Your boss is your laptop: Management Systematization at Bridgewater Associates

Are we approaching a time when day-to-day management—hiring, firing, decision-making—will be guided by software that understands individuals and teams better than your top ranked managers?

In 2016, the Wall Street Journal published an article on a “secret project” at Bridgewater Associates, the world’s largest hedge fund. The WSJ painted a particularly a picture evoking galvanism and Frankenstein- esque notions of the project, describing it as an attempt to “turn the founder Ray Dalio’s, brain into a computer”. This project, reportedly called “The Book of the Future” was being headed by David Ferrucci, who previously led IBM’s development of Watson, the supercomputer that beat humans at Jeopardy! It aims to systematize management and have management decisions made in a data- driven, principles based manner.

While this might seem like a stretch in any other company setting, it seems fairly unsurprising for Bridgewater Associates to try this approach in management given how highly data-driven the fund is, with meetings being recorded and staff asked to grade each other throughout the day using a ratings system called “dots”. Given the “dots”, the firm already holds a wealth of information on its people and the systematic way of making decisions is already embedded in how it makes its investment decisions.

The appeal for systematization in management is apparent given the reality that human managers have their biases or, to invoke Daniel Kahneman’s thesis, they are more prone to use the quick emotional System 1 way of thinking instead of the slower, deliberative System 2. Not only do I see management systematization as an ideal remedy for the emotional attachments humans have to their own conclusion, but a potential competitive advantage for businesses as artificial intelligence becomes more ubiquitous in our workplaces. When you get down to it, our brains are essentially computers that are programmed in certain ways, take in data, and give out instructions. To the degree that we can program the logic in our mind to the computer, or perhaps even go a step further and have the computer ‘learn’ and discover what the best logic is the more businesses will become impelled to use artificial intelligence in their decision making.

To explain this more practically, you can think of a successful business as a collection of the right people, in the right roles taking the right actions with the tools and environment that they need to achieve their best and highest use. The job of a manager is to design this organizational ‘machine’ and ensure it keeps on running seamlessly. The machine design aspect of management of getting the right people into the right roles and can easily be automated once we’re able to collect data on people (in order to find the right people) and determine what qualities are needed for different roles. By collecting data on people, a firm can learn what they are like, what jobs they are best suited for, and how they would most effectively work together. For example, the team lead in the marketing department might need to be high on creativity and lateral thinking whereas a coder would need to be logical and a linear thinker. Day to day hiring decisions can be automatically made once the decision making criteria has been determined.

Moreover, people can also learn a lot about themselves, with a great amount of detail, which helps them and their personal development. Computers have the potential to ensure well designed organizational machines run smoothly as performance data is tracked and tailored, actionable guidance is fed to teams in real time. We currently live in a world where we are using technology to connect to a global system in which you can input the issue you’re dealing with and have exchanges about what you should do and why with the highest-rated thinkers in the world. If we take this one step further, it is feasible that one can be able to not only tap the highest-quality thinking on nearly every issue they face, but also get the guidance of a computerized system that weighs different points of view. This guidance can be tailored based on what the individual is like.

Bridgewater argues that they only use their systems much as a driver uses a GPS in a car: not to substitute for the navigational abilities but to supplement them. However, automated management systemization is part of a broader wave- where artificial intelligence working on its own has begun outperforming not only human intelligence but also joint human- AI teams. The more this happens, the more likely it becomes that such algorithms become the driver and not simply the GPS in a car. This can be concerning in part. Indeed it has been predicted by futurists such as Yuval Noah Harari, author of Sapiens and Homo Deus, that by 2050 it is possible that a useless class will emerge given a shortage of jobs and lack of relevant education to address this.  If the experience of Deep Knowledge Ventures an Asian biotech fund is anything to go by, we might experience this sooner than we think. On their board sits an algorithm called Vital (stands for Validating Investment Tool for Advancing Life Sciences) which has been credited with pulling the fund from the brink of bankruptcy.

 

References:

Hope, Rob. 2020. “The World’S Largest Hedge Fund Is Building An Algorithmic Model From Its Employees’ Brains”. WSJ. https://www.wsj.com/articles/the-worlds-largest-hedge-fund-is-building-an-algorithmic-model-of-its-founders-brain-1482423694.

Harari, Yuval. 2020. “Why Technology Favors Tyranny”. The Atlantic. https://www.theatlantic.com/magazine/archive/2018/10/yuval-noah-harari-technology-tyranny/568330/.

Member, Deep. 2020. “Deep Knowledge Venture’S Appoints Intelligent Investment Analysis Software VITAL As Board Member”. Prweb. http://www.prweb.com/releases/2014/05/prweb11847458.htm#!.

Solon, Olivia. 2020. “World’s Largest Hedge Fund To Replace Managers With Artificial Intelligence”. The Guardian. https://www.theguardian.com/technology/2016/dec/22/bridgewater-associates-ai-artificial-intelligence-management.

 

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