Analysis of McKinsey & Company’s Digital Assessment for Hiring



Transformative advances in technology, such as the emergence of the “Internet of Things” (IoT) and Artificial Intelligence, are driving organizations to operate at a high rate of change in order to remain competitive.[1]  The continuously changing workplace dynamics in the “Big Data” era are driving employers to reexamine the “types” of skills individuals need to thrive in a rapidly evolving and dynamic environment.[2]  Arguably, these 21st challenges have led many organizations to embrace a business model centered on innovation.  This need to continually innovate presents a new set of challenges for leaders attempting to overcome barriers to change and overall organizational resistance.[3]  Perhaps resistance to change, or the inclination to ‘come from a place of no,’ stems from a lack of intellectual curiosity, problem-solving skills, and creativity needed to ‘get to yes’—in other words, to generate radical and innovative solutions to complex problems.

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This dilemma begs the question of whether the modern-day workforce has the right set of skills to continually adapt—and, if not, this then implies that the skills gap of the future workforce will certainly present a bigger predicament.  According to McKinsey & Company, sixty-two percent of executives foresee having to replace or retrain “more than a quarter of their workforce between now and 2023.”[4]  A 2015 “CEO Challenge” survey op top executives identified “human capital” and “innovation” as the top two long-term challenges of their organizations.[5]  Yet, we often focus the majority of our effort on transformation of the current workforce, and we place ancillary attention on the future workforce.  This paper examines the utility of McKinsey & Company’s “digital assessment gaming tool” as a method to selectively hire based on cognitive skills-sets and argues for the Intelligence Community’s adoption of digital assessments for selective hiring of innovative competencies (i.e., creativity, enterprising, integrating perspectives, forecasting, and managing change).[6]


McKinsey & Company, a world-renowned global management consulting firm, recently adopted a digital assessment tool as part of their hiring process.  The digital assessment was developed as a means for companies to assess “hard-to-measure” skillsets required to flourish in a modern-day work environment that is becoming increasingly more automated.  The developers, in coordination with a team of psychologists, developed a tool that accurately measures complex human cognitive abilities; such as, problem-solving, creativity, and critical thinking.[7]

Applicants interested in working for McKinsey are now required to take a “digital gamified assessment” designed to test an individual’s decision-making processes on seemingly abstract and ambiguous problem-sets (e.g., determining why animals in the wilderness have developed an unknown illness).[8]  It is important to denote that the intent of the assessment tool is to measure how an individual thinks about complex problems and is not singularly centered on the particular outcomes generated by the actions taken throughout the scenario.  Recruiters can thus examine the information the individual accessed to make their decision, providing further insight into one’s problem-solving capabilities.  The ability of a candidate to provide unorthodox and creative solutions to a given problem will likely elevate an individual’s prospects of securing a follow-on interview with the company.

The digital assessment tool measures five cognitive skills: (1) data-driven decision-making, (2) ability to make decisions under time pressure and with imperfect information, (3) aptitude in testing hypotheses and developing strategies, (4) overall situational awareness, and (5) understanding of multi-faceted issues and associated causes-and-effects.  The immersive simulation-based assessment essentially provides a “cognitive profile” of one’s metacognition, decision-making skills, and situational awareness.[9]

A supplementary, but extremely important benefit of the test is that it also helps to mitigate inherent unconscious or conscious biases that recruiters or hiring authorities might have (e.g., biases based on gender, age, similarities/likeness, appearances, education, etc.).  This bias moderation strategy is advertised by McKinsey & Company Recruiting on their website, where they claim that the tool will allow you to “think and approach problems regardless of your background.”[10]  Since McKinsey is a reputable and desirable place to work, recruiters may exploit the hyper competitiveness and only choose to screen for candidates that have attended Ivy League schools, whether subconsciously or knowingly.

