New Research: Individual -Team Performance. Misaligned. Misdiagnosed.
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Imagination is more important than knowledge - Einstein.
Project teams have become the driving force behind productivity and innovation. However, a recent Economist article highlights cross-sector research on two significant related management challenges.
I. Misalignment
Performance management is still largely a one-player sport.
HR practices traditionally focus on the individual rather than the team. It's, therefore, crucial to rebalance this misalignment by incorporating the importance of teamwork throughout the employee lifecycle. Where HR can better manage the connection between individual and team performance as follows:
However, considerable challenges must be addressed by management before any systemic shift may occur. For instance, tracking and quantifying contributions in typically cross-functional teams - departmental, fluid, and often short-lived? Additionally, ensuring fairness and preventing “slacking” within distributed teams requires careful consideration.
II. Misdiagnosis
The second challenge concerns managers' lack of understanding about their team's daily work. A study by Soroco, Harvard Business School, and the Wharton School of Business involved four Fortune 500 companies and 14 teams comprising 283 employees. These teams worked in:
Astonishingly, managers, on average, could only recall or knew 60% of their team's work, even in small teams of five members. .” Indeed, “managers were routinely shocked” by the results.
High Costs
This lack of understanding has significant consequences, including inaccurate diagnosis, decision-making, inefficient resource allocation, and immense pressure on teams.
“Everybody on the team knew this was a problem to some degree; they felt the friction every day; but nobody understood how bad the situation was until we helped them measure the gap of their manager’s underestimation.”
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“We saw cases where the manager typically taught a few examples of how they thought the work ought to happen, but the team executed the same work in different ways from what the manager expected. For example, when performing a trade reconciliation, several experienced members of a team had found shorter paths for achieving the reconciliation and hence deviated from the prescribed standard operating procedures.”
Machine Learning (ML)
The study introduced a Machine Learning (ML) algorithm informed by data provided by the participating managers. "Managers relied on their intuition, judgment, and experience" to describe what they "believed occupied most of their teams' efforts. This data formed the basis of a "work graph," a map of how these teams get work done." The results indicated that "managers had an outdated and/or incomplete view of their team's work patterns." In contrast, the algorithm accounts for multiple ways for the same work? and "find patterns without relying on pre-existing intuitions." Moreover, the authors predict "the best-intentioned managers will be measurable," providing the correct privacy laws are in play.
Conclusion
?If teams are where a lot of the magic happens, bosses should have better ways to get the most out of them.
The Economist article and the original HBR study emphasize the need for a much better understanding of teams' role in today's workforce,? including a more expansive framework to recruit for individual and team strengths and skills. By extension, it behooves managers to comprehend their team's daily work better, treating their experiences as invaluable data.
References
Economist, The. (2023, November 6). How to manage teams in a world designed for individuals. The Economist. https://www.economist.com/business/2023/11/06/how-to-manage-teams-in-a-world-designed-for-individuals
Murty, R. N., Das, R. B., Kominers, S. D., Narayan, A., Srinivasan, S., Khanna, T., & Hosanagar, K. (2021, December 1). Do you know how your teams get work done? Harvard Business Review. https://hbr.org/2021/12/do-you-know-how-your-teams-get-work-done
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