JISIB-vol-12_Nr-3(2022).pdf Journal of Intelligence Studies in Business Vol. 12 No. 3 (2022) Open Access: Freely available at: https://ojs.hh.se/ pp. 6–17 Competitive intelligence in an AI world: Practitioners’ thoughts on technological advances and the educational needs of their successors ABSTRACT: Information Age trends have caused the competitive intelligence (CI) industry interested in knowing what knowledge and skills are necessary for future practitioners. In 2022, addressed this topic’s relevancy, noting increases in CI departments 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 evolution (e.g., faster turnarounds, greater client expectations). While tech-savvy skills are disciplines that analyze data for business strategy. KEYWORDS: 1. INTRODUCTION Since the pandemic, the importance of intel- ligence in the corporate world has hit new heights. As misleading information prolifer- ates, so does the need for CI departments to aid companies in effective decision-making (Kolbe and Morrow, 2022). Calof et al.’s (2018) com- parative study discovered a widespread growth of CI over the last two decades with “87% of all responding organizations had some form of formal competitive intelligence structure and many organizations had multiple intel- ligence or intelligence type functions in their organization” (p. 675). A sister discipline to offering CI because “most faculty members do not view the intelligence profession as a dis- university resistance to CI appears to be break- ing down with the recognition of such CI activi- ties as monitoring competitors, benchmarking, and war-gaming (Barrett, 2010). CI skills are evolving due to technolog- ical advances. One of the most impactful is 7 the next years, AI will change learning, teach- ing, and education” (p. 2). Gunderson (2019) notes that “these rapid [technological] changes et al. (2019) asserts on the one hand “it is important to enable practitioners to “understand which skills and capabilities they should develop,” but then notes “there is currently no set framework of CI practitioners” (p. 720). This calls into question skills are necessary for CI prac- - ing needs of the 21st century, this study will research the following questions: environment and subsequently, the educa- tional needs for future practitioners? can educators best prepare future CI analysts? The paper will review CI’s evolution and the discipline. Methodology will cover sur- vey development and distribution followed by pedagogy. 2. LITERATURE REVIEW The origin of CI can be traced to (Porter, 1980). Porter advocated both “competitor monitoring” (p. 96) and “relating a company to its environment” (p. 3). Until the mid-1990s, intelligence was portrayed as a cloak-and-dagger activity (Miller, 2000). By the late 1990’s publications including Street Journal began to endorse intelligence drawing upon practices in the U.S. intelligence - ducing the CI cycle. Before the Information Age, “the scenery of science and technology was quite stable. Large and even small companies knew exactly their marketplace” (Dou et al., 1992, p. 35). Technological developments eliminated sta- bility, prompting the expansion of CI presence and scope. Some changes included the dig- itization of corporate information (Sadok et al., 2019), plummeting cost of data storage the start of the 21st century, 90% of the infor- mation needed by a company to monitor com- petitors and their industry was available 2002). A related development has been the proliferation of software designed to facili- tate and expedite the work of CI practitioners (Semerkova et al., 2017). CI’s evolution has seen the rise of Compe- titive Technical Intelligence (CTI), a branch of CI, used by companies to ensure they have “the best information possible on customer needs, technology options…and the compet- itive environment” (Paap, 2020, p. 41). Paap expanded CI’s traditional scope from Porter’s (1980) competitor focus to include customer needs and . In recent years, CTI has become more useful applying AI, coupled with big data, to reveal insights that were previ- ously unattainable (Porter, 2019). To gain CI knowledge and skills, profes- sionals often draw from trade organizations (e.g., SCIP: Strategic Competitive Intelligence Professionals) and academies. While univer- sities often incorporate business, library sci- resources are necessary, but recent research managing the profession’s demands. Applying the CI cycle as the framework (Dishman and will be discussed as it relates to the needs of Strategic thinking is necessary to do the back- ward planning to conceptualize, and achieve, a desired corporate end state (Wang et al., Kula and Naktiyok (2021) stated, “Strategic a CI perspective, this translates into imagining the future and having vision regarding such factors as the impact of emerging technology, the implications of competitor activities, or the effects of new regulations. Task force approach Collaboration is stage. Paap (2020) described how CI practi- tioners “have expertise on data collection and analysis” and turn to the company’s technical staff for expertise on technical issues (p. 44). Mabe et al. (2019) also stressed the importance of “relationship building (networking) skills in order to foster collaboration” (p. 724) calling them “the most required skills for CI practi- tioners” (p. 726). 