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This year try out a new perspective on data, people, projects, and innovation.


It's January of a new year! It's the time for new year's resolutions and fresh resolve to achieve those goals that remained elusive at the end of last year. Achieving a challenging objective often requires taking a new perspective. Since my new year's resolution is to blog more, I wanted to start out the year with a blog about 12 key areas where we've seen first-hand, working with organizations around the globe, the impact that taking a new perspective can have.

A well-known saying, probably misattributed to Einstein, says that "insanity is doing the same thing over and over again but expecting different results." If there's an objective you had trouble achieving last year, maybe this year you need to come at it from a new perspective.


Don't go insane! Try doing something different in 2022. Below are 12 things that I believe frequently get tackled in the wrong ways - and how I think we need to change our thinking if we are to achieve our goals. Note: Each of these will get elaborated on in a future blog post. Post in the comments if there's one you're particularly eager to learn more about and I'll prioritize my blogging based on the ones you ask for.

Firstly, the world increasingly runs on data, but we're storing data sub-optimally and leveraging it poorly. Here are three data-related areas where we need to change our perspective in order to get the most benefit:

1. Data Management. We have spent decades thinking of data as tables in a database or rows and columns in a spreadsheet. This works well for storing data but not for leveraging it. The value in data is not in being able to query for what you have but in being able to see how it's all connected. We need to shift away from thinking of our data as individual tables and towards realizing it's one big network. We need to mine it not by building lists but by making maps.

2. Data Analysis. The rapid growth in artificial intelligence has led to a focus on using computers to automate human intelligence. This will work wonders in certain areas, but not when it comes to complex challenges that require intellectual flexibility and creativity instead of just brute force. Of course, computational brute force is a great tool to have in the tool kit, but we must construct analysis systems that treat it as such. These human-in-the-loop systems use AI to augment the work of subject matter experts, not automate them.

3. FAIR Data. FAIR stands for findable, accessible, interoperable, and reusable. It's an acronym that almost always precedes the word "data", but we're doing ourselves a huge disservice if data are the only thing we try to make FAIR. We need FAIR people. We need FAIR algorithms. We need FAIR visualizations. We need to shift our perspective from the narrow view of FAIR data towards the broader goal of FAIR ideas in all their incarnations.

The only resource more valuable than data is people. Our thinking here would benefit from some new perspective as well. Below are three ways that people come together, often ineffectively, where a new perspective can dramatically change the nature of what can be produced:

4. Meetings. Ugh. Just the word can produce a sinking feeling in one's stomach. We tend to use meetings as a forum to disseminate and consume information instead of as an opportunity to produce it. When you are able to shift the way you run meetings towards co-production some amazing things can happen and people not only start enjoying the meetings, but they start to find them to be incredibly productive, as happened for Climate-KIC's Thinkers in Residence who participated in a knowledge production meeting every week for a year. What's the trick? Take a network approach to meeting facilitation and use technology as a mental prosthetic to help you keep the network dynamics in mind. Oh, and replace individual introductions with networked introductions instead - you'll never go back.

5. Teams. It's easy to think of teams simply as groups of people represented by org charts. This hierarchal perspective of teams does a disservice to the complex dynamics that make teams great and ignores the fact that a team is more than just its people. Those people exist not in a vacuum - they are in a particular context leveraging particular assets to achieve particular goals. To truly unlock the power of the teams we need to see them as networks not org charts. And we need to build those network representations based not on the standard social network analysis of who they know but based on what they know. Then we need to help the team become an analogy machine - making the non-obvious connections that bridge individuals knowledge in novel ways. The right network maps can act like roadmaps for this - showing exactly the analogical paths to travel down to converge this way. This is a different perspective not only on the nature of teams, but of facilitation, which gets its very own item lower down.

6. Communities. Have you tried building a community? It's hard. Part of the reason it's hard is because it's not the same thing as simply assembling a network. In the items above I've talked a lot about the value of shifting to a network perspective, but when it comes to communities this shift alone isn't sufficient. Often when we first adopt a network perspective we focus on the nodes. But the reality is that the magic of networks happens along the edges - the  connections between nodes. When we attempt to build a community it's easy to worry if you have enough stuff - whether you've hit critical mass based on the number of people involved. Instead we need to focus our metrics for success on the interactions, and the nature of those interactions. It's only by shifting one's perspective this way - from the transactional to the relational - that any "network effect" can actually be achieved.

