This is surprising given the estimated value of data. In March 2020, The Economist estimated that it is worth between US$1.4-2 trillion in the US alone. Given such valuation, why are companies not doing more to seize on the opportunities?
This question was the focus of a webinar discussion between Paul Sonderegger, senior data strategist at Oracle, Andrei Hagiu, associate professor of information systems from Boston University’s Questrom School of Business, and myself. We explored how companies should rethink their strategies and operations to unlock the value of the data they already collect and how they can enhance processes to be more sustainable and effective.
A data economy hidden from plain sight
As data continues to grow in importance and becomes a valuable resource that companies need to access easily, many struggle to navigate the sheer quantity of data they collect or produce. In order to create value—rather than complexity— from this data deluge, companies must think of data as fundamental to the production of digital goods and services, and not a by-product.
Rather than be buried within different silos throughout an organisation, Mr Sonderegger believes that data should be at the centre of all companies. To do this, however, organisations need the right technology foundations, such as autonomous databases that Oracle can deploy. They are important to avoid employing data wranglers to sort out the deluge.
Once the internal supply of data is sorted, firms have to understand where the demand is coming from. Today, most companies have a hidden data economy within their ecosystems—the data they produce is used primarily by themselves. Organisations need to rethink this strategy and devise models to extract the value of data, which comes from the insights harnessed from it in the form of big data & analytics as well as artificial intelligence (AI). Many companies will realise more value can be generated by allowing data to be used by external parties, instead of exclusively by themselves.
“The strangest characteristic of data is that most of it never goes to market. Data fulfils the literal economic textbook definition of capital.”
Paul Sonderegger, senior data strategist, Oracle
Mr Sonderegger suggests three key aspects companies should focus on to unlock the hidden data economy: liquidity, data productivity, and data security. “You kind of want your data to be a shapeshifter. Data has no intrinsic value of its own. It can only generate value or decrease cost when it is being applied to a process or a decision.” However, these value-adding activities need to be within the guardrails of compliance and risk management as data regulations become increasingly prevalent to protect all stakeholders.
Creating competitive advantage
Cloud-based services are fuelling the data deluge. Data can be collected and analysed in real-time and at scale, allowing companies who have learnt how to create value from data to enhance and personalise their products at much faster rates. Most companies are of the view that such data-enabled learning leads to a competitive advantage.
“The key question here is asking, for any company of any size: if we do have data-enabled learning, under what conditions does this kind of data-enabled learning actually lead to defensible competitive positions?”
Andrei Hagiu, associate professor of information systems, Boston University Questrom School of Business.
Mr Hagiu, however, cautions against making such an assumption and suggests that data-enabled learning creates a defensible competitive position for companies only upon fulfilling seven conditions, He considers two of those conditions to be critical: the value-added nature of data for customers and the speed of incorporating data insights into products and services. Each of them help to level the playing field for small- and medium-sized enterprises to access copious amounts of data, resulting in the barrier to entry for data-intensive businesses to be lower than many believe.
“If you find some datasets that you can buy, use that to train your algorithm; and use a few customers to get some novel insights—you’re in business,” explains Mr Hagiu. This simple approach to using data—and learning from it—wouldn’t be possible if we all had to be data scientists to interpret the findings. Thankfully there are tools available with intuitive user interfaces and strong visualisations, where machine learning does the heavy lifting to create predictive insights which business leaders can use. And if your also trying to wade through the data deluge, tools like Oracle’s analytics cloud goes one step further, Mr Sonderegger explains, by giving customers ubiquitous access to all data types, whether it’s legacy mainframe or a modern web application.
Key takeaways:
- Many enterprises will not survive unless they build a business model which better utilises the value of their data. To compete, companies need to collect more data and use it to make informed decisions about business processes, customer engagement, innovation and evolving business models.
- Data is capital and should be viewed in terms of supply and demand. Companies need to look beyond internal uses of their data. More value may be generated from external parties who can create better value from the insights generated.
- Data-enabled learning must be combined with network effects to create competitive advantages. Data learning alone will not create a competitive advantage due to the data deluge. Instead, the most valuable and profitable businesses will be built on regular network effects and data-enabled learning.
Watch the full webinar for more insights into the hidden data economy
