The Map Is Not The Territory, But Is Useful, Anyway
Researching our way to understanding the relative importance of emerging technologies
I joined Traction Technology Partners recently as a contributing editor to help develop a research agenda that will shed light on emerging technologies and their adoption by and impact on the enterprise. And also, by extension, on the impact that such technologies have on those working in the enterprise, and on customers buying goods and services, increasingly mediated by these technologies. [Note: one aspect of that research is gathering intelligence from the community, so we’ve created a survey on topics related to this post. Please take the time to participate, here — Building a Map of Emerging Technologies — even if you don’t have time to read this entire post.]
I start out with an acute awareness of the dizzying changes going on in the enterprise. The promise of digital transformation, AI, cloud computing, and myriad other technologies of nearly unprecedented scale and scope is more like a tsunami than the gentle adoption graphs popularized by Geoffrey Moore in his Crossing the Chasm series. A new wave of innovation and disruption drops on our heads every week, it seems, rather than the old-school annual product drops of the early part of this century.
We have the need, however, to try to make sense of all the innovation, transformation, and disruption: to be able to characterize what’s going on with specific companies, products, and markets even though everything is in flux.
I’ve been embroiled in discussions with the folks at Traction Technology Partners about how to triangulate on all the swirling and chaotic goings-on in emerging technologies. My plan is to look at how others are trying to model the world of emerging technologies and their current and foreseeable impacts, as well as asking our readers for their perceptions about these technologies and models, too.
The philosopher Alfred Korzybski famously said¹
The map is not the territory.
The reason that he felt it was necessary to point this out is that ‘Korzybski held that many people do confuse maps with territories, that is, confuse models of reality with reality itself’². However, the fact that people can fall into this confusion does not mean we should steer clear of maps. Indeed, they are immensely useful, both in the original use of the term, like when you’re trying to figure out the best route to drive somewhere on Google Maps, and in the metaphorical sense, like a chart that clarifies the differences, similarities, and overlap among dozens of technologies being brought to bear on the needs and aspirations of the enterprise.
Here at Traction Technology Partners, we are starting with a blank slate. Or actually, we’re starting with a fairly undifferentiated but annoyingly long list of technologies, trends, users, and vendors. But more than a list — even one weighted by some evaluation of relative importance to some idealized reader — we really need a map.
Other People’s Maps
I am deeply lazy, and so I decided to take a look at the maps of some analyst firms, namely Gartner and Forrester, as well as the way that emerging technologies and their impacts have been visualized in the past decades.
Perhaps the single most used approach is to tier layers of technologies in a stack, where the user is positioned at the top of the model immediately in contact with various applications or user interfaces, and at the bottom are arrayed the most foundational of technologies. Here’s an example of that:
This approach is too limited, I believe, to cover the spectrum of emerging technologies, but there is a degree of up/downness in the models that others are using, nonetheless. Some things feel more foundational — for example cloud computing serves as a foundation for AI — even as AI becomes integrated into almost everything.
Gartner, in its Top 10 Strategic Technology Trends 2017 clumps things into three layers, ordered logically not based on relative importance: Intelligent, Digital, Mesh. Everything in the map is important.
Also, there may be a bit of a stack feel in this chart, with Mesh feeling like the foundation for Digital and Intelligent systems, perhaps.
There are only seven cells in this table, which makes it easy to grasp, but necessarily, a great deal of detail is buried in a cell like ‘Mesh Apps and Service Architecture’.
- I won’t detail each cell, but the ‘Intelligent’ row is all about AI enabling ‘intelligent systems that understand, learn, predict, adapt and potentially operate autonomously’.
- ‘Digital’ captures the blurring between digital and physical worlds, as with virtual and augmented reality. ‘Digital Twins’ refers to creating digital models of real world things — like pressure gauges in manufacturing plants — as a means of managing real world objects’ state and actions.
