Making of an Expert: 9 Universal Abilities Every Expert Demonstrates

Making of an Expert: 9 Universal Abilities Every Expert Demonstrates

Share on facebook
Share on twitter
Share on linkedin

This article aims to summarize 9 unique characteristics (abilities) displayed by experts that differentiate them and represent their expertise.

Taking about expertise and accelerating time to expertise, three basic questions are raised: 1) What makes experts so special? 2) What characteristics set experts apart from the rest of us? 3) What traits or abilities define expertise?

In the last several posts, I focussed on skill development towards a higher level of expertise and how to accelerate progress towards expertise. While some of those posts like 5 Training Guidelines for Skill Acquisition Towards Unconscious CompetenceMastery Demystified: How Do the Skills of a Novice Develop into Mastery?7 Models That Explain How Novice Develops into an Expert

focussed on explaining the process of expertise development, others raised questions on how to accelerate and hasten that progression towards expertise or mastery in posts like Accelerated Expertise with Mentoring and Tough Cases6 Training Strategies to Accelerate Expertise from Sternberg’s ModelWhat Does 9 Famous Training Models Say About Accelerating Expertise? In this post, I will explain what makes an expert and what makes the expertise.

Expert, Expert Performance, and Expertise

Expertise typically has been viewed in terms of expert performance which means expertise in some abilities which are possessed by some and not all (Dror et al., 1993). These abilities may contain a range of skills, knowledge, and performance characteristics and it may vary from one domain to another.  Ericsson (1994) defines expert-level performance as “Usually if someone is performing at least two standard deviations above the mean level in the population, that individual can be said to be performing at an expert level.” Ericsson & Lehman (1996) further elaborated expertise or expert performance as consistently superior performance in tasks pertaining to the field of expertise.

Klein (1998) describes that expert performance comes by virtue of the expert’s ability to integrate information from a large array of accumulated experiences to assess the situation; select a course of action through recognition; and then assess the course of action through mental simulation. This is termed the intuitive capability that only experts are deemed to have.

Dror (2011) summarized the capabilities of experts that help them achieve such high-performance levels as: “experts need to have well-organized knowledge, use sophisticated and specific mental representations and cognitive processing, apply automatic sequences quickly and efficiently, be able to deal with large amounts of information, make sense of signals and patterns even when they are obscured by noise, deal with low quality and quantity of data, or with ambiguous information and many other challenging task demands and situations that otherwise paralyse the performance of novices” (p. 179).

Hoffman (1998) defines an expert as one whose judgments are uncommonly accurate and reliable, whose performance shows a range of skills with minimum effort, and who can deal effectively with certain types of tough cases. It is believed that experts within their domains are skilled, competent, and think in qualitatively different ways than do novices (Anderson, 2000; Chi et al., 1988). Glaser and Chi (1988) contested that there is a strong interplay between knowledge structures, processing capability, and problem-solving to develop desired expertise.

The pioneering research by de Groot (1946/1978) and Chase and Simon (1973) on differences in performance of novice and experts has generated a great deal of research like Chi, Glaser, & Farr (1988) and Ericsson & Smith (1991).

9 Universal Abilities Possessed by Experts And Indicative of Expertise

Several studies reported some characteristics in which experts were different from novices which I am trying to summarize below:

1.  Experts possess superb mental knowledge representations:

Experts are driven by the knowledge contained in specific mental representations and schemas which they have acquired by learning and experience (Russell, 1910). One of the most noticeable characteristics of experts that set them apart from non-expert is to use efficient mental representation to reduce cognition load and use computationally efficient methods.

They re-package the information in such a way that it is used more efficiently while performing certain tasks. As an expert gains more experience, he becomes good at chunking. Czerwinski et al. (1992) suggest that experts use an ability called ‘perceptual unitization’. The unitization creates new entities and neural processing that causes discrete components to join together in mental representation (Schyns and Rodet, 1997). This new organization is considered to play an important role in expertise (Goldstone, 2000; Shiffrin and Lightfoot, 1997). The ability of experts to reason, plan out and evaluate the consequences of possible actions has been seen to be associated with their superb mental representation of the relevant information about the situation. Such mental representations and information processing many times give rise to automatization (Schneider and Shiffrin, 1977; Shiffrin and Schneider, 1977). This is the stage where can perform them effortlessly.

2. Experts have the ability to handle complexity very well

Although the experts are not gifted with any better short-term memory than non-experts, they have the ability to use your short-term memory effectively. Research shows that expert has the advantage of using a larger chunk of information which may go up to seven chunks (Miller, 1956). This is the characteristic difference as compared to non-experts. The chunking of large information or several steps into a unified routine or schemata has also resulted in experts’ ability to handle complexity and solve complex problems during which they can respond quickly and also able to do more.

3. Experts display an ability to efficiently store and recall information

The historical studies on expertise started mostly around the game of chess. DeGroot (1966) compared the characteristics of experts vs. novice chess players. Chase and Simon (1973) noted that knowledge structure plays an important role in the performance of an expert by which experts could recall a large number of patterns by briefly glancing at the chessboard as compared to the non-expert.