8 Finding information. Online informa- tion that is publicly available and accessible on the web (data indexed by search engines) accounts for only four percent of what available in the so-called deep web (Iftikhar, and how to seek information is an increasingly valuable skill. External sources. Business intelligence practitioners access dedicated data warehouses of their company’s internal information to pro- vide diagnostic, prescriptive, and predictive information. CI practitioners acquire external information requiring a different approach because “the range of topics are too broad, and the frequency of looking at any individual area so spread out, that it is not practical to keep the database up-to-date” (Paap, 2020, p. 44). Rather than rely on databases, practitioners have “more reliance on external sources that are kept up to date by the service providers” (Paap, 2020, p. 44). Analysis Analytic skills. While big data may be to achieve maximum value. Saddhon et al. (2019) asserted that, “The keys to the fortu- nate utilization of competitive intelligence are analysis of information and synthesis of knowl- edge” (p. 156). Experienced analysts strive to professionalize analytic work to “get analysts to challenge their arguments and judgments, defend analytical positions and more effec- tively determine between what was fact and what was their opinion” (Walsh, 2017, p. 550). Technology forecasting encompas- ses futu re-oriented techniques developed by the U.S. Department of Defense and The RAND Corporation to assess and predict implications of future technologies (Cho and Daim, 2013). CI practitioners tasked to fore- cast technological developments must build expertise in these techniques (Paap, 2020, p. 49). Papp (2020) explained that a Science & Technology CI practitioner “uses tools to assess shows, and other sources of technical infor- mation to identify the who, where, why, and how fast new technologies are being developed or used” (p. 43). CI data may be structured, unstructured, or semi-structured, with user required to gather, store, and process that data (Gunderson, 2019, p. 9). Porter (2009) described the value of technically analyzing patent information. While, Paap (2020) also advocated it as it “can help you identify who the players are, new developments in a par- ticular technical area” and provide “insights on development trends” (p. 50). CL cucle of skills needed for future analysts. 9 Dissemination Communication is a critical skill throughout the entire CI process. Practitioners must effec- tively communicate with clients to understand and accurately capture information needs successfully communicated in writing and/or poor communication skills as one of the major contributors to a CI project failure. Due to the volume of data, communication through visualization has become an expectation by clients via dashboards and other graphical et al. (2019) used the example of overlaying visual- ization and network-based metrics for compet- itive intelligence analyses. Adaptability. CI “is characterized by nu merous ‘one-off’ intelligence efforts” seeking information from external sources (Paap, 2020, p. 44). A plethora of open-source information is now widely and equally available to all com- panies in any given industry. The companies that are able to rapidly identify, analyze, and turn information into actionable intelligence will likely gain competitive advantage (Gilad its ability to quickly adapt to changing market Practitioners rely on interpersonal skills to validate requirements, function as a team, obtain information from human sources, and deliver conclusions and insights to clients. At the same time, practitioners are expected to technology to perform their craft. These devel- opments prompted researchers to ask CI prac- titioners what they believe are the educational needs of the crop of college students who will ultimately replace them. 3. METHODOLOGY A survey was created based on the CI cycle and respective literature to address: 1) key evolu- tionary trends in CI, 2) needed skills for CI and 3) respective curriculum to prepare future analysts. Several curriculum-based questions were derived from Mercyhurst University’s Business & Competitive Intelligence program (established 2009). According to Kolbe and Morrow (2022) “academic institutions, such as Mercyhurst University, are producing a new generation of private-sector focused intelli- gence professionals” (para 5). Expert discussions from a CI Council webi- nar on the topic of preparing future analysts along with the researchers’ own expertise also - ity, questions were reviewed by CI experts and educators to ensure questions were relevant and meaningful, unambiguous, and easy to answer from the perspective of the participant (Connell, et al., 2018). The survey offered several open- ended questions for additional insights. valid inferences from survey data, respon- population (Malhotra, 2019). To achieve this, the study included members of the CI council, SCIP and Special Librarians Association, CI division. A two percent were part of SCIP, 40% Special Librarians Association and or on CI boards. Using ProQuest©, 721 individuals viewed the survey, 219 responded (30.3% response rate) and 134 were fully completed (18.6%). a growing issue in organizational research and noted “if there are no systematic differ- ences between respondents and non-respond- ents, then the sample