Category Archives: teams

The breakthrough power of bridging from novelty to the known

April 4, 2021 By in exploration, General, idea landscapes, teams Tags: , , ,
The breakthrough power of bridging from novelty to the known

How do we move within and across the spaces of ideas, to discover new possibilities? Should we leap into unexplored territory, or loop within and around what we know well? 

This is the classic choice in idea search between exploration and exploitation. Exploratory search is characterized by searching in novel and unfamiliar idea spaces, on the outer frontiers of what is known.  In contrast, exploitative search involves seeking within and around relatively familiar ideas, delving deeper into what’s already apparently known or understood.  

Exploration is characterized as decidedly risky, but it can lead to radical breakthrough innovations and revolutionary discoveries.  Exploitation, instead, leads to what seem to be more incremental (step-by-step) discoveries that are less impactful, and do not so sharply upturn or up-heave the idea/making landscape of a field or industry.   

But is this depiction of how breakthrough innovations come about fully accurate?  Or does it simplify a process that is more nuanced, iterative, and unfolding?

Re-evaluating the exploration vs. exploitation dichotomy

To address this question, two researchers at Harvard Business School turned to a very large database of possible innovations – more than 1.5 million U.S. patent applications, spanning some 30 years and more than 2,500 companies.  From within this dataset  they focused especially on those patents that were applied for in the year 2005.  To differentiate the patents that involved “breakthrough” inventions, they used a measure of how often the 2005 patent was itself cited (referenced) in later patents within the same technological class. The 4,743 patents that had a high level of forward citations (the top 5% of forward citations) were classified as “breakthroughs” and were compared with 69,499 non-breakthrough patents.  

Then, to gain a fuller and richer picture of the process leading up to successful innovations, the researchers specifically looked at all patent applications, not only those that were successful or granted patents. This provided information about what the firm was attempting to do, the technological information/know-how that the firms were using at that time, and how the firms believed their approach built upon and was different from prior patents (known as “prior-art citations”) in the same technology class.  

The researchers combined these data with other indices of the firm’s patents and related patents to create a new measure of how close the sought-for patent was to already-known technology.  This new measure, which they called “technological focal proximity” would have a value near one when the invention was very close to the previous theoretical knowledge of the firm, but would approach zero as the content of the patent application diverged very far away from the firm’s existing knowledge.

So what did they discover?

The process leading up to all of the patent applications, whether breakthrough or non-breakthrough, initially started at a point where the firms had comparatively less knowledge or expertise (average value of the “technological focal proximity” slightly below .20).  This suggests that innovation starts with a period of exploration, in a knowledge or idea space that is quite far away from the firm’s prior knowledge. 

The breakthrough vs. nonbreakthrough inventions also showed different knowledge trajectories. Charting the firms’ “technological focal proximity” to the patent applications over the 30 years prior to the application showed breakthrough and non-breakthrough inventions followed different trajectories.  Their trajectories were also non-overlapping.  This meshes nicely with the well-accepted notion that the search processes behind breakthrough versus non-breakthrough inventions are significantly different. 

Crucially, however, especially in the 10 years immediately prior to the application for the patent, the breakthrough patents were closer to the firm’s technological competence than were the non-breakthrough patents.  Surprisingly, and contrary to the conventional exploration-exploitation dichotomy, breakthrough patents were not farther away from the firm’s knowledge or competencies at any point across the 30 years.  

Indeed, breakthrough inventions were especially likely to emerge in those firms that, in the 5 to 10 years leading up to the patent application, concentrated their research and search efforts in the technological and knowledge neighborhood nearby to that of the invention.  As ideas and know-how within and surrounding the “promising find” are more deeply delved into and connected, the ideas/processes/materials that were once novel and unfamiliar become increasingly understood and familiar.  

Stated simply:  The story behind breakthrough innovations, then, is not only one of exploration, or only exploitation, but of both.  Although the learning and searching process for both breakthrough and non-breakthrough discoveries started out as exploratory, firms that transitioned to an increasingly concentrated exploitation search in once-unfamiliar idea territory were significantly more likely to produce breakthrough inventions.   

To think about

We’re remarkably adept at the mental act of categorizing things.  It is both a unique strength – and an often-encountered downfall – of the human mind.  

The strength of such categorizations, in dealing with one another and with our world, comes from how they allow us to notice and name what otherwise we might have missed.  Categorization can change our ways of interacting, responding, and forming effective working models of the world in our heads.  