4. Experts have the ability to process information efficiently with a minimum cognitive load

Halyoak (1991) stated that an expert is particularly skilled in general heuristics search.  In several studies, experts have been seen to use a top-down process of information processing which relies on pre-existing information, the context in which the data is presented, past experience and knowledge, expectations, etc. The top-down information allows for efficient and effective processing of the bottom-up data (Dror, 2011).  Researchers (Chi, Feltovich, & Glaser, 1981; Kraiger, Ford, & Salas, 1993) suggest that individuals who are proficient within a particular domain have an extensive and well-organized knowledge base that is constructed through experience.

5. Experts are good in the ability to selectively filter relevant information

The most important feature of expertise is experts’ ability to pay attention selectively and focus on the important or relevant information while filtering the irrelevant (Wood, 1999). Experts possess a better overall picture and are able to discriminate between relevant and irrelevant information.  Experts have abilities and knowledge that have been acquired by repeated exposure to the tasks they need to perform. With time, they tune into and pick out the important and relevant information, learning how to detect and use it well while ignoring and filtering out everything else (Kundel and Nodine, 1983; Wood, 1999). With expertise, an individual becomes more selective at a higher rate.  While a novice’s tendency is to make sense of the information, an expert may jump to the critical information (de Valk and Eijkman, 1984). As a result, experts can perform quickly and efficiently even in environments that contain little data or noise (Gold et al., 1999; Lu and Dosher, 2004).

6. Experts have acquired deep problem-solving skills

Larkin, Dermott, Simon & Simon (1980) in their studies noticed that experts were classifying based on deep structure whereas students classify physics problems based on their surface features. They also suggested that experts form an immediate representation of the problem that systematically cues their knowledge, whereas novices do not have this kind of orderly and efficient access to their knowledge.

7. Ability to recognize patterns is the hallmark of experts

Experts have the ability to notice meaningful patterns and features of a given knowledge that novices are not able to recognize at first glance (NRC, 2000). Several studies established in aviation (Endsley, 2006), sports (Williams and Ward, 2003), physics problem solving (Chi, 2006), and medical diagnosis (Norman, Eva, Brooks, & Hamstra, 2006) established that experts possess the ability of early detection and matching of patterns.  They further have the ability to identify new problem types and can actively work toward finding the solution for it (Meig, 2009). Studies by Bereiter and Scardamali (1986) and Chi and Glaser (1988) found that experts outshine in their ability to recognize knowledge patterns much faster than the novice in problem-solving.

8. Experts exercise better strategies and meta-skills

One of the key abilities that differentiate experts from the novice is that of meta-skills which guide experts to monitor, adjust and analyze one’s thinking, learning, and knowledge during problem-solving. Further experts are found to be more learning goals oriented than non-experts and know how to set the learning goals based on the available resources (Bereiter & Scardamalia, 1993).

9. Experts are apt at intuitive decision making and intuition

As per Dreyfus &Dreyfus (1986), experts don’t apply rules or uses any maxims or guidelines. He rather has an intuitive grasp of situations based on his deep tacit understanding. One key aspect of this level is that individual relies on intuition and the analytical approach is used only in new situations or unrecognized problems not earlier experienced. Experience-based deep understanding provides him with very fluid performance. At this stage, skills become automatic that even an expert is not aware of it. Based on priori experience, they can even come up with the solution for new never experienced before situations (DiBello, Lehman, Missldine, 2011).

What does it mean to Training Designers and Strategists?

As a training strategist and training professional, you may need to know the characteristics of experts, translate those characteristics into the jobs of the target employee groups and then scale it back to define the ‘desired proficiency’ expected in a given job. This will help you to develop higher-order training objectives and performance goals for the group.

Stay tuned for practical training strategies to design programs to accelerate expertise.


Attri, RK (2017), ‘Making of an Expert: 9 Universal Abilities Every Expert Demonstrates as Seen by Researchers’, [Blog post], Speed To Proficiency Research: S2PRo©, Available online at <>.


