“The leader is driven by a desire for power, while the organiser is driven by a desire to create.”
Coops attract organisers as the structure naturally diffuses the power of any single person. Of course the risk is entropy where coordinated action dissolves into a cacophony of voices. The aim of a coop is then to cultivate an active membership which focuses energy towards a common goal – following the adage that ‘power is focussed energy – that enables the ability to do a thing’…
We were brain-storming ideas for injecting some energy into the 888 Brewery Coop. It was on the long drove back from Horsham, the sun had gone down and we were listening to Radio Birdman descend into the maelstrom… and within mere minutes the discussion had gone from community engagement ideas to issuing ICO’s backed by kegs of beer.
So if Godwin’s law states that the probability of comparisons to Hitler rise to 100% the longer an online debate continues (which a study of Reddit discussions seems to confirm), perhaps crypto-currencies offer a greed-driven equivalent. Something like:
There are no more than six-degrees of separation between a good business idea and a get-rich-quick-crypto-currency-backed-ponzi-scheme.
Very productive day with the good folk from Birchip Cropping Group yesterday. It was our second workshop in the Farming Together sponsored project being undertaken by BCCM to help grain growers from the Wimmera-Mallee explore a data coop.
In a new land speed record, by the end of the workshop we had crossed everything off our wish-list in terms of things we needed to draw up a draft set of Co-operative Rules – once again proving that farmers and nurses are the most likely to survive the zombie apocalypse.
The data coop can be a big concept, and there are some key pieces of the puzzle that are still formative in their shape and readiness, so it was really encouraging that the farmers present were beginning to have concrete ideas about how it may work. There were some cracking specific examples that are likely to prove fertile ground for testing of the data coop mechanics and economics.
Perhaps more encouraging still was that we got the sense that the farmers were starting to take formal ownership of the project, thinking that they could build it from the ground up (rather than having a structure imposed on them). Notably, it was suggested that the data coop could leverage the BCG infrastructure to provide a springboard to get started.
Also, really interesting discussion about farming practices, quality assurance and compliance. Noting that the thinking to date has been that precision agriculture would lead the use cases for the data coop, we discussed the rising cost of compliance and increasing accuracy of testing and standards and whether this pushed ‘traceability’ higher up the priorities.
We were also lucky to have Leanne Wiseman and Jay Sanderson from Griffith University so we could untangle some of the trickier questions around rights to data. We sketched out some of the key structural elements that could be developed for the coop – such as members agreeing to an “Ethical Good Governance Code” that would be updated every year and would require things like disclosure of conflicts of interest, disclosure of 3rd party data sharing arrangements and agreement to minimum standards around data being shared, accuracy and types.
Finally, the emerging view seemed to be that the data coop would be akin to social infrastructure and would be best structured as a non-distributing coop. This would better align member and community interests and also enhance the collaborative business model with customers.
One of the challenges of a co-operative is balancing the interests of the group with those of each individual member. Unlike a proprietary limited company, stakeholder interests are not beholden to the profit motive. Rather the primary focus is on return to members – which can be delivered in a variety of ways including via dividends, rebates and patronage. The difficulty is that without a return on capital signal, the cooperative itself has to determine how value is distributed among its members.
A data co-operative provides a simple illustration of this challenge. On the one hand, members come together to aggregate market power – as individuals they are weakly positioned to bargain the terms on which they share their data, while as a collective their individual control is amplified. On the other, one of the principal objectives of a data coop is to enable individual members to have more control over their data. For this reason, a data coop will create permissioning mechanisms that enable the individual to differentially share their data with others. The data coop leverages group market power to deliver value for individual members.
But that is only part of the story. By aggregating control over data, the data coop will also enable sharing of data in aggregate. And there are likely to be circumstances where it is in the collective’s interests to share aggregate data. This is after all why Big Data and the Algorithms have been dominating the pop charts over recent years. For this reason, it may be a condition of membership that coop members agree to authorising the coop to share their data. You can see the challenge here…
For this reason, it is really important that cooperatives are very clear about how a cooperative distributes value amongst its members. If interests are not aligned, fractures across the points of difference are likely to occur when the structure is stressed.
Annie Duke, retired poker champion, talks about strategies to accelerate learning in her book “Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts”. A key one is drawing on your community – learning from the experience of experts, testing boundaries with peers, and simplifying ideas through teaching others. Really interesting question here about how to institutionalise these types of practices within an online cooperative community…
A data coop by definition aggregates the market power of its members. It enables them to collectively negotiate how their data can be shared and used by others – as well as enabling each individual member to manage how their data is shared. We think that this is key to the success of a co-operative – they empower the collective while also enabling individual agency.
It is kind of obvious, but can get lost in the mix, that for a data coop to work it must also benefit the customers…
I had a colleague once who for a time was the leading lights on the investment banking industry. He was in his early 40’s and was smart and full of confidence. Similar to a lot of his caste, his sense of the public good was tied to his power not in giving.
