Tuesday, February 27, 2024

g-f(2)2019 Unlocking Value: The Fusion of External Data and AI in Private Market Investing


genioux Fact post by Fernando Machuca and ChatGPT


In the realm of private equity and venture capital, the integration of external data sources, commonly known as "alternative data," is revolutionizing investment strategies. This fusion of AI and external data not only enhances investment discovery and evaluation but also empowers portfolio companies to make more informed decisions. The dynamic interplay between external data and AI is reshaping the landscape of private market investing, offering unprecedented opportunities for investors to gain a competitive edge and drive success.

genioux GK Nugget:

"The marriage of external data and AI in private market investing is unlocking untapped potential, enabling investors to uncover valuable insights, identify emerging trends, and make data-driven decisions with precision and agility." — Fernando Machuca and ChatGPT

genioux Foundational Fact:

Private equity and venture capital firms are increasingly leveraging alternative data, sourced from external sources such as social media, news feeds, government reports, and satellite imagery, to inform investment strategies, conduct due diligence, and drive value creation in portfolio companies.

10 Relevant genioux Facts:

  1. External data, often referred to as "alternative data," provides private investors with an outside-in view of companies and markets, offering crucial context and insights beyond internal data sources.
  2. Social media data offers valuable insights into consumer sentiment and behavior trends, enabling investors to gauge market dynamics and identify investment opportunities in real time.
  3. Algorithmic sourcing of external data allows firms to detect patterns, trends, and anomalies that may signal attractive investment propositions or M&A opportunities.
  4. An example from the retail sector demonstrates how anonymized credit card data and web traffic analysis can uncover overlooked market trends and inform investment decisions.
  5. External data-driven due diligence offers a more thorough and nuanced analysis compared to traditional methods, expediting the process and providing a competitive advantage in bidding processes.
  6. AI tools, such as large language models (LLMs), enable investors to analyze patent databases, clinical trial data, and public sentiment to assess a company's growth potential and market position.
  7. Portfolio companies can leverage external data to optimize talent sourcing, identify specialized professionals, and assemble high-performing teams tailored to their specific needs.
  8. The future of external data in private market investing holds promise for expanding the range of potential applications, including responsible investment factors and performance assessment against relevant metrics.
  9. Challenges in harnessing external data include data privacy, security, bias, and data provenance, highlighting the importance of ethical and responsible data sourcing and usage.
  10. Despite challenges, embracing external data offers significant rewards for private market investors, empowering them to gain a crucial competitive advantage and drive success in an increasingly data-driven landscape.


The integration of external data and AI in private market investing represents a transformative shift, offering unprecedented opportunities for investors to gain insights, make informed decisions, and drive success in a rapidly evolving landscape. As reliance on external data continues to grow, addressing challenges and ensuring ethical and responsible data practices will be paramount. However, for those willing to embrace the potential of external data, the rewards are vast, heralding a new era of innovation and opportunity in private market investing.


The g-f GK Article

Adam D. Nahari and Dimitris BertsimasExternal Data and AI Are Making Each Other More Valuable, Harvard Business Review, February 26, 2024.

Adam D. Nahari

Adam D. Nahari is an MIT System Design and Management Fellow¹². He has a diverse background in data science, investing, and technology². Here are some key points about him:

  • He leads Berkshire Partners’ innovative data science group, where he harnesses internal and external data in public and private equity investing¹.
  • Prior to joining Berkshire, he worked as a Research Scientist at Harvard Medical School’s Predictive Medicine Group, developing advanced predictive models in Medicine and Pharma¹.
  • He has also worked as a Data Scientist across multiple industries, leveraging advanced computational methods and Machine Learning techniques to inform strategic direction, design and implement innovative, data-driven processes and systems, and improve performance¹.
  • He began his career in the Israel Defense Forces, serving as an officer in Unit 8200 of the Intelligence Corps¹.
  • He received a B.A. from Harvard University and an M.S. from MIT¹.
  • His research lies at the intersection of technology, data science, and investing².

