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Free Labor, Bot Workers and the New Economics of Businesses

One of the most important megatrends of the last few years has been the reshuffling of the resources companies use to operate.
Martin Hoffmann is a private equity professional, turned author, publisher and entrepreneur. With dedicates his work to help knowledge workers & decision makers navigate an era of change by outlining patterns of change that happen across industries.
Martin Hoffmann is a private equity professional, turned author, publisher and entrepreneur. With dedicates his work to help knowledge workers & decision makers navigate an era of change by outlining patterns of change that happen across industries.

According to figures from GEM Global Report, a staggering 100 million businesses are launched annually. Thanks to increasingly cheap and accessible digital development tools and advanced R&D labs and funding offered by corporate and independent accelerator programs, we are witnessing global technological advancement on a scale never seen before.

From at-home coders, to well-funded startups in Silicon Valley and further afield, technology and businesses in general are changing so rapidly, keeping up to date with new trends can become a full-time job. This poses an interesting conundrum for investors, who need to be able to take a bird’s eye view of what is going on around the world to make smart investments. However while it might be tough to keep your finger on every new pulse, you can keep track of important megatrends.

One of the most important megatrends of the last few years has been the reshuffling of the resources companies use to operate. The economics of a business are largely driven by the type of resources a company applies and these resources are currently changing rapidly across industries.

I recently attended the Re Publica convention in Germany, which illustrated patterns of how these resources are changing:

1. Free Labor

In the past, companies’ operations were based on tangible assets like ‘in house’ human resources and hard assets like raw materials. However in the internet age, intangible assets are becoming increasingly important. The first wave of internet businesses were based on e-commerce and software, but now industry leaders’ value is based primarily on new intangible resources like network effects, audience reach and advertising potential.

After scanning 8000 Facebook (FB) patents to dissect and visualize Facebook’s algorithms Vladan Joler from the University of Novi Sad in Serbia exposed the raw resources that keep the “Facebook Factory” running. The numbers are fascinating.

Facebook had 1.6 billion active users in 2015, out of a world population of 7.5 billion. 1 billion people log in daily and share 4.6 billion items, upload 350 million photos and send 10 billion messages every day. Each of those activities drives users to use Facebook more, and in 2015 created an ad revenue of 17.93 billion dollars.

Let’s quickly put this into context: The best selling record albums ever reached 65 million copies. The PlayStation, one of the best selling products of all time sold 344 million units. Star Wars generated total sales of $4.6 billion. To simplify things, let’s assume that the average movie ticket costs $10 meaning 460 million people went to see Star Wars. That would be just a third of Facebook’s regular user base.

So why is this so important? While most people view Facebook as a social media platform, its revenue comes from being a marketing and content machine. However, instead of needing to hire content creators, and editors to curate the content, the Facebook users network does all of this for free. Supported by the power of Facebook’s algorithms, billions of users around the world not only provide the content to be shared, they also decide what is interesting, flag inappropriate content and share content which resonates with their own demographic.

Vladan Joler compared the average time, which users spend on Facebook each day — 20 minutes — to wages in his home country Serbia, and found that that amount of labor is worth 3.5 billion annual salaries of an average Serbian employee. Without realizing they are doing so Facebook users are creating content, sharing content, curating content, and Facebook gets all of this labor for free.

While Facebook is clearly the frontrunner, other companies such as Instagram, Slack and Evernote are benefiting from user generated content in similar ways. This includes developers and startups contributing slack bots to the Slack platform, effectively increasing its rich feature offering, to billions of Instagram users curating content through their ‘likes’. While this model is not new, the scale at which it is happening and the impact it has on the economics of how businesses are run will change how investors assess the strength of businesses in the future.

2. Data as a Resource

By harnessing the data from its huge user network, using algorithms to understand interests based on their online behavior, and then targeting them with the right paid advertising and content, Vladan Joler argues Facebook has made itself “the biggest marketing agency that exists in the world”.

But Facebook is just one example. In the modern landscape data has become a key resource and success factor for companies across a range of industries. From Netflix (NFLX), to Uber, to Amazon (AMZN), the world’s most successful companies are implementing ‘data driven’ systems where data is constantly being gathered, analyzed and tapped into for insights.

At current, many companies are gathering data, but few are using it correctly. A 2015 study showed that 43 percent of companies “obtain little tangible benefit” from their data — and 23 percent “derive no benefit whatsoever.” from the data collected. From bakers to brokers, in the near future success will be defined by those who can effectively use their existing data to improve processes, and lower outgoings.

For data to be useful, it needs to be operationalized. The company needs to know exactly what they are looking for in their data, and which areas they want to improve. The two main drivers towards data being used as a resource are access and analysis.

Thanks to increasingly affordable IoT sensors, there is more context data available than ever. Customer behaviour, production, inventories, logistics, can all now be monitored with telemetrics. Those who are able to access the available data will have an important source of competitive advantage at hand. Thanks to increasingly affordable data analysis tools, such as predictive analytics software, data visualizations, analysis capabilities are now available not only with incredible performance but also at low cost.

Whereas data analytics used to be stuck in the world of global tech giants, the future for businesses of all shapes and sizes lies in data driven decision making. Being able to use data to personalize and improve services, offering customers exactly what they want, without having to ask them, is becoming a driver for success. It no surprise therefore that the demand for data scientists is predicted to soar 28% by 2020.

3. Bot Workers

Another key driver for success in the modern landscape is automation. In their book The Second Machine Age, Erik Brynjolfsson and Andrew McAfee explain how in the last 20 years computers have moved from simple information processing tasks, to cognitive tasks that were once a domain of the human mind. This opens a whole range of new application areas for machines and artificial intelligence.

This transformation has endless social, legal or economic implications. Like with data analysis, the move towards automation is an issue of when not if.

In the future, success will be decided by the companies which can make the shift to a digital automated operation the quickest and train their human teams to efficiently co-exist with their technological co-workers in the most efficient manner. Bots and AI will be the new generation of outsourcing, and automated processes will lead to lower hiring and manufacture costs, thus offering an overall market advantage.

As an investor, it is important to understand which stage of the adoption cycle particular companies are in relation to other companies in their industry. The extend will vary from industry to industry. The media industry for example has already performed a large part of the hike up the digitalisation mountain. In the financial industry, the Big Four are now actively preparing their accounting and tax graduates for the realities of working with bot coworkers. As each industry applies its unique resources, the human-machine combination will take on different forms. But independent from these specifics, the current topics that are being discussed industry conferences will provide a quick and clear overview on whether an industry or company is still in the discovery or already in the implementation phase. A look at the job boards of companies will provide further evidence.

Take Away

What does all of this mean for us as investors? In this new world we can’t just look at revenues and cost any more. We need to look broader and assess the different input factors. Content production for FB for example, curation for Netflix, software development for Slack — offer a company an advantage over their competitors. Moreover, we need to keep our fingers on the pulse for changes and for how those changes affect either cost structure of revenues. Vladan Joler talks of “invisible infrastructures”, and this pretty much sums up how our investor perspective needs to change.

This is just a short outline of what’s to come. Put simply, we are in an era where not everything is as obvious as it used to be. In this new landscape, effective investing means looking below the surface at the hidden structures within.

Martin Hoffmann is the CEO and Founder of Business & Investor Labs , an organization which helps decision makers and forward thinkers understand and analyze businesses of the Digital Age.

What hidden structures and what changes are you seeing? If you were modeling the financial statements of a particular business on a very simple excel sheet, what line would be replaced, or changed, or added by including these invisible infrastructures? Feel free to share your findings with me by sending a quick comment at Clarintelligence, and I will make sure to include it in future articles.

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