The downfall of such categorizations is that we start to take these lines that we have drawn in the mental sands of our minds, as lines that are really out there, as sharp demarcations and solid boundaries that exist in the world outside our head.  We take (mis-take) conceptually created and mentally postulated lines for lines that are real.

Perhaps there are parallels here to another distinction often made with regard to the process of generating creative ideas:  that between flexibility (when we move across and between different domains or perspectives) and persistence (dwelling, staying with one domain or perspective to deeply mine and intermesh ideas).  Both flexibility and persistence are necessary.  Neither alone is sufficient.  For breakthrough inventions – or for everyday creatively adaptive problem solving – we need both flexibility and persistence, both exploration and exploitation.  And transitions between each. 

To deeply and meaningfully innovate, we need both leaps, and loops, in our idea spaces.

References

March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87. https://pubsonline.informs.org/doi/abs/10.1287/orsc.2.1.71

Nijstad, B. A., De Dreu, C. K. W., Rietzschel, E. F., & Baas, M. (2010).  The dual pathway to creativity model: Creative ideation as a function of flexibility and persistence. European Review of Social Psychology, 21, 34–77. https://www.tandfonline.com/doi/abs/10.1080/10463281003765323?journalCode=pers20

Sarnecka, D. K., & Pisano, G. P. (2020). The evolutionary nature of breakthrough innovation: Reevaluating the exploration vs. exploitation dichotomy.  Harvard Business School, Working Paper 21-071. https://hbswk.hbs.edu/item/the-evolutionary-nature-of-breakthrough-innovation

Wu, Y., & Koutstaal, W. (2020).  Charting the contributions of cognitive flexibility to creativity: Self-guided transitions as a process-based index of creativity-related adaptivity.  PLOS ONE, 15(6): e0234473. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0234473

Image Source: Karsten Knöfler via Wikimedia Commons

Team-to-Team Innovation Learning in Science

March 29, 2020 By in dynamic environments, idea landscapes, teams Tags: , , ,

New forms of mirroring to advance research. Source: Frans90245 via Wikimedia Commons

 

Many of us may have read the somewhat disheartening news about the frequency with which important new and breakthrough findings in the social and life sciences have turned out to be difficult for other researchers to replicate.  It’s even been given it’s own moniker:  “The replication crisis.”

A host of different factors may contribute to failures to replicate, but here let’s take a look at a novel approach to the challenge of replicating important complex and technologically advanced discoveries in biology.

Something new, something old, something borrowed…

At first blush the new approach seems remarkably simple. The new approach is to require the primary research team to be “shadowed” or “mirrored” by a second smaller team of independent experts.  The primary funded biological research group (for shorthand, let’s call them Team A) that is seeking to make cutting-edge discoveries is to be closely followed by the independent group of experts (Team B).  Team B is explicitly tasked with the primary goal of replicating the findings of Team A.

But there is a key and important twist:  Rather than waiting many months or years before Team A makes and publishes its discoveries and methods, Team A must – from the very beginning – share its innermost thoughts and workings with Team B.

No longer can Team A quietly work in secret, jealously shielding its latest experimental or conceptual breakthroughs from all possible competitors.  Instead, from the very outset of launching the research project and throughout the time of the project, Team A must openly share all of its ongoing findings and developing methods with its mirror team, Team B.  And that’s not all.  Team B is given all of the money, equipment, samples, and other resources it needs to be able to go off, on its own, and independently replicate what Team A has found.

So now Team A, for example, invites the mirror team members to come and closely watch them while they work through their protocols.  Team A shares with Team B its minor triumphs, its mini-successes, and its day-to-day failures or missteps.  Sometimes Team A also videotapes themselves as they go through a complicated protocol.  Step-by-step in the video they show Team B what they are doing, describing in painstaking detail each minor step or turn in the procedure.

But wait!  Why adopt what looks like such a “copycat” approach?  Isn’t it wasteful?  What’s to be gained from such extensive, intensive – and expensive – mirroring of one research team’s efforts by a second research team?

Why adopt a mirroring approach?

This innovative mirroring approach helps to tackle many of the pesky, persistent, and problematic obstacles standing in the way of one research lab being enabled to fully and faithfully replicate the complex biological and technological research methods and procedures of another lab.

Even when we earnestly try to communicate exactly what we’re doing, we may make assumptions or leave out important steps so that we don’t clearly communicate with each other.  Sometimes we’re not even aware that small details could make a large difference.  For example, in one case the reduced viability of an organism in a shadow lab was due to a difference of 2 degrees Celsius in the ambient lab temperature, whereas the Team A lab had a more constantly controlled temperature.  In other cases, how vigorously cells were washed, or using a slightly different size of a pipette tip, led to unpredictable changes in the results for Team A versus Team B.

