Introduction
Explore the latest business insights from Harvard Business School, curated for the Dean Srikant Datar, covering key topics like balanced scorecard, corporate governance, innovation, performance management, and strategy implementation that leverage recent research on generative AI, talent development, data governance, and regulatory changes.
Insights
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber
The Harvard USPTO Patent Dataset (HUPD) is a rich resource for studying patentability and understanding the evolution of concepts over time. With over 4.5 million patent applications and 34 structured data fields per patent, it provides a wealth of information that can be utilized for academic research at Harvard Business School. This could lead to new insights into patent trends, innovation, and the impact of intellectual property on business strategy.
The article highlights the potential of Natural Language Processing (NLP) in patent analysis. Given the increasing importance of AI and machine learning in business, consider incorporating more NLP-focused courses or modules in the curriculum. This will equip students with the necessary skills to leverage such datasets in their future careers, and keep Harvard Business School at the forefront of business education.
Case: Ribbit Capital and the Gauntlet Investment Opportunity
By: Shai Bernstein, Allison M. Ciechanover
Given the rapid growth of the crypto and blockchain space, with VC investment in crypto/blockchain startups hitting over $30B globally in 2021, it’s crucial for Harvard Business School to incorporate these topics into its curriculum. This will ensure students are equipped with the knowledge and skills to navigate this emerging field.
Foster DeFi Understanding
With over $150 billion in assets deposited in DeFi protocols in early 2022, and startups like Gauntlet experiencing rapid growth, it’s evident that DeFi is becoming a significant part of the financial landscape. Consider developing courses or workshops focused on DeFi to prepare students for this new frontier in finance.
The Crowdless Future? How Generative AI is Shaping the Future of Human Crowdsourcing
By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani
The paper demonstrates that generative AI can generate solutions of comparable quality to human crowdsourcing, but at a significantly faster rate and lower cost. As an educational institution, Harvard Business School could explore integrating AI into problem-solving exercises or case studies, potentially offering students a unique, tech-forward learning experience.
Enhance Innovation with AI
While human solutions were found to be more novel, AI solutions were rated higher on environmental/financial value. This suggests that a combination of human creativity and AI efficiency could lead to highly innovative and valuable solutions. Consider implementing this approach in research projects or business strategy sessions at Harvard Business School.
The study found that prompt engineering made AI solutions more human-like. This could be a valuable tool in teaching and learning, helping to guide students’ thought processes and stimulate innovative thinking.
Mapping Organizational-Level Networks Using Individual-Level Connections: Evidence from Online Professional Networks
By: Shelley Li, Frank Nagle, and Aner Zhou
Leverage Employee Networks
The article highlights the importance of non-executive employee networks in predicting a firm’s value and innovation. As a leader in education, Harvard Business School could incorporate this insight into its curriculum, emphasizing the importance of networking and collaboration at all levels of an organization, not just at the top.
Rethink Traditional Industry Classifications
The study found that communities of closely connected companies often differ from traditional industry classifications. This could have implications for how business strategies and competitive landscapes are taught, moving away from a strictly industry-based approach to one that considers these broader, cross-industry connections.
How Boards Can Drive Climate Performance
Moderated by George Serafeim, the panel includes Carter Roberts, Deb Spar, Bonita Stewar, and Lauren Taylor Wolfe
As the Dean of Harvard Business School, consider integrating more sustainability-focused courses into the curriculum. This will help prepare future business leaders to understand and tackle environmental issues, which is crucial as the panelists highlighted the need for companies and boards to educate themselves on these matters.
Foster Collaboration
Encourage students and faculty to collaborate across disciplines, particularly in areas of policy, science, civil society, finance, and production. The panelists emphasized the importance of attracting talent that can build bridges across these areas to drive systemic change. This could be achieved through interdisciplinary projects or initiatives that bring together different areas of the school.
How the Best Chief Data Officers Create Value
By: Suraj Srinivasan and Robin Seibert
The article emphasizes the importance of Chief Data Officers (CDOs) in creating value across four interconnected areas: data products, data assets and platforms, data architecture and governance, and organizational data-readiness. As a leader in an educational institution, consider how you can leverage these insights to enhance data-driven decision-making at Harvard Business School.