As a banker at the height of his game, he attracted customers like moths to a flame. It helped that he was in the real estate financing business and this was in the lead up to the GFC. As it turned out, he was instrumental in creating some of Australia’s biggest financial disasters that were to come, though he would never be held accountable.
So I remember in this one meeting with a property development company that was eager to float into the all too hungry oceans of investor capital. They had been granted an audience with my colleague who had sat quietly through their presentation whrre their sought to explain what they wanted to do. At the end, he approached the white board, drew three boxes and a couple of arrows and then explained how one plus one could equal three. This was the strategy he would recommend. And with that he finished with the line “You don’t pay for my time. You pay for my expertise.”
Now that is a very simple way of saying I’m bloody expensive. But is it actually accurate. After all, time is ultimately all we have to sell – particularly, when you are an investment banker who doesn’t physically produce anything tangible. It’s bothered me ever since. What was he actually saying?
My take on it was about positioning. His time was so precious that it looked damned silly as an hourly rate. He was creating scarcity around his brand. He had collected expertise and more importantly a network that he could call on to execute the transactions that could deliver them their dream outcome. He only needed 2 or 3 clients cause they were elephants that were totally aligned with him – they made more money, the more money they raised.
It’s a clever approach for a consultant, or anyone in the business of selling their time rather than a product (that could well be an asset created by an investment of their time). Professional sportsmen are faced with the same challenge. Their sunk costs are into themselves, they and their parents have invested years in creating their performance edge. And they are so acutely aware that their time at the top is finite.
One of the benefits of our social media age is that democratization of personal brands. With control of entertainment and information flows having been lost to the masses, the ability of just about anyone to rise up from the cacophony has been made possible. Not that it makes it any easier. The competition for attention has also been amplified by a factor of a large number.
This is the reason people like Seth Godin are so strong on recommending that you focus on your tribe- that group of people outside of your family and friends that will like your story. The more narrowly defined your tribe, the more likely that you can hone your message to resonate with them. It’s the same way that Kevin Kelly arrived at the conclusion that all you need is 1000 true believers to make a living.
So the lesson is if you are in the business of selling your time – which inescapably we all are. Then you better start by focusing on selling your message to a well defined audience. The tighter the framing, the more likely that you can tailor it to their needs. So much the better if that audience has very deep pockets, or in the case of my banker buddy, access to truckloads of other people’s money.
Where once we had red phones, we now have red buttons. The imagery of nuclear negotiation has morphed to reflect the times. When deterrence is based on mutually assured destruction, the need for direct negotiation to avoid misconstrued emoticons is paramount. But with North Korea the destruction isn’t assumed to be evenly shared – hence the bigger button – though perhaps the better image is a battery of buttons (or is the collective noun a ‘minefield’?).
Just how the US imagines it can prosecute regime change is the realm of Monte Carlo simulations. We can be sure that they have their plans, and that they are unlikely to include nuclear weapons – except as a retaliatory contingency. So what can we learn from negotiating nuclear-style?
Power asymmetry isn’t all it cracked up to be – Can the US really sustain an atomic explosion on its landmass? Can the US really justify total annihilation of the North in response? These are the implied positions – neither seem particularly sustainable. The implication is that bargaining from a position of relative strength doesn’t help, if the ramifications for any action using your strength are likely to be poor. There are no good nuclear wars.
You go first – in a gunfight, it’s the fastest draw that wins. It doesn’t work that way when both sides are missing body parts when the dust settles. The incentive is to avoid action regardless of your relative strengths. In these circumstances, the US has little leverage to force the hand of North Korea to abandon its program as it is caught in a ‘you-move-first’ bind.
How to make a credible threat – notwithstanding the above, no one wants to cross a crazy man. It’s the reason ‘white with anger’ is so much scarier than the everyday red-faced variety. In the game of bluster and bad behaviour, President Trump has demonstrated an expertise that none of his recent forebears could match. He is a better actor than Ronald Reagan and has none of the restraint or class of Obama. The thinking behind escalation strategy is to automate the launch process beyond a trigger point – midnight on the Doomsday clock. Trump’s crazy eyes and small hands are all designed to blur his fingers on that trigger.
Where’s the escape hatch – from a North Korean dictator perspective, there doesn’t seem to be an option that leaves me alive – let alone saving face. Given my demonstrated disregard for the people of my country, is it really likely that I’m going to get altruistic at the very last moment? What I need is a way out – short of being relocated in a witness protection program. Does the North become a vassal of China? At least that way, the nuclear codes join a bigger library.
Coalitions still win – which leads to the real problem with the current US strategy. Coalitions win conflict. Remember the invasion of Iraq, there was a whole sham thing about weapons of mass destruction? This time there can be no doubt about this. So why isn’t there a mass movement to de-arm?
