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.
“The world’s entire scientific … heritage … is increasingly being digitized and locked up by a handful of private corporations… The Open Access Movement has fought valiantly to ensure that scientists do not sign their copyrights away but instead ensure their work is published on the Internet, under terms that allow anyone to access it.” – Aaron Swartz
Information, in the context of scholarly articles by research at universities and think-tanks, is not a zero sum game. In other words, one person cannot have more without having someone have less. When you start creating “Berlin” walls in the information arena within the halls of learning, then learning itself is compromised. In fact, contributing or granting the intellectual estate into the creative commons serves a higher purpose in society – an access to information and hence, a feedback mechanism that ultimately enhances the value to the end-product itself. How? Since now the product has been distributed across a broader and diverse audience, and it is open to further critical analyses.
The universities have built a racket. They have deployed a Chinese wall between learning in a cloistered environment and the world who are not immediate participants. The Guardian wrote an interesting article on this matter and a very apt quote puts it all together.
“Academics not only provide the raw material, but also do the graft of the editing. What’s more, they typically do so without extra pay or even recognition – thanks to blind peer review. The publishers then bill the universities, to the tune of 10% of their block grants, for the privilege of accessing the fruits of their researchers’ toil. The individual academic is denied any hope of reaching an audience beyond university walls, and can even be barred from looking over their own published paper if their university does not stump up for the particular subscription in question.
This extraordinary racket is, at root, about the bewitching power of high-brow brands. Journals that published great research in the past are assumed to publish it still, and – to an extent – this expectation fulfils itself. To climb the career ladder academics must get into big-name publications, where their work will get cited more and be deemed to have more value in the philistine research evaluations which determine the flow of public funds. Thus they keep submitting to these pricey but mightily glorified magazines, and the system rolls on.”
JSTOR is a not-for-profit organization that has invested heavily in providing an online system for archiving, accessing, and searching digitized copies of over 1,000 academic journals. More recently, I noticed some effort on their part to allow public access to only 3 articles over a period of 21 days. This stinks! This policy reflects an intellectual snobbery beyond Himalayan proportions. The only folks that have access to these academic journals and studies are professors, and researchers that are affiliated with a university and university libraries. Aaron Swartz noted the injustice of hoarding such knowledge and tried to distribute a significant proportion of JSTOR’s archive through one or more file-sharing sites. And what happened thereafter was perhaps one of the biggest misapplication of justice. The same justice that disallows asymmetry of information in Wall Street is being deployed to preserve the asymmetry of information at the halls of learning.
MSNBC contributor Chris Hayes criticized the prosecutors, saying “at the time of his death Aaron was being prosecuted by the federal government and threatened with up to 35 years in prison and $1 million in fines for the crime of—and I’m not exaggerating here—downloading too many free articles from the online database of scholarly work JSTOR.”
The Associated Press reported that Swartz’s case “highlights society’s uncertain, evolving view of how to treat people who break into computer systems and share data not to enrich themselves, but to make it available to others.”
Chris Soghioian, a technologist and policy analyst with the ACLU, said, “Existing laws don’t recognize the distinction between two types of computer crimes: malicious crimes committed for profit, such as the large-scale theft of bank data or corporate secrets; and cases where hackers break into systems to prove their skillfulness or spread information that they think should be available to the public.”
Kelly Caine, a professor at Clemson University who studies people’s attitudes toward technology and privacy, said Swartz “was doing this not to hurt anybody, not for personal gain, but because he believed that information should be free and open, and he felt it would help a lot of people.”
And then there were some modest reservations, and Swartz actions were attributed to reckless judgment. I contend that this does injustice to someone of Swartz’s commitment and intellect … the recklessness was his inability to grasp the notion that an imbecile in the system would pursue 35 years of imprisonment and $1M fine … it was not that he was not aware of what he was doing but he believed, as does many, that scholarly academic research should be available as a free for all.
We have a Berlin wall that needs to be taken down. Swartz started that but he was unable to keep at it. It is important to not rest in this endeavor and that everyone ought to actively petition their local congressman to push bills that will allow open access to these academic articles.
John Maynard Keynes had warned of the folly of “shutting off the sun and the stars because they do not pay a dividend”, because what is at stake here is the reach of the light of learning. Aaron was at the vanguard leading that movement, and we should persevere to become those points of light that will enable JSTOR to disseminate the information that they guard so unreservedly.