  1. Dror, I. E., Kosslyn, S. M., & Waag, W. (1993). Visual–spatial abilities of pilots. Journal of Applied Psychology, 78: 763–73.
  2. Ericsson, K. A. & Charness, N. (1994). Expert performance – Its structure and acquisition. American Psychologist 49, 8, 725-747.
  3. Ericsson, K. A. & Lehmann, A. C. (1996). Expert and exceptional performance: Evidence of maximal adaptation to task constraints. Annu. Rev. Psychol., 47, 273-305.
  4. Dror, I. E. (2011). The paradox of human expertise: why experts get it wrong, 177–188.
  5. Hoffman, R. R. (1998). How can expertise be defined? Implications of research from cognitive psychology. In W. F. R. Williams, J. Fleck (Ed.), Exploring expertise (pp. 81-100). New York: MacMillan.
  6. Anderson, J.R., 2000. Cognitive Psychology and its Implications, fifth ed. Worth Publishing, New York.
  7. Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.). (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.
  8. Glaser, R., Chi, M., 1988. Overview. In: Chi, M., Glaser, R., Farr, M. (Eds.), The Nature of Expertise. Lawrence Erlbaum, NJ, pp. xv–xxxvi.
  9. de Groot, A. (1978). Thought and choice and chess. The Hague, The Netherlands: Mouton. (Original work published 1946)
  10. Chase, W. G., & Simon, H. A. (1973). The mind’s eye in chess. In W. G. Chase (Ed.), Visual information processing pp. 215-281). New York: Academic Press.
  11. Chi, M. T. H., Glaser, R., & Farr, M. (1988). The nature of expertise. Hillsdale, NJ: Erlbaum.
  12. Ericsson, K.A., Smith, J., 1991. Prospects and limits of the empirical study of expertise: an introduction. In: Ericsson, K.A., Smith, J. (Eds.), Towards and General Theory of Expertise. Cambridge University Press, Cambridge, pp. 1–38.
  13. Russell, B. (1910). Knowledge by acquaintance and knowledge by description. Proceedings of the Aristotelian Society, 11: 108–28. 
  14. Czerwinski, M., Lightfoot, N., & Shiffrin, R. M. (1992). Automatization and training in visual search. American Journal of Psychology, 105: 271–315.
  15. Schyns, P. G., & Rodet, L. (1997). Categorization creates functional features. Journal of Experimental Psychology: Learning, Memory and Cognition, 23: 681–96.
  16. Goldstone, R. L. (2000). Unitization during category learning. Journal of Experimental Psychology: General, 123: 178–200.
  17. Shiffrin, R. M., & Lightfoot, N. (1997). Perceptual learning of alphanumeric-like characters. In: Goldstone, R. L., Schyns, P. G. & Medin, D. L. (Eds.). The Psychology of Learning and Motivation, Volume 36. San Diego, CA: Academic Press, 45–82.
  18. Schneider, W, & Shiffrin, R. M. (1977). Control and automatic human information processing, I: Detection, search, and attention. Psychological Review, 84, 1-66.
  19. Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84: 127–90.
  20. Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review 63, 2, 81-97.
  21. Chi,M. T. H., Feltovich, P. J.,&Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.
  22. Klein, G., 1993. A recognition-primed decision (RPD) model of rapid decision making. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C. (Eds.), Decision Making in Action: Models and Methods. Ablex Publishing Corporation, NJ, pp. 138–147.
  23. Wood, B. P. (1999). Visual expertise. Radiology, 211: 1–3.
  24. Kundel, H. L., & Nodine, C. F. (1983). A visual concept shapes image perception. Radiology, 146: 363–8.
  25. de Valk, J. P. J., & Eijkman, E. G. J. (1984). Analysis of eye fixations during the diagnostic interpretation of chest radiographs. Medical and Biological Engineering and Computing, 22: 353–60.
  26. Gold, J., Bennett, P. J., & Sekuler, A. B. (1999). Signal but not noise changes with perceptual learning. Nature, 402: 176–8.
  27. Lu, Z. L., & Dosher, B. A. (2004). Perceptual learning retunes the perceptual template in foveal orientation identification. Journal of Vision, 4: 44–56.
  28. Larkin, J. H., Mc Dermott, J., Simon, D. P. & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science 208, 1335-1342.
  29. Williams, A. M., & Ward, P. (2003). Perceptual expertise: Development in sports.
  30. Chi MTH (2006) Two approaches to the study of experts’ characteristics. In: Ericsson KA, Charness N, Feltovitch PJ, Hoffman RR, eds. The Cambridge Handbook of Expertise and Expert Performance. Cambridge: Cambridge University Press. pp 21–30.
  31. Mieg, H.A. (2001). The social psychology of expertise: Case studies in research, professional domains, and expert roles. Mahwah, NJ: Erlbaum.
  32. Bereiter, C., Scardamalia, M. (1993). Surpassing Ourselves: An Inquiry into the Nature and Implications of Expertise. Open Court Publishing Company, Chicago.
  33. Dreyfus, H., Dreyfus, S. (1986). Mind over Machine: The Power of Human Intuition and Expertise in an Era of the Computer. Free Press, New York.

About Dr Raman K Attri

Dr Raman K Attri is the world’s #1 authority on the science of speed in professional and organizational settings. He is the world's only professional speaker speaking on the topic of the science of speed. He is the author of 23 multi-genre books. As a performance scientist, he has been recognized as one of the leading ‘Transformational Business Leaders’ of 2022. He was named as one of the ‘Global 500 Leaders’ of 2021, alongside stellar leaders like Oprah Winfrey, Gary Vee, Jim Kwik, and Jay Shetty, to name a few. He has made his space as a true accelerated learning guru, earning over 100 international credentials and degrees, including two doctorates in the learning domain, apart from some of the world’s highest certifications. A corporate business manager, he has been featured and cited in over 125 media features in TV/radio shows, magazines, podcasts, and forums.

Leave your thought here

Your email address will not be published.

This site uses User Verification plugin to reduce spam. See how your comment data is processed.




Be a member of GetThereFaster™ Club, today!!