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I used to tell people we use research to INFORM decisions and not MAKE decisions.
Then.
I told people we use numbers to INFORM decisions and not MAKE decisions.
Then.
I told people we use data to INFORM decisions and not MAKE decisions.
Now.
I tell people we use algorithms to INFORM decisions and not MAKE decisions.
Me
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“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.”
Laura Chiavone
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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. To be clear. “Culture” is not some ‘thing’, or values, or some nebulous feeling, it is an emergent consequence of how people interact with each other within a business. It is not what someone does or doesn’t do, it is what happens when people do things with each other. 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.
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“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 or what Donella Meadows called ‘leverage points.’.
“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 ripe 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.
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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.
Algorithm leadership.
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 reread Mike Walsh’s 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.’
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“The future of companies, regardless of size, will be shaped by algorithms.”
Mike Walsh
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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.
Uncertainty leadership.
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.
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“You must learn to be still in the midst of activity and to be vibrantly alive in repose.”
Indira Ghandi
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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 was 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.
Antifragile leadership.
Crisis, disaster resolution is rarely about resources available, but rather people* availability.
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* ‘people availability’: this is all of physical energy, skills and mental energy combined.
Here I lean in Taleb’s AntiFragile. 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/adaptable 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) based on the Law of the Situation. Great businesses have always been able to pivot to meet market challenges and opportunities. This is 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 or maybe better said “removers of obstacles to opportunistic behavior.’ (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.
Conclusion:
I think the smart businesses of the future 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.
And.
To realize algorithms will not replace people, but rather augment minds and skills OF people. Ponder.



But then there is this an added feature. And that would be group level selfishness. Humans aren’t stupid. Employees clearly understand what it takes to get ahead and to get more money and they understand they more than likely need other people to get what they individually want. Therefore, small groups form to not only fight within the system, but often to fend off the other groups from getting what they believe is a zero-sum pot of gold. It’s obvious this group level selfishness makes it hard for groups to get along. Like minded groups tend to amplify one key self-interest feature and that would be the different ideas of the appropriate terms of cooperation about what people should and should not expect from one another. Every individual has a point of view on this. Within a business, groups tend to coalesce around the common belief of their view on this. Obviously, what this means is that business has several different groups with number of different definitions of what they expect when they are asked to collaborate and cooperate with each other often of which are not in alignment.
Look. I am all for communities, informal networks, distributed decision making and a variety of other ideas with regard to alternative thinking to command-and-control, but I think a business is a microcosm of society – a social construct grounded in some social contracts. Social constructs are inherently, and naturally, territorial therefore it would seem like the only way to share in a desired outcome is to tap into ambitions (which is inevitably a type of social contract). Based on that I think we need to spend more time on the social contracts aspect, as in “shared ambitions.”
the thought. And then we should remember Faustus and his demon, Mephistopheles, wherein the insatiable thirst for individual knowledge leads him to make a pact with the devil – a message about human ambition and stretching the limits. Everyone, every individual, has ambition in some shape and size. But the reality is any one ambition has limits and constraints which can only be expanded upon by interacting with others. Yeah. When we share ambitions, the tide does lift everyone; maybe not always equally, but all get lifted. It is a little dangerous even if you balance it all fairly well. Clearly this is a tricky idea because to be as good as you can be you gotta give a little of yourself up to feed your talent and ambition to grow it beyond the normal levels. Someone is going to want to throw ‘trust’ into the ring here, but I will not. I tend to believe conflicting self interested groups will never really trust other groups, but they may trust in a more intangible, non human, thing like a shared ambition. In other words, we have the same ambition so despite their means, despite the fact they are ‘them’ and not us, they aren’t go to screw me/’us’. The good news with share ambition is that success at each level can be so addictive or pleasurable you have a tendency to want to feed it a little more. And maybe that’s the real prize with shared ambitions. Ponder.
This sure sounds like something you may have heard on CNN or BBC from someone talking about what is happening in the Middle East or Russia.
This is the craziest aspect.
In addition sometimes new people provide new perspective on their growth (success & failures) experience. The new people possibly have just seen “from the other side” and discern different learnings. They see what Taleb called “half invented ideas” and know how to fully invent them.
Why?
It makes me angry.
He skates on the slippery superficial surface of emotion and an enhanced feeling of irrelevance <or being marginalized> from a minority of the populace who has now found a voice.
And this also means, to Mr. Tump, he is never responsible for his words.
And, yeah, I am still angry.
While he’s narcissistic, self-absorbed, power hungry/crazy and driven by either greed or ‘winning by any measure” I almost think we are seeing a public case study example of the Dunning–Kruger effect.
And I am still angry at Mr. Trump.
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That said.
And unless someone is lying just to get everyone’s unrealistic hopes up, any hope is better than no hope. You can either not have hope, or have false hope, or real hope <albeit ‘real’ and ‘hope’ is a tenuous relationship>.


THE work (present & future) as concepts in combination with the ability to articulate it in ways that make it tangible enough to be understood and acted upon (this, generally, is an idea Dr. Jason Fox has discussed).
I would argue that over time the black box thinking <the intangible and vague ‘knowing’> becomes more tangible as well as we gain more faith in certain black box thinking applications. Given that belief I would also argue that Concepts, which outlines are vaguer in the beginning, gain substance & tangibleness over time.

arise with human judgment/assessment of organizational capabilities (mustering resources is accessing mental resources as well as tangible resources). In other words, articulating the varying concepts, defining the definitions, affect the way competing demands are described and how the resulting tensions are dealt with.
conventional wisdom from science, philosophy and knowledge. I would suggest people, mindful of the of the overarching issues with business (lack of moral leadership, hierarchy control limitations, diminished meaning and engagement in tasks and work) and aided by the easy movement of ideas created by technology, in a larger narrative, the Conceptual Age is seeking a new understanding of a human-centric world. The Conceptual Age will be a cornucopia of ideas, some of them contradictory, but will be defined by reason, conceptual thinking and, inevitably, how those concepts inspire progress.
I say this because everyone is different. Sometimes discernible to the naked eye and sometimes not, but different nonetheless.
They just don’t have the experience.
But with that encouragement also comes a responsibility. For if they do embrace their individuality they will also be embracing the fact that they are in some form or fashion … different.
I say that because we are often quite flippant with regard to the belief that we are ‘there for them’ and the reality is that sometimes when they fall in one of their holes … they not only lose sight of you <and everything else> but the abyss steals their voice.
First.
Well. Because none of those things make Life any ‘less’ or any less meaningful. They just make it a little less certain. They just make things a little more risky. They just make it all a little less straightforward.
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Because of that belief we are constantly investigating who we really are often desperately grabbing at clues or proof to provide some comfort that we have either solved the mystery or at least are on the path to solving it.
What a frustrating thought <at least to me>.
Well. The relationship between secrets and culture and community is one which is fraught with contradictions, conflict and humanness.
For many of us our behavior arcs toward what we can get away with. That doesn’t mean it is completely unethical, or some abhorrent behavior, just that while norms set a ‘median’ standard guideline Life is constantly suggesting ‘but this one time you can get away with doing this.”
Why hate?
believe we don’t think about this. We accept knowledge as … well … maybe like income earned – disposable income in fact. We worked for it, we earned it and it is now ours to spend as we choose.
knowledge. And therefore it also carries a burden, a responsibility, and a weight.
created some ‘auxiliary precautions’ to help us avoid unnecessary secrets.