All products go through a life-cycle. However, the genius of an organization lies in how to manage the life-cycle of the product and extend it as necessary to serve the customers. Thus, it is not merely the wizardry in technology and manufacturing that determine the ultimate longevity of the product in the market and the mind share of the customer. The product has to respond to the diversity of demands determined by disposable income, demographics, geography, etc. In business school speak, we say that this is part of market segmentation coupled with the appropriate marketing message. However, there is not an explicit strategy formulated around identifying
- Corporate Culture
- Extended Culture
To achieve success, firms increasingly must develop products by leveraging ad coordinating broad creative capabilities and resources, which often are diffused across geographical and cultural boundaries. But what we have to explore is a lot more than that from the incipient stages that a product has imagined: How do we instill unique corporate DNA into the product that immediately marks the product with a corporate signature? In addition, how do we built out a product that is tenable across the farthest reaches of geography and cultural diversity?
Thus, an innovative approach is called for in product development … particularly, in a global context. The approach entails getting cross-disciplinary teams in liberal arts, science, business, etc. to work together to gather deeper insights into the cultural strains that drive decisions in various markets. To reiterate, there is no one particular function that is paramount: all of them have to work and improvise together while ensuring that there are channels that gather feedback. The cross disciplinary team and the institutionalization of a feedback mechanism that can be quickly acted upon are the key parameters to ensure that the right product is in the market and that it will be extended accordingly to the chatter of the crowds.
Having said that, this is hardly news! A lot of companies are well on their way to instill these factors into product design and development. Companies have created organizational architectures in the corporate structure in a manner that culturally appropriate products are developed and maintained in dispersed local markets. However, in most instances, we have also seen that the way they view this is to have local managers run the show, with the presumption that these “culturally appropriate” products will make good in those markets. But along the way, the piece that dissembles over time on account of creating the local flavor is that the product may not mirror the culture that the corporate group wants to instill. If these two are not aptly managed and balanced, islands of conflict will be created. Thus, my contention is that a top-down value mandate ought to set the appropriate parameters inside which the hotbed of collaborative activity would take place for product design and development in various markets.
Thus the necessary top down value systems that would bring culture into products would be:
- Open areas for employees to express their thoughts and ideas
- Diversity of people with different skill sets in product teams will contribute to product development
- Encouraging internal and external speakers to expound upon the product touch points in the community.
- Empowerment and recognition systems.
- Proper formulation of monetary incentives to inspire and maintain focus.
Posted in Corporate Social Responsibility, Employee Engagement, Employee retention, Extrinsic Rewards, Innovation, Intrinsic Rewards, Leadership, Learning Organization, Learning Process, Organization Architecture, Product Design, Recognition, Rewards
“The reality distortion field was a confounding mélange of a charismatic rhetorical style, an indomitable will, and an eagerness to bend any fact to fit the purpose at hand. If one line of argument failed to persuade, he would deftly switch to another. Sometimes, he would throw you off balance by suddenly adopting your position as his own, without acknowledging that he ever thought differently. “
– Andy Hertzfield on Steve Jobs’ Reality Distortion Field.
Many of us have heard the word – Reality Distortion Field. The term has been attributed to Steve Jobs who was widely known to have communicated messages to his constituency in a manner such that the reality of the situation was supplanted by him packaging the message so that people would take the bait and pursue paths that would, upon closer investigation, be dissonant from reality. But having been an avid acolyte of Jobs, I would imagine that he himself would be disturbed and unsettled by the label. Since when did the promise of a radiant future constitute a Reality Distortion Field? Since when did the ability of a person to embrace what seemingly is impossible and far-fetched and instill confidence in the troops to achieve it constitute a Reality Distortion Field? Since when did the ability of leadership to share in the wonders of unique and disruptive creations constitute a Reality Distortion Field? Since when did dreams of a better future underpinned with executable actions to achieve it constitute a Reality Distortion Field?
The Reality Distortion Field usage reflects the dissonance between what is and what needs to be. It is a slapstick term which suggests that you are envisioning tectonic dissonance rifts between reality and possibilities and that you are leading the awestruck starry-eyed followers off a potential cliff. Some people have renamed RDF as hype of Bulls*#t. They believe that RDF is extremely bad for organizations because it pushes the people outside the comfort zone of physical and logical constraints and is a recipe for disaster. The argument continues that organizations that are grounded upon the construct of reality and to communicate the same are essential to advance the organization. I beg to differ.
So let me address this on two fronts: RDF label and if we truly accept what RDF means … then my position is that it is the single most important attribute that a strong leader ought to embrace in the organization.