Please note that this is a summary and may not include all of Adam D. Nahari's accomplishments and roles. For more detailed information, you may want to look at his official biography or reach out to him directly¹².

Source: Conversation with Bing, 2/28/2024

(1) Adam D. Nahari | Harvard Hillel. https://hillel.harvard.edu/people/adam-d-nahari.

(2) External Data and AI Are Making Each Other More Valuable. https://hbr.org/2024/02/external-data-and-ai-are-making-each-other-more-valuable.

(3) Harnessing External Data in Public and Private Market Investing. https://dspace.mit.edu/bitstream/handle/1721.1/150109/nahari-anahari-sm-sdm-2023-thesis.pdf?sequence=1.

Dimitris Bertsimas

Dimitris Bertsimas is the Boeing Leaders for Global Operations Professor of Management, a Professor of Operations Research, and the Associate Dean for the Master of Business Analytics at MIT¹². Here are some key points about him:

  • He has been a faculty member at MIT since 1988¹².
  • His research interests include optimization, stochastic systems, machine learning, and their application¹².
  • In recent years, he has worked in robust optimization, statistics, healthcare, transportation, and finance¹².
  • He was a cofounder of Dynamic Ideas, LLC, which developed portfolio management tools for asset management¹².
  • He is also the founder of Dynamic Ideas Press, a publisher of scientific books, and the cofounder of several companies¹².
  • He has coauthored more than 200 scientific papers and several books¹².
  • He has supervised numerous doctoral and Master students¹².
  • He is a member of the National Academy of Engineering and an INFORMS fellow¹².
  • He has received numerous research awards and recognition for his educational contributions¹².
  • He holds a BS in electrical engineering and computer science from the National Technical University of Athens, Greece, as well as an MS in operations research and a PhD in applied mathematics and operations research from MIT¹².

Source: Conversation with Bing, 2/28/2024

(1) Dimitris Bertsimas | MIT Sloan. https://mitsloan.mit.edu/faculty/directory/dimitris-bertsimas.

(2) Dimitris Bertsimas - Mobility Initiative. https://www.mmi.mit.edu/people/dimitris-bertsimas.

(3) Prof. Dimitris J Bertsimas | ILP. https://ilp.mit.edu/node/12839.

(4) undefined. https://dbertsim.mit.edu/.

Copilot's Summary

The article "External Data and AI Are Making Each Other More Valuable" from Harvard Business Review, authored by Adam D. Nahari and Dimitris Bertsimas, discusses the increasing value of external data and AI in private equity and venture capital¹.

Key points from the article include:

  • The term "alternative data" is used to describe information sourced from outside a company's internal systems, including social media chatter, news feeds, government reports, industry databases, anonymized credit card transactions, and satellite imagery¹.
  • Private investors are using these external data sources to identify potential investment opportunities, conduct due diligence, and add value post-investment¹.
  • The authors argue that AI is becoming a massive disruptive force, and the data sources undergirding the AI revolution haven't been used to their full potential¹.
  • They suggest that making good use of AI and machine-learning tools often entails having the right data strategy to support them¹.

The article provides insights into how the combination of external data and AI can offer significant opportunities for investors and companies across various industries¹.

Source: Conversation with Bing, 2/28/2024

(1) External Data and AI Are Making Each Other More Valuable. https://hbr.org/2024/02/external-data-and-ai-are-making-each-other-more-valuable.

(2) AI Can Help Companies Tap New Sources of Data for Analytics. https://hbr.org/2021/03/ai-can-help-companies-tap-new-sources-of-data-for-analytics.

(3) External Data and AI Are Making Each Other More Valuable. https://store.hbr.org/product/external-data-and-ai-are-making-each-other-more-valuable/H081JJ.

(4) Harvard Business Review - Ideas and Advice for Leaders. https://www1.qa.hbr.org/2024/02/external-data-and-ai-are-making-each-other-more-valuable?ab=HP-hero-latest-text-1.

The categorization and citation of the genioux Fact post


This genioux Fact post is classified as Breaking Knowledge which means: Insights for comprehending the forces molding our world and making sense of news and trends.

Type: Breaking Knowledge, Free Speech

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