remains representa- tive of the population and can provide valid inferences” (p. 4). The researchers deemed the response rate acceptable. Managerial and higher-level positions rep- resented 49% of the respondent pool, while perspectives at a strategic, operational, and experience, the distribution was roughly 1/3 representing the categories: 3 years or less, 4-6 years and 7+ years. Respondents were equally distributed in part-time and full time positions and as sole practitioner. In terms of education, 81% had a bachelor’s or higher degree. Industries represented: • IT (hardware, software, consulting) 22% • Consulting 18% • Construction or building trades 8% • Manufacturing 7% • Other categories < 5% 10 4. RESULTS Both quantitative and qualitative feedback were assessed to address the research ques- tions. The following section presents the cur- rent perspective of CI’s evolution, the CI cycle categories related to necessary skill sets and feedback regarding curriculum development and future skills needed. To fully assess the future of the discipline, how CI has changed over the past decade fol- lowed by an open-ended question to gather respondents rated four factors based on degree of change. Based on the mean values of the Likert scale, the impact of technology rep- resented the most change with client/customer Mean Standard Deviation 1. Impact of technology (N = 130) 3.87 .80 2. Doing more CI tasks in-house (N = 129) 3.52 .85 3. Nature of client taskings (N = 128) 3.52 1.04 4. Client or customer expectations (N = 129) 3.26 .79 Open-ended responses to w provided more insight. Common terms. Key quotes are presented: 1) Technology’s impact • - . • - • - 2) Customer expectations • • 3) Nature of Tasking • - 4) Change in perception of CI • - - ential and become a trusted business 5) In-house CI • • - Planning and the decision maker. (2017) noted that the planning step in the CI process is to ensure that not all possible infor- mation and data is collected, but instead iden- Planning is reliant on two primary conditions: a) an understanding of what CI provides an organization and b) actual decision maker support whether executive, manager or client have argued the need for leadership support in order for the discipline to grow and evolve - ning stage. Common themes (in order of response rate) 1) Building an understanding of what CI is and its value. • - 11 • - - • - 2) Time and technology limitations offer chal- lenges. • - - • - • 3) Executive reliance on own internal resourc- es as a trade-off to CI. • - • - Collecting. A question regarding the col- most commonly used by practitioners. Company website information and third-party sources were most common followed by news was used by only 10% of respondents identi- Analysis commonly includes using method- ologies to evaluate collected data and informa- tion. - age of structured analytic techniques (SAT) they used that were taught in college. There was an even distribution of responses with approximately 1/3 representing the categories of <40%, 41-60%, and >60%. Only 8% noted that they learned more than 80% of SAT in college indicating opportunities to build curric- ulum. Respondents also were to identify what - ket research were most common, while future oriented technology forecasting ranked much lower. Ironically, the top methodologies have been part of the CI discipline for decades. This may indicate an opportunity to build CI curricu- lum incorporating new techniques that address the complexity of evolving technologies. Common sources for research (N = 131). 12 Current CI techniques used N = 130. Structured Analytic Techniques Total % 1. SWOT Analysis 54.6% 2. 46.9% 3. Market research & analysis 45.4% 4. Scenario planning / simulation & modeling 38.5% 5. 36.2% 6. Benchmarking 34.6% 7. 33.8% 8. R&D / technology forecasting 33.1% 9. 31.5% 10. Trade show collection & analysis 29.2% 11. Win / loss 28.5% 12 Counterintelligence 23.8% 13. STEEP/PEST 23.1% 14. Other 9.2% CI Dissemination Methods. Mean SD Frequency* (N=130) 1. CI research reports (ad hoc tasking) 3.75 .97 2. In-depth analysis reports 3.68 .93 3. CI reports to other co. departments 3.53 .97 4. CI newsletter 3.49 1.09 5. (N=129) 3.43 .89 6. Periodic CI reports (monthly, quarterly) 3.42 .90 7. Other 3.26 1.12 8. Online forum (N=129) 3.02 1.06 9 Electronic CI alerts 2.85 1.05 Effectiveness** 1. (N=132) 3.61 1.02 2. 3.60 1.05 3. (130) 3.53 .97 4. Phone (132) 3.52 1.12 5. Company intranet (129) 3.18 1.01 6. Email newsletter- mass (130) 3.18 .90 7. Online forum (129) 3.06 1.12 8. Printed newsletter (130) 2.97 1.03 Dissemination. Two questions addressed the dissemination of CI: 1) most common meth- ods used and 2) effectiveness of methods. Based on frequency of use, project reports scored highest, while more technology based online forums and electronic alerts rated neutral or - nities to build curriculum expanding commu- nication methods to incorporate more technol- ogy-based dissemination. Written reports and personal dissemination were rated as the most effective methods pointing to the importance of interpersonal skills. Mass communication tools like newsletters and forums rated neutral indicating direct dissemination as being more effective. Practitioners were provided skill sets based on the literature and asked to rate how criti- cal these skills were for CI (1 = not critical at strong at 0.826 et al. 2010). One-sample greater than neutral (4.5) identifying them the top three variables as analytical, research and communication representing the key stages of the CI cycle. Curriculum development questions were asked regarding courses and degrees. Courses were rated in terms of professional utility for ranked based on means with top courses being BI/CI, market research, and data analytics being top rated over more traditional subjects. Respondents rated desirability of degrees - ogy (i.e., IT) were rated as more desirable over more traditional degrees. recommendations and suggestions for future See appendix for themes and key quotes. 