Towards Managerial Support for Data Analytics Results

Uroš Bole; Gregor Papa

doi:10.13052/jiems2446-1822.2020.001

Uroš Bole Glarminy.com, Slovenia
Gregor Papa Jožef Stefan Institute, Ljubljana, Slovenia

DOI: https://doi.org/10.13052/jiems2446-1822.2020.001

Keywords: Data, analytics, data mining, collaboration, support, stakeholder

Abstract

Studies of analytics integration management have largely focused on executive-led analytics at the enterprise level. However, in most organizations analytics initiatives do not enjoy executive support at the outset. Top management must first be convinced of the benefits, which slows down the path to competing via analytics. To successfully win top management support for broader analytics implementation an analytics pioneer should achieve five key aims: patiently build trust, manage interdisciplinary collaboration, focus on the problem solving action, facilitate the process, and importantly provide strong support to the embryonic analytics initiative. This is demonstrated through multiple-case study, presented in this paper. In embryonic analytics initiatives, the analytics champion appears locally, at mid-management level, and is up against the complex task of overcoming the resistance of an established organization, with its existing people, processes, data, technology, and culture. We examined what could be learned about the management of people-related issues in embryonic analytics processes. We studied the approaches used and lessons learned by all significant groups of stakeholders with the aim of helping managers show the value of analytics to their executives and colleagues.

Author Biographies

Uroš Bole, Glarminy.com, Slovenia

Uroš Bole, obtained his B.Sc. in Applied Mathematics and Economics from Brown University (1996), MBA from IESE Business School (2000) and a Ph.D. from Jožef Stefan International Postgraduate School (2013). His Ph.D. research revolved around the integration of data mining in organizations. His research interests span interdisciplinary collaboration, systemic thinking, business process reengineering,organizational learning, and process consultation. He is aco-founder of a startup providing data mining and stochastic optimization solutions, and an owner of Glarminy.com, a platform for exchange of ideas.

Gregor Papa, Jožef Stefan Institute, Ljubljana, Slovenia

Gregor Papa, is a senior researcher at the Jožef Stefan Institute, Ljubljana, Slovenia and an Associate Professor of Computer Science at the Jožef Stefan International Postgraduate School, Ljubljana, Slovenia. He holds B.S. (1997), M.Sc. (2000) and Ph.D. (2002) degrees from the Faculty of Electrical Engineering, University of Ljubljana. His current research interests include optimization techniques, metaheuristic algorithms, and hardware implementations of high-complexity algorithms. His work is published in several international journals and conference proceedings.

References

Kiron, D., and R. Shockley.2011.Creating Business Value with Analytics. MIT Sloan Management Review, vol. 53, no. 1:56–63.

Gartner. 2017.Gartner Identifies the Top 10 Strategic Technology Trends for 2018, https://www.gartner.com/en/newsroom/press-releases/2017-10-04-gartner-identifies-the-top-10-strategic-technology-trends-for-2018.

Luftman, J. and T. Ben-Zvi. 2010. Key Issues for IT Executives 2010. MIS Quarterly Executive, vol. 9, no. 4: 263–273.

LaValle, S., E. Lesser, R. Shockley, M.S. Hopkins and N. Kruschwitz.2011.Big Data, Analytics and the Path From Insigths to Value. MIT Sloan Management Review, vol. 52, no. 2: 21–32.

Rexer, K., 2011. 4th Annual Data Miner Survey – 2010 Survey Summary Report, https://www.rexeranalytics.com/Data-Miner-Survey-Results-2010.html.

Rexer, K.,2012. textit5th Annual Data Miner Survey – 2011 Survey Summary Report, https://www.rexeranalytics.com/Data-Miner-Survey-Results-2011.html.

Davenport, T.H., and J.G. Harris. 2007. Competing on Analytics: The New Science of Winning, HBS Press.

Davenport, T.H., J.G. Harris, and R. Morison, 2010, Analytics at Work: Smarter Decisions, Better Results, HBS Press.

Bole, U., A. Popoviè, J. Žabkar, G. Papa, and J. Jakliè. 2015. A case analysis of embryonic data mining success. International Journal of Information Management, vol. 35: 253–259.

Bole, U., 2013. Transcripts of semi-structured interviews with data mining practitioners. JSI Technical report, no. 11355, Ljubljana.

Senge, P.M., 2006. The Fifth Discipline: The Art and Practice of the Learning Organization, Doubleday.

Beers, P.J., H.P.A. (Els)Boshuizen, P.A. Kirschner and W.H. Gijselaers. 2005. Computer Support for Knowledge Construction in Collaborative Learning Environments. Computers in Human Behavior, vol. 21, no. 4: 623–643.

Du Chatenier, E., J.A.A.M. Verstegen, H.J.A. Biemans, M. Mulder and O. Omta. 2009. The Challenges of Collaborative Knowledge Creation in Open Innovation Teams. Human Resource Development Review, vol. 8, no. 3: 350–381.

Lichtenstein, S., D. Bendall, and S. Adam. 2008. Marketing Research and Customer Analytics: Interfunctional Knowledge Integration.International Journal of Technology Marketing, vol. 3, no. 1:81–96.

Markus, M.L., A. Majchrzak, and L. Gasser. 2002. A Design Theory for Systems That Support Emergent Knowledge Processes. MIS Quarterly, vol. 26, no. 3:179–212.

Holland, S., K. Gaston, and J. Gomes. 2000. Critical Success Factors for Cross-functional Teamwork in New Product Development. International Journal of Management Reviews, vol. 2, no. 3: 231–259.

Isaacs, W.N., 1993. Taking Flight: Dialogue, Collective Thinking, and Organizational Learning. Organizational Dynamics, no. Winter (1993):24–39;

Bohm, D., 2006. On Dialogue. Routledge.

Senge, P.M., 2006. The Fifth Discipline: The Art and Practice of the Learning Organization, Doubleday.

Hermiz, K., 1999. Critical Success Factors for Data Mining Projects. Information Management Magazine, http://www.information-management.com/issues/19990201/164-1.html.

King, E.A., and T.A. Rathburn. 2010. 101 Ways to Sabotage Your Predictive Analytics Project, Here Are the Top Five. BeyeNETWORK, http://www.b-eye-network.com/view/13685.

Viaene, S., and A. Van Den Bunder. 2011. The Secrets to Managing Business Analytics Projects. MIT Sloan Management Review, vol. 53, no. 1:64–70.

Highsmith, J., 2009. Agile Project Management: Creating Innovative Products, Addison-Wesley.

Gemino, A., B. Horner Reich, and C. Sauer. 2008. A Temporal Model of Information Technology Project Performance, Journal of Management Information Systems, vol. 24, no. 3: 9–44.

Howel, D., C. Windahl, and R. Seidel. 2010. A Project Contingency Framework Based on Uncertaingy and Its Consequences, International Journal of Project Management, vol. 28, no. 3: 256–264.