Are You Using the Right Data to Power Your Digital Transformation?
Most legacy firms rely on episodic data, generated by discrete events such as the shipment of a component from a supplier, or the sale of a product. The explosive power of digital platforms, on the other hand, stems from their use of interactive data, streamed by users interacting with platforms. Tapping the power of interactive data is more and more possible for legacy firms now, thanks to sensors and the internet of things (IoT). Shifting from episodic to interactive data is not easy. Yet it is an essential part of any legacy firm’s digital transformation initiatives. To remain relevant in the modern era, legacy firms must find ways to tap the power of real-time, interactive data.
Data per se is not a new, but its power to drive business value in modern times is unprecedented. This power is most evident in the business models of digital platforms such as Facebook, Amazon, and Google. But, for a vast majority of legacy firms operating with value-chain-driven business models, this newfound power of data remains untapped. A key reason that’s holding them back is their traditional approach to collecting and using data.
Most legacy firms rely on episodic data, generated by discrete events such as the shipment of a component from a supplier, or the sale of a product. The explosive power of the digital platforms, on the other hand, stems from their use of interactive data, streamed by users interacting with their platforms — such as by posting likes on Facebook or searching on Google. Facebook and Google together own almost 50% of the $200 billion digital advertising market in the U.S. because of such data. And as their business models are anchored on the internet, all of their data is interactive. Not all legacy firms can expect to derive value from data the way Facebook and Google have. But they can do far more with data than what was traditionally feasible. Tapping the power of interactive data is possible for legacy firms too, thanks to sensors and the internet of things (IoT).
Sleep Number is a great example of a legacy company that’s embracing the power of interactive data. The company uses sensors in their mattresses, which generate streams of interactive data on a user’s heart rate, breathing patterns, and body movements during sleep. Using this data, the company makes its mattresses unique to each user. But sensors don’t have to be physically embedded within products to be useful — they can be web- or app-based. For example, The Washington Post generates interactive data when readers browse for news and opinion articles on their website. Allstate Insurance’s app-based sensors stream data on how users drive their vehicles. Today, sensors are ubiquitous and available in several forms, making it possible for legacy firms to capture and use interactive data in unprecedented ways.
Attributes of Interactive Data
Two attributes of interactive data make its role in modern times far more expansive than episodic data: its ability to generate a new class of insights, and its amenability for widespread sharing. Together, these attributes empower legacy firms to offer rich digital experiences and expand business value propositions.
A New Class of Insights
Data has always provided insight. Episodic data on mattress sales, for instance, provides insights on what brands are selling, in which geographies, and in which segments. Typically, such insights come from analyzing aggregated after-the-fact data across categories of products, geographies, or segments. Such insights have typically been shared in daily, weekly, or monthly reports.
Interactive data, on the other hand, provides real-time insights in addition to after-the-fact insights. Interactive data from mattresses, for instance, generates insights on how well a user is sleeping in real-time. Such insight can be used to, say, dynamically adjust the contours of a mattress to improve sleep quality. Real-time data also ultimately turns into after-the-fact data for retrospective insights. But these after-the-fact insights are on pin-pointed subjects, such as the sleeping patterns of each individual user. Pinpointed insights generate rich user profiles, such as each user’s distinctive quality of sleep, and the unique factors that influence it. Sleep Number plans to use such insights from their data to identify chronic sleep issues like sleep apnea and restless leg syndrome, and eventually predict other health conditions such as heart disease and strokes. It has recently partnered with Mayo Clinic to further their sleep science research, and plans to expand its business scope from being a mattress producer to a company offering wellness services.
Ongoing streams of interactive data can further refine individual user profiles. Cloud technologies allow firms to maintain vast repositories of profiles and ongoing real-time data sourcing from each sensing unit. AI, machine learning, and data analytics further amplify the insight-building processes for each profile. Consequently, firms can leverage new insights from interactive data to offer more customized product features and new experiences for customers, and to generate fresh opportunities for value creation.
Amenability for widespread sharing
Legacy firms closely guard their episodic data for competitive reasons. They rarely share this data externally. Even internally within firms, their aggregated analyses and reports are often shared selectively.
Real-time interactive data, on the other hand, can be shared widely, even with third-party entities. In fact, sharing amplifies its value. Real-time interactive data on a user’s sleep from smart mattresses can be shared with a host of external objects in the room — such as lighting systems, music systems, or television sets. By turning off lights, music, and televisions once it detects that a user is asleep, the mattress offers users a superior sleep experience. Similarly, real-time interactive data from sensors that detect the likelihood of frozen pipes in homes — if shared with service providers designated by a homeowner, can help insurance companies initiate preventative action, and avoid costly damage. As more connected entities become available to complement user experiences, the more real-time data’s value can be amplified when shared with those entities.
Real-time interactive data is inherently transient. Its value from sharing exists only in real time. With mattress users, the value is in shutting off lights or music the moment they fall asleep; for homeowners, it is before frozen pipes begin leaking water. This value to external entities disappears after the fact, as they can no longer meaningfully act on that data. This transient nature of real-time data makes it particularly amenable for sharing with external entities. Competitive concerns associated with sharing stored after-the-fact data do not apply here. Moreover, because sharing amplifies its value, there is an added incentive for firms to share real-time data.
Real-time interactive data sharing is also possible because of an explosion of connected IoT devices in recent years. Around 30 billion connected assets are expected in the coming years, creating vast opportunities to tap interactive data for richer customer experiences and business scope expansion. Home insurance companies, for instance, can enlarge their business scope from compensating losses to also preventing losses. Future revenues then are not restricted to risk estimation capabilities and profitable policies. They grow from new data-driven services that prevent losses and offer timely repairs.
Shifting from episodic to interactive data is not easy. Yet it is an essential part of a legacy firm’s digital transformation initiatives. To remain relevant in the modern era, legacy firms must find ways to tap the power of interactive data.