algorithmic leaders, uncertainty & antifragile
I used to tell people we use research to INFORM decisions and not MAKE decisions.
I told people we use numbers to INFORM decisions and not MAKE decisions.
I told people we use data to INFORM decisions and not MAKE decisions.
I tell people we use algorithms to INFORM decisions and not MAKE decisions.
“An idea of working based on three pillars: science, insight and faith. Science because I’m a social scientist by training. I believe in data, robustness of information, making sure you’re on the right track. Insight because if you’re not able to draw insights from research, you’re not a strategist, just someone observing the data. And faith because you never know what’s going to work, so you always need a bit of faith to get everyone started.”
I believe great companies have one common infrastructure characteristic: culture. Good companies can be grounded in systems, processes, operations, etc, however, the step up to ‘great’ demands a culture (which is always implemented by people) to elevate the ‘infrastructure aspects. I thought of this because Mike Walsh has a new book, The Algorithm Leader, which suggests that the most successful companies of the future will support/augment/enhance that culture infrastructure – with algorithms. Now. Before anyone defaults into thinking this translates into “empty soul, technology order taker” company, or even holocracy (ponder how polar opposites could be relevant to the algorithm topic), let me share some thoughts on how I believe the thinking suggests structural value creation lift: for business & humans. To me this will occur through a balance of stability (knowledge infrastructure), uncertainty (quests versus missions) & understanding of Antifragility (selective redundancy maximizing untidy opportunities).
Let me pose some thoughts on the relationship between algorithms and antifragility upfront.
“It is optionality that makes things work & grow.” AntiFragile
Maybe algorithms shouldn’t provide answers, but options. Maybe, more importantly, we become a little less comfortable with the need for construct and more comfortable with using algorithms as dynamic application of ‘movable construct’ at the right time & place.
“The antifragility of some comes necessarily at the fragility of others. In a system the sacrifice of some units – fragile units or people – are often necessary for the well-being of other units or the whole.” AntiFragile
Maybe algorithms should evaluate tradeoffs, fragility versus antifragility & well-being factors (of units & whole).
“The crux of complex systems , those with interacting parts, is that they convey information to these component parts through stressors.” AntiFragile
Maybe algorithms should not highlight solutions, but rather stressors.
“There is a category of things that we can call half invented, and taking the half invented into the invented is often the real breakthrough.” AntiFragile
Maybe algorithms shouldn’t seek new innovations but rather ‘half invented’ ideas rip for innovation maturity.
“Meaningful progress is non-linear.” How To Lead a Quest
Algorithms should enable an organization to identify progress paths to explore and discover rather than simply meet the needs of present identified ‘paths’ of progress or solve present identified issues & vulnerabilities.
Full disclosure on my business beliefs. Throughout my career I have always felt comfortable by making the less certain decisions just certain enough that someone would go “well, it seems riskier, but, if you own it, go do it.” I say all that because I believe all Future of Work discussion should be grounded on the relationship between certainty & uncertainty – for the business, the people within the business organization and people’s minds/attitudes.
Most people want certainty therefore they let research make decisions, use numbers to make decisions, show data to make decisions and, increasingly, will suggest algorithms make decisions.
This is just a different type of efficiency couched in efficient operations. It will be called “efficient decision making.” The problem is this efficiency is just an attempt to strip a decision of uncertainty and, well, the best, most effective; decisions always carry along some burden of uncertainty.
What made me think about this? I just finished rereading AntiFragile (Nassim Taleb) and Mike Walsh just shared the first chapter of his new book The Algorithm Leader.
The former is about figuring out how to maximize from disorder or uncertainty while the latter is not becoming too dependent upon seemingly ‘certainty.’
“The future of companies, regardless of size, will be shaped by algorithms.”
Ultimately, it will be humans who use the shapes created by algorithms to assess options, evaluate antifragile components and navigate asymmetrical uncertainty.
It within this dynamic environment in which we should note business is inherently fragile. HBR once said “business is a quivering mass of vulnerabilities.” I say that because as a pendulum swings one way it will inevitably want to swing the other way. We inherently feel the fragile pendulum swing and start seeking to build ‘un-natural’ antifragile aspects to create a sense of antifragility. Aspects like systems, process, rules, KPIs, data/dashboards and, yes, algorithms. Depending on how fragile we see, or feel, the business to be the more likely we use the created mechanisms to ‘tell us what to do.’ We must fight against those instincts.
Frankly, this is where generations DO become relevant in discussing business. Older workers, 50somethings, can be an impediment by seeing past experience as ‘certainty’ . On the other hand, some 50somethings can actually be a bridge between some certainty-type learnings and younger people who are more comfortable with disorder (but they don’t necessarily have the expertise do discern the best bridges between certainty & uncertainty).
