Competitive Intelligence in a Data
Driven Environment: The Managerial perspective
Advances in technology do have a direct bearing on
the competitiveness of organizations ranging from business, industry,
government and academia. An ancient discipline like Competitive Intelligence,
which was initiated as the mother of spy craft, state craft and war craft
slowly found its way into the world of commerce and economics. It
differentiated itself from Industrial Espionage and corporate spying by taking
the legal course and valuing individual ethics. However, innovations in Big
data riding on the wave of new discoveries in Artificial Intelligence and its
branch machine learning have taken the degree of Competition between rivals to
an altogether new level. In the present times, our biggest competitor in the
making may not be in our business or even related. FMCG companies have entered
real estate and computer companies have started producing mobile phones.
Artificial Intelligence, Benchmarking, Big Data,
Business Intelligence, Competitive Intelligence, Competitive Advantage, Data
Science, Machine Learning, Reconnaissance, Remote Strategy, Sensing, Surveillance,
On a planet, where there are limited resources and
unlimited wants, the competition for resources is inevitable for survival of
all species, including mankind     Thus, seen is the
rise of theory of the ‘survival of the fittest’ by Darwin. The definition of
being fit had a conditional variance. Initially, for the animal as well as for
the human being, physical capability, in terms of superior speed and strength
had been the mainstay  . However, as evolution took its course
, something far more significant came into being that decided the
winner and the loser of every competition . This phenomenon is
termed as Awareness   .
Being aware, is a state of having acquired
information pertaining to the subject under consideration and its corresponding
surroundings  . When the subject is the sum total of the
resource being competed for plus the competitor  and the
environment encompassing that section of the universe , this is
the process of acquisition of Information pertaining to the surroundings 
Figure 1 CI V/s Spying/espionage
The processing of information acquisition and
analysis is termed as Intelligence .
Also, there certain parameters set, within which, a
competition takes place . These parameters may be imposed by the
environment or mutually agreed by the competing entities or a third party
acceptable to both  . This process of acquisition of
information pertaining to Competition within the established framework of
mutually agreed terms  and conditions within the law of land is
understood as Competitive Intelligence .
Within the human species, Competition exists in
forms of war, politics, sports, academics and business .
However, there are circumstances, wherein mutually agreed terms and values are
surpassed for acquiring information  . Such Intelligence
acquisition process is termed as Espionage or Spying . This
prevails primarily in military and political perspective , and
in the recent times, has found its way into the business and Industry .
from Literature review
an environment with cut-throat competition, mathematics and technology are
pushed to their limits, so as to access and analyze vital information through
techniques such as market research, data-driven Business Intelligence and so on
. While these
tools may give one a bigger picture of present trends and extrapolation based
forecasting, they fail to withstand the onslaught of uncertainty and the
repercussions it can have on an organisation in an unforeseen and unprepared
for situation .
Competitive Intelligence fills this gap by tactical and strategic simulation of
War gaming and Scenario Planning respectively . The inputs for both simulation exercises are derived
from qualitative analysis of Competitive Intelligence from the field . The outcome of this
exercise when supplemented by Data-driven Business Intelligence is a formidable
combination . And
yet, uncertainty remains and will remain forever . This risk mitigation is where the element of Intuition
comes in . And
this Intuitive capability is what distinguishes a Competitive Intelligence
professional from a Market Researcher, a Business Analyst or a Data Miner . He is not a number
cruncher like a conventional manager or information gatherer. Number crunching
and information pursuit is what the computers and the Internet are meant for. He does what these and
conventional managers can’t do. And that is, the quality to see beyond the
Intuition enabling of the Intelligence process is pictorially explained below.
Figure 2 CI in a data driven age
new age CI Professional
capability expected of a true blooded CI Professional is very different from
that of the Conventional Managers of in the corporate world . Unlike the various
managerial styles of Leadership, he assumes a form which immunes and
differentiates him from the susceptibility to shortfalls of the run-of-the-mill
Organizational functioning. Combining the inputs from the ancient wisdom on
strategy, the three key personalities in one state of mind is what a CI
professional may be identified with .