The RDF label:
We all know this to be true: A rose by any other name is still a rose. We just happen to call this rose in this context a RDF. It is presumed to be the ability of a person to cast possibilities in a different light … so much so that the impossibilities are reduced to elements just within the grasp of reality. Now I ask you – What is wrong with that? For a leader to be able to cast their vision within the inimitable grasp of an organization is a huge proxy for the faith of the leader of the people in the organization. If a project realistically would take 3 months but a RDF is cast to get a project done in 15 days – that is a tall order – but think of the consequences if people are “seduced” into the RDF and hence acts upon it. It immediately unfolds new pathways of collaboration, unforeseen discoveries into super-efficient and effective methods, it creates trench camaraderie, it distills focus into singularity points to be executed against, it instills and ignites a passion and an engagement around the new stakes in the ground, people become keepers of one another for a consequential and significant conquest, it brings out the creative energies and the limitless possibilities, once the goal is accomplished, of disruptive innovation in means and ends. Of course, one could also counter-argue a plethora of incidental issues in such cases: employees would burn out under the burden of unrealistic goals, employees are set more for failing than succeeding, it would create a disorderly orientation upon groups working together to meet RDF standards, and if one were to fall short …it would be a last straw that may break the camel’s back. So essentially this speaks to the ordinal magnitude of the RDF schema that is being pushed out by leadership.
RDF and the beneficial impact to an organization:
It is the sine qua non of great leadership to be able to push organizations beyond the boundaries of plain convenience. I have, in my career, been fortunate to have been challenged and on many occasions, forced out of my comfort zone. But in having done so successfully on many occasions, it has also given me the confidence to scale mountains. And that confidence is a perquisite that the organization leadership has to provide on a daily basis. After all, one of the biggest assets that an employee in an organization ought to have is pride and sense of accomplishment to their work. RDF unfolds that possibility.
We hear of disruptive innovations. These are defined as innovations that leapfrog the bounds of technology inertia. How does a company enable that? It is certainly not incremental thinking. It is a vision that marginally lies outside our aggregated horizon of sight. The age today which is a result of path breaking ideas and execution have been a result of those visionaries that have aimed beyond the horizons, instilled faith amongst the line men to align and execute, and made the impossible possible. We ought to thank our stars for having leaders that emit an RDF and lead us off our tenebrous existence in our diurnal professional lives.
There is absolutely no doubt that such leadership would create resistance and fierce antipathy among some. But despite some of the ill effects, the vector that drives great innovations lies in the capacity of the organization to embrace degrees of RDF to hasten and make the organizations competitive, distinctive and powerful.
Tags: boundaries, communication channel, creativity, discipline, extrinsic motivation, focus, innovation, intrinsic motivation, learning organization, meaning, organization architecture, strategy, vision
“Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had and synthesize new things. And the reason they were able to do that was that they’ve had more experiences or they have thought more about their experiences than other people.”
– Steve Jobs
What is the Medici Effect?
Frans Johanssen has written a lovely book on the Medici Effect. The term “Medici” relates to the Medici family in Florence that made immense contributions in art, architecture and literature. They were pivotal in catalyzing the Renaissance, and some of the great artists and scientists that we revere today – Donatello, Michelangelo, Leonardo da Vinci, and Galileo were commissioned for their works by the family.
Renaissance was the resurgence of the old Athenian democracy. It merged distinctive areas of humanism, philosophy, sciences, arts and literature into a unified body of knowledge that would advance the cause of human civilization. What the Medici effect speaks to is the outcome that is the result of creating a system that would incorporate what on first glance, may seem distinctive and discrete disciplines, into holistic outcomes and a shared simmering of wisdom that permeated the emergence of new disciplines, thoughts and implementations.
Supporting the organization to harness the power of the Medici Effect
We are past the industrial era, the Progressive era and the Information era. There are no formative lines that truly distinguish one era from another, but our knowledge has progressed along gray lines that have pushed the limits of human knowledge. We are now wallowing in a crucible wherein distinct disciplines have crisscrossed and merged together. The key thesis in the Medici effect is that the intersections of these distinctive disciplines enable the birth of new breakthrough ideas and leapfrog innovation.
So how do we introduce the Medici Effect in organizations?
Some of the key ways to implement the model is really to provide the support infrastructure for
1. Connections: Our brains are naturally wired toward associations. We try to associate a concept with contextual elements around that concept to give the concept more meaning. We learn by connecting concepts and associating them, for the most part, with elements that we are conversant in. However, one can create associations within a narrow parameter, constrained within certain semantic models that we have created. Organizations can hence channelize connections by implementing narrow parameters. On the other hand, connections can be far more free-form. That means that the connector thinks beyond the immediate boundaries of their domain or within certain domains that are “pre-ordained”. In those cases, we create what is commonly known as divergent thinking. In that approach, we cull elements from seemingly different areas but we thread them around some core to generate new approaches, new metaphors, and new models. Ensuring that employees are able to safely reach out to other nodes of possibilities is the primary implementation step to generate the Medici effect.