Thus, the new digital assessment tool provides an avenue for applicants, regardless of alma mater, to be competitive.  In essence, this creates a more level playing field.  Previous hiring methods might have completely eliminated a qualified individual before they were ever given the opportunity to come in for an interview.  Lastly, the assessment serves as an appealing alternative for individuals who do not perform as well on standardized tests, but clearly possess superior cognitive skills needed to thrive in the modern-day workplace.  Additionally, the unique gaming design potentially appeals to younger generations who have grown up in the digital age.[11]  The next section of this paper will discuss why innovative competencies are critical proficiencies for IC analysts and leaders.


What “types” of skillsets do intelligence analysts need in today’s workplace and the workplace of the future?  Data-driven analysis requires analysts to parse out the “signal” from the “noise” and make accurate probabilistic estimates, even during times of high uncertainty and with imperfect data.  Technological advances have significantly widened the aperture for data that can be collected and analyzed in real-time.  In turn, this has increased the demand for analysts to be able to synthesize and make sense of data from multiple sensors and across multiple domains. An anecdotal examination of characteristics exhibited by reputable and renowned strategic warning analysts suggests there are certain personality traits that increase one’s propensity to make reliable forecasting and probabilistic assessments.  Namely, the key traits of successful analysts included: intellectual curiosity, creativity, retentive memory, aptitude for research, and ability to recognize what is important (i.e., identify the signal from the noise).[12]

A separate two-year study aimed at improving forecasting and prediction in the IC revealed similar traits for individuals who succeeded in making accurate and predictive assessments.  The study included a sample size of 743 participants across 199 events.  There was a higher rate of success for those with cognitive ability, knowledge, and open-mindedness.  Additionally, collaboration coupled with more frequent belief updating were key factors in accurate forecasting.  The analysts were able to cognitive biases and pitfalls by challenging their previously held beliefs each time they were presented with new information.  Their creative thinking allowed them to adopt non-conventional predictions, thus increasing their success rate.

The necessity of taking an unorthodox approach was further emphasized by former National Intelligence Officer for Warning Mary McCarthy, who cited the importance of imagination, diversity of outlook, and ability to tolerate the absurd as essential factors in the ‘art and science’ of assessing threats.[13]  Thus, the innovative competencies are not only desirable skills for driving innovation in the workplace; but, they also lend a hand to one’s ability to appropriately synthesize complex and ambiguous information to make predictive assessments.

The desirability of these traits in the IC will increase ten-fold with the advent of Artificial Intelligence in intelligence processes.  An analyst’s ability to synthesize information will be in greater demand, particularly as the fundamentals of future warfare change drastically (i.e., speed of data and decision-making).  In 2015, Deputy Secretary of Defense Robert Work outlined the integration of AI as the Department of Defense’s (DoD) Third Offset strategy, the next revolution in military affairs to maintain competitive advantage against adversaries.[14]  Retired Marine Corps four-star general John Allen coined the term  “hyperwar” to characterize this future AI-enabled accelerated decision-action cycle.[15]  The implications of future warfare bring to bear the criticality of decision advantage in an information saturated environment.  Decision advantage ultimately hinges on the ability of intelligence analysts to provide timely and accurate warning of discontinuities (anticipatory intelligence).  These emerging trends demand a relook at the criteria in which the IC determines the qualifications of an individual for hiring purposes.  There is sufficient evidence to suggest that innovative competencies serve as a solid foundation for becoming a first-rate analyst and for being an innovative leader.

A study by XBInsight examined competency data across 5,000 industry leaders to identify traits of innovative leaders. They found that innovative leaders succeed in being able to manage risk, demonstrate curiosity, lead courageously, seize opportunities, maintain strategic business perspective, and maintain order and accuracy.[16]  Thus, there is a case to be made that innovative competencies are essential for both analysts and leaders and for creating a coalition of willing when it comes to innovation in the workplace.  The IC should place greater importance on hiring criteria beyond just education and experience.  Targeted recruiting will generate a cadre of collaborators and thinkers that can anticipate dilemmas and find unorthodox solutions to solve complex problems; and, also bring in talented leaders who are able to think critically about how to transform and inculcate an innovative culture.

