There are two models in complexity. Complex Physical Systems and Complex Adaptive Systems! For us to grasp the patterns that are evolving, and much of it seemingly out of our control – it is important to understand both these models. One could argue that these models are mutually exclusive. While the existing body of literature might be inclined toward supporting that argument, we also find some degree of overlap that makes our understanding of complexity unstable. And instability is not to be construed as a bad thing! We might operate in a deterministic framework, and often, we might operate in the realms of a gradient understanding of volatility associated with outcomes. Keeping this in mind would be helpful as we deep dive into the two models. What we hope is that our understanding of these models would raise questions and establish mental frameworks for intentional choices that we are led to make by the system or make to influence the evolution of the system.
Complex Physical Systems (CPS)
Complex Physical Systems are bounded by certain laws. If there are initial conditions or elements in the system, there is a degree of predictability and determinism associated with the behavior of the elements governing the overarching laws of the system. Despite the tautological nature of the term (Complexity Physical System) which suggests a physical boundary, the late 1900’s surfaced some nuances to this model. In other words, if there is a slight and an arbitrary variation in the initial conditions, the outcome could be significantly different from expectations. The assumption of determinism is put to the sword. The notion that behaviors will follow established trajectories if rules are established and the laws are defined have been put to test. These discoveries by introspection offers an insight into the developmental block of complex physical systems and how a better understanding of it will enable us to acknowledge such systems when we see it and thereafter allow us to establish certain toll-gates and actions to navigate, to the extent possible, to narrow the region of uncertainty around outcomes.
The universe is designed as a complex physical system. Just imagine! Let this sink in a bit. A complex physical system might be regarded relatively simpler than a complex adaptive system. And with that in mind, once again …the universe is a complex physical system. We are awed by the vastness and scale of the universe, we regard the skies with an illustrious reverence and we wonder and ruminate on what lies beyond the frontiers of a universe, if anything. Really, there is nothing bigger than the universe in the physical realm and yet we regard it as a simple system. A “Simple” Complex Physical System. In fact, the behavior of ants that lead to the sustainability of an ant colony, is significantly more complex: and we mean by orders of magnitude.
Complexity behavior in nature reflects the tendency of large systems with many components to evolve into a poised “critical” state where minor disturbances or arbitrary changes in initial conditions can create a seemingly catastrophic impact on the overall system such that system changes significantly. And that happens not by some invisible hand or some uber design. What is fundamental to understanding complex systems is to understand that complexity is defined as the variability of the system. Depending on our lens, the scale of variability could change and that might lead to different apparatus that might be required to understand the system. Thus, determinism is not the measure: Stephen Jay Gould has argued that it is virtually impossible to predict the future. We have hindsight explanatory powers but not predictable powers. Hence, systems that start from the initial state over time might represent an outcome that is distinguishable in form and content from the original state. We see complex physical systems all around us. Snowflakes, patterns on coastlines, waves crashing on a beach, rain, etc.
Complex Adaptive Systems (CAS)
Complex adaptive systems, on the contrary, are learning systems that evolve. They are composed of elements which are called agents that interact with one another and adapt in response to the interactions.
Markets are a good example of complex adaptive systems at work.
CAS agents have three levels of activity. As described by Johnson in Complexity Theory: A Short Introduction – the three levels of activity are:
- Performance (moment by moment capabilities): This establishes the locus of all behavioral elements that signify the agent at a given point of time and thereafter establishes triggers or responses. For example, if an object is approaching and the response of the agent is to run, that would constitute a performance if-then outcome. Alternatively, it could be signals driven – namely, an ant emits a certain scent when it finds food: other ants will catch on that trail and act, en masse, to follow the trail. Thus, an agent or an actor in an adaptive system has detectors which allows them to capture signals from the environment for internal processing and it also has the effectors that translate the processing to higher order signals that influence other agents to behave in certain ways in the environment. The signal is the scent that creates these interactions and thus the rubric of a complex adaptive system.
- Credit assignment (rating the usefulness of available capabilities): When the agent gathers experience over time, the agent will start to rely heavily on certain rules or heuristics that they have found useful. It is also typical that these rules may not be the best rules, but it could be rules that are a result of first discovery and thus these rules stay. Agents would rank these rules in some sequential order and perhaps in an ordinal ranking to determine what is the best rule to fall back on under certain situations. This is the crux of decision making. However, there are also times when it is difficult to assign a rank to a rule especially if an action is setting or laying the groundwork for a future course of other actions. A spider weaving a web might be regarded as an example of an agent expending energy with the hope that she will get some food. This is a stage setting assignment that agents have to undergo as well. One of the common models used to describe this best is called the bucket-brigade algorithm which essentially states that the strength of the rule depends on the success of the overall system and the agents that constitute it. In other words, all the predecessors and successors need to be aware of only the strengths of the previous and following agent and that is done by some sort of number assignment that becomes stronger from the beginning of the origin of the system to the end of the system. If there is a final valuable end-product, then the pathway of the rules reflect success. Once again, it is conceivable that this might not be the optimal pathway but a satisficing pathway to result in a better system.