2. Collaborations: Connecting different streams of thought in different disciplines is a primary and formative step. To advance this further, organization need to be able to provide additional systems wherein people can collaborate among themselves. In fact, the collaboration impact accentuates the final outcome sooner. So enabling connections and collaboration work in sync to create what I would call – the network impact on a marketplace of ideas.
3. Learning Organization: Organizations need to continuously add fuel to the ecosystem. In other words, they need to bring in speakers, encourage and invest in training programs, allow exploration possibilities by developing an internal budget for that purpose and provide some time and degree of freedom for people to mull over ideas. This enables collaboration to be enriched within the context of diverse learning.
4. Encourage Cultural Diversity: Finally, organizations have to invest in cultural diversity. People from different cultures have varied viewpoints and information and view issues from different perspectives and cultures. Given the fact that we are more globalized now, the innate understanding and immersion in cultural experience enhances the Medici effect. It also creates innovation and ground-breaking thoughts within a broader scope of compassion, humanism, social and shared responsibilities.
Implementing systems to encourage the Medici effect will enable organizations to break out from legacy behavior and trammel into unguarded territories. The charter toward unknown but exciting possibilities open the gateway for amazing and awesome ideas that engage the employees and enable them to beat a path to the intersection of new ideas.
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
MECE is a thought tool that has been systematically used in McKinsey. It stands for Mutually Exclusive, Comprehensively Exhaustive. We will go into both these components in detail and then relate this to the dynamics of an organization mindset. The presumption in this note is that the organization mindset has been engraved over time or is being driven by the leadership. We are looking at MECE since it represents a tool used by the most blue chip consulting firm in the world. And while doing that, we will , by the end of the article, arrive at the conclusion that this framework alone will not be the panacea to all investigative methodology to assess a problem – rather, this framework has to reconcile with the active knowledge that most things do not fall in the MECE framework, and thus an additional system framework is needed to amplify our understanding for problem solving and leaving room for chance.
So to apply the MECE technique, first you define the problem that you are solving for. Once you are past the definition phase, well – you are now ready to apply the MECE framework.
MECE is a framework used to organize information which is:
- Mutually exclusive: Information should be grouped into categories so that each category is separate and distinct without any overlap; and
- Collectively exhaustive: All of the categories taken together should deal with all possible options without leaving any gaps.
In other words, once you have defined a problem – you figure out the broad categories that relate to the problem and then brainstorm through ALL of the options associated with the categories. So think of it as a mental construct that you move across a horizontal line with different well defined shades representing categories, and each of those partitions of shades have a vertical construct with all of the options that exhaustively explain those shades. Once you have gone through that exercise, which is no mean feat – you will be then looking at an artifact that addresses the problem. And after you have done that, you individually look at every set of options and its relationship to the distinctive category … and hopefully you are well on your path to coming up with relevant solutions.
Now some may argue that my understanding of MECE is very simplistic. In fact, it may very well be. But I can assure you that it captures the essence of very widely used framework in consulting organizations. And this framework has been imported to large organizations and have cascaded down to different scale organizations ever since.
Here is a link that would give you a deeper understanding of the MECE framework:
Now we are going to dig a little deeper. Allow me to digress and take you down a path less travelled. We will circle back to MECE and organizational leadership in a few moments. One of the memorable quotes that have left a lasting impression is by a great Nobel Prize winning physicist, Richard Feynman.
“I have a friend who’s an artist and has sometimes taken a view which I don’t agree with very well. He’ll hold up a flower and say “look how beautiful it is,” and I’ll agree. Then he says “I as an artist can see how beautiful this is but you as a scientist takes this all apart and it becomes a dull thing,” and I think that he’s kind of nutty. First of all, the beauty that he sees is available to other people and to me too, I believe. Although I may not be quite as refined aesthetically as he is … I can appreciate the beauty of a flower. At the same time, I see much more about the flower than he sees. I could imagine the cells in there, the complicated actions inside, which also have a beauty. I mean it’s not just beauty at this dimension, at one centimeter; there’s also beauty at smaller dimensions, the inner structure, also the processes. The fact that the colors in the flower evolved in order to attract insects to pollinate it is interesting; it means that insects can see the color. It adds a question: does this aesthetic sense also exist in the lower forms? Why is it aesthetic? All kinds of interesting questions which the science knowledge only adds to theexcitement, the mystery and the awe of a flower! It only adds. I don’t understand how it subtracts.”
