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Scaling business value with data

Dr. Thilo Löwe,

When we consider the focus of Chinese and American investors and the research areas of Alphabet, Facebook, Amazon, Baidu, and Tencent, there can be no doubt that artificial intelligence (AI) is the megatrend that will fundamentally influence the development and valuation of companies in the years ahead. The development of AI has become so advanced that we now find ourselves shifting from the "age of discovery" to the "age of implementation" (comp. Kai-Fu Lee: AI Superpowers). In this phase, the ability to develop sophisticated AI algorithms is again becoming less important, because for these relevant libraries become increasingly helpful. Instead, access to relevant and as comprehensive as possible information is critical so that deep learning algorithms can be trained.

As a result, the established talk about the significance of data in the future value of companies is becoming more urgent: As the performance ability of implemented AI increasingly determines the competitiveness of a company, the scope, quality, and relevance of information accessed by this AI become more significant.

Information as an Asset with Specific Features

In his pivotal book Infonomics from 2017, Douglas Laney created the terminological cornerstone that considers and values information as a company asset. The way in which company value can be created with information is shown in no small part by Statista. From its inception, the creation of Statista was oriented towards the collection, evaluation, and monetization of information: Since then, Statista has customers in over 100 countries.

The example of Statista can also be used to explain the specific features of the asset class 'information':

Of course, most companies in the meantime – from athletic shoe to automobile manufacturer, from bank to airline – have recognized the value of information and initiated projects to systematically gather information and compile it in the most centralized way possible. Often, these are still IT projects that tend to be managed according to the logic of a 'cost center' rather than that of 'business development'. With this, they fail to tap into the full value potential of information for the company.

Information as a Value Lever

To do justice to the crucial significance that the access to information will play in the soon-to-be competitive rivalry of AI-supported companies, it is worthwhile to adopt a radical perspective according to which the value of future companies will be determined:

  1. the scope and quality of information available to a company,
  2. its ability to monetize this information, and
  3. its uniqueness of information access and its expertise to utilize the data

From this perspective, traditional material production assets obtain their value by monetizing information, such as automotive fleets that monetize information about which time a particular customer wants to reach a particular destination. In this regard, big data analyses are not so much a means for streamlining efficiency of existing production assets but first and foremost justify ones's own production as the best way to monetize the inventory of information in a company.

These points of view have of course been broadly simplified. Nonetheless, it is sensible to adopt them in order to examine how a strategic approach to information can serve to increase corporate value.

One example is Toutiao: Highly popular in China, this app by a subsidiary of the company ByteDance offers completely personalized news pages based on AI algorithms. Toutiao tracks individual user behavior down to the smallest detail and after that compiles a relevant information supply from third-party sources. Despite heavy criticism of the app as a multiplier of fake news and Chinese governmental opinions, the valuation of ByteDance in the most recent financing round was at appr. US$75 billion, which is at the same level as Uber (the valuation is attributed more or less equally to Toutiao and the video app TikTok that is also well-known here ). By way of comparison: Toutiao's Western counterpart BuzzFeed, a news aggregator that tends to operate in a more traditional fashion, has a valuation of appr. US$1.5 billion.

Another case in point is The Climate Corporation: Originally established with the idea to offer insurance against weather-related revenue losses, The Climate Corporation quickly developed into a data platform for the agricultural industry. For each field, information about the weather, soil conditions, plant health, and historical crops is aggregated and under the application of scientific findings, recommendations for seed and fertilizer are extrapolated. In addition to weather data, comprehensive proprietary test series, satellite images, and user measurements also serve as data sources. In 2013, seven years after it was launched, The Climate Corporation was purchased by Monsanto at a valuation of US$1.1 billion.

A third example is Conexus: with its software Conexus Insight and Conexus Engage, this Norwegian company provides tools to optimize lessons. Data about social demographics and from student surveys, grades, and test results are consolidated into these tools in such a manner that learning successes and challenges are clearly and comparably illustrated at the district, school, instructor, classroom, and individual student levels. Administrative bodies, teachers, and students are provided with crucial support to optimize lessons, and problematic cases become apparent. These tools have already been implemented into more than half of the Norwegian schools and have presumably contributed to the fact that in OECD comparisons of 'social mobility' (i.e., the opportunity to surpass the social level of the parents), Norway has been among the top performers for several years.

How to Play

In order to realize the value of information, it is important that it not be conceived as a by-product of a production and marketing process. To a greater extent, information illustrates its point of departure, and at the same time, it is one of its most pivotal results in that it provides the next point of departure. In our examples, the basis of information was expanded around new data points in a consistently dynamic manner. And for the most part, it did not consist only of the information from the company's core business. Furthermore, information originated from:

  • Third-party sources (for example: weather data, information from various medical providers, sociodemographic information)
  • Additionally-appended processes for acquiring information (for example: evaluating satellite images for soil data)
  • Information categories that are newly defined and recorded with new measurement methods (for example: 'self-esteem index' for students that includes the relevant psychological survey)

In addition to expanding the basis of information, diversifying the use of information is the second central value lever. Clearly, the use of information is intended to optimize existing business. In addition, information-based opportunities emerge to expand the existing business and introduce additional products. And ultimately, there is the option to market the information itself, either in raw form (e.g., databank) or in an aggregated and analyzed manner (e.g., report).

The path to creating value with information leads rightwards along the axis of information extraction and upwards along the axis of information analysis.

Conclusion

Concealed behind the outlook of information are value levers for every company whose significance with the arrival of AI is becoming increasingly essential. Alphabet, Amazon, Facebook, Baidu, Tencent, and numerous additional internet flagships now function as though their company value is a product of the scope and ability to monetize information within their grasp. Indeed, all the evidence suggests that we should not wait until more capable AI algorithms are available, but instead begin now with aggregating and expanding the basis of information and pursuing additional paths to monetize information.

 

Based on our experience from the creation and expansion of Statista as well as from a variety of projects, we assist our clients in using this central and increasingly significant value lever for their own companies.

Feedback, questions or recommendation regarding this article?
Please contact the author at thilo.loewe@nxt.statista.com

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