Category Archives: Social Network
Network Theory and Network Effects
Complexity theory needs to be coupled with network theory to get a more comprehensive grasp of the underlying paradigms that govern the outcomes and morphology of emergent systems. In order for us to understand the concept of network effects which is commonly used to understand platform economics or ecosystem value due to positive network externalities, we would like to take a few steps back and appreciate the fundamental theory of networks. This understanding will not only help us to understand complexity and its emergent properties at a low level but also inform us of the impact of this knowledge on how network effects can be shaped to impact outcomes in an intentional manner.
There are first-order conditions that must be met to gauge whether the subject of the observation is a network. Firstly, networks are all about connectivity within and between systems. Understanding the components that bind the system would be helpful. However, do keep in mind that complexity systems (CPS and CAS) might have emergent properties due to the association and connectivity of the network that might not be fully explained by network theory. All the same, understanding networking theory is a building block to understanding emergent systems and the outcome of its structure on addressing niche and macro challenges in society.
Networks operates spatially in a different space and that has been intentionally done to allow some simplification and subsequent generalization of principles. The geometry of network is called network topology. It is a 2D perspective of connectivity.
Networks are subject to constraints (physical resources, governance constraint, temporal constraints, channel capacity, absorption and diffusion of information, distribution constraint) that might be internal (originated by the system) or external (originated in the environment that the network operates in).
Finally, there is an inherent non-linearity impact in networks. As nodes increase linearly, connections will increase exponentially but might be subject to constraints. The constraints might define how the network structure might morph and how information and signals might be processed differently.
Graph theory is the most widely used tool to study networks. It consists of four parts: vertices which represent an element in the network, edges refer to relationship between nodes which we call links, directionality which refers to how the information is passed ( is it random and bi-directional or follows specific rules and unidirectional), channels that refer to bandwidth that carry information, and finally the boundary which establishes specificity around network operations. A graph can be weighted – namely, a number can be assigned to each length to reflect the degree of interaction or the strength of resources or the proximity of the nodes or the ordering of discernible clusters.
The central concept of network theory thus revolves around connectivity between nodes and how non-linear emergence occurs. A node can have multiple connections with other node/nodes and we can weight the node accordingly. In addition, the purpose of networks is to pass information in the most efficient manner possible which relays into the concept of a geodesic which is either the shortest path between two nodes that must work together to achieve a purpose or the least number of leaps through links that information must negotiate between the nodes in the network.
Technically, you look for the longest path in the network and that constitutes the diameter while you calculate the average path length by examining the shortest path between nodes, adding all of those paths up and then dividing by the number of pairs. Significance of understanding the geodesic allows an understanding of the size of the network and throughput power that the network is capable of.
Nodes are the atomic elements in the network. It is presumed that its degree of significance is related to greater number of connections. There are other factors that are important considerations: how adjacent or close are the nodes to one another, does some nodes have authority or remarkable influence on others, are nodes positioned to be a connector between other nodes, and how capable are the nodes in absorbing, processing and diffusing the information across the links or channels. How difficult is it for the agents or nodes in the network to make connections? It is presumed that if the density of the network is increased, then we create a propensity in the overall network system to increase the potential for increased connectivity.
As discussed previously, our understanding of the network is deeper once we understand the elements well. The structure or network topology is represented by the graph and then we must understand size of network and the patterns that are manifested in the visual depiction of the network. Patterns, for our purposes, might refer to clusters of nodes that are tribal or share geographical proximity that self-organize and thus influence the structure of the network. We will introduce a new term homophily where agents connect with those like themselves. This attribute presumably allows less resources needed to process information and diffuse outcomes within the cluster. Most networks have a cluster bias: in other words, there are areas where there is increased activity or increased homogeneity in attributes or some form of metric that enshrines a group of agents under one specific set of values or activities. Understanding the distribution of cluster and the cluster bias makes it easier to influence how to propagate or even dismantle the network. This leads to an interesting question: Can a network that emerges spontaneously from the informal connectedness between agents be subjected to some high dominance coefficient – namely, could there be nodes or links that might exercise significant weight on the network?