Here is what I do know. Business people inherently abhor risk, business organizations inherently gravitate toward the ‘safest’ and numbers, research, data & algorithms look like life rafts in a risky, safe seeking business world. That said. I also know progress is rarely found without some risk and is often found on ‘not-the-safest’ path. Algorithms create a false sense of ‘right thing to do.’ any leader who leans on algorithms too much isn’t leading. Period.
For this I lean in on How to Lead a Quest by Dr. Jason Fox. In times of uncertainty a business does not need business ‘heroes’ but rather people aligned on a quest and leaders who embrace the uncertainty of a complex interconnected multi-dimensional business world.
“You must learn to be still in the midst of activity and to be vibrantly alive in repose.”
Contrary to popular belief I would suggest a highly successful algorithmic leader is likely a 50something who has navigated research, then data, the ‘dictating’ decisions challenge gauntlet, & who were more likely to see how seemingly unrelated disparate fragments could be coalesced into decisions and futures that the numbers/data didn’t completely support, but also did not completely discount. That ws a long winded way to introduce the idea of “data decipherers”. This type of leadership invaluable to an organization more & more steeped in numbers, dashboards, data & algorithms.
Jason Fox calls this “shining a light on the path before us.” leadership will not use algorithms for ‘squinting into the future but rather to identify the stepping stones in a sea of uncertainty. They will offer people moments of some certainty without promising a certain future nor even promising steady progress organizationally. It will be more about uncovering options, making choices to alleviate stressors, so that teams can breakthrough while others provide the organization with the redundancies to protect an organization from uncertainty vulnerabilities.
Here is what I do know. psychologically businesses will arc toward a belief algorithms will provide an increased tidiness and symmetry to business. that is a false sense of tidiness. Business will become increasingly untidy, the paths will become increasingly complex, therefore business will become increasingly uncertain with regard to the best, and proper steps, necessary for progress. Pragmatically business will need more, and better, leadership comfortable with uncertainty despite more numbers, data and algorithms.
Crisis, disaster resolution is rarely about resources available but rather people availability.
Here I lean in Taleb’s AntiFragile because I just reread it. We tend to build redundancies incorrectly, don’t assume for disorder well & only enhance fragility in plans. We too often see AntiFragile as a “leadership concept” when in reality it is best absorbed by Agile teams.
Risk management almost always solely focuses on resources necessary to sustain, and manage, foreseen crisis. As Taleb points out the largest flaw in that is most crisis do not look similar to ones on the past (they will have similarities but still be unique). In addition. Most organizations build in redundancy safety nets as, well, a net. Because we dislike fragility so much we start building in antifragile everywhere. We tend to think of leadership as “what if” redundancy design. Antifragile leadership should be more ‘aligning resources to meet different scenarios.” Some people would call this ‘agile.’ I would not. I would simply call this pivoting (I am old school). great businesses have always been able to pivot to meet market challenges and opportunities. This may be a hyperized version of that, but it is still pivoting – no more, no less.
This is where I would view using algorithms a little differently than other people. Algorithms tend to look at opportunities when I believe they could be better used to identify stress points and stressors. Most good leaders are best as problems solvers (that doesn’t mean they don’t optimize existing operations/situations just that where good leaders get paid the big bucks is getting moments/situations unstuck). I would also argue identifying stressors permits smarter experimenting and tinkering.
Here is what I do know. Algorithms, used properly, permit people to stop just optimizing for the present and start attempting to optimizing the future. Yes. It may mean being less efficient in the short term (sometimes), but, done well, will create a more effective long term construct.
I think we will be “directed to act” by algorithms, but not managed by. The latter demands acceptance of algorithm as qualified to make us to do something behaviorally, the former demands we accept algorithms as something that ‘informs’ our doing. Somewhere in between is the decision of how much we, people, are accountable for thinking. Algorithms inherently encourage us to believe business is not best when it is random. Yet. The best businesses resist the urge to suppress randomness and permit people to be more accountable for some untidy decisions with some untidy outcomes.
All businesses will exist, in some form or fashion, grounded in algorithms. I am fairly sure that’s a given. The challenge will be to not get consumed by algorithms.
To realize algorithms do not give answers, but outline options.
To realize algorithms don’t define redundancies, but rather where and when to apply redundancy resources (therefore help to define how to create proper redundancies).
To realize algorithms don’t necessarily create innovation opportunities but rather find opportunities to ‘reinvent’ ideas.
To realize algorithms will not replace people but rather augment minds OF people.