Selective hiring practices, or cultural embedding, allow leaders to incrementally transform an organization[17] and “shape innovation” through workforce composition.[18]  By fostering a creative workforce through selective hiring, employers are better postured to quickly adapt to emerging trends and unanticipated requirements.  Ultimately, enabling organizations to be more competitive while ensuring their viability in a rapidly changing global environment.  Google for instance, hired voice recognition engineers with a unique set of skill sets without having an initial plan on what to do with them.  The team, however, drove substantial advances in machine algorithm software and were ahead of the power curve in quickly responding to consumer needs for speech recognition software.[19]  In this sense, Google remained competitive by adopting a blue ocean strategy (i.e., uncontested market space)[20] through selective hiring and talent management of specific skillsets. Selective hiring will bring members into the IC who have already demonstrated a propensity to identify problems, collect and analyze data, and make decisions under time pressure and with imperfect information.


The argument against including diagnostic hiring based on cognitive skills is that non-cognitive (i.e., emotional intelligence) skills are equally, if not more important, than cognitive skills.  Successful innovation requires a workforce to have diversity in thought, experience, and in skillsets across a “range of innovation processes.” [21] The composition of a truly successful workforce is certainly not one comprised only of creative thinkers.  Emotional intelligence, arguably is at the forefront of leadership studies and can serve as a fairly good predictor of someone’s ability to foster collaboration and teamwork—vital skills needed for leading change.  While this paper argues for hiring practices focused on cognitive skills, this is not to suggest that digital assessments should completely replace the already existing hiring processes.  Hiring authorities should utilize the digital assessment as a complementary tool to identify qualifiers outside of education and experience alone.  Innovative competencies, or “power skills” (e.g., creativity, critical thinking, and emotional intelligence) can only be determined by leveraging a varied array of hiring methods (e.g., face-to-face interviews).[22]


The IC’s adoption of a digital assessment tool focused on testing one’s innovative competencies will provide a mechanism for recruiting officers and hiring authorities to selectively hire based on skillsets that cannot be determined solely by examining an individual’s education and experience listed on professional resume.  While interviews may provide greater clarity on an individual’s observable or non-verbal traits, inherent biases may result in authorities overlooking qualified candidates. Additionally, interviews—while useful—do not allow organizations to carefully and methodologically examine an individual’s decision-making processes for insight into their overall problem-solving skills.

A screening battery that tests for innovative thinking can help alleviate the administrative burden of combing through hundreds of resumes that ‘fit the USA jobs criteria’ based on key words listed in the application.  Thus, having a digital assessment tool that serves as a screening mechanism will allow employers to more readily identify individuals for interviews.  The increased diversity of criteria fosters parity in ensuring greater diversity of thought and experience in the workplace—balancing cognitive and non-cognitive skills). In the end, an individual who is unable to think outside the box and “get to yes” won’t be able to keep up with the pace of 21st century workplace demands.


  • Denning, Stephanie. “The New Hiring Practices at McKinsey and Goldman Sachs.” Forbes. Last modified April 27, 2019. //
  • Gentry John, and Joseph Gordon. Strategic Warning Intelligence: History, Challenges, and Prospects. Washington, DC: Georgetown University Press, 2019.
  • Graham-Leviss, Katherine. “The 5 Skills that Innovative Leaders Have in Common.” Harvard Business Review. Last modified December 20, 2016.// December 20, 2016.
  • Husain, Amir. The Sentient Machine: The Coming of Age of Artificial Intelligence. New York, NY: Scribner, 2017.
  • Hunter Samuel T., and Lily Cushenbery, “Leading for Innovation: Direct and Indirect Influences.” Advances in Developing Human Resources 13 (December 2011): 248-265.
  • “Innovation Competency Model” Innovation in Practice. Last modified September 18, 2011. //
  • Kantar, Rebecca, Keith McNulty, Erica L. Snow, Matthew A. Emergy, Richard Wainess, and Sonia D. Doshi, “Constructive Cognitive Profiles for Simulation-Based Hiring Assessments.” Accessed October 20, 2019. //
  • Kim, W. Chan, and Renee Mauborgne, “Blue Ocean Strategy.” Harvard Business Review (October 2004): 70-80.
  • Kotter James P., and Leonard A. Schlesinger. “Choosing Strategies for Change.” Harvard Business Review On Point (Winter 2014): 38-47.
  • Kotter, John P. Leading Change. Boston, MA: Harvard Business Review Press, 2012.
  • “McKinsey’s Digital Assessment,” McKinsey & Company. Last accessed October 20, 2019. //
  • Palmer, Kelly. “Closing America’s Skills Gap.” Barron’s Online (May 2019). //
  • Schein, Edgar H. Organizational Culture and Leadership 4th ed. San Francisco, CA: John Wiley & Sons, 2010.

