People have questions. Sometimes they find answers. More often than not they construct answers from what they find. More frequently still they construct provisional answers and muddle along. This has always been the case. But as with so many things, what we have always done is being thrown into a new digital light as we grapple with a landscape filled with new technologies and novel techniques. One thing we can say with confidence is that, relative to the past, we have managed to stir up even more questions and simultaneously we have made it more difficult to find or construct answers. We rock!
So the question that comes to mind is - Does it actually make sense to talk about "looking for answers"?
Well, not really.
Or perhaps we can say something a little less negative like "in a certain sense and then only partially".
People familiar with my penchant for logic-chopping will be rolling their eyes right about now. But I am being less obtuse than usual in this one case. My point is that it is only occasionally, and actually quite rarely, that the questions we have will encounter ready-made answers waiting just for them.
Conversations about intelligent information, and especially those undertaken with people we would like to engage as sponsors or customers, will often include declarations like "we want to return answers not results" or "we need to expose the answers already present in our content". When the conversations get serious, however, we need to add something like "of course, you realize that the number of possible questions is infinite and there is no way you can answer every question that comes along". In fact, the best you can do is answer a small percentage of the questions that might be raised. And even then you can only guess at which of the questions will actually get asked and thus justify the effort of preparing answers in advance. Depression soon sets in.
But we don't need to feel too bad about things. None of this is new. Communicators have always had to posit a reasonable set of questions and to fashion practical answers to those questions. And they are used to the idea that they will also provide a set of reference resources that users can use to construct their own answers to questions that no one would have ever thought up beforehand. At a higher level, businesses have always had to ask themselves questions such as what will the market look like next year or what features should our product have — questions for which answers are anything but easy or certain. And those businesses cannot be sure that they are even asking the right questions, especially in a marketplace that can change as rapidly as it can today. And still the information is evaluated, decisions are taken, investments made, and outcomes measured.
Embracing the brave new digital world, we might even start to feel a little better about things. Why? Because now we have the technologies and techniques that we can use to design, prepare, and deploy information in a way that is fundamentally more intelligent — that is granular in way that befits the subject being addressed and that can be profiled so it fits into specific situational contexts. And information in this state, intelligent information, can be retrieved and assembled by users in a multitude of ways and used to construct answers that exactly match their unique circumstances — that answer their questions.
It is the self-serve model taken to its logical extreme. One organization will share what they know about what they are offering in such a way that other organizations, partners and customers, can mix and match that content with their own and that of other organizations to then assemble answers that they, and their systems, can act on. This is what I was talking about, to a large and largely baffled plenary audience some 20 years ago, when I spoke of "managing knowledge in the fractal enterprise". It has taken that long for us to get to the point where everyone can approach their information in this way. Indeed today, under the driving momentum of digital transformation and the fourth industrial revolution, what is now a possibility has also become an obligation. The time has come to either embrace intelligent information or take up farming, and even then you are unlikely to escape it for long unless you choose to work a small plot by hand.
Applying a digital lens to our content and to the information services we have historically provided, we see that we can indeed expose the details inside the information in ever more precise and useful ways so that users can get on with constructing the answers they need. And when providing information that is granular and contextualized, we can also provide the tools that those users can use to accelerate their progress towards useful answers and to turn those answers into effective actions — at the end of the day the real objective. What tools we might provide would, like the information content itself, be components that are portable, can work in a user's environment, and interact with their tools or those they engage dynamically in the cloud. If we take this digital revitalization even further the intelligent information that is provided is also used as a way to channel the measurements taken on the outcomes of the resulting actions back to the original information manufacturers. In this way everyone learns; everyone gets better. And this feeds up into those business questions we touched on earlier about what a business should be endeavouring to do. This is what the fourth industrial revolution means for information and for information specialists.
Where have we arrived? We see, I think, that questions present a complex challenge and we cannot simply pretend that we can have all the answers ready beforehand. But rather than becoming overwhelmed by this recognition we also see that if we structure and contextualize our information in the right way, if we make it intelligent, we can move past this question, as it were, to get to where what we are doing is providing the tools so our partners and customers can construct the answers they need — using our information, their own, and that of others. We no longer try to serve up enough fish. Instead we provide the capability for our customers to fish for themselves. It is an answer that can scale and one that is ultimately far better for everyone.
Within my blog, I have been battering away at this topic for an embarrassingly long period of time. Below are some past posts that might be useful for people interested in exploring the question "how will intelligent information shape our future?" Note that when we look inside information, as we must if we are going to make it intelligent, then we find that we are looking at the content of that information and this explains the prominence of the term "content" in my discussions of making information intelligent.
- Content 4.0
- The Marriage of Structure and Semantics
- Defining Intelligent Content
- A Short Primer on Intelligent Content
- The Truth about Content
- The Birth of Content
In constructing answers to the questions that surface around the idea of intelligent information, we are inevitably confronted with the overarching question of what is the best way to proceed? Does our future lie with Artificial Intelligence (AI) and increasingly capable Natural Language Processing (NLP) services? Or does it lie in semantic technologies and the escalating precision and usefulness of knowledge graph tools and techniques? Or do we need to invest further in advancing and applying content technologies to making information intrinsically more granular and contextualized? The answer in this one case is easy. It's "yes". They are all needed and our progress on one track will need to feed into and inform the others and vice versa. It is in the co-evolution of these capabilities that we will see the real answer emerge. Then we will see what intelligent information really looks like and it is only then that we will have a full sense of how we should address the question of "how will intelligent information shape our future?"