When smart people informed by rich data work together effectively - through truly collaborative meetings, convergent teams, and connected communities - they can produce some amazingly successful projects. Managers and funders get excited when they see this happen and naturally want to amplify the impact of individually successful projects by building large "synergistic" portfolios of many projects aligned toward a common goal. But synergy is much more easily said than achieved, which is why it has become a near-meaningless buzzword. Here are three types of aggregate endeavors that need to be approached in new ways if there is ever to be real synergy:

7. Open Science Collaborative Research Initiatives. There is no doubt in my mind that this is the way of the future. We've plucked most of the low-hanging fruit that science has to offer. If we hope to solve hard problems like lessening the global burden of disease and finding more sustainable ways to live on the planet, we're only going to do it through increasingly collaborative endeavors that do to scientific problems what Wikipedia did to the encyclopedia. But my work at Exaptive has, for over a decade, given me a front-row seat to watch many large-scale collaborative research projects fail to achieve the level of impact they aspired to. These projects aim for collaboration but are built up from researchers that have spent their entire careers within a system of grad school, publication, and tenure that almost exclusively rewards individual contribution with money and recognition as zero-sum scarce resources. Many people recognize this and are working to change the system, but it won't change over night. I see a way to make an immediate impact in this area without waiting for the system to be entirely restructured. It involves shifting our perspective away from valuing just the primary scientific outputs (e.g. did your drug cure the disease, or did your device save energy?) and looking more closely at the hidden value of the tangential outputs that were produced on the way towards the primary goal. (e.g. how did you harmonize that dataset, how did you make that machine learning model work with satellite images?) It's going to be a long time before scientists and researchers can feel comfortable being less precious with their coveted primary outputs. And rightly so - their livelihood depends on it. But these secondary outputs are ripe for the taking and there are legions of under-appreciated grad students, data scientists, and humanists, whose livelihood would benefit greatly if their supporting work was more broadly disseminated.  

8. Enterprise Innovation. The change in perspective discussed above for scientific initiatives is just as valuable when applied to enterprise innovation efforts. Many companies are now setting up "innovation labs" but often these labs suffer from too overt a focus on the problems their business currently face than on the underutilized knowledge they have accumulated from the past problems they have already solved. The change in perspective required here is to ask your subject matter experts less about their actual subject matter and more about the methodologies that they have become skilled in through the pursuit of that subject matter. This shift is subtle but powerful - it extracts horizontal knowledge from vertical expertise. And that horizontal knowledge is what innovation labs can use repeatably to solve new problems, bring new products to market, and have huge impact - like when Stephen Phillips from AT&T Labs realized that the algorithms used in the telecommunications industry to reroute calls when there were network failures could be used to help heal damaged ecosystems

9. Startup Accelerators. Just like scientists are worried about getting scooped and this can work against collaboration, startup founders are very protective of their nascent business ideas, which can limit the thought partnerships they are open to. They tend not to want to collaborate with projects tackling a similar area, and they tend to think that projects in a different area don't have much to offer them. This is again the trap of a perspective focused on the vertical market instead of the horizontal methodologies. All startups need to make something, sell something, drive messaging outside the company, and maintain morale inside the company. Good accelerators and mentorship programs, like the MIT Venture Mentoring Service, recognize the translatability of these horizontal skills, but it can still be a challenge to connect ventures to the right horizontal knowledge at scale in a reliable way. Taking a network perspective, as we've been discussing, can make it easier and more scaleable. Map the horizontal knowledge of your ventures and your mentors and then focus on driving interactions based on the edges between them.

Why do we care so much about the nine items mentioned above? They are all tangram shapes in the giant Tetris puzzle that is innovation. We believe that if we can connect the data, the people, and the projects - connect them in just the right way - we can produce not just more ideas, but truly new ideas, and we can not only generate these ideas, but execute on them as well. We can execute on ideas that not only allow companies to bring compelling new products to market but allow governments to vanquish this pandemic and avoid the next one. We can execute on ideas that not only improve the health of every person on the planet but improve the health of the planet itself. We desperately need these innovations, but to achieve them we need to think differently about some of the core processes we associate with innovation, and challenge our default assumptions about them:

10. Problem Solving. The standard question posed to any new entrepreneur is "What problem are you trying to solve?" Focusing all your work efforts with the paradigm of solving problems is certainly a good way to make money but it's not what leads to radical innovation. Hindsight is 20/20 so it's always easy to look at successful innovations and retroactively find a problem that they successfully solved, but rarely was that the actual impetus for the innovation. GPS has allowed ride sharing services like Uber and Lyft to completely disrupt the transportation industry, but making it easier to catch cabs was not the problem the US Department of Defense was trying to solve when they started putting GPS satellites into orbit. If we are hoping to advance society by fostering entrepreneurship and intrapreneurship, expecting these efforts to lead to breakthough innovations, we need to change the question "What problem are you trying to solve?" to "What underutilized resource are you allowing to be better utilized?" Was Wikipedia's success that they solved the problem that encyclopedias weren't comprehensive enough, or was it that they realized that there was a vast global cognitive surplus that was barely being utilized? Was YouTube's success because they solved the problem of not enough television programming to watch, or was it because they allowed every person with an internet connection to better utilize their creativity? The questions we ask ourselves are important because our lives are nothing more than the enacted answers to the questions we ask. If all we ask of ourselves and others is to solve problems, we will - but we won't really move the needle on the status quo. We'll make better things, but we won't make truly different things. Try this for a month: instead of looking for unsolved problems, look for untapped potential - and tell me if it doesn't change the way you see opportunities for innovation.

