• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Team Success: Aligning Means with Objectives

Team Success: Aligning Means with Objectives

© iStock

In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.

Managers regularly face the challenge of building an optimal team. Should team members have similar skills and expertise, or is it better to select individuals with diverse backgrounds? The literature offers differing perspectives: some studies argue that diverse teams are more effective, while others suggest that such teams are more prone to conflict and harder to coordinate.

The authors of the paper developed a formal model showing how the optimal level of skill and expertise diversity in a team depends on its ultimate objective. The researchers distinguish between two types of objectives: in the first, achieving a high average performance is key; in the second, minimising the risk of failure is critical. This, in turn, determines the optimal team composition.

For example, in medicine, it is not sufficient to focus solely on achieving a high average outcome: a failure in a single complex case can harm a patient, leading to lawsuits and serious reputational damage that cannot be offset by successes in other cases. Therefore, a hospital must ensure a minimum acceptable standard of care across different types of patients. In research and innovation-driven projects, the logic is often different: a team’s overall success may hinge on its strongest outcomes—a breakthrough discovery, a high-impact publication, a patent, or a new product—while unsuccessful attempts are treated as part of the search process. A similar dynamic exists in the film industry, where a single hit can offset several less successful projects.

If the objective is to maximise average performance, teams composed of members with similar backgrounds tend to perform better. The notion is not that diversity of skills is harmful, but that when the focus is on average outcomes, it is advantageous for the team to be well aligned with the most common, routine tasks. Accordingly, team members’ expertise should be similar to one another and closely matched to the demands they encounter most frequently: consistently high performance in a large number of cases raises the average more than preparedness for rare, non-standard situations.

Conversely, when avoiding mistakes is critical, diversity becomes an advantage. A team with varied backgrounds is more likely to handle a wide range of problems. For example, a hospital’s emergency department requires specialists with different expertise—trauma physicians, surgeons, anaesthesiologists, and others.

Tatiana Mayskaya

'Organisations often overestimate universal approaches, trying to assign diverse teams to every task. Our paper shows that there is no one-size-fits-all solution; much depends on the objective,' says Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economics and the International College of Economics and Finance. 'To build a team effectively, managers should ask themselves: “do we want to achieve strong average results or avoid failures?” In the former case, all else being equal, a team with similar backgrounds tailored to typical tasks is appropriate; in the latter, a team with a broader range of competencies—better able to cover different scenarios and prevent worst-case outcomes—is optimal.'

See also:

Biologists Discover 'Molecular Fingerprint' of Preeclampsia

Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

‘Hedgehog’ Versus ‘Relatives’: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech

Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.

HSE Researchers Create New Corpus of Early Child Speech in Russian

Researchers at the HSE Centre for Language and Brain have presented RusLan-M, an open multimedia corpus that makes it possible to trace the development of early child speech in Russian from first words to the emergence of complex grammatical constructions. The database contains around 41 hours of video recordings and more than 35,000 child utterances. The new resource will help researchers study more precisely how children acquire Russian and, in the longer term, develop more reliable tools for assessing speech development. The study has been published in Language Resources and Evaluation.

Scientists Develop Algorithm for More Reliable Processors in Data Centres

Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.

Researchers Rank Recommendation Algorithms Using Sports Tournament Model

Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed an approach for selecting recommendation algorithms more effectively. Their approach uses pairwise comparisons of algorithms to create a tournament table, with the overall ranking based on their performance across all datasets in the tournament. This can reduce the number of algorithms that need to be tested when developing new services, saving both time and money. The study was presented at the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026).

Researchers Develop Method for Direct Generation of Regulatory DNA

Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’

Researchers at HSE University and Sber Train Neural Networks to Better Predict User Preferences

The HSE FCS AI and Digital Science Institute and Sber have introduced a new architecture for recommendation systems that combines two classes of models, enabling algorithms to better predict users’ interests and needs. A preprint of the paper has been published on arxiv.org and presented at Urban ML.

Physicists Discover What Happens Inside a Stable Vortex

Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.

‘The Peak of Stupidity’ and ‘The Valley of Despair’: HSE Economists Propose an Explanation for the Dunning–Kruger Effect

The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

Toffee and Risk: Scientists Discover Why People Who Crave Sweets Make More Impulsive Choices

Having a sweet tooth may be linked not only to eating habits but also to the way people make decisions. Researchers at HSE University have found that people with a preference for sweet foods tend to behave more impulsively—not because they want immediate rewards, but because they are less willing to tolerate uncertainty. These findings may help improve treatments for addiction. The study findings have been published in Frontiers in Psychology.