The economic value from data will be even greater than oil. But oil and data have very different characteristics.
It’s a claim you’ve probably heard many times – “Data is the new oil”. The concept is usually credited to Clive Humby, the British mathematician who established Tesco’s Clubcard loyalty program, as early as in 2006. But although data and oil both can generate value, the analogy has always been strained. Sitting on a pool of data doesn’t turn a company into a high-tech Saudi Arabia.
Data is more valuable than oil
It’s true. Data and oil can both generate considerable value. According to a report by Norwegian consultancy company Menon, the Norwegian data economy represents a yearly value of 150 billion NOK (£12,5 billion) in 2020. This value creation has the potential to reach 300 billion NOK (£25 billion) in 2030. That is approximately 7 percent of the Norwegian GNP. This would mean that the value creation from data will surpass the value creation from oil in 2030 in Norway, one of the world’s largest exporters of oil. The Menon report states that data in Norway will outpace oil, by far, if we also include other economics benefits data value will bring to society, not currently measured in GNP.
Data value creation is happening everywhere. The OECD estimates that in 2015, the global volume of data amounted to 8 zettabytes (8 trillion gigabytes). A staggering eight-fold increase since 2010. By 2020, that volume is expected to increase up to 40 times, as technologies including the Internet of Things (IoT) create vast new data sets. This sheer increase in quantity has pushed data up the political agenda, capturing the attention of businesses and policy-makers alike. The value of data is already a considerable economic contributor in most countries. In the UK, according to a UK Government report from 2018 – “The Economic Value of Data” – data-driven technologies will contribute over £60 billion per year to the UK economy by 2020.
But even if the value from data is already considerable, it is not the new oil. Oil and data have very different characteristics.
Increased use = increased value
Unlike oil, data will not be “used up”; data is infinitely renewable. The same data can be used and utilized in multiple ways, included in algorithms and programs, without decreasing value. On the contrary, the value of data will often increase when used and applied over and over again. Merging two or more complementary data sets can provide more insight than keeping them apart. It is also worth pointing out that data has no value by itself. Data value is created in a business when data is used as a contributing factor for improvement, renewal, and creation.
What is data?
It is difficult to estimate how data can provide business value without having a fundamental understanding of what data really is, and what “everything else” related to data is. All this “other stuff” is first and foremost technologies used to capture data, put data together, share data and analyze data. That is, everything that makes data valuable.
Data is data, as my professor used to say. It’s not really that difficult. Data can be everything from personal data like age, gender, and height, to data collected from sensors on ships or from the production process in a factory. You’ll find data in words, pictures, sound, ideas, facts, measurements, statistics or anything else that can be handled by computers (broken down to binary numbers, 1s and 0s).
Base- and system technologies
It may be helpful to group some key technologies when discussing data and data value creation. Digital21, a Norwegian government project initiative to speed up digitalization in society, has identified certain key technologies as particularly important to data value creation. They are referred to as base- and system technologies.
Base technologies are those that are not really useful for data value creation by themselves. It is only when used in conjunction with other technologies and programs they will contribute to creating data value. Examples would be sensors, blockchain, big data, and 3D-printing.
System technologies are those which comprise solutions at a higher systematic level where base technologies and other technologies and tools are joined together. Examples are cloud computing, robots, drones, Internet of Things (IoT) and autonomous systems.
5 key technologies
From these base- and system technologies, Digital21 has highlighted 5 technologies that will be crucial for businesses and society on our path to a more digital future. These technologies are artificial intelligence, Big Data, Internet Of Things (IoT), autonomous systems, and robotics and automation. The common denominator for all these technologies, and the most important ingredient, is data itself.
Creating value from data
Unlike oil, the value of data doesn’t grow by merely accumulating more. It is the insights generated through analytics and combinations of different data sets that provide the real value. In an increasingly networked world, the long-term advantage comes from maintaining a pace of innovation that keeps you abreast of tech trends and ahead of customer needs. When businesses use data to create value, they do this in order to streamline their operation, influence their ability to change or renew their business, or both. That is:
- Improve business operations. This could involve making business processes more effective, make more precise predictions, better – and quicker – customer response, more user-centric behavior, better quality decision making processes, etc.
- Influence own ability for creation: This could mean developing a new organizational model, new communication channels or develop completely new products and services.
It is clear that the use of data has the potential to enhance economic competitiveness and productivity growth across our economy, whether that is through fostering new products, processes, organizational methods and markets, or even enabling entirely new business models.
Three examples from the real world
Many companies and public initiatives are already demonstrating how they are unlocking the value of data. Here are three examples:
- Mowi, the largest producer of farm-raised salmon in the world, is rolling out a new sensing system that will gather real-time intelligence on the fish in its ocean pens. The advanced underwater sensing and software analysis platform will gather intelligence on real-time growth, weight distribution, feeding control, and automatic lice counting for salmon. It was developed by Tidal at X, the R&D innovation engine of Google’s Alphabet. By employing artificial intelligence to analyze big data, Mowi hopes to understand and respond to long-term trends in fish behavior and thereby further optimize ocean farming.
- UK initiative 5G RuralFirst launched a smartphone app in March called Me+Moo, which lets farmers track a “connected” cow and receive daily updates on the animal’s health and behavior. The system, which is being tested on cows at the Agri-Epi Center in Somerset, England, is funded in part by a UK government grant and supported by the tech company Cisco. The cows wear 5G-connected collars that send data to the app on everything from what they’re eating to how they’re sleeping. Farmers can see the info instantly, and pass it on to veterinarians or nutritionists. The technology could help irrigation systems to turn on at the optimal time of day, or cattle to be grazed on areas that provide the best nutrition. By improving efficiency, it will be possible to produce more food.
- In Azets’ customer portal CoZone there are about 6,300 managers approving 55,000 time reports every month. These managers are often very busy; approving time reports is not on the top on their priority list. Moreover, it is very natural for humans to make a few mistakes. Quite understandably, there are time reports with errors being approved incorrectly every now and then. This is obviously not desirable. Azets developed a solution, based on artificial intelligence and machine learning, which automatically helps these managers find mistakes in their own time reports – before they approve them. More about the solution here: How we use artificial intelligence to help 6,300 Nordic managers.
At the end of the day, data is just data. Nothing more or less. That is, until you feed it into something else that extracts new insights and value.
Then data can show its real value, which can turn out to be even more valuable than oil.