Nemo was a special snowflake. Unique just like all the clownfish that had come before him. That is the way evolution works – flawed replication fidelity. Does that make him important? Well, yes to his dad at least. But that is different from the sense of entitlement that comes with being told as a peanut that he was destined to change the world. Not every clown fish can make a dent in the universe. So how did he do it?
Consider again the school of fish. By definition not everyone can be the leader of the pack. If you are a fish that is travelling in the middle of the school it is nigh on impossible for you to go in any direction other than the same one as those around you. If you try to deviate, you’ll bump into your neighbour and they are in the same boat as you. You may as well be travelling in a bus that someone else is driving.
To lead the direction of the school, you really need to be on the edge where you are responding to the environment external to your school. And to be a little clearer, its better to be towards the leading edge of the school.
To swim at the leading edge is to be exposed. The risks to your wellbeing are heightened. The protection of the herd is a function of you being the first to fall – like a centurion in the front line of the phalanx, your role is blunt an attack and give those on the inside time to respond. Whether you survive is as much down to luck as it is to good management by you.
And what does management mean in this context? Your options are limited. You make a difference at the edge – literally. You are subject to the same inertia as those in the middle. The difference is that you can try to change direction. Say you are the first to spot a very large set of teeth bearing down on the school. You try to change direction and bump into your neighbor. In a fright, they see what you see and turn the same way you are trying to go. They bump into their neighbor and so on.
You can see where the idea of a tipping point comes from in network effects. A small and determined group of fish can turn the direction of the herd. They must for the survival tactic of herding to work.
So some lessons in leadership from the school:
It’s a risky endeavor, whether you succeed or fail is a function of luck as much as determination
Inertia is your friend…eventually. It’s not like turning the oil-tanker, you have to convince a few before you can convince the many. You are looking for a tipping point in order for the herd to respond
Find the front, that is where current trends are taking everyone. From there you can make your move.
The alternative is to swim off by yourself and live in a cave. Nothing wrong with that. Plenty of fish have done it and lived out their days in existential bliss. Just don’t expect to impact the herd from the safety of your cave. They are off in the depths doing their own thing.
Ever been culpable of rolling an idea up a hill beyond its use-by date? Even with the benefit of hindsight, it can be kinda difficult to spot the optimal moment when it would have been wise to let go. Which is why this ‘fail fast’ fad has me flummoxed. I’d hoped that I could apply it to experience and not repeat the mistakes of the past, but I’ve been struggling to understand what it actually means.
See, I first took it that decisions to abandon a project can be accelerated. The lean model talks about testing your hypotheses and quitting as soon as they fail. So failing fast becomes about setting specific and measurable benchmarks that trigger the escape hatch if they are not met.
A problem with this is that benchmarks may not be simple to define and can be harder to measure – particularly where the concepts are emergent. For example, how do you define a benchmark to filter out the positive responses in market testing that, combined with a little confirmation bias and a dash of inertia, provide more than enough motivation to keep going.
Another assumption is that you can save money, time and effort by stopping out of failures early. But as any trader will tell you, a stop-loss can quickly become a target that simply gets triggered before the bigger trend resumes. The last thing you need if you are committed to a project is to exit just before the opportunity can be made real.
A plan, like a tree, must have branches – if it is to bear fruit. A plan with a single aim is apt to prove a barren pole. – Basil Liddell Hart, 1954
Perhaps the point then is that it is more important to get the big picture right – the big trend that will ultimately underpin the market dynamics that can support success. It’s like the difference between losing a battle and a war.
The genius of Winston Churchill was his ability to filter the chaos through the big picture, so that decisions were optimised for the very uncertain circumstances. “There must be that all-embracing view which presents the beginning and the end, the whole and each part, as one instantaneous impression retentively and untiringly held in the mind.” He had a framework within which to respond to challenges and take advantage of opportunities as they arose. Individual failures are simply events that help to shape the direction taken to achieve the ultimate objective.
David Einhorn likens the challenge to playing poker – where there are things that you know with certainty (your cards, everyone’s wagers), things you can surmise (that fellow’s playing style) and things that you don’t know except at the limits (the number of cards still to be played). There’s a spectrum of uncertainty along which calls are made. The challenge is to identify the key calls, those decisions that will make the biggest difference to the outcome – and tilt the odds in your favour. Again, it’s his ability to assess the context and then the circumstances within that determine the appropriate choices. Failing fast may mean folding early on a hand, but in doing so you’re more likely to have the resources to bet big when the opportunity arises.
So perhaps failing fast is a really a short-term concept within a long term context. And just as “a plan doesn’t survive first contact”, it’s understanding the potential points of failure and being aware of the contingent paths that will optimise chances of success. If failing fast is a skill, it is referring to the ability to dynamically choose the path not the destination. The objective remains to scale the hill, just that it may require pivoting along a few paths to get there. Even Sysiphus can have his good days when it’s as much about the journey as the destination.
I'm Rohan Clarke. I help leaders build communities...
Pazzomundo is the re-birthing of a very old