The primary-plus-mirror teams arrangement has now been in progress for over three years.  Both Team A and Team B have been funded by the Biological Technologies Office of DARPA – the US Defense Advance Research Projects Agency.  The team-to-team innovation tracking arrangement has uncovered many “how-to” lessons that can benefit nearly all scientific and technological teams in their ongoing creative search and experimentation.

Yet, although the Team A plus Team B structure is quite new to complex biological research, it is not new to more traditional forms of engineering or electronics.  Here a processs of “independent validation and verification” has been part and parcel of research for decades.  Take NASA for example.  A separate “independent validation and verification” facility has long been an integral part of NASA — with more than 300 employees specifically tasked with independently testing and giving a “thumbs up” (or thumbs down) to the computer code and components for satellites developed by other NASA teams.  The same is true for teams working in electronics.  But, until recently, it has not been been true for research in complex biological and biological-engineering sciences.

Thinking together in physical space

Why is it sometimes important for teams or individuals to actually meet in the same physical space or to watch and hear the step-by-step videotapes of a lab procedure?

Some clues can be found in an earlier integrative review – fittingly titled “distance matters” – by two researchers who, for decades, researched the thinking, working, and social processes of teams “co-located” in space and time versus teams connected by various modes of technology.  Based on their findings, the researchers pointed to several advantages of individuals being together in the same space, or being co-located as they work on a complex problem.  To highlight three of these advantages:

(1) Rapid feedback:  If someone has misunderstood or misinterpreted something, or glossed over an important detail, if they are physically together in the same place, Team B could “pipe up” to ask for elaboration or a re-statement of the points, right then and there.

(2) Multiple communication channels:  Written verbal or text-based descriptions or diagrams are invariably abstractions.  They emphasize some aspects and details, but omit others. Working in person and side-by-side allows team members to perceive and interpret many richly informative, often nuanced, visual, auditory, and social interactional cues such as facial expressions, gestures, and body posture, that are not readily conveyed in words.  This may include implicit cues that we may not even know we are using – and may perhaps be especially true for well-practiced routine laboratory procedures that have become a form of “muscle memory”.

(3) Shared spatial layout and spatial referencing: By observing and experiencing a methodological procedure step-by-step and in-person, Team B is in “the same space” as Team A.  From there, Team B can see many small yet crucial details of how – exactly – a specimen or instrument is moved or placed, and the direction of a researcher’s gaze or gestures can quickly and easily identify what is meant, again with a level of rich precision that can be difficult to fully convey using words or static diagrams.

There have been recent calls in the behavioral and life sciences to study behavior in the “real world” – in dynamic, complex, richly multi-modal contexts – rather than in the “sterile” highly controlled environment of the experimental laboratory.  At first, it might seem that the mirror-team approach  – with its borrowed from engineering “independent validation and verification” steps – is directly contrary to, or incongruent with, this movement toward scientific discovery tied to the “real world” and “the life of behavior.”

But, looked at slightly differently, it can be seen as, perhaps, a confirmation and validation of this recent turn.  Scientific research, too, needs to be studied as a complex form of embodied behavior in a dynamically changing context, with the scientist’s brain in a scientist’s body, contingent on context (space) and history (time).  Seen from this perspective, the mirror-team approach may itself be a way of stepping away from “automatized and sterilized” approaches to studying behavior and studying biological phenomena.  It may be a welcome and needed step toward recognizing how we, as human scientists, act on and in the world.

References

Gomez-Marin, A., & Ghazanfar, A. A. (2019).  The life of behavior.  Neuron, 104, 25–36.

Olson, G., and Olson, J. (2000).  Distance matters.  Human-Computer Interaction, 15, 139–178.

Raphael, M. P., Sheehan, P. E., & Vora, G. J. (2020). A controlled trial for reproducibility.  Nature, 579, 190–192.

Creativity: What’s privacy got to do with it?

August 5, 2018 By in dynamic environments, idea landscapes, teams Tags: , , , , ,

An open-plan aquarium. Source: Miguel Hermoso Cuesta via Wikimedia Commons

 

How might a lack of privacy influence our creative thinking?  Our general common sense might suggest a number of reasons that being constantly “on view” for others to see us, as in an open-plan office, could bring with it cognitive costs.  Considerable mental effort may be needed to stay focused on one’s own work, and not be distracted by nearby sounds, movements, happenings, the coming and going of others.

