Competitive intelligence in an AI world: Practitioners’ thoughts on technological advances and the educational needs of their successors

Authors

DOI:

https://doi.org/10.37380/jisib.v12i3.893

Keywords:

artificial intelligence, Big Data Analytics, Competitive Intelligence System, pedagogy

Abstract

Information Age trends have caused the competitive intelligence (CI) industry to flourish while changing the way CI is conducted. Universities educating CI analysts are interested in knowing what knowledge and skills are necessary for future practitioners. In 2022, Harvard Business Review addressed this topic’s relevancy, noting increases in CI departments and growing demand for analysts to sift through unconfirmed information. This study addresses the question of what skill sets are needed for future CI analysts and how do instructors prepare them for an evolving and dynamic future in CI? Over 130 CI practitioners were surveyed about recommended skills and curriculum for the next generation. Results confirmed CI’s technology evolution (e.g., faster turnarounds, greater client expectations). While tech-savvy skills are essential, soft skills consistently ranked as top requirements. Findings are applicable to other disciplines that analyze data for business strategy.

Author Biographies

Dr. Shelly Freyn, Alfred University

Shelly Freyn is Assistant Professor of Marketing at Alfred University and a Competitive Intelligence Fellow. She has twenty years in industry experience and has taught marketing and competitive intelligence (CI) for over a decade. She is co-creator of one of the first undergraduate programs in CI. Shelly presents at national and international conferences on competitive intelligence and received the Strategic Competitive Intelligence Professionals Distinguished Member award in academia along with both the Academic Scholar award and Teaching Excellence award at Alfred University. Her research efforts apply CI to improving strategic decision making in both the boardroom and the classroom. 

Dr. Fred Hoffman, Mercyhurst University

Fred Hoffman is an Assistant Professor of Intelligence Studies at Mercyhurst University, Erie, Pennsylvania. He previously served as an Associate Professor of Military Science at The Johns Hopkins University and as Research Director with Cipher Systems LLC, a competitive intelligence firm in Annapolis, Maryland. Fred holds a D.Sc. in Information Systems and Communications from Robert Morris University, an MS in Strategic Intelligence from National Intelligence University, and an MA in Asian Studies (Chinese) from the University of Michigan. He transitioned to academia after a 30-year military and government career as a human intelligence professional, military attaché, and information operations practitioner.  

References

Barrett, S. E. 2010. Competitive intelligence: Significance in higher education. World Future Review, Vol. 4, pp. 26-30.

Calof, J., Arcos, R., and Sewdass, N. 2018. Competitive intelligence practices of European firms. Technology Analysis & Strategic Management, Vol. 30 No. 6, pp. 658-671.

Cho, Y., and Daim, T. 2013. Technology forecasting methods. In Research and Technology Management in the Electricity Industry, Springer, London. pp. 67-112.

Connell, J., Carlton, J., Grundy, A., Buck, E., Keetharuth, A., Rickets, T., Burkham, M., Robotham, D., Rose, D., and Brazier, J. 2018. The importance of content and face validity in instrument development: lessons learnt from service users when developing the Recovering Quality of Life measure (ReQoL). Quality of Life Research, Vol. 27, pp. 1893-1902. https://doi.org/10.1007/s11136-018-1847-y

Dishman, P. and Calof, J. 2008. Competitive intelligence: A multiphasic precedent to marketing strategy. European Journal of Marketing, Vol. 42 No. 7/8, pp. 766-778.

Dou, H., Hassanaly, P., Quoniam, L., and La Tela, A.1993. Technology watch and competitive intelligence: a new challenge in Education for Information. Education for information, Vol. 11 No. 1, pp. 35-45.

Erickson, G. S., and Rothberg, H. 2012. Intelligence in action: Strategically managing knowledge assets. Palgrave Macmillan.

Freyn, S. 2017. Understanding the competitive intelligence process of the firm and the factors that impact its effectiveness. Doctoral dissertation. Anderson University, IN.

Fulton, B. 2016. Organizations and survey research: Implementing response enhancing strategies and conducting nonresponse analyses. Sociological Methods & Research, Vol. 47 No. 2, pp. 1-37. DOI: 10.1177/0049124115626169

Gilad, B., and Fuld, L. M. 2016. Only half of companies actually use the competitive intelligence they collect. Harvard Business Review Digital Articles, pp. 2–4.

Gunderson, S. H. 2019. The rise of a new competitive intelligence: need of real-time competitive intelligence and the impact on decision-making. Doctoral dissertation.

Hair, J., Black, W., Babin, B., and Anderson, R. (2010), Multivariate data analysis. New Jersey: Prentice Hall.

Herring, J. P. 1991. Senior Management Must Champion Business Intelligence Programs. Journal of Business Strategy, Vol. 12 No. 5, p. 48.

Herring, J. P. 1999. Key Intelligence Topics: A Process to Identify and Define Intelligence Needs. Competitive Intelligence Review, Vol. 10, No 2, pp. 4–14.

Hoffman, F. P. 2018. Considerations for successfully investing in commercial intelligence and knowledge management. International Journal of Management, Knowledge and Learning, Vol. 1, pp. 5-18.

Hoffman, F. P., and Freyn, S. L. 2020, July 29. The future of intelligence in an AI-enabled

World. CI Fellows Webinar series: 2020. available at: https://www.cifellows.com/resources/webinars-videos/ci-fellows-webinar-series-2020 (accessed 13 August 2021).