11. Facilitation. If we are to successfully make the shifts of perspective described in this post - whether related to making better use of data, achieving increased convergence of people, or finding more impactful synergies of projects - it will require a shift in perspective on the role of facilitation, and of facilitators. Currently, being a facilitator is pretty much a thankless job. It's a role that tends to be equated with time-keeping, minute-taking, and action-item-assigning. These tasks are useful, but none of them are really facilitation. Facilitation is about pulling at the links in the network of ideas to bring distant nodes closer together. And when those nodes get close enough, it's about being a good enough "translator" to help the people on each of those nodes see the potential and not just push them apart again. This idea of facilitation as translation belongs to Dr. Alicia Knoedler, who used to be Director of Team Innovation at Exaptive and I'm proud to say recently got selected by the NSF to lead the Office of Integrative Activities. Alicia's not the only skilled facilitator who is working hard to find a better word to replace "facilitation". Dr. Pips Veazey, who helped to start the International Network for the Science of Team Science kindly included me in a discussion group of professional facilitators all searching for a better way to describe what they really do. Dr. Christine Hendren kindly included me in a similar discussion at a meeting of her INTEREACH group. There was no easy consensus. In these meetings, when I was asked to describe facilitation, I borrowed a phrase from anthropology that I learned from my wife - it's about making the strange familiar and the familiar strange. Good facilitators do this on a regular basis, and with some amazing results. But they rarely get the credit for the Ah-ha! moments they produce. We won't be able to truly shift our perspective on facilitation until we can also see the facilitator as a critical catalyst in the complex reaction that is innovation.

12. Incentivization. This whole blog post is about change. It's about changing our individual perspectives and collectively changing the way that we work. As a general rule people don't like change, so we need incentives, both positive and negative. Capitalism provides these through money and competition. If you do the right thing you'll get rich and if you do the wrong thing you'll be devoured by the circling sharks. There's only one problem with this approach: it doesn't really work anymore. I think that capitalism worked well when capital actually mattered. That is, it used to take a lot of money to make a lot of money, and competition was grounded in a world of limited resources and zero-sum games. These things are no longer true in a knowledge economy. In a knowledge economy two people can put an app in the appstore that makes millions with hardly any capital investment at all. In a knowledge economy where "things" are more virtual than physical and it costs mere pennies to store their ones and zeros, we find ourselves closer than ever before to a post-scarcity world where if I give something to you it doesn't mean that I lose the ability to give it to someone else too. Twenty years ago, when I loaned you a CD or gave you a print of a photograph, I lost the ability to loan that CD to anyone else or show anyone else that picture. The mp3 and the jpg have made that predicament laughable. Yet we still operate within a system that assumes our resources are finite, our games are zero-sum, and the distribution of money is the only arbiter. We need only look at how our global money is distributed to see there is a problem. These views used to be quite controversial - called "heterodox" and ostracized by mainstream economics. But there are a growing number of heterodox voices - from academic essays to popular books to blog posts about Star Trek - putting capitalism on notice. I am interested in these conversations because I believe that all of the ideas in this blog post rely on figuring out how to reward cooperation not just competition. Ant colonies are able to perform some amazing feats, but it's because they are rewarded collectively for having the fittest colony, not individually for having the fittest ants. I think our species needs to become more ant-like if our global colony is to thrive. We just haven't figured out the incentives that drive collective action nearly as well as we have the ones for individual action. I feel optimistic in this area because I believe the virtual world of the knowledge economy provides a unique environment in which we can construct completely new currencies and rules for using them, and we can show the tremendous value that can be produced with just a little bit of heterodox thinking.  

If you've made it this far down this very long blog post, thank you! This turned into a huge post, but that's because my own new year's resolution is to blog more frequently and this post will serve as my guiding framework for a year of writing. Over the next 12 months I'll blog in more detail about each of the 12 items above. If there is a particular item in the list above that you think might help you achieve your own goals for this new year, post about it in the comments below. I will prioritize my writing based on any items that get specifically requested. This blog post has been about breadth, but each of the subsequent ones will be about depth - I'll get very concrete, explaining not just the new perspective that is required for each topic, but exactly how you can implement that new perspective in your own day-to-day work.

In 1997 Steve Jobs launched Apple's most famous ad campaign telling people to "think different". The only problem with those ads is that he didn't actually tell us how. 25 years later it's still the case, perhaps more than ever, that we need to think different. I'll try my best over the course of this year to explain how I know from experience that we all can.

Here's to 2022 - a year for not just thinking different but for doing different. I look forward to seeing the results!


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