But are we fully aware of all the different ways that lack of privacy might influence our thinking?  And, apart from simply asking people for their self-reports, how might we get a clearer and evidence-based understanding of how a lack of privacy impacts our thinking and making?

Let’s take a look at two highly creative experimental approaches – and the unique insights they provide – on the creativity-privacy connection.

—> For more see Wilma’s post: “Does an Open Office Plan Make a Creative Environment?: New support for the value of privacy at work.”

What helps us to recognize good novel ideas?

December 2, 2017 By in exploration, idea landscapes, teams Tags: , , , ,

Source:Flickr: Smelling the Roses via Wikimedia Commons

 

Not every good new idea gets the recognition it deserves. Promising novel ideas are often overlooked, ridiculed, or dismissed. But why?

Read more at: https://www.psychologytoday.com/blog/our-innovating-minds/201712/seeing-the-creative-value-in-new-good-idea-isnt-easy

What’s Your Innovation Mindset? Gaining new creative traction through changing how we think

October 31, 2017 By in exploration, goals, teams Tags: , , ,

Market vendors in Niamtougou, Togo
Source: Grete Howard via Wikimedia Commons

 

Are there different routes to learning how to be more innovative and entrepreneurial?  And, which might you expect would work best:

  1. teaching good business skills, such as accounting and marketing, or
  2. being taught to adopt an adaptively flexible, opportunity-seeking mindset?

To answer these questions, an international team of researchers from the U.S. World Bank and universities in Singapore and Germany compared the effects of two different multi-week training interventions on the business performance of some 1500 small business enterprises in Togo, West Africa.

—> For more see Wilma’s Psychology Today blog post.

Too perfect: Inviting creativity through improvisable gaps

November 2, 2016 By in detail stepping, representations, teams Tags: , ,

Take a look at these two images:

icons_finished_unfinished

Source: Jonathan Binks, adapted from McGrath, Bresciani, & Eppler (2016)

How do they make you feel? How are they different?

For some recent research exploring how images that you use can invite you and others to playfully and creatively elaborate on ideas see: https://www.psychologytoday.com/blog/our-innovating-minds/201611/too-perfect-no-room-newness

New ways to think about how to turn limitations into helpful guides and goads

May 1, 2016 By in creative constraints, General, idea landscapes, making and finding, teams

All of us have deadlines and limitations on how much money, time, and other resources we have for our creative projects.

We can see these constraints as irksome or anxiety provoking, and this they sometimes are! But is this our only option?

In the words of musician Joe Henry: “You don’t have endless resources and endless time. I don’t see that as an obstruction. Instead, I see it as something else that’s guiding us.”

Sometimes what we see as blocking our way can be just what we need to creatively guide us forward. . .

For how constraints can be both guides and goads, see Wilma’s Psychology Today blog post: Corner Flags, Constraints, and Creativity.

Our constraints can be seen as "corner flags." Image source: Idlir Fida via Wikimedia Commons

Our constraints can be seen as “corner flags.” Image source: Idlir Fida via Wikimedia Commons

 

 

Staying the course

January 23, 2016 By in dynamic environments, making and finding, teams Tags: , , , , ,

Korean traffic detour sign. Source: P.Ctnt via Wikimedia Commons.

Korean traffic detour sign. Source: P.Ctnt via Wikimedia Commons.

Take a look at this Apple web page describing ways producer/musician Greg Kurstin, in working with the singer/songwriter Adele, anticipates — and eludes — likely detours during their creative process.

  • What are the materials that are ready to hand/ready to mind for Kurstin? How did they get there?
  • How does he clear the path to capturing ideas? What different ways does he use to make sure his ideas don’t escape?
  • How do gaps in time contribute to their creative process?
  • How does the thinking-making process repeatedly interweave between singer/songwriter and producer/musician?

With these insights in mind, what possible obstacles are detouring you on your creative path — and how could you better elude them?

Salt and sharing

January 9, 2016 By in creative constraints, exploration, goals, teams Tags: , , , , ,

Situated on the Lower Manhattan waterfront, near Hudson River Park, the new Spring Street Salt Shed can hold up to 5,000 tons of de-icing road salt.

But it’s no ordinary “shed.”

Taking inspiration from the crystalline form of salt itself, the 69-foot tall building evokes other analogies. As David W. Dunlap of The New York Times describes it: “Folded, creased, dimpled and chamfered, its windowless, enigmatic facade is like a monumental work of origami.”

