Knowledge management in the NBA: lessons from the Luka Dončić and Anthony Davis trade

Introduction

In the fast-paced and thrilling world of professional sports, the NBA offers not only exciting on-court action but also strategic team planning that drives success. One of these strategies that is often overlooked is knowledge management (KM). KM refers to¹ the processes of applying a systematic approach to the capture, structuring, management, and dissemination of knowledge throughout an organization to work faster, reuse best practices, and reduce costly rework from project to project.

In the context of sports organizations, effective KM practices can enhance decision-making, improve team performance, and foster a culture of continuous innovation². As a long-time fan who has been watching games for 10 years while taking KM courses, I have often wondered about the applications of KM in the US National Basketball Association (NBA). Recently, a shock trade took place where Luka Dončić³ the star of the Dallas Mavericks⁴ and Anthony Davis⁵ a key member of the Los Angeles Lakers⁶ swapped teams. In this article, I explore the application of KM principles in professional sports, using this trade as inspiration.

The trade: a brief overview

The Dallas Mavericks and Los Angeles Lakers have struck a stunning deal that sees Luka Dončić and Anthony Davis swap teams. Dončić is the Mavericks’ ace—a young European player known for his unique dribbling rhythm and shooting prowess. Davis, on the other hand, is a top draft pick in his prime, known for his combination of offense and defense. This trade has far-reaching implications not only for the teams involved but also for the entire NBA landscape.

Knowledge management in the NBA

Dončić’s rise in the Mavericks is as good as it gets. His individual ability is unquestioned, whether it’s scoring, assisting, or rebounding, his all-round performance is amazing. But at the same time, although plagued by injuries, “the Brow”, as Davis is nicknamed, has super defence and scoring ability, making him an absolute star player. Such a comparison is not just a comparison of statistics, but also a collision of different strategies and different team cultures.

NBA franchises operate within a complex knowledge ecosystem, where both explicit and tacit knowledge shape player evaluations, strategic planning, and team performance. Explicit knowledge, such as player statistics, contract details, and injury reports, is readily available through databases and analytics. Tacit knowledge, including coaching insights, team chemistry, and individual player adaptability, remains harder to quantify but is equally crucial in trade decisions.

Behind every detail of the trade is a fresh plan for the team’s future. Basketball is a team sport, and high-level players must be combined with the right tactics to be most effective. As the soul of the Mavericks, how to play in the new environment will be another major challenge for Dončić’s career. The Lakers, on the other hand, are faced with the question of how to reshape the team around a new core, so the role of the Brow similarly cannot be ignored.

In this process, the development of trade strategy is not only a simple superimposition of economic considerations, but also a profound interpretation of the value of the player. When teams consider a trade, they often need to assess the player’s status, team fit, future potential and other factors. Such evaluation not only affects the team’s performance in the short term but also determines the team’s long-term development.

1. Capturing knowledge: data analytics and player performance

A crucial aspect of NBA KM is capturing and analyzing player performance data. Advanced metrics such as player efficiency rating (PER)⁷, win shares⁸, and real plus-minus (RPM)⁹ are indispensable for team decision-making. These metrics enable informed decisions on player acquisitions, trades, and game strategies.

In the Dončić-Davis trade, both teams rely heavily on data analytics. For the Dallas Mavericks, acquiring Anthony Davis means integrating a dominant defender into their system, while the Los Angeles Lakers gain a young, dynamic playmaker in Luka Dončić.

2. Distributing knowledge: coaching and player development

Effective KM ensures that the right insights reach the right people at the right time. In the NBA, this involves robust coaching strategies and comprehensive player development programs.

For the Mavericks, integrating Anthony Davis requires meticulous planning by the coaching staff. They must develop a game plan that leverages Davis’s strengths while mitigating any weaknesses. For example, building on Davis’s previous experiences with the Lakers by coordinating with players like Irving and Dinwiddie can create more opportunities on offense.

Similarly, the Lakers face challenges with ball distribution. With both James and Luka Dončić requiring ample possessions, the coaching team must devise strategies that optimize offensive efficiency while addressing defensive concerns due to Davis’s departure.

3. Applying knowledge: strategic decision-making

The ultimate goal of KM is to apply knowledge to drive success. In the NBA, this is achieved through strategic decision-making at both the macro and micro levels. The Dončić-Davis trade exemplifies how teams leverage KM to align with their long-term objectives.

For the Dallas Mavericks, the trade underscores a commitment to present competitiveness by adding Anthony Davis’s experience and skill set to bolster both offense and defense. Conversely, the Los Angeles Lakers are looking to the future by investing in Luka Dončić, a young talent seen as a long-term cornerstone of the franchise.

Applying the SECI Model¹⁰ to the trade:

• Socialisation: Team executives, scouts, and coaches exchange tacit knowledge through discussions, player observations, and networking within the NBA community. Evaluating Luka Dončić’s leadership style or Anthony Davis’s adaptability relies heavily on qualitative insights.
• Externalisation: Observations are converted into structured reports by scouts and analysts, transforming tacit insights into explicit recommendations that inform trade negotiations.
• Combination: These reports are integrated with statistical models, salary cap considerations, and trade simulations, providing a comprehensive framework for decision-making.
• Internalisation: Once a trade decision is finalized, teams implement strategies to ensure that players adapt to their new environments, effectively converting explicit knowledge into practice.

Conclusion

By capturing, distributing, and applying knowledge effectively, teams can make informed decisions that drive success on and off the court. As the NBA continues to evolve, the role of KM will only become more critical in shaping the future of the league.

The trade shocked the entire league, for example, Timberwolves star Anthony Edwards said¹¹ “I’m scared … When Luka is traded, anybody is able to get traded at that point.” While I was shocked, I also had some thoughts about the application of KM in the NBA, so I wrote this article, hoping to provide some experience and theoretical basis for those who share my passion for the NBA and have management experience to study the rules of the NBA.

Article source: Adapted from Knowledge Management in the NBA: Lessons from the Luka Doncic and Anthony Davis Trade, prepared as part of the requirements for completion of course KM6304 Knowledge Management Strategies and Policies in the Nanyang Technological University Singapore Master of Science in Knowledge Management (KM).

Header image source: Markus Spiske on Pexels.

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