Measure and Show Value Contribution
The article suggests that CDOs should develop qualitative and quantitative measurements to demonstrate their value contribution. This could be particularly useful in an academic setting where data can be used to track and improve various aspects of the institution, from student performance to operational efficiency.
The article highlights the importance of developing data literacy across the organization. As the Dean, you could consider implementing data literacy programs for both faculty and students to ensure they are equipped with the necessary skills to navigate the increasingly data-driven world.
Case: Sparking Innovation in the U.S. Air Force
By: Michael Parzen, Alexander Farrow, Paul Hamilton, Jessie Li
The article highlights the tension between standardization and agency among the Spark Cells. While complete standardization may stifle creativity, a lack of it can lead to inefficiencies. Harvard Business School could consider developing case studies or courses that explore this balance in the context of innovation management. This could provide valuable insights for future leaders navigating similar challenges in their organizations.
Develop Metrics for Innovation Productivity
The article mentions the challenge of determining key performance indicators for the network’s innovation productivity. This is a common issue in many organizations striving for innovation. Harvard Business School could leverage this as an opportunity to conduct research or host discussions on how to effectively measure innovation, which would be beneficial for students and businesses alike.
Unlocking Personal Devices for AI – Applications of Hybrid-AI for Businesses
By: Sushant Tripathy
The article highlights the increasing importance of Hybrid-AI in businesses. As the Dean of Harvard Business School, it would be beneficial to incorporate this emerging technology into the curriculum. This will equip students with the necessary skills to navigate the evolving business landscape.
The article also discusses the significance of data privacy in the application of Hybrid-AI. It would be valuable to emphasize this aspect in your courses, ensuring that future business leaders understand the importance of privacy policies and data protection in the era of AI.
The article suggests that the future of technology lies in overcoming privacy protection layers and developing generative AI models that can run on user devices. Encouraging more research in this area could position Harvard Business School as a leader in this field.
HBR: 8 Questions About Using AI Responsibly, Answered
By: Tsedal Neeley
The article suggests that everyone in an organization should work towards achieving at least 30% fluency in a handful of topics such as AI, machine learning, algorithms, cybersecurity, and data-driven experimentation. This will help in fostering a digital mindset and ensuring effective collaboration with AI systems.
Prioritize Transparency and Fairness
The article highlights the importance of transparency and fairness in AI systems. It suggests that to combat harmful bias, developers must be able to understand and document the risks inherent to a dataset, which might mean using a smaller one. Also, diversifying data and development teams can help ensure that people with a variety of perspectives and identities are represented in the AI models.
Generative AI in Corporate Finance: Where Are We Headed?
This article is based on an D^3 Assembly Talk with Alexandra Mousavizadeh, Glenn Hopper, and Sanjay Srivastava, hosted y Professor Suraj Srinivasan of the Digital Value Lab at D^3.
Given the potential of generative AI in making finance functions more efficient, it would be beneficial for Harvard Business School to incorporate this into its curriculum. This could include case studies on how AI is transforming corporate finance, as well as practical courses on AI applications in finance. This will equip students with the necessary skills and knowledge to navigate the evolving finance landscape.
As the article highlights the need for people with both domain expertise and technical literacy, consider introducing interdisciplinary programs that combine finance and technology. This could help in producing graduates who are well-versed in both areas, making them valuable assets in the corporate world.
Given the challenges around data privacy and IP protection, it would be beneficial to offer courses on data governance. This could help future finance professionals understand the importance of data protection and how to implement effective data governance strategies.
The regulatory landscape for AI in finance is uncertain and evolving. It would be beneficial for Harvard Business School to stay abreast of these changes and incorporate them into the curriculum. This will ensure that students are prepared for any regulatory changes that may affect the finance industry.
In Summary
The latest research offers valuable insights into generative AI, talent development, data governance and regulatory changes — all key areas of interest for Dean Srikant Datar. Incorporating these aspects into HBS’s curriculum aligns with his focus on balanced scorecard, corporate governance, innovation, performance management and strategy implementation. It could equip HBS students with up-to-date, relevant skills, setting them up for success in the rapidly evolving landscape of business and finance.