A macro shot of salt crystals taken in the Natural History Museum of Vienna. Source: w?odi via Wikimedia

A macro shot of salt crystals taken in the Natural History Museum of Vienna. Source: w?odi via Wikimedia

And it doesn’t stand alone.

Partnered with a five-story, 425,000-square-foot New York City Department of Sanitation garage, also designed by Dattner Architects with WXY Architecture + Urban Design, the two buildings share more than proximity.

The buildings share a palpable sense of responsibility for their role in their neighborhoods. Let us count (some of) the ways:

  • the garage has a sound-blocking curtain wall for noise reduction
  • to stay in tune with surrounding buildings, the garage’s height was kept low, retaining the character of the neighborhood
  • topped with a “green roof” the LEED-certified garage offers, along with energy and environmental benefits, visual pleasure for those who overlook it from nearby buildings
  • along the street, the Salt Shed’s walls gently taper in, providing ample pedestrian space
  • inside, too, there’s consideration for multiple stakeholders as the garage includes a gym for employees and a central staircase invites them to opt to take the stairs rather than energy-intensive elevators (it’s part of the NYC Active Design program)
  • from a broader perspective, the integration of important utility buildings throughout the city reduces undue burdens on any one area, while also minimizing vehicle miles, with corresponding improvements in air quality

Similarly, how could your next creative project synergistically incorporate the values of “sharing” across a range of dimensions and constraints: aesthetics, sustainability, health and well-being, efficiency, collective responsibility and “neighborliness”? . . .

How do we (really) keep our creative momentum?

December 2, 2015 By in detail stepping, goals, teams Tags: , , ,

We often like to simplify things but — let’s face it — creativity is a messy business. It’s filled with trial and error, trying this and trying that. It reaches across time (minutes, hours, weeks or months, sometimes years) and space. It’s rife with unpredictable spurts forward and sudden stops or detours as unforeseen obstacles loom on the horizon. How then can we ever see “inside creativity” — peering into this dynamically changing thinking-making process to learn what works well, and what doesn’t?

One promising approach is to generate a sort of “creative micro-world” —setting out a creative challenge that can be taken up in a somewhat limited period of time (say a few hours), with specific constraints and goals. Then the entire thinking-making process of creative designers or engineers can be observed (perhaps videotaped and audiotaped). The designers might also be asked to “think aloud” — telling us, moment by moment, what they’re thinking, what problem they’re facing, what options they see, or what next steps they’re mentally testing out (or ruling out). . . .

For more please see WK’s Psychology Today post “Inside Creativity: Charting Innovation as it Happens.”

Keep Moving . . .

November 10, 2015 By in dynamic environments, exploration, making and finding, teams Tags: ,

Asked to conjure up a mental image of someone who is thinking, many of us will envision a seated figure.  Perhaps we imagine something like Auguste Rodin’s famous statue of “The Thinker” — he leans over, resting his chin on his hand, still, silently lost in thought.

But opposing this sedentary image there may be other images or recollections that come to mind instead.  Prompted by our associations, we may bring to mind, instead, the prodigious walking habits of such diverse thinker/creators as Charles Darwin, Ludwig van Beethoven, or more recently, the intense walking-meetings of the late CEO of Apple, Steve Jobs.

. . . For more on “tracking down how and why physical activity boosts creative thinking” see Wilma’s Psychology Today post here.

Guinness beer, “absorptive capacity,” and innovation

August 8, 2015 By in exploration, idea landscapes, teams Tags: , , , , ,

In its everyday sense, to absorb something refers to our ability to take it in or soak it up or learn it well. But how do organizations absorb new knowledge or skills?

In Innovating Minds (p. 183), we explore what has been called the “absorptive capacity” of an organization. Absorptive capacity refers to:

“the ways in which teams and organizations evaluate, receive, and integrate new ‘external knowledge.’ [It] depends on their dynamic ability to recognize the value of new external information, assimilate it, and apply it. This capacity of an organization to productively absorb new information . . . applies not only to concepts but also to skills and meta-skills or ‘skills of skills,’ such as learning to learn. Appreciating the potential value of new information is something that may not come easily or automatically and needs to be fostered.”

So what’s this all got to do with Guinness beer and innovation?

Let’s travel back in time—to October 1899—in Dublin Ireland. The Guinness Brewery has just hired the young William Gosset, fresh out of New College, Oxford. Gosset’s stellar academic performance in math and chemistry has brought him to the attention of the company and he is recruited as a junior brewer. He will be joining four other recent recruits—all selected to spearhead a newly launched “scientific” approach to brewing.

