Samuli. (2019). Changes in roles, responsibilities and ownership in organizing master data management. International Journal of Information Management, 47, 76-87. doi: 10.1016/j.ijinfomgt.2018.12.017

Yang, Fang, Wen, Xueguo, Aziz, Asad, & Luhach, Ashish Kr. (2021). The need for local adaptation of smart infrastructure for sustainable economic management. Environmental Impact Assessment Review, 88. doi: 10.1016/j.eiar.2021.106565

Zúñiga, Daniel Vásquez, Cruz, Romina Kukurelo, Ibañez, Carlos Raymundo, Dominguez, Francisco, & Moguerza, Javier M. (2018). Master Data Management Maturity Model for the Microfinance Sector in Peru. Paper presented at the Proceedings of the 2nd International Conference on Information System and Data Mining.

DOI: http://dx.doi.org/10.4301/S1807-1775202219017

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