Monk: A Seeker of Truth using Big Data and Analytics
most managers in the organization, the CI professional doesn’t believe in
pleasing the Management by giving them what they would like to hear . Instead, his hardcore
integrity propels him to deliver nothing but the Truth. He relies on pure data
using advanced mining algorithms and analytics which are simple to understand
and present . He
rises much above the organizational issues of internal quarrel and petty
politics and lets his work speak for itself, instead of raising his voice and
marketing him selves like his peers . He is an effective and a gentle communicator with
words of velvet, but arguments of steel. His mind is far more aware and
composed than any other personnel of his organization, for it is that ability
by the virtue of which, he can see and hear, what they can never think of . Its knowledge that he
seeks and yet does not violate the Ethics and legal norms of the environment he
searches it in .
He just lets the management see the truth through simple data sets .
Warrior of Artificial Intelligence: The Fearless one who visualizes data
telling the truth to the management may not suffice. This is where the first
step of a data visualization driven CI manager comes in . For him, every problem is
an opportunity, for it lets him taste victory and success at all costs . The fear of failure and
stress of the corporate life do not affect him in any which way. He is far
above the worry of recession and job security, and his only professional goal
is, success of his project at all costs, under all circumstances, as if failure
was never an option . He innovates through personal experience
and keeps the books of conventional business practice, where they belong i.e.
the Library. He charters the road never taken and creates a path that never
existed . He lets the management see the reality, even if it
needs to be augmented or virtually done. Mere Pi charts and graphs may not be
strong enough so he creates dynamic dashboards to make a deep impact. The
greater the challenge, the sweeter is the overcoming of it . Data
visualization driven by AI, VR and AR make the cut for him.
competes, for it is his inherent nature to live with competition, as if it was
like living for war . He improvises new SWAT (Superior Weapons
And Tactics) and believes in Counter attack than more than defense .
Hunter who uses Machine learning: The Patient one
learning, a subset of the huge universe of Artificial Intelligence Universe,
comes across as the newest weapon in town to take down competition .
A manager acquainted with this technology sure knows how to let his data
crunching and analytics algorithms do the heavy lifting for him .
He has far greater power of observation and concentration than an ordinary
executive who follows the book by the word. In order to accomplish the set
objective, his patience will not waiver, when others would give up on something
. He walks the mile to implement programs that observe and
correct and improve and build upon their experience, or in other words, learn
themselves. His interpretation of his environment is far more accurate than any
of his targets. His mind is free of emotions such as fear, anger, worry and
stress, for this allows him to function at much higher effectiveness than his
colleagues and competitors who budge under pressure and anxiety of the
corporate world, because his ML Algorithm has already taken care of that aspect
. Thus he remains the Hunter, while other Hunters become his
prey. It is but a trait much like the Shinobi who destroys the Samurai for his
arrogance, a human emotion that the true CI professional would not entertain,
for this allows complacency to creep in .
is visible here is, that data driven management has come to the new age,
wherein data alone may not suffice . How fast once can analyse and put it to
good use may matter more. But what will be essential to survive is, being able
to manage uncertainty and put the computing power to some good use .
While Data Science may have made an entry in a big way into the world of
Management decision support, it still needs to be driven by human manager to
make its contribution count . Artificial Intelligence has been
considered as one of the technologies that can bring down both the manpower
cost and count, however when it comes to Competitive Intelligence, HUMIT will
be the cutting edge always  .
(6th Century BC). The art of war. e-artnow.
(3rd Century BC). Arthashastra.
M. (1645). The book of five rings. Shambhala Publications.
D. (2002). Saladin: Noble Prince of Islam. HarperCollins
Clausewitz, C. (1832). On war. Digireads. com Publishing.
R. (2000). The 48 laws of
R. (2007). The 33 strategies
of war. Profile Books.
L. K. (Ed.). (2010). The Oxford handbook of national security
intelligence. Oxford University Press, USA.
