The end of platforms as we have known them seems to be around the corner. This blog is the first chapter in our blog series “Rise and fall of the platform business”. The abundance of self-powering independent sensors ultimately means that the world around us becomes data. Sensors are the…
The end of platforms as we have known them seems to be around the corner. This blog is the first chapter in our blog series “Rise and fall of the platform business”.
The abundance of self-powering independent sensors ultimately means that the world around us becomes data. Sensors are the means to collect data for platforms to use. They are therefore a crucial part of the business model of the platform economy. In this cycle, ever-increasing machine learning capabilities play a major role. The greater availability of data improves algorithms, which in turn helps to create better and better platforms. Also, the quality of the data collected by sensors improves, as algorithms refine their information needs.
In this way, platforms are the natural corporate structures for the era of superabundant data. For instance, Accenture has claimed that digital economy could make up 25% of the world’s economy by 2020 (Knickrehm 2016). The most important way platforms are enhanced is through a victorious cycle, where the quality of the platform offering leads to more users, and thus more and better data. This data enables more efficient machine learning, which in turn can be used to improve the platform offering.
The unfair advantage of the platform economy companies is not based on their digital platforms, products or machine learning abilities. It’s all based on data. This is indeed the winning model: when a platform company is able to continuously and exponentially improve, personalize and position their offerings via machine learning, its competitors have very little chance of competing since they lack access to both the data and technology to iterate their technology to be at the forefront.
Furthermore, the significance of data has only grown with the recent advances of machine learning technologies. Many platform companies launch products only in order to gather data. The data is used for teaching the new machine learning algorithms that improve somewhat linearly in relation to the amount of data used.
The better the machine learning capabilities of a company are, the faster the company can create a completely unfair offering in the market, utterly destroying competition. The loop is exponential: what kind of dataset the company starts with matters a lot. The few data-heavy companies, such as Amazon, Baidu, Google, Tencent (WeChat) and Facebook as well as the few data-heavy government agencies such as the NSA, tax authorities and health authorities, are able to utilize this advantage if they act quickly. However, if a company has no access to the requisite data, it does not stand a chance.
The best possible data in any industry or market area always wins if the company has sufficient machine learning capabilities and a typical platform business model. What if this changes? Then, the platform companies might be making a mistake.
What to read next?
Continue to Chapter 2: Four reasons why competitive advantage from data is disappearing
Continue to Chapter 3: The fall of platform business model
Read the intro: Rise and fall of the platform business
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The blog series “Rise and fall of the platform business” is contributed by senior expert Johannes Koponen. Follow Johannes on Twitter.