Hoffman, F. P., and Freyn, S. L. 2019. The future of competitive intelligence in an AI-enabled world. International Journal of Value Chain Management, Vol, 10 No. 4, pp. 275-289.

Iftikhar, F., Gull, S., Shoaib, M., Shoaib, S., and Karim, K. 2011. An Ajax powered forms-based approach for crawling the deep web. Pakistan Journal of Science. Vol. 63 No. 3.

Jin, T., and Ju, B. 2014. The corporate information agency: Do competitive intelligence practitioners utilize it? Journal of the Association for Information Science and Technology, Vol. 65 No. 3, pp. 589–608.

Kolbe, P. R., and Morrow, M. R. 4 Jan 2022. How corporate intelligence teams help businesses

manage risk. Harvard Business, available at: https://hbr.org/2022/01/how- corporate-intelligence-teams-help-businesses-manage-risk (accessed 15 May 2022).

Kula, M. E., and Naktiyok, A. 2021. Strategic thinking and competitive intelligence: Comparative research in the automotive and communication industries. Journal of Intelligence Studies in Business, Vol. 11 No. 2, pp. 53-68.

Lackman, C., and Lanasa, J. 2013. Competitive intelligence and forecasting systems: Strategic marketing planning tool for SME’S. Atlantic Marketing Journal, Vol. 2 No. 2, pp. 98-109.

Mabe, K., Sibeko, N., Morake, T., and Nkadimeng, L. 2019, September. Competitive intelligence skills and capabilities required from CI practitioners in South Africa. In European Conference on Knowledge Management, Academic Conferences International Limited, pp. 708-716.

Malhotra, N. 2019. Marketing research: An applied orientation (Seventh ed.). Upper Saddle River, NJ: Pearson/Prentice Hall.

Maungwa, T., and Fourie, I. 2018. Exploring and understanding the causes of competitive intelligence failures: an information behaviour lens. Proceedings of ISIC: The Information Behaviour Conference, Krakow, Poland, 9-11 October 2018: Part 1.

Miller, J. P. (2000), Millennium Intelligence. Understanding and Conducting Competitive Intelligence in the Digital Age. CyberAge Books. Medford, New Jersey, pp. 55-67.

McGonagle, J. J., and Vella, C. M. 2002. A case for competitive intelligence. Information Management, Vol. 36 No. 4, p. 35.

Nohria, N. 2021. How CEOs should manage their time in the hybrid workplace. Harvard Business Digital Articles, pp. 1-8. available at: https://hbr.org/2021/08/how-ceos-should-manage-their-time-in-the-hybrid-workplace (accessed 25, May 2022).

Paap J. 2020. Mapping the Technological Landscape to Accelerate Innovation. Foresight and STI Governance, Vol. 14, No. 3, pp. 41–54. DOI: 10.17323/2500-2597.2020.3.41.54

Porter, A. L. 2019. Data Analytics for Better Informed Technology & Engineering Management. IEEE Engineering Management Review, Vol. 47 No. 3, pp. 29-32.

Porter, A. L. 2009. Tech mining for future-oriented technology analyses. Futures Research Methodology, pp. 1-20.

Porter, M. 1980. Competitive strategy. The Free Press.

Ranjan, J., and Foropon, C. 2021. Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, Vol. 56, p. 102231.

Saddhono, K., Chin, J., Toding, A., Qadri, M. N., and Wekke, I. S. 2019. Competitive intelligence: Systematic collection and analysis of information. Journal of Critical Reviews, Vol. 6 No. 5, pp. 155-159.

Sadok, M., Welch, C., and Bednar, P. 2019. A socio-technical perspective to counter cyber-enabled industrial espionage. Security Journal, pp. 1-16.

Sarica, S., Yan, B., Bulato, G., Jaipurkar, P., and Luo, J. 2019, January. Data-Driven Network Visualization for Innovation and Competitive Intelligence. In Proceedings of the 52nd Hawaii International Conference on System Sciences, pp. 127-136.

Semerkova, L. N., Zaretskiy, A. P., Divnenko, Z. A., Grosheva, E. S., and Vishnevskaya, G. V. 2017.Application of information technologies in competitive intelligence. In 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM) (pp. 804-807). IEEE.

Tuomi, I. 2018. The impact of artificial intelligence on learning, teaching, and education. JRC Science for Policy Report. Luxembourg: Publications Office of the European Union, pp. 1-47.

Walsh, P. F. 2017. Improving strategic intelligence analytical practice through qualitative social research. Intelligence and National Security, Vol. 32 No. 5, pp. 548-562.

Wang, C.J., Hoffman, F.P., Lim, A., and Kwon, J. 2019. From artificial to emotional intelligence: Integrating five types of intelligence to achieve organizational excellence. International Journal of Management, Knowledge and Learning, Vol. 8 No. 2, pp. 125-144.

Zheng, J. G. 2017. Data visualization in business intelligence. In Global Business Intelligence: Routledge, pp. 67-81.

Downloads

Published

2023-03-09

Issue

Vol. 12 No. 3 (2022): Journal of Intelligence Studies in Business

Section

Article

License

Copyright (c) 2022 Journal of Intelligence Studies in Business

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).