Gossett soon is confronted with the very practical problem of what to make of the results of their many experiments with samples of malt and hops and plots of barley. Because of financial and other constraints, all of their experiments are based on very small sample sizes. It’s difficult to reach firm conclusions with such small samples because the numbers bounce around so much from one sample to the next.

He begins to see that standard practices won’t work and writes an internal company report suggesting a way forward. The report is well received.

But he and the company’s leadership realize that they need greater expertise and exposure to the very latest statistical methodology—that is only available outside the company. With this in mind, the company grants Gosset a one-year leave to go to England to study at University College London (UCL) with the pioneering statistician Karl Pearson.

Once at UCL, and working collaboratively with Pearson, Gosset recognizes that his small sample problems will require their own unique approach. This heralds the development of foundational insights that allow sound inferences to be drawn even from small sample sizes and a publication leading to what is now known as Student’s t-test. (If you have ever encountered this statistical test to compare two means, “Student” is a pseudonym adopted by William Gosset—see below.)

The fact that the company directly encouraged Gosset to leave Dublin to acquire deeper knowledge underscores that the organization understood the value of purposefully “absorbing” new knowledge and meta-skills into their idea landscapes. The company realized it needed to reach beyond its considerable internal expertise to draw on the insights and novel methods of others—extending its absorptive capacity.

Gosset_paper_1908

—> For further background see:

Phillip J. Boland (2011). William Sealy Gosset — An Inspiring ‘Student’,’ Proceedings of the 58th World Statistical Congress (Session STS028), pages 2650-2655.

The Magic of “Inside Out”

July 4, 2015 By in control dialing, detail stepping, dynamic environments, goals, idea landscapes, teams Tags: , , , , ,

If you’ve just seen, or are about to see, the magically profound and profoundly magical Pixar film “Inside Out,” here are a few questions we invite you to think about:

  • What might it mean to have a control console in your head?
  • Fear, sadness, anger, joy, disgust… each is so identifiable and tangibly distinct, so affectionately near yet far. Why is caricaturing these emotions so helpful?
  • If memories aren’t really little crystal-ball-like orbs, what are they?
  • If we touch a memory (recall it), how and why do we modify it?
  • In order to grow and meet changing circumstances, how important is it to forget (or to re-characterize) our past?
  • How can all of our emotions work better together as team players—integrating and tempering each other, in ongoing interplay with our changing goals?
  • If you could add to the console team other emotions, beyond the five, what would they be, and why?

 

 

What makes some teams smarter than others?

April 29, 2015 By in idea landscapes, teams, thinking components Tags: , , , , ,

How could we answer this question? To find out what makes some teams smarter and work better than others we could look separately at the characteristics of individuals in the team (e.g., how intelligent they each are or how open to experience they each are). Or, instead, we could look at how the team as a team worked and problem-solved together.

To answer what enabled teams to work well collectively, researchers looked at newly formed teams (of four members each) who were asked to think together to perform a wide range of tasks. They were asked to generate ideas, solve puzzles, detect patterns, and make evaluative judgments.

Groups that collectively showed greater intelligence, as shown in higher performance across this wide range of tasks, were distinguished by two factors:

(1) They communicated more often and their communications were more evenly distributed across the team.

(2) Individuals on the team excelled on a test that measures social/emotional perceptiveness (“Reading the Mind in the Eyes Test”). This test asks you to judge someone’s mental state (e.g., curious, preoccupied, interested) from a photograph of just that person’s eyes.

These two factors were earlier established as important to effective team collaboration in experiments using small face-to-face teams. A more recent study (published in late 2014) asked a new question—would the collective intelligence of groups that met solely online or only virtually be influenced by these same two factors?

Newly formed teams of four people were situated in a room. There were two types of teams, and two types of rooms. For face-to-face teams, the members met in a small room, each team member with a laptop, and they could all see one other, talk directly, and they knew who was on their team. For the online teams, the team members were randomly co-located with other team members in a large room interspersed with other similarly scattered teams, where they did not know or see each other and could communicate solely on laptops using text-based chat online.

If directly reading subtle interpersonal cues (e.g., facial expressions, tone of voice, body language) during face-to-face interactions is a critical team mechanism then it would be expected that online teams would perform more poorly. But that wasn’t what was found—the online teams, who scored high on the Reading the Mind in the Eyes Test, did just as well as the face-to-face groups who also had high abilities on that test. This suggests that the virtual teams could still perceive subtle interpersonal cues in the text messages they shared, perhaps conveyed through sentence structure, phrasing, word choice, timing, or tone.