J. D. (2013). Competitive Intelligence for Dummies. John Wiley
10. Heuer, R. J. (1999). Psychology of
intelligence analysis. CIA Publishing
11. Kahaner, L. (1997). Competitive intelligence: how to
gather analyze and use information to move your business to the top. Simon
12. Waters, T. J. Hyperformance: using
competitive intelligence for better strategy and execution. John Wiley
& Sons, 2010.
13. Oriesek, M. D. F., & Schwarz, M. J. O.
(2012). Business wargaming:
securing corporate value. Gower Publishing, Ltd
14. Bernhardt, D. C. (1994). ‘I want it fast,
factual, actionable’—tailoring competitive intelligence to executives’ needs. Long Range Planning, 27(1), 12-24.
15. Kahane, A., & Van Der Heijden, K. (2012). Transformative scenario planning:
Working together to change the future. Berrett-Koehler Publishers.
16. Prescott, J. F., & Miller, S. H. (Eds.).
(2002). Proven strategies in
competitive intelligence: lessons from the trenches. John Wiley & Sons.
17. Sutton, H. (1988, June). Competitive
intelligence. Conference Board.
18. Rouach, D., & Santi, P. (2001). Competitive
Intelligence Adds Value:: Five Intelligence Attitudes. European Management Journal, 19(5), 552-559.
19. Teo, T. S., & Choo, W. Y. (2001). Assessing
the impact of using the Internet for competitive intelligence. Information & management, 39(1), 67-83.
20. Prescott, J. E. (1995). The evolution of
competitive intelligence. International
Review of Strategic Management, 6,
21. Chen, H., Chau, M., & Zeng, D. (2002). CI
Spider: a tool for competitive intelligence on the Web. Decision Support Systems, 34(1), 1-17.
22. Zanasi, A. (1998). Competitive intelligence
through data mining public sources.Competitive Intelligence Review, 9(1), 44-54.
23. Bose, R. (2008). Competitive intelligence
process and tools for intelligence analysis. Industrial
Management & Data Systems, 108(4),
24. Vedder, R. G., Vanecek, M. T., Guynes, C. S.,
& Cappel, J. J. (1999). CEO and CIO perspectives on competitive
of the ACM, 42(8),
25. Gilad, B. (2003). Early warning: using competitive
intelligence to anticipate market shifts, control risk, and create powerful
strategies. AMACOM Div American Mgmt Assn.
26. Fleisher, C. S., & Blenkhorn, D. L. (2001). Managing frontiers in competitive
intelligence. Greenwood Publishing Group.
27. Fleisher, C. S., & Bensoussan, B. E.
(2003). Strategic and competitive
analysis: methods and techniques for analyzing business competition (p. 457). Upper Saddle River, NJ:
28. Ettorre, B. (1995). Managing competitive
29. Wright, S., & Calof, J. L. (2006). The quest
for competitive, business and marketing intelligence: A country comparison of
current practices. European
Journal of Marketing, 40(5/6),
30. Wright, S., Pickton, D. W., & Callow, J.
(2002). Competitive intelligence in UK firms: a typology. Marketing Intelligence &
31. Calof, J. L., & Wright, S. (2008).
Competitive intelligence: a practitioner, academic and inter-disciplinary
perspective. European Journal
of Marketing,42(7/8), 717-730.
32. Groom, J. R., & David, F. R. (2001). Competitive
intelligence activity among small firms. SAM
Advanced Management Journal, 66(1),
33. Dishman, P. L., & Calof, J. L. (2008).
Competitive intelligence: a multiphasic precedent to marketing strategy. European Journal of Marketing, 42(7/8), 766-785.
34. Xu, K., Liao, S. S., Li, J., & Song, Y.
(2011). Mining comparative opinions from customer reviews for Competitive
Intelligence. Decision support
35. Cronin, B., Overfelt, K., Fouchereaux, K.,
Manzvanzvike, T., Cha, M., & Sona, E. (1994). The Internet and competitive
intelligence: a survey of current practice. International
journal of information management, 14(3),
36. Yufeng, Q. J. D. (2000). On Knowledge
Management and Competitive Intelligence [J]. Library
and Information Service, 4,
37. Bergeron, P., & Hiller, C. A. (2002).
Competitive intelligence. Annual
review of information science and technology, 36(1), 353-390.
