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Speed and quality of complex strategic decisions
21.09.2026
The research article by Uwe Sunde, Dainis Zegners, and Anthony Strittmatter has been published in PNAS! We asked economist Uwe Sunde, to share their key insights.
The research article by Uwe Sunde, Dainis Zegners, and Anthony Strittmatter has been published in PNAS!
We asked economist Uwe Sunde to share their key insights.
Discover why spending more time on a complex strategic decision does not always lead to better outcomes, and what professional chess can teach us about decision-making under uncertainty.
Strategic decisions, from the boardroom to the battlefield, often have to be made under time pressure. Your paper argues that spending more time on a decision does not necessarily improve the outcome. To begin, why is the link between decision time and decision quality unclear?
Taking more time can mean two different things. On the one hand, extra time may help someone consider more options, process more information, and make a better decision. On the other hand, a decision may take longer simply because it is more difficult. For example, because the alternatives are hard to compare or the outcome is uncertain. In that case, longer decision time reflects the difficulty of the problem rather than improving the quality of the decision.
Why did you choose professional chess as the setting for studying this question?
Professional chess provides a unique environment for us: it combines high stakes, strategic interaction and exceptionally detailed data. Every move is a strategic choice with clear consequences, and players repeatedly face different configurations of the board under different levels of time pressure. Importantly, we can compare a human player’s move with a computational benchmark from a chess engine, allowing us to measure decision quality objectively rather than relying on subjective assessments.
So how exactly does your study measure decision quality?
We compare each move played by professional chess players with the best move suggested by a state-of-the-art chess engine. The engine evaluates the entire position and identifies the move that maximizes the player’s expected outcome under optimal play. We measure whether the human player selected this benchmark move, and we also consider alternative measures based on the distance between the actual move and the engine’s recommended move. This provides a detailed measure of decision quality at the level of individual decisions.
What kind of data did you use to study these decisions in such detail?
Our analysis uses more than 215,000 moves from around 3,600 professional over-the-board chess games. The data covers three different formats: Classical, Rapid, and Blitz chess, which create different levels of time pressure. Because we observe many decisions made by the same players against different opponents and in different board configurations, we can compare decisions within the same decision maker, or even within the same pair of players, while accounting for individual playing styles and other systematic differences.
What is your main finding?
Faster decisions are associated with higher decision quality. This pattern remains even after controlling for important factors that could explain the relationship, including remaining time on the clock, computational complexity of the chess position, and how easy it is to distinguish the best move from alternatives. The result suggests that long decision times often reflect difficult decisions rather than better reasoning. Fast decisions may instead indicate strong intuition, experience, or early recognition of the right move.
In other words: When a player spends a long time thinking, this may indicate that the decision problem is genuinely perceived as difficult to solve. The additional time spent does not necessarily overcome that difficulty. In contrast, fast decisions may reflect that the player quickly recognizes a promising option based on experience and accumulated knowledge. In this sense, speed can sometimes be a signal of expertise rather than carelessness.
Fig. 1. Decision time and move quality across the time distribution.
Moves are sorted by how long the player took to make them, then split into ten equal-sized groups, called bins (based on the number of moves), separately for Classical, Rapid, and Blitz games. All values are shown relative to the fastest 10% of moves (the [0, 10%] bin). For instance, the value for the (70%, 80%] bin shows how much more or less likely the best move was to be played in that bin, compared to the fastest 10% of moves, within the same time control.
It still seems counterintuitive that thinking longer doesn't help, especially since we typically view time pressure as the ultimate enemy of good decision-making. In your analysis, how do you separate the effect of a player’s overall time pressure from the objective complexity of the specific decision?
We control for time pressure, computational complexity, and decision time as separate independent variables. The "counterintuitive" result emerges when you look at these factors simultaneously. Even when you compare two moves that have the exact same complexity and the exact same time pressure (remaining clock time), the move that the player spent more time on is still more likely to be an error. "Spending time" is not the same as "having time." While having more time helps you perform better, spending a lot of it on one specific move is a signal that you are experiencing "cognitive uncertainty" or subjective difficulty that the extra minutes simply cannot fix. In high-stakes environments, speed is often a byproduct of pattern recognition and expertise, while long deliberation is a symptom of being lost in a problem you cannot solve.
While your research uses professional chess as a specialized 'laboratory,' one could wonder about the broader implications. Is this pattern unique to elite chess players, or does the negative link between decision time and decision quality apply more broadly to other high-stakes settings, such as corporate leadership or political crises, where experts face both complexity and time pressure?
Although our data comes from elite chess, we believe the underlying mechanism may apply more broadly.
Like grandmasters, leaders and policymakers must compare alternatives, anticipate others’ actions, and make decisions under uncertainty and time pressure. Experts in these settings also rely on a mix of pattern recognition, intuition, and deliberate analysis.
Chess is especially useful because it allows us to measure decision time, complexity, and quality with unusual precision. It therefore serves as controlled environment for studying a broader feature of expert decision-making under pressure.
Read the article: Uwe Sunde, Dainis Zegners, and Anthony Strittmatter: Speed and quality of complex strategic decisions In: PNAS