After reading about deconstruction and reconstruction thinking with regard to what I believe is how business thinking should be, one could easily become fearful of “frozen.” In other words what I have described to date with the Conceptual Age and a Conceptual Age organization, in which it seems that every person in the organization is being barraged by a knowledge-based software with random information and being asked to make sense of it all, well, it sounds overwhelming. It also sounds like there must be a direct relationship between information received and information used. If it sounds like that then, of course, we all recognize that when people get overwhelmed, they ‘freeze’ – make no decisions. I’d suggest that success within complexity, and complex organizations , is more like ‘obliquity’ – achieving complex objectives indirectly.
So let’s think about how we achieve this obliquity within the Conceptual Age organization business model idea.
It was Daniel Schmachtenberger who said we are “making more and more consequential decisions with worse and worse sensemaking to inform those decisions.” The basis of this thought, in business, is the consequence of a business environment invested in “data dumps” on people who are, for the most part, not particularly data literate. In pragmatic terms we have more knowledge and information than what we know what to do with. The cognitive complexity of most problems, and opportunities is beyond the capability of a single mind. This does not mean everything needs to be met with collaboration (in fact collaboration may actually mean a worse conclusion than a single mind incapable of assimilating all knowledge) but it does mean individuals need to become better at sensemaking and conceptual thinking. Now. There are two sides to this equation. The human mind and what is presented to the human mind in terms of knowledge and information. I will set aside the mind as a given (capable of reaching clarity and data assimilation) and focus on the input. In a Conceptual Age Organization, I am suggesting an Intelligence Driven software parsing out knowledge in ways that engage cognitively within a conceptual, sensemaking, framework. Rather than think about this in an ‘overwhelming’ way I choose to view the possibilities in terms of effective information distribution is all about the mental narrative battle. The challenge, and opportunity, is to distribute knowledge and, yet, eliminate cognitive load. Returning to Daniel Schmachtenberger, it is he who suggests society & civilization is suffering from a damaged information ecology. I am simply suggesting building a business model grounded in a healthier information ecology.
With that in mind, what is a healthier information ecology in a Conceptual Age organization? Well. Let’s accept the fact that all ideas can be weaponized – for opportunities or to make something worse. With that acceptance the organization should seek to create a battlefield on which the combatants, the employees, can be successful. We need to not only create the technological tools, but wield the technological tools in a way which can shape the thinking, and concepts, from which business potential can be achieved. As Marshall McLuhan said “we shape the tools and the tools shape us.”
This is where nuanced algorithm delivery of information matters. There is a “zone” in which information provided will generate a “return on information.”
In 1957 John William Atkinson wrote Motivational Determinants of risk-taking Behavior in Psychological Review. He suggested that if you can choose the grade of complexity <difficulty> of a task most of the decisions are taken in a mid-complexity-level. Too easy tasks or too difficult tasks can neither provoke a strong feeling of satisfaction nor a strong disappointment and vice versa.
Highly motivated people often choose a realistic complexity of tasks whereas low motivated people choose tasks that are finally to easy or too difficult for them.
Now. I would debate JW Atkinson because I believe if I set aside the fact bills have to be paid at some point, I would say he doesn’t give ‘appeal of success’ enough emphasis. Especially if the appeal of success is tied to “doing something” or maybe better said ‘doing something that may truly matter.’
What I mean is that if you consciously decide to ‘go big and win big <or lose big>’ your satisfaction criteria changes and, therefore, you are willing to plow your way through more complexity and difficulty.
This chart, and concept, is quite similar to the one Ian Leslie outlined in his book Curious about Curiosity.
Low knowledge discourages curiosity in that they don’t know enough to focus the pursuit (its kind of like lack of return on energy). Either we find it difficult to believe it would be interesting to pursue this knowledge or, with no knowledge, it can feel too daunting a task.
This means having medium knowledge, aware but not an expert, increases curiosity (and the pursuit of knowledge). High knowledge discourages curiosity because we feel like we know I well enough there would be diminishing returns if we invested in out curiosity to get more.
Ian Leslie notes that neither of these things make someone incurious, this simply showcases the walls we put up against certain curiosity.
We willingly enter the “curiosity zone” when we know something, but not too much.
This is all a derivative of George Lowenstein’s “information gap” – the gap between what we know and what we want to know – and curiosity is actually a response to this gap.
Now. People being people, if upon entering the information gap our curiosity is faced with too much complexity it will likely veer off on a different tangent.
This is where I circle back to complexity. Complexity and curiosity are linked.
See enough complexity and your curiosity views it as a puzzle to solve, but too much complexity and it becomes a mystery. Puzzles have definitive answers. Mysteries are messier and often do not have clear answers and you have to get comfortable with the truth you inevitably end up with probabilities. The truth is complexity, itself, is a mystery to be managed and navigated and complications are puzzles.
