The advanced analytics Jumpstart: definition, process model, best practices

Jeremy Rose, Mikael Berndtsson, Gunnar Mathiason, Peter Larsson


Companies are encouraged by the big data trend to experiment with advanced analytics and many turn to specialist consultancies to help them get started where they lack the necessary competences. We investigate the program of one such consultancy, Advectas - in particular the advanced analytics Jumpstart. Using qualitative techniques we investigate the nature and value of the Jumpstart concept through five projects in different companies. We provide a definition, a process model and a set of thirteen best practices derived from these experiences, and discuss the distinctive qualities of this approach.


advanced analytics; big data; case study; best practice

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Barton, D., & Court, D. (2012). Making Advanced Analytics Work For You. Harvard Business Review, 90(10), 78-83.

Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The Case Research Strategy in Studies of Information Systems. MIS Quarterly, 11(3), 369-386.

Berelson, B. (1952). Content Analysis In Communicative Research. New York: Free Press.

Brown, B., & Gottlieb, J. (2016). The need to lead in data and analytics. Retrieved from McKinsey & Company:

Carroll, J. M., & Swatman, P. A. (2000). Structured-case: a methodological framework for building theory in information systems research. European Journal of Information Systems, 9(4), 235-242.

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.

Davenport, T. H. (2013). Analytics 3.0. Harvard Business Review(December).

Davenport, T. H., Harris, J. G., & Morison, R. (2010). Build an analytical culture Analytics at Work: Smarter Decisions, Better Results: Harvard Business Press.

Davenport, T. H., & Patil, D. J. (2012). Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review, 90(10), 70-76.

Eisenhardt, K. M., & Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Academy of management journal, 50(1), 25-32.

Franks, B. (2012). To Succeed with Big Data, Start Small. Harvard Business Review Digital Article.

Groves, P., Kayyali, B., Knott, D., & Van Kuiken, S. (2013). The ‘big data’ revolution in healthcare. Retrieved from McKinsey Quarterly:

He, W., Zha, S., & Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33(3), 464-472.

Henke, N., Bughin, J., & Chui, M. (2016). Most Industries Are Nowhere Close to Realizing the Potential of Analytics. Harvard Business Review Web Article.

Krippendorff, K. (2004). Content Analysis Thousand Oaks: Sage.

Kumar, V. D., & Alencar, P. (2016). Software engineering for big data projects: Domains, methodologies and gaps. Paper presented at the 2016 IEEE International Conference on Big Data (Big Data).

Lahrmann, G., Marx, F., Winter, R., & Wortmann, F. (2011). Business intelligence maturity: Development and evaluation of a theoretical model. Paper presented at the Proceedings of the 44th Hawaii International Conference on System Sciences.

Larson, D., & Chang, V. (2016). A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management, 36(5), 700-710. doi:

LaValle, S., Hopkins, M. S., Lesser, E., Shockley, R., & Kruschwitz, N. (2010). Analytics: The New Path to Value. Retrieved from MIT Sloan Management Review:

LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big Data, Analytics and the Path From Insights to Value. MIT Sloan Management Review, 52(2), 21-32.

Marchand, D. A., & Peppard, J. (2013). Why IT Fumbles Analytics. Harvard Business Review, 91(1-2), 104-112.

Mazzei, C., McShea, C., & Oakley, D. (2016). How CEOs Can Keep Their Analytics Programs from Being a Waste of Time. Harvard Business Review Web Article.

Miele, S., & Shockley, R. (2013). Analytics: The real-world use of big data. Retrieved from IBM Institute for Business Value, Said Business School:

Ohlsson, F. (2017). Building a global culture of analytics. Beslutsstödsdagen 2017, Stockholm.

Rose, J., & Lennerholt, C. (2017). Low Cost Text Mining as a Strategy For Qualitative Research. Electronic Journal of Business Research Methods, 15(1), 2-16. doi:

Saltz, J. S. (2015). The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness. Paper presented at the 2015 IEEE International Conference on Big Data (Big Data).

Shah, S., Horne, A., & Capellá, J. (2012). Good data won't guarantee good decisions. Harvard business review, 90(4).

Turban, E., Sharda, R., Delen, D., Aronson, J. E., Lian, T.-P., & King, D. (2015). Business intelligence and analytics : systems for decision support. Harlow, Essex: Pearson Education.

Watson, H. J. (2016). Creating a Fact-Based Decision-Making Culture. Business Intelligence Journal, 21(2), 5-9.

Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626-639.

Wilkinson, S. (1997). Focus group research. In D. Silverman (Ed.), Qualitative Research: Theory, Method and Practice (pp. 177-199). London: Sage.

Wirth, R., & Hipp, J. (2000). CRISP-DM: Towards a standard process model for data mining. Paper presented at the Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining.

Wixon, B. H., Yen, B., & Relic, M. (2013). Maximizing Value from Business Analytics. MIS Executive Quarterly, 12(2), 111-123.

Yin, R. K. (2013). Case study research: Design and methods (4th ed.). Thousand Oaks, California: Sage Publications.


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