Equally important, the effects of conversational turn taking also were the same in both groups. In online teams where participation was more equally shared, and not dominated by one or two individuals, online teams performed a wide range of tasks just as well as their face-to-face peers who also had a democratic approach to group problem solving.

So, it’s not just your cognitive ability or how smart as an individual you or your team members are—it’s also how well you can coordinate and be “heedful” of others in your group and the situation you jointly find yourselves in (whether working virtually or face-to-face). Part of the key to better team performance is also making sure that each team member shares in communicating within the group.

Sharing in communication and noticing interpersonal cues, whether in the eyes or “between the lines,” may contribute to a broader group characteristic of heedfulness. As we observe in Innovating Minds:

 “In heedfulness the actions and thinking of a group or team emerge based not entirely on habit but on a ‘heedful’ monitoring and comprehending of an unfolding dynamic situation. Each person acts in a way that converges, supplements, or assists with the overall collective effort.

Heedfulness is not solely an effort at paying attention. Rather it is this, combined with an active taking care and staying in touch with new information and its immediate and broader implications—for ourselves, for others, and for a collective envisioning of a larger unfolding joint enterprise.”

—> For more see also:

David Engel, Anita Williams Woolley, Lisa X. Jing, Christopher F. Chabris, & Thomas W. Malone (2014). Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face. PLoS ONE, 9, e115212, pp. 1-16.

Anita Williams Woolley, Christopher F. Chabris, Alex Pentland, A, Nada Hashmi, & Thomas W. Malone (2010). Evidence for a Collective Intelligence Factor in the Performance of Human Groups. Science, 330, pp. 686–688.

An example of the Reading of the Mind in the Eyes test can be found here.

 

Beyond simple brainstorming: Emerging, without submerging, good ideas

November 4, 2014 By in associative cuing, idea landscapes, teams Tags: , ,

Most everyone knows what brainstorming is—the group idea generation process where any and all ideas are welcomed, and ideas can be combined or built upon. Not being “judgy” is key, etc.

But how many of us know how to assess the effectiveness of a brainstorming session? And how to make what may be a good process even better?

Compared to what?

Individuals in a group brainstorming session may generate many ideas—but how do those ideas compare with the number and quality of ideas that would be produced by the same number of individuals working alone generating their own ideas?

Many research studies and meta-analyses show that typical interacting face-to-face group brainstorming sessions produce fewer unique (non-redundant) ideas than do the same number of individuals working alone. The ideas generated in the typical face-to-face group are also of lower average quality than if the individuals had worked independently.

Why might this be?

Hearing the ideas of others has the effect of associatively cuing our ideas in the same direction as what we are hearing. This can be helpful if it occurs at the right time by cognitively stimulating our thinking in new and useful directions. But such associative cuing can be a big drawback if it occurs at the wrong time, or too soon, preventing us from reaching and articulating ideas we otherwise would have formed.

Another factor is that ideas compete with one another for emergence in our awareness and “bottlenecks” may be created while we wait our turn to speak.

As we observe in Innovating Minds: “Verbally expressing our ideas to the group too soon may lead to a single shared idea landscape—without the beneficial input of each individual’s contributions and successive reworkings. Variations on simpler face-to-face group brainstorming are attempts to avoid the drawbacks of jumping into a single idea space too soon.”

Brainstorming variants

So what should we do?

We might try brainwriting. Here we each individually and silently write down our ideas and place them on idea sheets in the center of a table. People in the group, when they feel they are ready, can select and read the ideas of others, adding to or elaborating on those ideas if they choose. Another approach is to pass the idea sheets along. In the 6-3-5 method: 6 people each generate and write down 3 ideas on their own. Then they pass them along 5 times, silently and in parallel building on the ideas of others, until the idea sheet returns to where it started.

Sketches rather than words could also be circulated this way or later displayed as a “gallery” of ideas. Or ideas could be generated individually and then selectively shared and later broadcast more widely electronically via a computer network.

Each of these are potential ways of maximizing the diverseness of our idea landscapes, reaping the cognitively stimulating benefits of encountering the ideas of others without incurring creativity costs. Such “pairs of pairs of pairs” methods allow varied contributions and intermeshing of the contributions of others in a way that can optimize both individual and group idea generation.

