Innovation consultant Hans Villarica shares how companies can deliver and monetise new data-driven services to users
Data monetisation is at a standstill. While bankers, marketers and insurers have successfully sifted through Big Data to learn how to improve their decisions and offerings, the payoff has remained more elusive for those uninvolved in data analytics.
In particular, data architects, who have chosen to capture value by designing data sets to engender new experiences, have hit a wall. And it’s not for lack of trying.
This underrated data monetisation path, which prizes experiences over insights, involves many more prerequisites and risks. It requires users, developers, governments and companies to play well together. It requires that these parties be incentivised to let data flow, to foster interoperability of connected devices, to address people’s privacy and security concerns, and to develop legal frameworks and technological standards that don’t inhibit innovation. Through it all, they need to envision human-centred experiences and stay committed to making them real.
One thing going for the data architect’s effort is money. Data analytics can optimise existing operations, but designing data experiences can deliver fundamentally new revenue streams worth billions. For example, by offering a data-driven home-security experience, where connected devices intelligently ward off intruders and notify homeowners, neighbours and the police, an estimated $31 billion in annual service revenues can be earned. Even better, minimal expenses for new product development are needed, as data experiences can be fuelled by existing data from the likes of Facebook (social connections), Philips Hue (home automation) and Apple iPhone (personal location). Companies would do well to work with corporations and developers to craft their own data sets, since the so-called innovation involved in the data experience economy isn’t new at all. It’s called sharing.
So who can pull this off? No one can. But there are players who are better positioned to lead this necessarily collaborative effort. The initial challenge for prospective data experience providers is to quickly assess their companies’ capabilities and, since data cuts across industries, to subsequently identify threats, partners and frenemies that may go beyond their traditional set of competitors, substitutes, complements and alternatives.
To do this analysis well and efficiently, it’s essential to use a data experience framework that covers three prime capabilities—user affinity, data vision and innovation engine. Factoring in user affinity ensures that companies can identify and solve strong user needs. Considering data vision ensures that they can mine and combine relevant quantitative and qualitative data to power these solutions. And examining their innovation engines ensures that these solutions can reach the market.
After sizing up companies at a distance, the real hard work of monetising data-driven experiences takes centre stage: building trust to create bridges across people, institutions and the many devices between them. And, unfortunately, there’s no shortcut for this. It will entail building solid connections. It will require a mindset shift from competition to cooperation, from quibbling with partners on margins to co-creating new revenue streams together. Still, though the rewards will likely take some time and patience, as with most relationships, they will also be very real.