- Rule discovery (generating new capabilities): Performance and credit assignment in agent behavior suggest that the agents are governed by a certain bias. If the agents have been successful following certain rules, they would be inclined toward following those rules all the time. As noted, rules might not be optimal but satisficing. Is improvement a matter of just incremental changes to the process? We do see major leaps in improvement … so how and why does this happen? In other words, someone in the process have decided to take a different rule despite their experiences. It could have been an accident or very intentional.
One of the theories that have been presented is that of building blocks. CAS innovation is a result of reconfiguring the various components in new ways. One quips that if energy is neither created, nor destroyed …then everything that exists today or will exist tomorrow is nothing but a reconfiguration of energy in new ways. All of tomorrow resides in today … just patiently waiting to be discovered. Agents create hypotheses and experiment in the petri dish by reconfiguring their experiences and other agent’s experiences to formulate hypotheses and the runway for discovery. In other words, there is a collaboration element that comes into play where the interaction of the various agents and their assignment as a group to a rule also sets the stepping stone for potential leaps in innovation.
Another key characteristic of CAS is that the elements are constituted in a hierarchical order. Combinations of agents at a lower level result in a set of agents higher up and so on and so forth. Thus, agents in higher hierarchical orders take on some of the properties of the lower orders but it also includes the interaction rules that distinguishes the higher order from the lower order.
Most of you today have heard the word “pivot”. It has become a very ubiquitous word – it pretends to be something which it is not. And entrepreneurs and VC’s have found oodles of reasons to justify that word. Some professional CXO’s throw that word around in executive meetings, board meetings, functional meetings … somehow they feel that these are one of the few words that give them gravitas. So “pivot” has become the sexy word – it portrays that the organization and the management is flexible and will iterate around its axis quickly to accommodate new needs … in fact, they would change direction altogether for the good of the company and the customers. After all, agility is everything, isn’t it? And couple that with Lean Startup – the other Valley buzz word … and you have created a very credible persona. (I will deal with the Lean Startup in a later blog and give that its due. As a matter of fact, the concept of “pivot” was introduced by Eric Ries who has also introduced the concept of Lean Startup).
Pivots happen when the company comes out with product that is not the right fit to market. They assess that customers want something different. Tweaking the product to fit the needs of the customer does not constitute a pivot. But if you change the entire product or direction of the company – that would be considered a pivot.
Attached is an interesting link that I came across —
It gives examples of eight entrepreneurs who believe that they have exercised pivot in their business model. But if you read the case studies closely, none of them did. They tweaked and tweaked and tweaked along the way. The refined their model. Scripted.com appears to be the only example that comes closest to the concept of the “pivot” as understood in the Valley.
Some of the common pivots that have been laid out by Eric Ries and Martin Zwilling are as follows 😦http://blog.startupprofessionals.com/2012/01/smart-business-knows-8-ways-to-pivot.html). I have taken the liberty of laying all of these different pivots out that is on Mr. Zwilling’s blog.
- Customer problem pivot. In this scenario, you use essentially the same product to solve a different problem for the same customer segment. Eric says that Starbucks famously did this pivot when they went from selling coffee beans and espresso makers to brewing drinks in-house.
- Market segment pivot. This means you take your existing product and use it to solve a similar problem for a different set of customers. This may be necessary when you find that consumers aren’t buying your product, but enterprises have a similar problem, with money to spend. Sometimes this is more a marketing change than a product change.
- Technology pivot. Engineers always fight to take advantage of what they have built so far. So the most obvious pivot for them is to repurpose the technology platform, to make it solve a more pressing, more marketable, or just a more solvable problem as you learn from customers.
- Product feature pivot. Here especially, you need to pay close attention to what real customers are doing, rather than your projections of what they should do. It can mean to zoom-in and remove features for focus, or zoom-out to add features for a more holistic solution.
- Revenue model pivot. One pivot is to change your focus from a premium price, customized solution, to a low price commoditized solution. Another common variation worth considering is the move from a one-time product sale to monthly subscription or license fees. Another is the famous razor versus blade strategy.
- Sales channel pivot. Startups with complex new products always seem to start with direct sales, and building their own brand. When they find how expensive and time consuming this is, they need to use what they have learned from customers to consider a distribution channel, ecommerce, white-labeling the product, and strategic partners.
- Product versus services pivot. Sometimes products are too different or too complex to be sold effectively to the customer with the problem. Now is the time for bundling support services with the product, education offerings, or simply making your offering a service that happens to deliver a product at the core.
- Major competitor pivot. What do you do when a major new player or competitor jumps into your space? You can charge ahead blindly, or focus on one of the above pivots to build your differentiation and stay alive.
Now please re-read all of the eight different types of “pivot” carefully! And reread again. What do you see? What do you find if you reflect upon these further? None of these are pivots! None! All of the eight items fit better into Porter’s Competition Framework. You are not changing direction. You are not suddenly reimagining a new dawn. You are simply tweaking as you learn more. So the question is – Is the rose by any other name still a rose? The answer is yes! Pivot means changing direction … in fact, so dramatically that the vestiges of the early business models fade away from living memory. And there have been successful pivots in recent business history. But less so … and for those who did, you will likely have not heard of them at all. They have long been discarded in the ash heap of history.
Great companies are established by leaders that have vision. The vision is the aspirational goal of the company. The vision statement reflects the goal in a short and succinct manner. Underlying the vision, they incorporate principles, values, missions, objectives … but they also introduce a corridor of uncertainty. Why? Because the future is rarely a measure or a simple extrapolation of expressed or latent needs of customers in the past. Apple, Microsoft, Oracle, Salesforce, Facebook, Google, Genentech, Virgin Group, Amazon, Southwest Airlines etc. are examples of great companies who have held true to their vision. They have not pivoted. Why? Because the leaders (for the most part- the founders) had a very clear and aspirational vision of the future! They did not subject themselves to sudden pivots driven by the “animal spirits” of the customers. They have understood that deep waters run still, despite the ripples and turbulence on the surface. They have honed and reflected upon consumer behavior and economic trends, and have given significant thought before they pulled up the anchor. They designed and reflected upon the ultimate end before they set sail. And once at sea, and despite the calm and the turbulence, they never lost sight of the aspirational possibilities of finding new lands, new territories, and new cultures. In fact, they can be compared to the great explorers or great writers – search for a theme and embark upon the journey …within and without. They are borne upon consistency of actions toward attainment and relief of their aspirations.
Now we are looking at the millennial generation. Quick turnarounds, fast cash, prepare the company for an acquisition and a sale or what is commonly called the “flip” … everything is super-fast and we are led to believe that this is greatness. Business plans are glibly revised. This hotbed of activity and the millennial agility to pivot toward short-term goal is the new normal — pivot is the concept that one has to be ready for and adopt quickly. I could not disagree more. When I hear pivots … it tells me that the founders have not deliberated upon the long-term goals well. In fact, it tells me that their goals are not aspirational for the most part. They are what we call in microeconomic theory examples of contestable agents in the market of price-takers. They rarely, very rarely create products that endure and stand the test of time!
So now let us relate this to organizations and people. People need stability. People do not seek instability – at least I can speak for a majority of the people. An aspirational vision in a company can completely destabilize a certain market and create tectonic shifts … but people gravitate around the stability of the aspirational vision and execute accordingly. Thus, it is very important for leadership to broadcast and needle this vision into the DNA of the people that are helping the organization execute. With stability ensured, what then happens are the disruptive innovations! This may sound counter-factual! Stability and disruptive innovations! How can these even exist convivially together and be spoken in the same breath! I contend that Innovation occurs when organizations allow creativity upon bedrock of discipline and non-compromising standards. A great writer builds out the theme and let the characters jump out of the pages!
When you have mediocrity in the vision, then the employees have nothing aspirational to engage to. They are pockets sometimes rowing the boat in one direction, and at other times rowing against one another or in a completely direction. Instability is injected into the organization. But they along with their leaders live behind the veil of ignorance – they drink the Red Bull and follow the Pied Piper of Hamelin. So beware of the pivot evangelists!
Tags: boundaries, choice, core, creativity, employee engagement, extrinsic motivation, intrinsic motivation, lean startup, learning organization, mass psychology, organization architecture, pivot, platform, talent management
Democracy is defined as a form of government in which the supreme power is vested in the people and exercised directly by them or by their elected agents under a free electoral system. This abstraction goes back to the old Greek states that spontaneously emerged and coalesced to form one of the greatest civilizations in world history. This was further refined by the great English political philosophers and more importantly, put to test in the pamphlets that led to the founding of the United States of America. The debates that reverberated in the pages of the Federalist Papers still continue to be amplified over the years into the political theater today … and more importantly; it plays a big role in the technology theater.
I have, over the years, found it a fascinating exercise to connect the dots. It is my firm belief that learning can be ported from many different and seemingly discrete and distant disciplines … to connect them is not a Nietzschian leap or a metamorphosis from a man to superman thinking. It is forging creativity, introducing dialogue between the wedges, creating an infrastructure and support system to promote association and free thought … and the abstractions would thus reduce to more concrete and practical rules for the advancement in daily living. Thus, despite being in finance, I have kept my sensibilities open to a plethora of fuzzy possibilities that may affect my realm, as much as explore the fuzzy stretches of finance that may affect the concrete realities in other areas … either in or outside of the corporate environment. I am enamored of the intellectual elasticity that has become a generational bar that the open society has enabled through technology.
So as we enter the domain of technology and mesh it with the advances in our understanding of an idyllic society with fine workings of democracy, we have to keep a few things in mind. These few things are important enough to understand in order to build out product and service solutions that are injected into mass gatherings and conversations, albeit in the virtual space. They are as follows:
1) Privacy: Man is a social animal. That being said, we crave for society but we seek solace in ourselves. Hence, science and religion coexist happily. There is never so much of each to drive the other out, since the final questions that one ultimately asks is meta-scientific. In seeking our silent spaces, the proxy in a social network is privacy. We impute value to this quaint notion which has different magnitudes across different cultures … however, my contention is that a true democratic system will allow its citizenry to preserve their spaces and enforce property rights upon such spaces. If a social network is a microcosm … an experiment playing out in the petri dish of events in our world, the network will have to embrace the democratic ideals and ensure privacy. The privacy can be protected through statutory means, business rules implemented in the system, technical do’s and don’ts, self-governing protocols, etiquettes for mutual understanding etc. These are the attributes that the right network will imbibe in the framing and final design of its own emergence.
2) Ease of Use: It is upon the network to enable the participants to speak and quickly adopt to common practices, learn new languages, adapt to changes, and to be wooed by the beauty of minimalism and simplicity. Urban planning is a lot different today than it was a 100 years ago. The good old times were not really the good old times … we live today in the best of times, and it will only get better. We are dealing with the consequences of advances in medical sciences, disaster recovery, and a general increase in income, et al… all of these translating into a burgeoning global population. Despite this and the adverse impact on the environment and having aptly defined the gloom and doom prophecy of Rome diatribe – we are not under the shadow of a Tower of Babel, lost in a litany of tongues. Rather, we are happily skewed toward embracing the common denominator, the ultimate leveler, the common theme, a grand platform. This de facto standardization of diverse orientations is making us more proficient in people finding greater meaning in their lives. The virtual network exist to allow such meaning, if the participants use it accordingly and most importantly … be able to step back and reflect upon the dialogues that they see or participate in. So the network must appeal in a manner to advance the common parlance … the global village is less a village … it is a megapolis of spontaneous evolution of innovation and knowledge. The pace of innovation in the next 10 years will outpace innovation over the last 100 years.
3) Mass Psychology – When I read Malcolm Gladwell’s Blink, I recall thinking that indeed … years of experience can effectively shortcut a process to arrive at conclusions that may be correct. Arriving to a meaningfully correct judgment happens despite one not working through heaps and layers of data, analysis, observations etc. Thereafter, I read Crowdsourcing by Howe and that opened up another world … there indeed is this wisdom of the crowds. I have, as you recall, referred to Hayek who had always been optimistic toward an aggregate marketplace of opinions … Crowdsourcing empirically confirmed that theses. So now one need not necessary get to Blink when there are infrastructures setup to crowd source reference points to get you meaningfully within a safe distance from a “blink” conclusion, the latter fermented over years of experience. A great network is the one that enables such crowdsourcing to occur… functionally and aesthetically. It takes years out of the equation; it advances knowledge at stupendous pace. Somewhere I read that innovation in the next 10 years will outpace innovation over the last 100 years … I imagine that the network of connections, social or otherwise, across a standard operational platform is enabling this effusion of ideas and innovation that is and will continue to permeate our daily living.
4) Communication Channels: Finally, the virtual network must create a flurry of communication channels. I am abstracting communication to a higher level … to a plane wherein the underlying meaning is to exchange messages that drive people to act toward something. Communication is not passive; even it would engender a dialogue as commonplace or existential as “Who am I”. The value-based virtual network ought to be responsible for parsing all the touch points that impact the sensibilities of a user. These sensibilities constitute the perennial target … but unfortunately it is a moving target since new contexts emerge rapidly and may change the underlying value from which the sensibilities are wrought.
So the networks that we know today – the big elephants in the room: FB, LinkedIn, Twitter have to reinvent themselves to go deeper into capturing the intrinsic value of the participant. Or it may serve the system of surfacing the extrinsic and articulated needs of the participants … thus leaving open the possibility of ushering a new generation of niche networks that can tap into the god and the devil within us. As long as it proscribes to the four rules outlined above, I am optimistic that these cocktails will advance us sooner to the better and more productive lives in the future.