I would argue the business of the future will use algorithms to deliver knowledge to individuals so that they purposefully step into information gaps, gain the data & knowledge they need to navigate the curiosity zone and make decisions, isolate probabilities and pursue progress (which is typically found in more knowledge and more about navigating the information gaps businesses inherently have).
Look. I don’t think I am different than most people. We all want to ‘do something.’ And I would argue most of us like to solve complexity. that doesn’t mean we want to fight it 24/7 just that we get a lot of satisfaction in facing down the mysteries of complexity and still figure out how to make some progress with, or within, it. I believe we know, consciously or subconsciously, that effectively navigating complexity maximizes, well, everything – life or business. I also believe we understand that today’s complexity is only going to get more complex. I also believe that while complexity can be frustrating and we can doubt we can solve complexity, in general we know complexity can always be navigated. That said. Not everyone has a map nor has the time to figure out the map. But what we do know is that the enemy is complications – complications are roadblocks to potential within the complexity. therefore, simplistically, success opportunities, good decisions, exist within complexity only if complications can be removed.
I am not a personal branding fan, but in this case I think most everyone would like to be able to say “in a complex world we navigate complexity to uncover, and eliminate, complications blocking potential.”
I say that we would all like this because I also believe most people are confident enough to think they can get the resources they need to solve any problem they can actually see (or any opportunity they can see clearly enough).
- Complexity is a given.
- Complexity is expansive. Tapping into it maximizes potential. It is networked and non linear both of which are what makes a people, or business, successful.
- Complicated is reductive. It keeps things from potential. It is a linear connection which no longer works efficiently or effectively.
- Simplicity cannot exist without complexity. It is embracing complexity to the benefit of people, business, systems, communication etc. or. Maybe better said. Efficient bundling of complexity to increase effectiveness.
It is standard operating procedure in today’s world, whether you like it or not, that people are expected to cope with increasing complexity, change and diversity. The tricky part is that complexity IS the nature of things, not things themselves. It was Russell Ackoff who labeled these interconnected systems as ‘messes’. This means looking at things, or something, close enough and it only seems to get bigger in its connectedness (degrees of consequences and connections). This means decisions do not hold true to a cause & effect, but rather shifting contexts with shifting consequences.
Simplistically this means in a complexity world people are asked to tackle a much greater diversity of problems/opportunities. All the while we seek to maintain some of the efficiencies of life (or the business) – the rituals, replicable events, etc. – but to get ahead, or maintain some progress, knowledge and information has to be absorbed to meet the demands of future problems/opportunities.
Complexity demands structure AND flexibility. And while that sounds almost impossible if not uncomfortable, I will remind you of Atkinson “Motivational Determinants of risk-taking Behavior” and Leslie’s “curiosity zone.” We are capable enough, all of us, to navigate complexity if placed in the right mindset and if the appropriate knowledge connects with our curiosity.
Once curiosity is engaged one can see existing patterns as well as new patterns.
** note: this human pattern recognition is tied to the algorithm-based Intelligence based Software idea I have wherein I suggest two threads of information flow – predictive and emergent – are created in aligning Cloud, institutional knowledge and individual potential/thinking.
Let me end on this thought about decision making and complexity.
Discovery has always been grounded in knowledge – the known and the unknown. People knew about gravity before Newton nailed it down, knew Earth circled the sun, effective building of structures and even Columbus knew the world wasn’t flat when he decided to set sail <fairly common knowledge the world wasn’t flat to sailors>. Yet we spend a lot of time seemingly reeducating ourselves on what I would call “institutional knowledge”. We do that a lot in business too.
I imagine my point is that “institutional knowledge exists” <even in basic principles> and we loop back on it throughout the knowledge lifespan challenging it. I would also point out that this knowledge, or any knowledge I imagine, is progressed by how it is articulated. And then proof varies depending upon the technology (or whatever is needed to prove) at that time. I say all that to suggest that there are no real secrets or 100% mysteries. The truth is humans, given the right knowledge & information in the right context (not too complex and in an information gap), figure things out no matter how complex it may appear. And in doing so they take the old thought or knowledge and bring it slightly further along than where it last rested. That is called ‘progress.’ And that is also my proof that complexity is expansive, if not infinite, because when complications are solved & removed, complexity just expands to accommodate more people, ideas, curiosity and activity.
I will end where I began – “obliquity.” The process of completing complex objectives indirectly. Accepting complexity and tackling complexity are distinctly different things. Acceptance is simply recognition it exists, and go forth. Tackling is an agreement you will wrestle with complexity. To me, a Conceptual Age organization demands acceptance, if not celebration of, complexity but not tackling it. In other words, accepting complexity is an indirect means to an end in that you can seek solutions without trying to solve it.