38. Du Toit, A. S. A. (2003). Competitive
intelligence in the knowledge economy: what is in it for South African manufacturing
Journal of Information Management, 23(2),
39. Miller, S. H. (2001). Competitive
Intelligence–an overview. Competitive
Intelligence Magazine, 1(11).
40. Liebowitz, J. (2006). Strategic intelligence: business
intelligence, competitive intelligence, and knowledge management. CRC
41. Jaworski, B. J., Macinnis, D. J., & Kohli,
A. K. (2002). Generating competitive intelligence in organizations. Journal of Market-Focused
42. Babbar, S., & Rai, A. (1993). Competitive
intelligence for international business. Long
Range Planning, 26(3),
43. McGonagle, J. J., & Vella, C. M. (2002). A
case for competitive intelligence.Information Management, 36(4), 35.
44. Norling, P. M., Herring, J. P., Rosenkrans, W.
A., Stellpflug, M., & Kaufman, S. B. (2000). Putting competitive technology
intelligence to work. Research-Technology
45. Fleisher, C. S. (2004). Competitive
intelligence education: competencies, sources, and trends. Information Management, 38(2), 56.
46. Shih, M. J., Liu, D. R., & Hsu, M. L.
(2010). Discovering competitive intelligence by mining changes in patent
trends. Expert Systems with
47. Cleland, D. I., & King, W. R. (1975).
Competitive business intelligence systems. Business
48. Fleisher, C. S., & Blenkhorn, D. L. (2003). Controversies in competitive
intelligence: The enduring issues. Greenwood Publishing Group.
49. Fleisher, C. S. (2001). An introduction to the
management and practice of competitive intelligence (CI). Managing frontiers in competitive
50. Prescott, J. E. (2001). Competitive
intelligence: lessons from the trenches.Competitive intelligence review, 12(2), 5-19.
51. Davison, L. (2001). Measuring competitive intelligence
effectiveness: insights from the advertising industry. Competitive Intelligence Review, 12(4), 25-38.
52. Gibbons, P. T., & Prescott, J. E. (1996).
Parallel competitive intelligence processes in organisations. International Journal of Technology
53. Lackman, C. L., Saban, K., & Lanasa, J. M.
(2002). Organizing the competitive intelligence function: a benchmarking study. Proven Strategies in Competitive
Intelligence: Lessons from the Trenches, 11(1),
54. Saayman, A., Pienaar, J., De Pelsmacker, P.,
Viviers, W., Cuyvers, L., Muller, M. L., & Jegers, M. (2008, July).
Competitive intelligence: construct exploration, validation and equivalence. In Aslib Proceedings (Vol. 60, No. 4, pp. 383-411). Emerald
Group Publishing Limited.
55. Prescott, J. E., & Bhardwaj, G. (1995).
Competitive intelligence practices: a survey. Competitive
Intelligence Review, 6(2),
56. Myburgh, S. (2004). Competitive intelligence:
bridging organizational boundaries. Information
Management, 38(2), 46.
57. Denise Lemos, Â., & Carlos Porto, A.
(1998). Technological forecasting techniques and competitive intelligence:
tools for improving the innovation process. Industrial
Management & Data Systems, 98(7),
58. Tarraf, P., & Molz, R. (2006). Competitive
intelligence at small enterprises.SAM Advanced Management Journal, 71(4), 24.
59. Viviers, W., Saayman, A., & Muller, M. L.
(2005). Enhancing a competitive intelligence culture in South Africa. International Journal of Social
60. Blenkhorn, D. L. (2005). Competitive intelligence and global
business. Greenwood Publishing Group.
61. Marin, J., & Poulter, A. (2004).
Dissemination of competitive intelligence.Journal of information science, 30(2), 165-180.
62. Desouza, K. C. (2001). Intelligent agents for
competitive intelligence: survey of applications. Competitive Intelligence Review, 12(4), 57-63.
63. Crane, A. (2005). In the company of spies: When
competitive intelligence gathering becomes industrial espionage. Business Horizons, 48(3), 233-240.