13 5. DISCUSSION The intent of this research was to address questions pertaining to CI’s evolution with technology in the hopes of guiding educators to better prepare students. One common theme related to curriculum supported the incorpo- ration of more specialized courses relevant to the discipline (i.e., BI/CI, Analytics) and gain- ing experiences prior to graduation. Beyond traditional business curriculum, open-ended feedback stressed liberal arts-based skills as being essential. Ironically, more collection-based courses lower with several comments regarding Critical skill sets for CI (N = 130) and ( = 129). Skills Mean SD t Sig 1. Analytical (N = 129) 8.02 2.01 16.79 2. Communication Skills 7.80 1.67 15.72 3. Research 7.66 1.66 14.85 4. 7.57 1.76 13.36 5. Adaptability 7.55 1.62 14.32 6. IT/Computer 7.36 1.57 13.56 7. 7.28 1.93 10.54 8. Presentation 7.12 1.64 11.26 9. Strategic 7.08 2.01 8.93 (N = 131). Course Mean SD 1. Intelligence Studies (N = 129) 7.61 2.02 2. Business & Competitive Intelligence (130) 7.49 1.82 3. Information technology 6.74 2.33 4. Management 6.60 1.98 5. Library Science (130) 6.36 2.37 6. Math (130) 6.07 2.35 7. Accounting 4.99 2.16 * (N = 130) and ( = 129). Course Mean SD 1. BI/CI course 3.95 1.1 2. Market Research 3.76 .79 3. Data Analytics 3.74 .78 4. Business 3.72 .57 5. Economics 3.64 .82 6. Statistics 3.61 .82 7. Collection (N = 129) 3.60 1.0 8. Computer Programming 3.30 .95 9. Library Science (N = 129) 3.20 .99 10. Accounting 2.95 .79 * 14 as AI had led to unrealistic expectations of data having all the answers and situations of “a world where human analysts have been as a top competency, instructors may want to ensure that research is presented holisti- cally stressing the synergistic value of data thinking and analytical skills. Respondents stressed the need for students to be versed in SATs recommending more ana- lytics focused courses. As noted in the liter- ature, analysts are impacted by AI and navi- gating evolving technologies may require more 2019). Based on the lower ranking of futuristic SATs like technology forecasting, instructors may want to continue to build the curriculum with a focus on more technology-based tech- niques. denoted as essential for a CI analyst’s suc- cess. Popular methods of dissemination were methods may need to incorporate more electronically based dissemination especially for executives (Nohria, 2021). Themes, beyond curriculum, parallel the CI cycle (Dishman and Calof, 2008). Many com- ments reinforced the need of planning and having the research capabilities to know where and how In addressing the evolution of CI, technol- from emerging platforms and big data to some interpersonal skills. With technology, CI professionals reinforced the idea that expecta- tions are growing for more concrete and faster analysis of what it all means (especially AI) is still in pioneering stages. This may be the skills new analysts can to bring to the table. Most in general as more organizations recognize its value (Kolbe and Morrow, 2022). 6. CONCLUSION This study gained valuable insight into the current CI environment, its challenges and its evolution with technological advances. Survey feedback supported the CI cycle regard- ing necessary skills from strategic thinking to research capabilities and analytical compe- tencies. Communication skills were ranked as most valuable in the discipline, while courses future curriculum. Results indicate a shift to more focused degrees in intelligence studies over traditional business degrees. technologies is evolving the discipline, softer skills like communication and analytical skills will never waiver in importance. These should remain a focus in curriculum development, as synergies will ensure not only a tech savvy analyst, but a successful one too. This study serves as a starting point in building curriculum to prepare future CI ana- lysts. Expanded research could build the frame- - cipline with the goal to evolve curriculum for the AI-enabled world. With the growing speed of technology along with rising expectations, this topic will only continue to increase in relevancy. that the submission has not been previously published and has not been submitted to or is not under review by another journal or under consideration for publication elsewhere, and, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright- holder. - The anonymized research data will be made available if required and if the university eth- ics board permits. To the best of our knowledge there is no copyright material in this paper. No funding was received for this study. 15 REFERENCE LIST Barrett, S. E. 2010. Competitive intelli- Calof, J., Arcos, R., and Sewdass, N. 2018. 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