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Algorithms start to get more important for companies every day. They can help companies make predictions and decisions, but since algorithms are black boxes and extremely literal, companies need to know how to manage them. The article written by Luca, Kleinberg and Mullainathan (2016) in Harvard Business Review explains more about the challenges you face when using algorithms and about how to avoid as much problems as possible. This blogpost will give you a short summary about the insights of the article.

As mentioned, algorithms are black boxes and extremely literal. Algorithms often can predict the future with great accuracy but tell you neither what will cause an event nor why. This phenomenon is called black box. Besides, algorithms are extremely literal, which means that is does exactly what it is being told. For example, when you tell an algorithm to maximize user click-throughs, websites will show low-quality click-bait articles. This leads to higher clicks, but customer satisfaction might decrease. The goal might be accomplished since user click-through is maximized, but a decrease of customer satisfaction is of course not what companies want. Therefore, it is important to know how algorithms work and how to manage them. Luca, Kleinberg and Mullainathan (2016) have set up two steps to manage algorithms better.

First of all, you should be explicit about all your goals. It is important to be clear about all the goals that you want to achieve, including your soft goals. Second, you need to minimize myopia. This means that you should not only focus on the short term (maximizing clicks or number of orders), but that you should also think about your goals on the long term. Some articles might get more clicks because they are shocking, but it could decrease customer satisfaction. It is the same for maximizing orders. Some products might sell better than others, but their return rates are also higher, which eventually does not lead to the highest possible profit. Therefore, companies should also include long-term goals.

Understanding what algorithms can’t do is as much as important as understanding what algorithms can do. Following the mentioned steps above will make it easier to interact with algorithms and use them in your business to make predictions and decisions.

References
Luca, M., Kleinberg, J., & Mullainathan, S. (2016). Algorithms need managers, too. Harvard Business Review.

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Platforms play a huge role in today’s society. We use platforms to get in touch with family and friends, to order a taxi, and to order clothes online. One of the key characteristics of a platform is that it promotes interactions among different partners in a multi-sided market. A few examples are Uber that connects drivers with riders and YouTube that connects videographers with viewers. The more users that are active, the more value the platform gets, which will lead to more users. This is a constant process that eventually can make a platform extremely powerful.

As mentioned, different partners play an important role within a platform. Uber could not exist if there were no drivers available. Therefore, it is important to keep them happy and satisfied. Unfortunately, this is not always the case, but it is hard for platform workers to go against it.

Workers and creatives that create value for platform companies, and rely on platforms for their livelihoods, often have little power when it comes to getting their concerns addressed (Jin, Kominers & Shroff, 2021). Since platform workers often are not in direct contact with each other it is hard for them to create change. Besides, platform workers most of the time have little leverage because of an excess of willing participants on the supply side and low barriers to entry. Since individual effort has no impact on the platform, workers and creatives that create value for platforms protest collectively, which is called decentralized collective action (DCA). An example is the Twitch case, where protestors protested against the fact that creators on the platform were harassed. Collectively, they managed to decrease the views on the platform by 5% to 15% on a particular day. Thus, the protests had big impact on the company, but it only lasted for one day. This shows that even through decentralized collective action it is hard to achieve sustained impact.

In what ways do you think individuals that create value for platforms can address their concerns and achieve sustained impact? Leave your suggestions in the comments below.

Reference:
Jin, Kominers & Shroff (2021): https://hbr.org/2021/09/a-labor-movement-for-the-platform-economy