The above quote by Feynman lays the groundwork to understand two different approaches – namely, the artist approaches the observation of the flower from the synthetic standpoint, whereas Feynman approaches it from an analytic standpoint. Both do not offer views that are antithetical to one another: in fact, you need both to gather a holistic view and arrive at a conclusion – the sum is greater than the parts. Feynman does not address the essence of beauty that the artist puts forth; he looks at the beauty of how the components and its mechanics interact well and how it adds to our understanding of the flower. This is very important because the following dialogue with explore another concept to drive this difference between analysis and synthesis home.
There are two possible ways of gaining knowledge. Either we can proceed from the construction of the flower ( the Feynman method) , and then seek to determine the laws of the mutual interaction of its parts as well as its response to external stimuli; or we can begin with what the flower accomplishes and then attempt to account for this. By the first route we infer effects from given causes, whereas by the second route we seek causes of given effects. We can call the first route synthetic, and the second analytic.
We can easily see how the cause effect relationship is translated into a relationship between the analytic and synthetic foundation.
A system’s internal processes — i.e. the interactions between its parts — are regarded as the cause of what the system, as a unit, performs. What the system performs is thus the effect. From these very relationships we can immediately recognize the requirements for the application of the analytic and synthetic methods.
The synthetic approach — i.e. to infer effects on the basis of given causes — is therefore appropriate when the laws and principles governing a system’s internal processes are known, but when we lack a detailed picture of how the system behaves as a whole.
Another example … we do not have a very good understanding of the long-term dynamics of galactic systems, nor even of our own solar system. This is because we cannot observe these objects for the thousands or even millions of years which would be needed in order to map their overall behavior.
However, we do know something about the principles, which govern these dynamics, i.e. gravitational interaction between the stars and planets respectively. We can therefore apply a synthetic procedure in order to simulate the gross dynamics of these objects. In practice, this is done with the use of computer models which calculate the interaction of system parts over long, simulated time periods.
The analytical approach — drawing conclusions about causes on the basis of effects – is appropriate when a system’s overall behavior is known, but when we do not have clear or certain knowledge about the system’s internal processes or the principles governing these. On the other hand, there are a great many systems for which we neither have a clear and certain conception of how they behave as a whole, nor fully understand the principles at work which cause that behavior. Organizational behavior is one such example since it introduces the fickle spirits of the employees that, at an aggregate create a distinct character in the organization.
Leibniz was among the first to define analysis and synthesis as modern methodological concepts:
“Synthesis … is the process in which we begin from principles and [proceed to] build up theorems and problems … while analysis is the process in which we begin with a given conclusion or proposed problem and seek the principles by which we may demonstrate the conclusion or solve the problem.”
So we have wandered down this path of analysis and synthesis and now we will circle back to MECE and the organization. MECE framework is a prime example of the application of analytics in an organization structure. The underlying hypothesis is that the application of the framework will illuminate and add clarity to understanding the problems that we are solving for. But here is the problem: the approach could lead to paralysis by analysis. If one were to apply this framework, one would lose itself in the weeds whereas it is just as important to view the forest. So organizations have to step back and assess at what point we stop the analysis i.e. we have gathered information and at what point we set our roads to discovering a set of principles that will govern the action to solve a set of problems. It is almost always impossible to gather all information to make the best decision – especially where speed, iteration, distinguishing from the herd quickly, stamping a clear brand etc. are becoming the hallmarks of great organizations.
Applying the synthetic principle in addition to “MECE think” leaves room for error and sub-optimal solutions. But it crowd sources the limitless power of imagination and pattern thinking that will allow the organization to make critical breakthroughs in innovative thinking. It is thus important that both the principles are promulgated by the leadership as coexisting principles that drive an organization forward. It ignites employee engagement, and it imputes the stochastic errors that result when employees may not have all the MECE conditions checked off.
In conclusion, it is important that the organization and its leadership set its architecture upon the traditional pillars of analysis and synthesis – MECE and systems thinking. And this architecture serves to be the springboard for the employees that allows for accidental discoveries, flights of imagination, Nietzschean leaps that transform the organization toward the pathway of innovation, while still grounded upon the bedrock of facts and empirical observations.
Posted in Business Process, Employee Engagement, Innovation, Leadership, Learning Organization, Learning Process, Management Models, Model Thinking, Motivation, Organization Architecture, Recognition, Risk Management, Social Dynamics, Social Systems
Tags: Analysis, creativity, employee engagement, employee recognition, innovation, learning organization, mass psychology, Mental Construct, Mental Models, organization architecture, social network, social systems, Synthesis, Systems Thinking, talent management, uncertainty