Collaboration is more important than ever given the rate of digital transformation organizations are going through today.
While collaboration has always been a needed skill in the workplace, increasingly distributed workforces, knowledge silos and new developments in technology have put renewed pressure on learning the art and science of collaborative work. Because today people aren't only collaborating with people, they have the added challenge of collaborating with machines.
The following three skills will help organizations meet collaboration demands now and in the near future.
1. Successful Information Transfer
Probably the most important skill is the ability to transfer critical information to other team members. Doing this well involves trust, clarity of speech, understanding of the information you are relaying, time management skills, as well as many other factors.
Communicating via 'Talking Dominos'
One of the games St. Louis-based educational organization EnTeam does to help develop this clarity of statements is called “Talking Dominos.” In the game each pair of people receives three or four dominos each, and each pair has the same dominos. The idea is to see how few communications it takes for the second person to create the same configuration as the first.
Numbers, positioning, orientation and more need to be clearly communicated to succeed. Good communicators can usually get these instructions across within three or four directions, while other pairs can take twice that. One very practiced team was able to do over 60 different domino set-ups in a few minutes.
Simulation-Based Learning
When dealing with other people, your tone of voice, even the expression on your face, can help or hinder these interactions. The best way I have been able to help others learn various collaboration skills is through playing a game or scenario. Learning this way seems to have the greatest impact and improves the rate of retention. Lecturing people on how to collaborate just doesn’t work — believe me, I learned that the hard way.
So when workshops failed, I chose a collaborative simulation based on my experience playing Dungeons and Dragons. While working with our initial client, we learned to keep the problem challenging, and the roles in the simulation different from the job they had in the organization. We would make a CIO into a secretary, and a secretary into a project manager or data gatherer. This helped them suspend disbelief, and made it easier for them to get into their roles.
These scenarios had such an impact, that a decade later while speaking at a conference, some of the players from that first client approached me after my talk to discuss their game experience. How many times do you teach something and have someone want to talk to you about it a decade later?
2. Adapt a Collaborative Mindset
The ability to listen to others, make a judgement on what they say without being dismissive and potentially building on that initial idea requires the ability to hold several conflicting strategines in your head at the same time, as well as a level of respect between all participants. This makes it possible to deal with “wicked problems” (problems where you can’t see the solution when you start working on the problem, but as you work your way through it the solution becomes clear) and involves learning from past situations that may have been similar.
This skill is really about strategy, and the willingness to recognize that “all of us, is smarter than one of us.” It is not about being the smartest person at the table, but is about the ability to put “we” before “me.” It is the willingness to work as part of a team, and focus on a common goal.
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3. Person with Machine Collaboration
Collaborating with intelligent agents, bots, conversational interfaces, etc. may not be critical today, but it's becoming more critical as every day goes by. A few challenges crop up here. First, is having the machine (computer) understand you. Sometimes it requires training the device to your voice. This is true for conversational interfaces, as well as Siri, Alexa and Cortona.
The second problem is the limited scope of the intelligent agent. You can ask Alexa to play music, adjust the lights in the room, check your calendar for an upcoming appointment, which may make it might be easy to anthropomorphisize or overestimate the capabilities of these bots or conversational interfaces. In reality they are still very limited in what they can do.
Those skills are currently limited to a few powers within a specific domain, such as home entertainment or the smart home. I once asked Siri, “Who is the best baseball team in America today?” the day after the Astros won the world series. The response was, “Sorry, David, I don’t know the answer to that one.” So know the limits of what the machine can do in responding to you. Language also matters, as unlike people, intelligent agents don’t have the general knowledge to interpret slang or idioms, so phrase your question or command deliberately.
I believe conversational interfaces will surpass typing in a command as the norm within the next five years. But voice is probably not the most efficient way to interact with intelligent agents. Direct neural interfaces, such as the one developed at Brown University (seen in the image below), allow direct commands to a BrainGate
prosthetic control mounted on the head.
Imagine a warehouse worker with such a device, being able to lift vast amounts through the control of a prosthetic skeleton. Elon Musk is working on interlacing an implantable device to help merge human intelligence with AI at one of his newest companies, Neuralink.
Although some of this may sound like the stuff of science fiction today, five years from now it may well enter the realm of the norm as the technology advances. And when the machines can help in developing these interfaces, the field will advance exponentially.
What do you think? Any skills you see as necessary for collaboration? Leave them in the comments below.
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