- ‘Mesh’ is an attempt to characterize the ‘dynamic connection of people, processes, things, and services supporting intelligent digital ecosystems’. That’s not only a mouthful, but it’s self-referential, too. I can’t knock Gartner for that, since everything is everything with these technologies: they all rely on each other in obvious and unexpected ways. ‘Mesh App and Service Architecture’ is another example of how what goes on in any cell of this table depends on every other cell, and vice versa. ‘The mesh app and service architecture (MASA) is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs and events to deliver modular, flexible and dynamic solutions.’ Got that? And their ‘Digital Technology Platforms’ is actually five platforms: information systems, customer experience, analytics and intelligence, IoT, and business ecosystems.
As I consider Gartner’s map, I realized I was looking at an org chart, as well. Not an org chart of the typical business applying these technologies and practices, but Gartner’s org chart: how the research practices are organized, with a research VP or director for each of the five platforms in ‘Digital Technology Platforms’, for example. Again, that’s not a knock of Gartner, at all.
Forrester is the leading competitor to Gartner in influence on business. And they, of course, have their own chart of the territory.
Forrester has three regions, which have a bit of a stack orientation, since ‘Supporting technologies’ certainly sounds like it supports the ‘Systems of engagement technologies’ and ‘Systems of insight technologies’ that sit above it.
The use of a ‘systems of’ approach has a long history. People have been making the distinction of ‘systems of record’, ‘systems of engagement’, and various other ‘systems of’ for decades. It feels like ‘systems of insight technologies’ is a replacement for and extension of the historic ‘systems of record’ where the core purpose has been extended from storage and retrieval of information to the analysis and insight from those resources.
Also note that in Forrester’s depiction of the chart (not included in my recasting) they included an arrow from ‘systems of insight’ to ‘systems of engagement’ with the label ‘insight improves action’, and on in the opposite direction reading ‘action enables more insight’. This is a dynamic characterization of a virtuous cycle involving the users of the systems, and demonstrates that while seemingly distinct the two sides of the top tier are actually tightly linked.
What’s Missing?
After digging into these approaches I came away feeling that something is missing, although the two approaches accomplish at least one important goal: they create a relatively small, 2-D map that a reader can grasp in 15 minutes or so, and which accomplishes the paradoxical and essential job of pulling all the emerging technologies into one map while dividing them into different and more-or-less well-defined neighborhoods. And of course, that map provides a way for Gartner to organize its research, and direct its subscribers to the appropriate content depending on their interests.
The first problem is that the approaches are basically static — models based on nouns — while the world seems more fluid than ever, so there should be more verbs. Or, more prosaically, perhaps we need to make the trends themselves part of the map, explicitly, like maps of the earth that show the prevailing winds and ocean currents as well as the continents.
Secondly, nothing is restricted to just one neighborhood any more. AI will be a key element of conversational interfaces directly communicating with users — Alexa, add toothpaste to the shopping list — but also central to delving into massive data derived from retail shopping, and squeezing inhuman insights out of it that would escape us.
Lastly, Gartner and Forrester portray their beliefs in what might be considered a ‘word of God’ mode. They show us their model and offer up a pitch for us to believe in it, or not. The arguments that various analysts in those firms had while developing the model are all redacted from the record. And the opinions of their subscribers — the community reading Gartner’s definitions and trying to conceptualize the relative merits of different elements of the models — are not present at all.
We don’t have a definitive solution, but intend to build a path to get there by a process of discussion with our readers, and a research panel that I am developing. And I anticipate that we will try to incorporate the thinking of that greater community into our models, and perhaps in a variety of ways.
As just one element of that, consider this bar chart from eMarketer, based on a survey in October 2016, which shows the results of a survey weighing the relative importance of various emerging technologies.
However we decide to ultimately draw our maps of emerging technologies, a central aspect will be the perception of those technologies by our community, both in terms of the relative importance of technologies, as in the chart above, but also in terms of the trends that form the ocean currents in the world we live and work in.
Today, we are starting with the first survey on this quest. Please take the time to participate, here: Building a Map of Emerging Technologies. It should only take a few minutes, and you’ll be helping us start the process that will lead to a map we all can use. I’ll analyze the results, and then we’ll take the next step.
- More or less. The actual quotation is ‘A map is not the territory it represents, but, if correct, it has a similar structure to the territory, which accounts for its usefulness.’
- Wikipedia.
