At this very moment I am feeling an element of regret that I’m unable to code a robot rabbit to teach another robot rabbit to write this article on my behalf. I am even slightly remorseful that I didn’t even try and code a robot rabbit to teach another robot rabbit to write this article on my behalf, and then document the process. This would have (at a minimum) both shown a higher level of tenacity and provided some valuable content, which I may yet need.
Every article I read or presentation I see at the moment is about robot rabbits teaching other robot rabbits to write articles. OK, less robot rabbits, and more articles on AI, machine learning, internet of things, bots, and the demise of humanity for the betterment of… well… humanity.
What we are reading about primarily in these articles are the predicted implications for business and industry, and how to harness and take advantage of the technologies to say ahead – aka techniques (here is a good example incase you have been trapped on the Isle of Wight for the last 12 months).
In my past I have managed to keep a Tamagotchi alive for a week, used Siri to fool my children that there is a little man who lives in my phone, and then progressed onto developing strategies for how major companies transform how they interact with their customers using technology; but I’m not yet feeling comfortable that I know enough about DeepMind or Swarm Intelligence to write an article on the implication for the FTSE 500.
However, that’s OK, because what I’m really obsessed with right now is how we prepare ourselves in terms of learning culture to cope with the implications of technological disruption and the accelerated speed of digital change. The techniques are one thing, but our evolution cannot be technique dependent – we can’t evolve techniques quickly enough to cope with the discomfort of change at the scale we are facing.
It reminds of that old proverb, teach a person to build a robot rabbit, and they can survive for a day. Teach a person to adapt to the robot rabbit takeover…
In the last article I wrote for The Drum I suggested a path through the maze of discomfort (it was actually an article about ambiguity, but like Blade Runner this sequel is consistent and more technically competent). In this article I am advocating that the only way through the maze (which is actually a series of mazes with no ending) is to embrace being comfortable with being uncomfortable. It is culture, as much as technique, that will help us thrive in our machine dominated and complex futures.
I want to be Jeff Bezos for three reasons: mainly the money, a little bit because robot rabbits controlled by other robot rabbits bring him breakfast (unsubstantiated rumour), but also because his letter to shareholders in 2016 on ‘Always day One’ is the corporate handbook we all need. He has embedded change and learning, and by default failure, into the fabric of the internal Amazon culture. (I have heard speculation that forgiveness for failure isn’t as well established.)
At VML we’re trying to get everyone comfortable with being uncomfortable. Everyone from the CFO – who, lets face it, is uncomfortable with the comfortable – to the graduate trainee, and increasingly to our clients, all need to recognise and accept that they’re not going to know the answers, nor can they afford to wait for the assurance of success. The only way any of us will lead, rather than survive, is get it wrong faster.
We actually want people to be uncomfortable, because as Bezos himself said: “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death”. Reassuring as ever, Jeff. But you can’t just say as the CEO: “I’m glad you’re uncomfortable – get used to it”; it has to be part of a system, with process and practices around it.
So, how are we, or might we go about creating this culture?
1. We communicate more
By talking about it we legitimise it and define the boundaries around it. It’s OK to be uncomfortable or to not know. More so, it’s healthy to walk towards discomfort and away from what we’ve done before. To do this we need to broaden our exposure and trust that others know as much, or more, than we do, which means we share more. It’s clear that we need more exposure, more information and faster processing of that information. While we don’t have the machine power of Amazon we can learn quicker as a team, even more so as a global team, and we are putting that into practice daily. The collective brain is better than the individual brain.
2. Reduce experiential hierarchy
There’s nothing more poisonous to a learning culture than training everyone to unconsciously rely on the people who’ve done it before. Organisations must empower expertise without compartmentalising it. A divide and conquer methodology might get a job done and solves near-term deadlines, but it sacrifices learning and development and puts dependencies into a few people that will eventually fail. We’re working hard to do two things:
- Bring people along for the ride. Sure, a key workshop meeting might be ‘covered’ adequately by a single competent individual, but when we send three people (two of whom are asking themselves, “WTF am I doing here?”) we create the potential and momentum of three competent individuals. All of whom are ready to work together solving complex problems with the aid of multidisciplinary viewpoints. If clients refuse to pay for your staff to learn, pay it off as training. It’s way better than any seminar you could invest in.
- We put our people into cross-disciplinary training and we mandate a hunger for learning in every employee’s objectives. We must stop sending creatives to creative conferences and technologists to innovative ones. Send Client Engagement to Cannes, and creatives to Devcon. Then have to teach each other.
3. We question best practice
The difference between those who survive long term and those that do not, is the energy expended trying to change the system, rather than trying to hold on to old systems in the face of change. We no longer use the term best practice, because the best practice of today is not the best practice of tomorrow. There is only the delivery of a solution and the measurement of that solutions’ success. If it works, don’t get comfortable; there is a still a high likelihood it won’t work twice. The balance between constant re-invention and efficient repetition is difficult to find. Iterate and evolve constantly.
4. We accept we will be wrong.
As adults (lest leaders of companies) we’re not trained to think that being wrong is acceptable, or that making mistakes is good. Our tolerance for ‘failure’ is low, often tied to the fact that our perception of the consequences of mistakes are greater than the reality of those consequences; and that being correct now, is better than being wrong but learning for the future (Neuroscience documents the release of chemicals such as adrenalin and dopamine when we are ‘correct’).
Our corporate cultures still also typically reflect and enhance these schemas, and we have to break that. We fundamentally are training ourselves to believe that getting an answer wrong is the fastest way to learn to solve a problem in the best way. There is no optimization in early success, simply the false positive of what is likely only a moderately successful outcome. This requires us to be honest about our solutions and change reward structures, which currently focus on self-preservation of reputation over honesty.
As I conclude this article, seven other companies will have coded a robot rabbit to teach another robot rabbit to communicate with their customers on their behalf. But tomorrow a smarter robot rabbit will have coded a robot fox to eat all the robot rabbits and infect them with robot myxomatosis. I am uncomfortable with that last sentence for many reasons but that’s OK, I’m getting comfortable being uncomfortable.
Chris Wood is executive director of VML Europe. He co-wrote this piece with Robb Smigielski, executive creative director of VML London