There are many mainly abstract concepts that bring potential benefits that are impossible to quantify, such as “digital transformation.” Data, however, is not so abstract – it is real, it is tangible, and the benefits understanding and leveraging it brings to enterprises can make a measurable, notable difference.
Call it what you will, but data “disruption,” as described in a recent McKinsey report, is a great way to describe the impact of a well-tuned, innovative data analytics strategy that turns corporate thinking on its head.
It’s notable that these are still the very, very early days of data disruption, and most organizations have not fully realized, let alone recognized, its potential. “Most companies are capturing only a fraction of the potential value from data and analytics. Our 2011 report estimated this potential in five domains; revisiting them today shows a great deal of value still on the table,” write a team of McKinsey analysts led by Nicolaus Henke. “The greatest progress has occurred in location-based services and in retail, both areas with digital native competitors. In contrast, manufacturing, the public sector, and health care have captured less than 30 percent of the potential value we highlighted five years ago. Further, new opportunities have arisen since 2011, making the gap between the leaders and laggards even bigger.”
Notably, Henke and his team are adamant that the potential of data disruption “has not been overhyped.”
So, the data revolution is coming, where and how will it deliver? The McKinsey team provides some clues, describing six key areas in which data disruption will likely – or already is, in some cases – making its mark:
Orthogonal data opens up new ways of looking at opportunities and problems. There are many types of data from many different sources, and as organizations open up to new data, they will open up new avenues of business. “In industries where most incumbents have become used to relying on a certain kind of standardized data to make decisions, bringing in fresh types of data sets to supplement those already in use can change the basis of competition,” Henke and his co-authors observe. Insurance companies, for example, are beginning to discover the power of orthogonal data. “New companies have entered the marketplace with telematics data that provides insight into driving behavior — this is orthogonal to the demographic data that had previously been used for underwriting.”
Data opens up market-driven platform-based services. Big data is giving rise to digital marketplaces that don’t produce goods or services themselves, but provide data-driven solutions that bring producers and consumers together to address market needs. “Platforms such as Uber, Lyft, and Chinese ride-sharing giant Didi Chuxing have been able to expand rapidly without acquiring huge fleets themselves, making it easy for new drivers to put their own underutilized assets to work,” the McKinsey team observes. Such platform-based businesses employ data and analytics to deliver data “in real time and on an unprecedented scale—and this can be transformative in markets where supply and demand matching has been inefficient.”
Data and analytics enable “radical personalization.” The ability to parse and analyze large data sets paves the way to “micro-segment a population based on the characteristics of individuals,” Henke and his co-authors relate. A breakthrough application area is healthcare, they illustrate, offering “a more complete view of the patient,” enabling more targeted treatments and, in the process, saving money.
Data and analytics opens up new possibilities for discovery and innovation. “Throughout history, innovative ideas have sprung from human ingenuity and creativity,” the McKinsey team relates. “But now data and algorithms can support, enhance, or even replace human ingenuity in some instances.” Data and analytics, they illustrate, “can test hypotheses and find new patterns that may not have even occurred to managers. Vast amounts of email, calendar, locational, and other data are available to understand how people work together and communicate, all of which can lead to new insights about improving performance. In product innovation, data and analytics can transform research and development in areas such as materials science, synthetic biology, and life sciences.”
Data greatly enhances decision making. Algorithms may never replace human decision-making, but they can certainly help better target it. “Data and analytics can bring in more data points from new sources, breaking down information asymmetries, and adding automated algorithms to make the process instantaneous. As the sources of data grow richer and more diverse, there are many ways to use the resulting insights to make decisions faster, more accurate, more consistent, and more transparent.” This can play a role in all types of decisions, from avoiding medical errors from drug interactions to providing greater transparency to hiring decisions.