 

–> For a recent extensive review see: Wolfgang Stroebe, Bernard A. Nijstad, & Eric F. Rietzschel, “Beyond Productivity Loss in Brainstorming Groups: The Evolution of a Question” Advances in Experimental Social Psychology, Volume 43, 2010, Pages 157–203.

So what’s a robot for?

September 27, 2014 By in detail stepping, exploration, making and finding, teams Tags: , , , ,

Most of us have encountered the notion of “functional fixedness” – our tendency to yoke a particular use or function on to objects. For example, we might assume that a spoon is for scooping or a chair is for sitting, but less readily recognize that a spoon might serve as a lever or a chair might act as a doorstop.

So what’s a robot for?

Cirque du Soleil, partnering with ETH Zurich’s Flying Machine Arena, sought to creatively call upon precision aerial robots as collaborative dance performers. They experimented with sundry semblances and scenarios but discovered that the quadrocopters truly came into their own as…. lampshades. The lampshades each can sport multicolor designs and textures, tassels and various appendages, and convincingly assume idiosyncratic roles and personalities.

In the words of the actor Nicolas Leresche, who fluidly interplayed with the flying machines:

“Actors think they are the ones who make objects move. I think that, on the contrary, it’s the objects that make us move. In the case of drones, even more so! They are companions (in an etymological sense), confrères, brothers.”

–> Here’s the quote and a video tracking parts of the team’s creative process.

Creativity friendly environments: Two examples

September 19, 2014 By in idea landscapes, making and finding, teams Tags: , , , , , , , , 1 Comment

What makes for a “creativity friendly” environment?

There is no single “one size fits all” answer… but here are some broader themes to think about. Let’s look at two recent examples through the lens of our iCASA framework.

(1) Shared learning and experimentation space

A very large Chinese factory that produced mobile phones had a massive open floor plan where the workers on the production lines and the supervisors were continually and readily seen. What would happen to production speed and quality if some of the lines were surrounded by a privacy curtain?

A field study with four production lines randomly chosen to be surrounded by such a curtain for several months found that the curtain increased improvisation, encouraged “productive deviance,” and led to higher productivity and quality. The comparative increase in team privacy afforded by the curtain allowed temporary, smaller issues to be solved locally through line-level learning and it promoted collective team knowledge.

Observations by embedded student researchers on the curtain-surrounded lines revealed that the workers actively switched roles to learn multiple tasks and enable team cross-support, fluid adaptation, experimentation, and learning.

The innovations that were observed “were a mix of preexisting and new ideas: some of these were ideas that were just waiting for an opportunity at experimentation, while others reflected novel learning on the line through the increased levels of experimentation the curtain enabled.’’ (Bernstein, 2012, p. 202)

The curtain allowed the line to collaborate and discuss new ideas and to iteratively test and try process improvements, arriving at successful prototypes before sharing them outside of their local idea landscape. It formed a “scrutiny-reduced” supportive making-and-finding environment where the workers and the line managers could adaptively and contextually experiment with an increased degree of autonomy.

—> For the research study, see Ethan S. Bernstein, The transparency paradox: A role for privacy in organizational learning and operational control, Administrative Science Quarterly, 57, 181–216. Also, see Bernstein’s, “The transparency trap”

(2) Cross-pollination at IKEA

IKEA’s product catalogs feature multi-color contemporary images of home furnishings in various natural looking settings. The company, though, was looking to move from its longstanding tradition of studio photography of its products to computer-generated images. Transitioning to computer-generated imagery would greatly reduce logistical and environmental costs because the many products would no longer need to be flown in and configured on site. Instead of physically creating multiple culturally specific settings, for example a typical Japanese kitchen, a German kitchen, and an American kitchen, computer-generated imagery would make such reconfigurations much simpler. But how could IKEA make this transition in a creativity-friendly way, while preserving catalog image quality and empowering employees throughout the change process?

The solution was simple and incisively creative: They started small scale, and then scaled up. After initial experimentation and demonstration of the feasibility of the computer-generated imagery process, all of IKEA’s studio photographers were required to learn to use the 3D computer generated process and vice versa. This in-depth cross-training extended the skills and understanding of both groups, and led to an increase in quality, with computer-generated images that were essentially indistinguishable from conventional photographs. There was a synergistic meeting of the two approaches to image making, and a fuller appreciation of the goals, aspirations, and constraints that each uniquely faced. The merging of techniques expanded and deepened everyone’s individual and shared idea landscapes and mental models. There was learning and unlearning at the same time.

—> For more background on the IKEA process, see: Kirsty Parkin, “Building 3D with IKEA”