We've been talking about Adaptive Intelligence (AI) for a while now. As a refresher, AI is is the real-time, multidirectional sharing of data to derive contextually appropriate, authoritative knowledge that helps maximize business value.
Increasingly in inquiries, workshops, FLB sessions, and advisories, we hear from our customer insights (CI) clients that developing the capabilities required for adaptive intelligence would actually help them solve a lot of other problems, too. For example:
A systematic data innovation approach encourages knowledge sharing throughout the organization, reduces data acquisition redundancies, and brings energy and creativity to the CI practice.
A good handle on data origin kickstarts your marketing organization's big data process by providing a well-audited foundation to build upon.
Better data governance and data controls improve your privacy and security practices by ensuring cross-functional adoption of the same set of standards and processes.
Better data structure puts more data in the hands of analysts and decision-makers, in the moment and within the systems of need (eg, campaign management tools, content management systems, customer service portals, and more).
More data interoperability enables channel-agnostic customer recognition, and the ability to ingest novel forms of data -- like preference, wearables data, and many more -- that can vastly improve your ability to deliver great customer experiences.
There’s no doubt that, to consumer marketing professionals, data about the users of mobile network are highly valuable. But AT&T is finding that enterprise application designers, corporate security & risk professionals, corporate trainers and CFOs are very interested in this data as well - so much so that the US-based network operator is turning access to and collaboration on its data into a new business service.
Under the guidance of Laura Merling, VP of Ecosystem Development & Platform Services (and formerly of Mashery), AT&T Business Solutions is embarking on an ambitious plan for sharing its data in a secure programmatic fashion leveraging RESTful APIs. It had previously shared it data in a more informal fashion with selected partners and customers but found this approach difficult to standardize and repeat on a larger scale. It also has participated in data collaboration efforts such as the well-known hackathon with American Airlines at South by Southwest earlier this year.
There is a reason the phrase, “beauty is in the eye of the beholder,” has held significance and power in our society for so many generations. And in that phrase is a lesson for all of us about business analysis. The power of different points of view examining a given set of inputs is key to truly understanding what lies before us and seeing the new possibilities and different threats looming.
Sit silently in a museum listening to the patrons take in just a single painting and within a day you will hear a hundred different insights, many of which you didn’t see before. Insights that show you things in that artwork you never would have seen, such as the way greens and reds are mixed to create hues that don’t invoke their origins, the style of brushstrokes used that convey depth and how a pattern viewed up close can be very different than the whole. So much insight doesn’t stem from the painting but from the varied experiences, backgrounds, cultures and histories the observers bring with them. The same is true in data analysis. It’s through different points of view that something can be fully analyzed. Each person brings their varied experiences (their data) to the analysis.
As businesses we tend not to sit silently and take in what others see about ourselves and our data. We tend not to expose our data at all to our partners, trusted third parties or potential collaborators (like our customers) and by not doing so, they cannot combine their data with ours and uncover things we cannot see. As a result, we cannot see the broader picture. And this leads to bad business decisions based on a myopic point of view.
With the employer mandate delays being the latest setback to U.S. president Obama's push for national healthcare, it's worth looking at how other countries are successfully tackling the same problem. The United Kingdom has had nationalized healthcare for years, and one of the things that makes this effort so successful is its approach to data collaboration — something Forrester calls Adaptive Intelligence.
While the UK hasn't successfully moved into fully electronic health records, it has in place today a health records sharing system that lets its over 27,000 member organizations string together patient care information across providers, hospitals, and ministries, creating a more full and accurate picture of each patient, which results in better care. At the heart of this exchange is a central data sharing system called Spine. It's through Spine that all the National Health Service (NHS) member organizations connect their data sets for integration and analysis. The data-sharing model Spine creates has been integral in the creation of summary care records across providers, an electronic prescription service, and highly detailed patient care quality analysis. As we discussed in the Forrester report "Introducing Adaptive Intelligence," no one company can alone create an accurate picture of its customers or its business without collaborating on the data and analysis with other organizations who have complementary views that flesh out the picture.
As an analyst on Forrester's Customer Insight's team, I spend a lot of time counseling clients on best-practice customer data usage strategies. And if there's one thing I've learned, it's that there is no such thing as a 360-degree view of the customer.
Here's the cold, hard truth: you can't possibly expect to know your customer, no matter how much data you have, if all of that data 1) is about her transactions with YOU and you 2) is hoarded away from your partners. And this isn't just about customer data either -- it's about product data, operational data, and even cultural-environmental data. As our customers become more sophisticated and collaborative with each other ("perpetually connected"), so organizations must do the same. That means sharing data, creating collaborative insight, and becoming willing participants in open data marketplaces.
Now, why should you care? Isn't it kind of risky to share your hard-won data? And isn't the data you have enough to delight your customers today? Sure, it might be. But I'd put money on the fact that it won't be for long, because digital disruptors are out there shaking up the foundations of insight and analytics, customer experience, and process improvement in big ways. Let me give you a couple of examples:
Every company generates data that would be of significant value to its customers, partners and potential partners; information that could be combined with insights from this ecosystem, public data and other sources to generate significant new discoveries, products and business values. But making our data available, easily consumable and getting payback for sharing it are significant hurdles.
Over many years we have built up an ever-more complex web of security, legal and data management practices that make it nearly impossible to share valuable info between companies in an open marketplace style – which is exactly what is needed to open up this value.
But it doesn’t have to be this way. There is a new approach that leading enterprises and governments are taking today that is significantly simpler, more manageable and empowers companies to share their key data more freely, opening up massive new market opportunities for all. Here's how a few Forrester clients are taking advantage of this new model: