Category Archives: Narratives
Chaos and the tide of Entropy!
We have discussed chaos. It is rooted in the fundamental idea that small changes in the initial condition in a system can amplify the impact on the final outcome in the system. Let us now look at another sibling in systems literature – namely, the concept of entropy. We will then attempt to bridge these two concepts since they are inherent in all systems.
Entropy arises from the law of thermodynamics. Let us state all three laws:
- First law is known as the Lay of Conservation of Energy which states that energy can neither be created nor destroyed: energy can only be transferred from one form to another. Thus, if there is work in terms of energy transformation in a system, there is equivalent loss of energy transformation around the system. This fact balances the first law of thermodynamics.
- Second law of thermodynamics states that the entropy of any isolated system always increases. Entropy always increases, and rarely ever decreases. If a locker room is not tidied, entropy dictates that it will become messier and more disorderly over time. In other words, all systems that are stagnant will inviolably run against entropy which would lead to its undoing over time. Over time the state of disorganization increases. While energy cannot be created or destroyed, as per the First Law, it certainly can change from useful energy to less useful energy.
- Third law establishes that the entropy of a system approaches a constant value as the temperature approaches absolute zero. Thus, the entropy of a pure crystalline substance at absolute zero temperature is zero. However, if there is any imperfection that resides in the crystalline structure, there will be some entropy that will act upon it.
Entropy refers to a measure of disorganization. Thus people in a crowd that is widely spread out across a large stadium has high entropy whereas it would constitute low entropy if people are all huddled in one corner of the stadium. Entropy is the quantitative measure of the process – namely, how much energy has been spent from being localized to being diffused in a system. Entropy is enabled by motion or interaction of elements in a system, but is actualized by the process of interaction. All particles work toward spontaneously dissipating their energy if they are not curtailed from doing so. In other words, there is an inherent will, philosophically speaking, of a system to dissipate energy and that process of dissipation is entropy. However, it makes no effort to figure out how quickly entropy kicks into gear – it is this fact that makes it difficult to predict the overall state of the system.
Chaos, as we have already discussed, makes systems unpredictable because of perturbations in the initial state. Entropy is the dissipation of energy in the system, but there is no standard way of knowing the parameter of how quickly entropy would set in. There are thus two very interesting elements in systems that almost work simultaneously to ensure that predictability of systems become harder.
Another way of looking at entropy is to view this as a tax that the system charges us when it goes to work on our behalf. If we are purposefully calibrating a system to meet a certain purpose, there is inevitably a corresponding usage of energy or dissipation of energy otherwise known as entropy that is working in parallel. A common example that we are familiar with is mass industrialization initiatives. Mass industrialization has impacts on environment, disease, resource depletion, and a general decay of life in some form. If entropy as we understand it is an irreversible phenomenon, then there is virtually nothing that can be done to eliminate it. It is a permanent tax of varying magnitude in the system.
Humans have since early times have tried to formulate a working framework of the world around them. To do that, they have crafted various models and drawn upon different analogies to lend credence to one way of thinking over another. Either way, they have been left best to wrestle with approximations: approximations associated with their understanding of the initial conditions, approximations on model mechanics, approximations on the tax that the system inevitably charges, and the approximate distribution of potential outcomes. Despite valiant efforts to reduce the framework to physical versus behavioral phenomena, their final task of creating or developing a predictable system has not worked. While physical laws of nature describe physical phenomena, the behavioral laws describe non-deterministic phenomena. If linear equations are used as tools to understand the physical laws following the principles of classical Newtonian mechanics, the non-linear observations marred any consistent and comprehensive framework for clear understanding. Entropy reaches out toward an irreversible thermal death: there is an inherent fatalism associated with the Second Law of Thermodynamics. However, if that is presumed to be the case, how is it that human evolution has jumped across multiple chasms and have evolved to what it is today? If indeed entropy is the tax, one could argue that chaos with its bounded but amplified mechanics have allowed the human race to continue.
Let us now deliberate on this observation of Richard Feynmann, a Nobel Laurate in physics – “So we now have to talk about what we mean by disorder and what we mean by order. … Suppose we divide the space into little volume elements. If we have black and white molecules, how many ways could we distribute them among the volume elements so that white is on one side and black is on the other? On the other hand, how many ways could we distribute them with no restriction on which goes where? Clearly, there are many more ways to arrange them in the latter case.
We measure “disorder” by the number of ways that the insides can be arranged, so that from the outside it looks the same. The logarithm of that number of ways is the entropy. The number of ways in the separated case is less, so the entropy is less, or the “disorder” is less.” It is commonly also alluded to as the distinction between microstates and macrostates. Essentially, it says that there could be innumerable microstates although from an outsider looking in – there is only one microstate. The number of microstates hints at the system having more entropy.
In a different way, we ran across this wonderful example: A professor distributes chocolates to students in the class. He has 35 students but he distributes 25 chocolates. He throws those chocolates to the students and some students might have more than others. The students do not know that the professor had only 25 chocolates: they have presumed that there were 35 chocolates. So the end result is that the students are disconcerted because they perceive that the other students have more chocolates than they have distributed but the system as a whole shows that there are only 25 chocolates. Regardless of all of the ways that the 25 chocolates are configured among the students, the microstate is stable.
So what is Feynmann and the chocolate example suggesting for our purpose of understanding the impact of entropy on systems: Our understanding is that the reconfiguration or the potential permutations of elements in the system that reflect the various microstates hint at higher entropy but in reality has no impact on the microstate per se except that the microstate has inherently higher entropy. Does this mean that the macrostate thus has a shorter life-span? Does this mean that the microstate is inherently more unstable? Could this mean an exponential decay factor in that state? The answer to all of the above questions is not always. Entropy is a physical phenomenon but to abstract this out to enable a study of organic systems that represent super complex macrostates and arrive at some predictable pattern of decay is a bridge too far! If we were to strictly follow the precepts of the Second Law and just for a moment forget about Chaos, one could surmise that evolution is not a measure of progress, it is simply a reconfiguration.
Theodosius Dobzhansky, a well known physicist, says: “Seen in retrospect, evolution as a whole doubtless had a general direction, from simple to complex, from dependence on to relative independence of the environment, to greater and greater autonomy of individuals, greater and greater development of sense organs and nervous systems conveying and processing information about the state of the organism’s surroundings, and finally greater and greater consciousness. You can call this direction progress or by some other name.”
Harold Mosowitz says “Life is organization. From prokaryotic cells, eukaryotic cells, tissues and organs, to plants and animals, families, communities, ecosystems, and living planets, life is organization, at every scale. The evolution of life is the increase of biological organization, if it is anything. Clearly, if life originates and makes evolutionary progress without organizing input somehow supplied, then something has organized itself. Logical entropy in a closed system has decreased. This is the violation that people are getting at, when they say that life violates the second law of thermodynamics. This violation, the decrease of logical entropy in a closed system, must happen continually in the Darwinian account of evolutionary progress.”
Entropy occurs in all systems. That is an indisputable fact. However, if we start defining boundaries, then we are prone to see that these bounded systems decay faster. However, if we open up the system to leave it unbounded, then there are a lot of other forces that come into play that is tantamount to some net progress. While it might be true that energy balances out, what we miss as social scientists or model builders or avid students of systems – we miss out on indices that reflect on leaps in quality and resilience and a horde of other factors that stabilizes the system despite the constant and ominous presence of entropy’s inner workings.
Chaos as a system: New Framework
Chaos is not an unordered phenomenon. There is a certain homeostatic mechanism at play that forces a system that might have inherent characteristics of a “chaotic” process to converge to some sort of stability with respect to predictability and parallelism. Our understanding of order which is deemed to be opposite of chaos is the fact that there is a shared consensus that the system will behave in an expected manner. Hence, we often allude to systems as being “balanced” or “stable” or “in order” to spotlight these systems. However, it is also becoming common knowledge in the science of chaos that slight changes in initial conditions in a system can emit variability in the final output that might not be predictable. So how does one straddle order and chaos in an observed system, and what implications does this process have on ongoing study of such systems?
Chaotic systems can be considered to have a highly complex order. It might require the tools of pure mathematics and extreme computational power to understand such systems. These tools have invariably provided some insights into chaotic systems by visually representing outputs as re-occurrences of a distribution of outputs related to a given set of inputs. Another interesting tie up in this model is the existence of entropy, that variable that taxes a system and diminishes the impact on expected outputs. Any system acts like a living organism: it requires oodles of resources to survive and a well-established set of rules to govern its internal mechanism driving the vector of its movement. Suddenly, what emerges is the fact that chaotic systems display some order while subject to an inherent mechanism that softens its impact over time. Most approaches to studying complex and chaotic systems involve understanding graphical plots of fractal nature, and bifurcation diagrams. These models illustrate very complex re occurrences of outputs directly related to inputs. Hence, complex order occurs from chaotic systems.
A case in point would be the relation of a population parameter in the context to its immediate environment. It is argued that a population in an environment will maintain a certain number and there would be some external forces that will actively work to ensure that the population will maintain at that standard number. It is a very Malthusian analytic, but what is interesting is that there could be some new and meaningful influences on the number that might increase the scale. In our current meaning, a change in technology or ingenuity could significantly alter the natural homeostatic number. The fact remains that forces are always at work on a system. Some systems are autonomic – it self-organizes and corrects itself toward some stable convergence. Other systems are not autonomic and once can only resort to the laws of probability to get some insight into the possible outputs – but never to a point where there is a certainty in predictive prowess.
Organizations have a lot of interacting variables at play at any given moment. In order to influence the organization behavior or/and direction, policies might be formulated to bring about the desirable results. However, these nudges toward setting off the organization in the right direction might also lead to unexpected results. The aim is to foresee some of these unexpected results and mollify the adverse consequences while, in parallel, encourage the system to maximize the benefits. So how does one effect such changes?
It all starts with building out an operating framework. There needs to be a clarity around goals and what the ultimate purpose of the system is. Thus there are few objectives that bind the framework.
- Clarity around goals and the timing around achieving these goals. If there is no established time parameter, then the system might jump across various states over time and it would be difficult to establish an outcome.
- Evaluate all of the internal and external factors that might operate in the framework that would impact the success of organizational mandates and direction. Identify stasis or potential for stasis early since that mental model could stem the progress toward a desirable impact.
- Apply toll gates strategically to evaluate if the system is proceeding along the lines of expectation, and any early aberrations are evaluated and the rules are tweaked to get the system to track on a desirable trajectory.
- Develop islands of learning across the path and engage the right talent and other parameters to force adaptive learning and therefore a more autonomic direction to the system.
- Bind the agents and actors in the organization to a shared sense of purpose within the parameter of time.
- Introduce diversity into the framework early in the process. The engagement of diversity allows the system to modulate around a harmonic mean.
- Finally, maintain a well document knowledge base such that the accretive learning that results due to changes in the organization become springboard for new initiatives that reduces the costs of potential failures or latency in execution.
- Encouraging the leadership to ensure that the vector is pointed toward the right direction at any given time.
Once a framework and the engagement rules are drawn out, it is necessary to rely on the natural velocity and self-organization of purposeful agents to move the agenda forward, hopefully with little or no intervention. A mechanism of feedback loops along the way would guide the efficacy of the direction of the system. The implications is that the strategy and the operations must be aligned and reevaluated and positive behavior is encouraged to ensure that the systems meets its objective.
However, as noted above, entropy is a dynamic that often threatens to derail the system objective. There will be external or internal forces constantly at work to undermine system velocity. The operating framework needs to anticipate that real possibility and pre-empt that with rules or introduction of specific capital to dematerialize these occurrences. Stasis is an active agent that can work against the system dynamic. Stasis is the inclination of agents or behaviors that anchors the system to some status quo – we have to be mindful that change might not be embraced and if there are resistors to that change, the dynamic of organizational change can be invariably impacted. It will take a lot more to get something done than otherwise needed. Identifying stasis and agents of stasis is a foundational element
While the above is one example of how to manage organizations in the shadows of the properties of how chaotic systems behave, another example would be the formulation of strategy of the organization in responses to external forces. How do we apply our learnings in chaos to deal with the challenges of competitive markets by aligning the internal organization to external factors? One of the key insights that chaos surfaces is that it is nigh impossible for one to fully anticipate all of the external variables, and leaving the system to dynamically adapt organically to external dynamics would allow the organization to thrive. To thrive in this environment is to provide the organization to rapidly change outside of the traditional hierarchical expectations: when organizations are unable to make those rapid changes or make strategic bets in response to the external systems, then the execution value of the organization diminishes.
Margaret Wheatley in her book Leadership and the New Science: Discovering Order in a Chaotic World Revised says, “Organizations lack this kind of faith, faith that they can accomplish their purposes in various ways and that they do best when they focus on direction and vision, letting transient forms emerge and disappear. We seem fixated on structures…and organizations, or we who create them, survive only because we build crafty and smart—smart enough to defend ourselves from the natural forces of destruction. Karl Weick, an organizational theorist, believes that “business strategies should be “just in time…supported by more investment in general knowledge, a large skill repertoire, the ability to do a quick study, trust in intuitions, and sophistication in cutting losses.”
We can expand the notion of a chaos in a system to embrace the bigger challenges associated with environment, globalization, and the advent of disruptive technologies.
One of the key challenges to globalization is how policy makers would balance that out against potential social disintegration. As policies emerge to acknowledge the benefits and the necessity to integrate with a new and dynamic global order, the corresponding impact to local institutions can vary and might even lead to some deleterious impact on those institutions. Policies have to encourage flexibility in local institutional capability and that might mean increased investments in infrastructure, creating a diverse knowledge base, establishing rules that govern free but fair trading practices, and encouraging the mobility of capital across borders. The grand challenges of globalization is weighed upon by government and private entities that scurry to create that continual balance to ensure that the local systems survive and flourish within the context of the larger framework. The boundaries of the system are larger and incorporates many more agents which effectively leads to the real possibility of systems that are difficult to be controlled via a hierarchical or centralized body politic Decision making is thus pushed out to the agents and actors but these work under a larger set of rules. Rigidity in rules and governance can amplify failures in this process.
Related to the realities of globalization is the advent of the growth in exponential technologies. Technologies with extreme computational power is integrating and create robust communication networks within and outside of the system: the system herein could represent nation-states or companies or industrialization initiatives. Will the exponential technologies diffuse across larger scales quickly and will the corresponding increase in adoption of new technologies change the future of the human condition? There are fears that new technologies would displace large groups of economic participants who are not immediately equipped to incorporate and feed those technologies into the future: that might be on account of disparity in education and wealth, institutional policies, and the availability of opportunities. Since technologies are exponential, we get a performance curve that is difficult for us to understand. In general, we tend to think linearly and this frailty in our thinking removes us from the path to the future sooner than later. What makes this difficult is that the exponential impact is occurring across various sciences and no one body can effectively fathom the impact and the direction. Bill Gates says it well “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.” Does chaos theory and complexity science arm us with a differentiated tool set than the traditional toolset of strategy roadmaps and product maps? If society is being carried by the intractable and power of the exponent in advances in technology, than a linear map might not serve to provide the right framework to develop strategies for success in the long-term. Rather, a more collaborative and transparent roadmap to encourage the integration of thoughts and models among the actors who are adapting and adjusting dynamically by the sheer force of will would perhaps be an alternative and practical approach in the new era.
Lately there has been a lot of discussion around climate change. It has been argued, with good reason and empirical evidence, that environment can be adversely impacted on account of mass industrialization, increase in population, resource availability issues, the inability of the market system to incorporate the cost of spillover effects, the adverse impact of moral hazard and the theory of the commons, etc. While there are demurrers who contest the long-term climate change issues, the train seems to have already left the station! The facts do clearly reflect that the climate will be impacted. Skeptics might argue that science has not yet developed a precise predictive model of the weather system two weeks out, and it is foolhardy to conclude a dystopian future on climate fifty years out. However, the alternative argument is that our inability to exercise to explain the near-term effects of weather changes and turbulence does not negate the existence of climate change due to the accretion of greenhouse impact. Boiling a pot of water will not necessarily gives us an understanding of all of the convection currents involved among the water molecules, but it certainly does not shy away from the fact that the water will heat up.
Managing Scale
| I think the most difficult thing had been scaling the infrastructure. Trying to support the response we had received from our users and the number of people that were interested in using the software. – Shawn Fanning |
Froude’s number? It is defined as the square of the ship’s velocity divided by its length and multiplied by the acceleration caused by gravity. So why are we introducing ships in this chapter? As I have done before, I am liberally standing on the shoulder of the giant, Geoffrey West, and borrowing from his account on the importance of the Froude’s number and the practical implications. Since ships are subject to turbulence, using a small model that works in a simulated turbulent environment might not work when we manufacture a large ship that is facing the ebbs and troughs of a finicky ocean. The workings and impact of turbulence is very complex, and at scale it becomes even more complex. Froude’s key contribution was to figure out a mathematical pathway of how to efficiently and effectively scale from a small model to a practical object. He did that by using a ratio as the common denominator. Mr. West provides an example that hits home: How fast does a 10-foot-long ship have to move to mimic the motion of a 700-foot-long ship moving at 20 knots. If they are to have the same Froude number (that is, the same value of the square of their velocity divided by their length), then the velocity has to scale as the square root of their lengths. The ratio of the square root of their lengths is the the square of 700 feet of the ship/10 feet of the model ship which turns out to be the square of 70. For the 10-foot model to mimic the motion of a large ship, it must move at the speed of 20 knots/ square of 70 or 2.5 knots. The Froude number is still widely used across many fields today to bridge small scale and large-scale thinking. Although this number applies to physical systems, the notion that adaptive systems can be similarly bridged through appropriate mathematical equations. Unfortunately, because of the increased number of variables impacting adaptive systems and all of these variables working and learning from one another, the task of establishing a Froude number becomes diminishingly small.
The other concept that has gained wide attention is the science of allometry. Allometry essentially states that as size increases, then the form of the object would change. Allometric scaling governs all complex physical and adaptive systems. So the question is whether there are some universal laws or mathematics that can be used to enable us to better understand or predict scale impacts. Let us extend this thinking a bit further. If sizes influence form and form constitute all sub-physical elements, then it would stand to reason that a universal law or a set of equations can provide deep explanatory powers on scale and systems. One needs to bear in mind that even what one might consider a universal law might be true within finite observations and boundaries. In other words, if there are observations that fall outside of those boundaries, one is forced into resetting our belief in the universal law or to frame a new paradigm to cover these exigencies. I mention this because as we seek to understand business and global grand challenges considering the existence of complexity, scale, chaos and seeming disorder – we might also want to embrace multiple laws or formulations working at different hierarchies and different data sets to arrive at satisficing solutions to the problems that we want to wrestle with.
Physics and mathematics allow a qualitatively high degree of predictability. One can craft models across different scales to make a sensible approach on how to design for scale. If you were to design a prototype using a 3D printer and decide to scale that prototype a 100X, there are mathematical scalar components that are factored into the mechanics to allow for some sort of equivalence which would ultimately lead to the final product fulfilling its functional purpose in a complex physical system. But how does one manage scale in light of those complex adaptive systems that emerge due to human interactions, evolution of organization, uncertainty of the future, and dynamic rules that could rapidly impact the direction of a company?
Is scale a single measure? Or is it a continuum? In our activities, we intentionally or unintentionally invoke scale concepts. What is the most efficient scale to measure an outcome, so we can make good policy decisions, how do we apply our learning from one scale to a system that operates on another scale and how do we assess how sets of phenomena operate at different scales, spatially and temporally, and how they impact one another? Now the most interesting question: Is scale polymorphous? Does the word scale have different meanings in different contexts? When we talk about microbiology, we are operating at micro-scales. When we talk at a very macro level, our scales are huge. In business, we regard scale with respect to how efficiently we grow. In one way, it is a measure but for the following discussion, we will interpret scale as non-linear growth expending fewer and fewer resources to support that growth as a ratio.
As we had discussed previously, complex adaptive systems self-organize over time. They arrive at some steady state outcome without active intervention. In fact, the active intervention might lead to unintended consequences that might even spell doom for the system that is being influenced. So as an organization scales, it is important to keep this notion of rapid self-organization in mind which will inform us to make or not make certain decisions from a central or top-down perspective. In other words, part of managing scale successfully is to not manage it at a coarse-grained level.
The second element of successfully managing scale is to understand the constraints that prevent scale. There is an entire chapter dedicated to the theory of constraints which sheds light on why this is a fundamental process management technique that increases the pace of the system. But for our purposes in this section, we will summarize as follows: every system as it grows have constraints. It is important to understand the constraints because these constraints slow the system: the bottlenecks have to be removed. And once one constraint is removed, then one comes across another constraint. The system is a chain of events and it is imperative that all of these events are identified. The weakest links harangue the systems and these weakest links have to be either cleared or resourced to enable the system to scale. It is a continuous process of observation and tweaking the results with the established knowledge that the demons of uncertainty and variability can reset the entire process and one might have to start again. Despite that fact, constraint management is an effective method to negotiate and manage scale.
The third element is devising the appropriate organization architecture. As one projects into the future, management might be inclined toward developing and investing in the architecture early to accommodate the scale. Overinvestment in the architecture might not be efficient. As mentioned, cities and social systems that grow 100% require 85% investment in infrastructure: in other words, systems grow on a sublinear scale from an infrastructure perspective. How does management of scale arrive at the 85%? It is nigh impossible, but it is important to reserve that concept since it informs management to architect the infrastructure cautiously. Large investments upfront could be a waste or could slow the system down: alternative, investments that are postponed a little too late can also impact the system adversely.
The fourth element of managing scale is to focus your lens of opportunity. In macroecology, we can arrive at certain conclusions when we regard the system from a distance versus very closely. We can subsume our understanding into one big bucket called climate change and then we figure out different ways to manage the complexity that causes the climate change by invoking certain policies and incentives at a macro level. However, if we go closer, we might decide to target a very specific contributor to climate change – namely, fossil fuels. The theory follows that to manage the dynamic complexity and scale of climate impact – it would be best to address a major factor which, in this case, would be fossil fuels. The equivalence of this in a natural business setting would be to establish and focus the strategy for scale in a niche vertical or a relatively narrower set of opportunities. Even though we are working in the web of complex adaptive systems, we might devise strategies to directionally manage the business within the framework of complex physical systems where we have an understanding of the slight variations of initial state and the realization that the final outcome might be broad but yet bounded for intentional management.
The final element is the management of initial states. Complex physical systems are governed by variation in initial states. Perturbation of these initial states can lead to a wide divergence of outcomes, albeit bounded within a certain frame of reference. It is difficult perhaps to gauge all the interactions that might occur from a starting point to the outcome, although we agree that a few adjustments like decentralization of decision making, constraint management, optimal organization structure and narrowing the playing field would be helpful.
Emergent Systems: Introduction
The whole is greater than the sum of its parts. “Emergent properties” refer to those properties that emerge that might be entirely unexpected. As discussed in CAS, they arise from the collaborative functioning of a system. In other words, emergent properties are properties of a group of items, but it would be erroneous for us to reduce such systems into properties of atomic elements and use those properties as binding elements to understand emergence Some common examples of emergent properties include cities, bee hives, ant colonies and market systems. Out thinking attributes causal effects – namely, that behavior of elements would cause certain behaviors in other hierarchies and thus an entity emerges at a certain state. However, we observe that a process of emergence is the observation of an effect without an apparent cause. Yet it is important to step back and regard the relationships and draw lines of attribution such that one can concur that there is an impact of elements at the lowest level that surfaces, in some manner, at the highest level which is the subject of our observation.
Jochenn Fromm in his paper “Types and Forms of Emergence” has laid this out best. He says that emergent properties are “amazing and paradox: fundamental but familiar.” In other words, emergent properties are changeless and changing, constant and fluctuating, persistent and shifting, inevitable and unpredictable. The most important note that he makes is that the emergent property is part of the system and at the same time it might not always be a part of the system. There is an undercurrent of novelty or punctuated gaps that might arise that is inexplicable, and it is this fact that renders true emergence virtually irreducible. Thus, failure is embodied in all emergent systems – failure being that the system does not behave according to expectation. Despite all rules being followed and quality thresholds are established at every toll gate at the highest level, there is still a possibility of failure which suggests that there is some missing information in the links. It is also possible that the missing information is dynamic – you do not step in the same water twice – which makes the study to predict emergent systems to be a rather difficult exercise. Depending on the lens through which we look at, the system might appear or disappear.
There are two types of emergence: Descriptive and Explanatory emergence. Descriptive emergence means that properties of wholes cannot be necessarily defined through the properties of the pasts. Explanatory emergence means laws of complex systems cannot be deduced from the laws of interaction of simpler elements that constitute it. Thus the emergence is a result of the amount of variety embodied in the system, the amount of external influence that weights and shapes the overall property and direction of the system, the type of resources that the system consumes, the type of constraints that the system is operating under and the number of levels of sub-systems that work together to build out the final system. Thus, systems can be benign as in the system is relatively more predictable whereas a radical system is a material departure of a system from expectation. If the parts that constitute a system is independent of its workings from other parts and can be boxed within boundaries, emergent systems become more predictable. A watch is an example of a system that follows the different mechanical elements in a watch that are geared for reading the time as it ultimate purpose. It is a good example of a complex physical system. However, these systems are very brittle – a failure in one point can cascade into a failure of the entire system. Systems that are more resilient are those where the elements interact and learn from one another. In other words, the behavior of the elements excites other elements – all of which work together to create a dance toward a more stable state. They deploy what is often called the flocking trick and the pheromone trick. Flocking trick is largely the emulation of the particles that are close to each other – very similar to the cellular automata as introduced by Neumann and discussed in the earlier chapter. The Pheromone trick reflects how the elements leave marks that are acted upon as signals by other elements and thus they all work together around these signal trails to behave and thus act as a forcing function to create the systems.
There are systems that have properties of extremely strong emergence. What does Consciousness, Life, and Culture have in common? How do we look at Climate? What about the organic development of cities? These are just some examples of system where determinism is nigh impossible. We might be able to tunnel through the various and diverse elements that embody the system, but it would be difficult to coherently and tangibly draw all set of relationships, signals, effectors and detectors, etc. to grapple with a complete understanding of the system. Wrestling a strong emergent system would be a task that might even be outside the purview of the highest level of computational power available. And yet, these systems exist, and they emerge and evolve. Yet we try to plan for these systems or plan to direct policies to influence the system, not fully knowing the impact. This is also where the unintended consequences of our action might take free rein.
Comparative Literature and Business Insights
“Literature is the art of discovering something extraordinary about ordinary people, and saying with ordinary words something extraordinary.” – Boris Pasternak
“It is literature which for me opened the mysterious and decisive doors of imagination and understanding. To see the way others see. To think the way others think. And above all, to feel.” – Salman Rushdie
There is a common theme that cuts across literature and business. It is called imagination!
Great literature seeds the mind to imagine faraway places across times and unique cultures. When we read a novel, we are exposed to complex characters that are richly defined and the readers’ subjective assessment of the character and the context defines their understanding of how the characters navigate the relationships and their environment. Great literature offers many pauses for thought, and long after the book is read through … the theme gently seeps in like silt in the readers’ cumulative experiences. It is in literature that the concrete outlook of humanity receives its expression. Comparative literature which is literature assimilated across many different countries enable a diversity of themes that intertwine into the readers’ experiences augmented by the reality of what they immediately experience – home, work, etc. It allows one to not only be capable of empathy but also … to craft out the fluid dynamics of ever changing concepts by dipping into many different types of case studies of human interaction. The novel and the poetry are the bulwarks of literature. It is as important to study a novel as it is to enjoy great poetry. The novel characterizes a plot/(s) and a rich tapestry of actions of the characters that navigates through these environments: the poetry is the celebration of the ordinary into extraordinary enactments of the rhythm of the language that transport the readers, through images and metaphor, into single moments. It breaks the linear process of thinking, a perpendicular to a novel.
Business insights are generally a result of acute observation of trends in the market, internal processes, and general experience. Some business schools practice case study method which allows the student to have a fairly robust set of data points to fall back upon. Some of these case studies are fairly narrow but there are some that gets one to think about personal dynamics. It is a fact that personal dynamics and biases and positioning plays a very important role in how one advocates, views, or acts upon a position. Now the schools are layering in classes on ethics to understand that there are some fundamental protocols of human nature that one has to follow: the famous adage – All is fair in love and war – has and continues to lose its edge over time. Globalization, environmental consciousness, individual rights, the idea of democracy, the rights of fair representation, community service and business philanthropy are playing a bigger role in today’s society. Thus, business insights today are a result of reflection across multiple levels of experience that encompass not the company or the industry …but encompass a broader array of elements that exercises influence on the company direction. In addition, one always seeks an end in mind … they perpetually embrace a vision that is impacted by their judgments, observations and thoughts. Poetry adds the final wing for the flight into this metaphoric realm of interconnections – for that is always what a vision is – a semblance of harmony that inspires and resurrects people to action.
I contend that comparative literature is a leading indicator that allows a person to get a feel for the general direction of the express and latent needs of people. Furthermore, comparative literature does not offer a solution. Great literature does not portend a particular end. They leave open a multitude of possibilities and what-ifs. The reader can literally transport themselves into the environment and wonder at how he/she would act … the jump into a vicarious existence steeps the reader into a reflection that sharpens the intellect. This allows the reader in a business to be better positioned to excavate and address the needs of current and potential customers across boundaries.
“Literature gives students a much more realistic view of what’s involved in leading” than many business books on leadership, said the professor. “Literature lets you see leaders and others from the inside. You share the sense of what they’re thinking and feeling. In real life, you’re usually at some distance and things are prepared, polished. With literature, you can see the whole messy collection of things that happen inside our heads.” – Joseph L. Badaracco, the John Shad Professor of Business Ethics at Harvard Business School (HBS)
Disseminating financial knowledge to develop engaged organizations
Financial awareness of key drivers are becoming the paramount leading indicators for organizational success. For most, the finance department is a corner office service that offers ad hoc analysis on strategic and operational initiatives to a company, and provides an ex-post assessment of the financial condition of the company among a select few. There are some key financial metrics that one wants to measure across all companies and all industries without exception, but then there are unique metrics that reflect the key underlying drivers for organizational success. Organizations align their forays into new markets, new strategies and new ventures around a narrative that culminates in a financial metric or a proxy that illustrates opportunities lost or gained.
Having been cast in operational finance roles for a good length of my career, I have often encountered a high level of interest to learn financial concepts in areas such as engineering, product management, operations, sales, etc. I have to admit that I have been humbled by the fairly wide common-sense understanding of basic financial concepts that these folks have. However, in most cases, the understanding is less than skin deep with misunderstandings that are meaningful. The good news is that I have also noticed a promising trend, namely … the questions are more thoroughly weighed by the “non-finance” participants, and there seems to be an elevated understanding of key financial drivers that translate to commercial success. This knowledge continues to accelerate … largely, because of convergence of areas around data science, analytics, assessment of personal ownership stakes, etc. But the passing of such information across these channels to the hungry recipients are not formalized. In other words, I posit that having a formal channel of inculcating financial education across the various functional areas would pay rich dividends for the company in the long run. Finance is a vast enough field that partaking general knowledge in these concepts which are more than merely skin-deep would also enable the finance group to engage in meaningful conversations with other functional experts, thus allowing the narrative around the numbers to be more wholesome. Thus, imparting the financial knowledge would be beneficial to the finance department as well.
To be effective in creating a formal channel of disseminating information of the key areas in finance that matter to the organization, it is important to understand the operational drivers. When I say operational drivers, I am expanding that to encompass drivers that may uniquely affect other functional areas. For example, sales may be concerned with revenue, margins whereas production may be concerned with server capacity, work-in-process and throughput, etc. At the end, the financial metrics are derivatives. They are cross products of single or multiple drivers and these are the elements that need to be fleshed out to effect a spirited conversation. That would then enable the production of a financial barometer that everyone in the organization can rally behind and understand, and more importantly … be able to assess how their individual contribution has and will advance organization goals.
Darkness at Noon in Facebook!
Facebook began with a simple thesis: Connect Friends. That was the sine qua non of its existence. From a simple thesis to an effective UI design, Facebook has grown over the years to become the third largest community in the world. But as of the last few years they have had to resort to generating revenue to meet shareholder expectations. Today it is noon at Facebook but there is the long shadow of darkness that I posit have fallen upon perhaps one of the most influential companies in history.
The fact is that leaping from connecting friends to managing the conversations allows Facebook to create this petri dish to understand social interactions at large scale eased by their fine technology platform. To that end, they are moving into alternative distribution channels to create broader reach into global audience and to gather deeper insights into the interaction templates of the participants. The possibilities are immense: in that, this platform can be a collaborative beachhead into discoveries, exploration, learning, education, social and environmental awareness and ultimately contribute to elevated human conscience. But it has faltered, perhaps the shareholders and the analysts are much to blame, on account of the fangled existence of market demands and it has become one global billboard for advertisers to promote their brands. Darkness at noon is the most appropriate metaphor to reflect Facebook as it is now.
Let us take a small turn to briefly look at some of other very influential companies that have not been as much derailed as has Facebook. The companies are Twitter, Google and LinkedIn. Each of them are the leaders in their category, and all of them have moved toward monetization schemes from their specific user base. Each of them has weighed in significantly in their respective categories to create movements that have or will affect the course of the future. We all know how Twitter has contributed to super-fast news feeds globally that have spontaneously generated mass coalescence around issues that make a difference; Google has been an effective tool to allow an average person to access information; and LinkedIn has created professional and collaborative environment in the professional space. Thus, all three of these companies, despite supplementing fully their appetite for revenue through advertising, have not compromised their quintessence for being. Now all of these companies can definitely move their artillery to encompass the trajectory of FB but that would be a steep hill to climb. Furthermore, these companies have an aura associated within their categories: attempts to move out of their category have been feeble at best, and in some instances, not successful. Facebook has a phenomenal chance of putting together what they have to create a communion of knowledge and wisdom. And no company exists in the market better suited to do that at this point.
One could counter that Facebook sticks to its original vision and that what we have today is indeed what Facebook had planned for all along since the beginning. I don’t disagree. My point of contention in this matter is that though is that Facebook has created this informal and awesome platform for conversations and communities among friends, it has glossed over the immense positive fallout that could occur as a result of these interactions. And that is the development and enhancement of knowledge, collaboration, cultural play, encourage a diversity of thought, philanthropy, crowd sourcing scientific and artistic breakthroughs, etc. In other words, the objective has been met for the most part. Thank you Mark! Now Facebook needs to usher in a renaissance in the courtyard. Facebook needs to find a way out of the advertising morass that has shed darkness over all the product extensions and launches that have taken place over the last 2 years: Facebook can force a point of inflection to quadruple its impact on the course of history and knowledge. And the revenue will follow!
Importance of Heroes and Narratives in Organizations
“My own heroes are the dreamers, those men and women who tried to make the world a better place than when they found it, whether in small ways or great ones. Some succeeded, some failed, most had mixed results… but it is the effort that’s heroic, as I see it. Win or lose, I admire those who fight the good fight.” – George Martin
“Stories, like people and butterflies and songbirds’ eggs and human hearts and dreams, are also fragile things, made up of nothing stronger or more lasting than twenty-six letters and a handful of punctuation marks. Or they are words on the air, composed of sounds and ideas-abstract, invisible, gone once they’ve been spoken-and what could be more frail than that? But some stories, small, simple ones about setting out on adventures or people doing wonders, tales of miracles and monsters, have outlasted all the people who told them, and some of them have outlasted the lands in which they were created.” – Neil Gaiman
Heroes are not born. Circumstance and happenstance create heroes. In some cases, heroes are individuals who walk into a minefield of uncertainty that threatens their natural inclination for self-preservation in the interest of value systems and people that are alien to the individual. Thus, a private in an army is a hero already in the fact that he/she is walking into possible harm’s way and serving a cause to serve and protect people not necessarily related to him/her. One has heard the adage – one man’s freedom fighter is another person’s terrorist. Thus, someone whom we call a terrorist may be perceived a hero by someone else. Thus, in this case …it all becomes a matter of a point of view, but the fundamental point remains – a hero is considered a person who abnegates and abjures their rights to self-preservation for some greater perceived good.
Sustaining innovation is a vital yet difficult task. Innovation requires the coordinated efforts of many actors to facilitate (1) the recombination of ideas to generate novelty, (2) real-time problem solving, and (3) linkages between present innovation efforts with past experiences and future aspirations. Innovation narratives are cultural mechanisms that address these coordination requirements by enabling translation. Specifically, innovation narratives are powerful mechanisms for translating ideas across the organization so that they are comprehensible and appear legitimate to others. Narratives also enable people to translate emergent situations that are ambiguous or equivocal so as to promote real-time problem solving. With their accumulation, innovation narratives provide a generative memory for organizations that enable people to translate ideas accumulated from particular instances of past innovation to inform current and future efforts.
The concept of collective identity has gained prominence within organizational theory as researchers have studied how it consequentially shapes organizational behavior. However, much less attention has been paid to the question of how nascent collective identities become legitimated. Although it is conventionally argued that membership expansion leads to collective identity legitimacy, one draws on the notion of cultural entrepreneurship to argue that the relationship is more complex and is culturally mediated by the stories told by group members. Legitimacy is more likely to be achieved when members articulate a clear defining collective identity story that identifies the group’s orienting purpose and core practices. Although membership expansion can undermine legitimation by introducing discrepant actors and practices to a collective identity, this potential downside is mitigated by compelling narratives, which help to coordinate expansion. And that is where the heroes can be interwoven into organizational theory and behavior. It is important to create environments that by happenstance and circumstance create heroes. The architecture of great organizations imputes heroes and narratives in their tapestry.
Heroes and narratives are instrumental in organizations that forge a pathway to long-term sustenance and growth. Hence, we are quick to idolize figures – Iacocca, Welch, Jobs, Ellison, Gates, Benioff, Gerstner, Branson, Bezos, Zuckerberg, Brin and Page, etc. We learn narratives through case studies, news print, scholarly books on successful companies; and we emulate and steal and copy and parody and so much more … not necessarily because we want to be them but we want to create our identity in our own lair in ecosystems that move with or against the strongest currents.
So it is essential to celebrate the heroes and the narratives of great companies as an additional instrument to ignite engagement and foray into uncharted territories and conquer the unknown. Hence, personally I have also found solace in reading biographies of people who have made a difference, and a great pleasure in vicariously living through the ebbs and troughs of great companies
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