Why big data and algorithms are necessary but not sufficient


While I read The Wall Street Journal every day I rarely find anything I want to read on the Opinion pages.  But today was different. The article Models Will Run the World by Steven A. Cohen and Matthew W. Granade caught my eye. But as usual with the Journal, it was the subtitle that kept my eye moving down the page: The software revolution has transformed business. What’s next? Processes that constantly improve themselves without need of human intervention. And if you skip to the end of the article you will see the authors’ credentials. I’m finding that some of the best writing on business and on entrepreneurship is being done by professional investors, like Mr. Cohen and Mr. Granade.

Businesses are constantly searching for how to make their business processes more efficient. That’s the best road to increase productivity, meaning you get more output with the same level of input, or you have the option to reduce your input (costs) to keep the same level of output (revenue). And today the road to productivity is paved with data, but the authors clearly elucidate exactly what businesses need to do with that data:

We believe a new, more powerful, business model has evolved from its software predecessor. These companies structure their business processes to put continuously learning models, built on “closed loop” data, at the center of what they do. When built right, they create a reinforcing cycle: Their products get better, allowing them to collect more data, which allows them to build better models, making their products better, and onward. These are model-driven businesses. They are being created inside incumbents and startups across a range of industries.

Founders may feel like ignoring this article, after all by definition startups have no customer or other data so why be wasting time to create a model for it? Because the best time to architect a new process is tabula rosa, with a clean sheet of paper, or today a clean screen. Building learning models as you build your company is far more effective than attempting to retrofit a business process model onto an existing business. So while your incumbent competitors may well have reams more data than you, your advantage can come from building a model-driven business from the get-go, as the authors make clear:

A model-driven business is something beyond a data-driven business. A data-driven business collects and analyzes data to help humans make better business decisions. A model-driven business creates a system built around continuously improving models that define the business. In a data-driven business, the data helps the business; in a model-driven business, the models are the business.

Perhaps one of the most well-known and heavily used business process model is Netflix’s recommendation model. In fact they recently announced the shutdown of user reviews, as they added no value to the Netflix model. It’s recommendation model is a good example of a close loop: as a user accepts or rejects a recommendation the model learns and improves, with no human intervention needed.

The authors list five key implications of the model-driven business. Read the article to dive into the detail if you are interested.

  1. It’s not just the quantity of data a business creates, it’s also the completeness, which is a good judge of quality. For example, it wouldn’t help Netflix to improve its recommendation engine without its profile of its users. The more complete that profile, in terms of correlations between profile elements, such as age, gender and location, the better the quality of data and thus the better quality of the model.
  2. The goal of a model-driven business is to create the flywheel or virtuous circle. Models improve products, products get used more, this new data improves the product even more. This creates a near-frictionless process of continuous improvement, fueling itself, rather than being driven by human judgments and advancements.
  3. As pointed out previously, incumbents have a distinct advantage over startups in that they already have a trove of business data. So startups need to architect their business from the get-go to collect data. But they may need to go beyond that by purchasing data, or if they are backed by a smart and deep-pocketed investor, to actually buy companies with the data they need. The aqui-hire becomes the
    aquidata. A middle ground for a startup may be forging a strategic relationship with a company owning valuable data.
  4. Building, maintaining and improving business process models requires new skills. … the people, processes and technologies required to develop, validate, deliver and monitor models that create that critical competitive advantage.
  5. Monitoring privacy and security of your company’s data and business process models will become increasingly important as the war between hackers and data-rich companies escalates. You don’t want to be in the position of either having to pay ransom to a hacker  to unlock your data or explaining to some congressional committee exactly what it is you do with your customer’s data.

So founders: you do need a business model, that is how do you make money. But today that’s necessary but not sufficient. You also need business process models as well. You can think of the business model as the outward facing, customer facing model and the business process models as the inward facing, operational models. And I can see a new opportunity for consultants to help companies design and run those business process models.

Mr. Cohen is founder, chairman, and CEO of Point72 LP, which includes Point72 Asset Management and Point72 Ventures. Mr. Granade is managing partner of Point72 Ventures and chief market intelligence officer at Point72 Asset Management. In 2013, he co-founded Domino Data Lab. Point72 Asset Management makes long and short investments in all of the public companies named in this article, and the authors have direct ownership in inVia Robotics through Point72 Ventures.

Author: Mentorphile

Mentor, coach, and advisor to entrepreneurs, small businesses, and non-profit organizations. General manager with significant experience in both for-profit and non-profit organizations. Focus on media and information. On founding team of four venture-backed companies. Currently Chairman of Popsleuth, Inc., maker of the Endorfyn app for keeping fans updated on new stuff from their favorite artists.

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