[1] John P. Kotter, Leading Change (Boston, MA: Harvard Business Review Press, 2012), 169-171.

[2] Kelly Palmer, “Closing America’s Skills Gap,” Barron’s Online (May 2019), //

[3] James P. Kotter and Leonard A. Schlesinger, “Choosing Strategies for Change,” Harvard Business Review On Point (Winter 2014): 38-47.

[4] Kelly Palmer, “Closing America’s Skills Gap,” Barron’s Online (May 2019), //

[5] Katherine Graham-Leviss, “The 5 Skills that Innovative Leaders Have in Common,” Harvard Business Review, last modified December 20, 2016,// December 20, 2016.

[6] “Innovation Competency Model” Innovation in Practice, last modified September 18, 2011, //

[7] Rebecca Kantar, Keith McNulty, Erica L. Snow, Matthew A. Emergy, Richard Wainess, and Sonia D. Doshi, “Constructive Cognitive Profiles for Simulation-Based Hiring Assessments,” accessed October 20, 2019, //

[8] Stephanie Denning, “The New Hiring Practices at McKinsey and Goldman Sachs,” Forbes, last modified April 27, 2019. //; “What You Need to Know About McKinsey’s New Digital Assessment,” My Consulting Offer, last modified October, 2019, //

[9] Rebecca Kantar, Keith McNulty, Erica L. Snow, Matthew A. Emergy, Richard Wainess, and Sonia D. Doshi, “Constructive Cognitive Profiles for Simulation-Based Hiring Assessments,” EDM (2018), //

[10] “McKinsey’s Digital Assessment,” McKinsey & Company, last accessed October 20, 2019, //

[11] Stephanie Denning, “The New Hiring Practices at McKinsey and Goldman Sachs,” Forbes, last modified April 27, 2019, //

[12] John Gentry and Joseph Gordon, Strategic Warning Intelligence: History, Challenges, and Prospects (Washington, DC: Georgetown University Press, 2019), 178.

[13] Ibid., 180-182.

[14] Amir Husain, The Sentient Machine: The Coming of Age of Artificial Intelligence (New York, NY: Scribner, 2017), 85-88.

[15] Ibid., 90-94.

[16] Katherine Graham-Leviss, “The 5 Skills that Innovative Leaders Have in Common,” Harvard Business Review, last modified December 20, 2016,//

“Innovation Competency Model” Innovation in Practice, last modified September 18, 2011, //

[17] Edgar H. Schein, Organizational Culture and Leadership 4th ed (San Francisco, CA: John Wiley & Sons, 2010), 249-250.

[18] Samuel T. Hunter and Lily Cushenbery, “Leading for Innovation: Direct and Indirect Influences, Advances in Developing Human Resources 13 (December 2011): 248-265.

[19] Samuel T. Hunter and Lily Cushenbery, “Leading for Innovation: Direct and Indirect Influences, Advances in Developing Human Resources 13 (December 2011): 248-265.

[20] W. Chan Kim and Renee Mauborgne, “Blue Ocean Strategy,” Harvard Business Review (October 2004): 70-80.

[21] Samuel T. Hunter and Lily Cushenbery, “Leading for Innovation: Direct and Indirect Influences, Advances in Developing Human Resources 13 (December 2011): 248-265.

[22] Kelly Palmer, “Closing America’s Skills Gap,” Barron’s Online (New York, (May 2019): //



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