The network has to align to its environment. The environment can place constraints on the network. In some instances, the agents have to figure out how to overcome or optimize their purpose in the context of the presence of the environmental constraints. There is literature that suggests the existence of random networks which might be an initial state, but it is widely agreed that these random networks self-organize around their purpose and their interaction with its environment. Network theory assigns a number to the degree of distribution which means that all or most nodes have an equivalent degree of connectivity and there is no skewed influence being weighed on the network by a node or a cluster. Low numbers assigned to the degree of distribution suggest a network that is very democratic versus high number that suggests centralization. To get a more practical sense, a mid-range number assigned to a network constitutes a decentralized network which has close affinities and not fully random. We have heard of the six degrees of separation and that linkage or affinity is most closely tied to a mid-number assignment to the network.
We are now getting into discussions on scale and binding this with network theory. Metcalfe’s law states that the value of a network grows as a square of the number of the nodes in the network. More people join the network, the more valuable the network. Essentially, there is a feedback loop that is created, and this feedback loop can kindle a network to grow exponentially. There are two other topics – Contagion and Resilience. Contagion refers to the ability of the agents to diffuse information. This information can grow the network or dismantle it. Resilience refers to how the network is organized to preserve its structure. As you can imagine, they have huge implications that we see. How do certain ideas proliferate over others, how does it cluster and create sub-networks which might grow to become large independent networks and how it creates natural defense mechanisms against self-immolation and destruction?
Network effect is commonly known as externalities in economics. It is an effect that is external to the transaction but influences the transaction. It is the incremental benefit gained by an existing user for each new user that joins the network. There are two types of network effects: Direct network effects and Indirect network effect. Direct network effects are same side effects. The value of a service goes up as the number of users goes up. For example, if more people have phones, it is useful for you to have a phone. The entire value proposition is one-sided. Indirect networks effects are multi-sided. It lends itself to our current thinking around platforms and why smart platforms can exponentially increase the network. The value of the service increases for one user group when a new user group joins the network. Take for example the relationship between credit card banks, merchants and consumers. There are three user groups, and each gather different value from the network of agents that have different roles. If more consumers use credit cards to buy, more merchants will sign up for the credit cards, and as more merchants sign up – more consumers will sign up with the bank to get more credit cards. This would be an example of a multi-sided platform that inherently has multi-sided network effects. The platform inherently gains significant power such that it becomes more valuable for participants in the system to join the network despite the incremental costs associated with joining the network. Platforms that are built upon effective multi-sided network effects grow quickly and are generally sustainable. Having said that, it could be just as easy that a few dominant bad actors in the network can dismantle and unravel the network completely. We often hear of the tipping point: namely, that once the platform reaches a critical mass of users, it would be difficult to dismantle it. That would certainly be true if the agents and services are, in the aggregate, distributed fairly across the network: but it is also possible that new networks creating even more multi-sided network effects could displace an entrenched network. Hence, it is critical that platform owners manage the quality of content and users and continue to look for more opportunities to introduce more user groups to entrench and yet exponentially grow the network.
Posted in Analytics, Business Process, Complexity, exponential, growth, Innovation, Leadership, Learning Organization, Learning Process, Management Models, Model Thinking, network theory, Social Network, Social Systems, startup, Virality
Comments Off on Network Theory and Network Effects
Tags: business cases, design, environment, experiments, innovation, network, platform, startup, system thinking, uncertainty
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)
LinkedIn Endorsements: A Failure or a Brilliant Strategy?
LinkedIn endorsements have no value. So says many pundits! Here are some interesting articles that speaks of the uselessness of this product feature in LinkedIn.
I have some opinions on this matter. I started a company last year that allows people within and outside of the company to recommend professionals based on projects. We have been ushered into a world where our jobs, for the most part, constitute a series of projects that are undertaken over the course of a person’s career. The recognition system around this granular element is lacking; we have recommendations and recognition systems that have been popularized by LinkedIn, Kudos, Rypple, etc. But we have not seen much development in tools that address recognition around projects in the public domain. I foresee the possibility of LinkedIn getting into this space soon. Why? It is simple. The answer is in their “useless” Endorsement feature that has been on since late last year. As of March 13, one billion endorsements have been given to 56 million LinkedIn members, an average of about 4 per person. What does this mean? It means that LinkedIn has just validated a potential feature which will add more flavor to the endorsements – Why have you granted these endorsements in the first place?
Thus, it stands to reason the natural step is to reach out to these endorsers by providing them appropriate templates to add more flavor to the endorsements. Doing so will force a small community of the 56 million participants to add some flavor. Even if that constitutes 10%, that is almost 5.6M members who are contributing to this feature. Now how many products do you know that release one feature and very quickly gather close to six million active participants to use it? In addition, this would only gain force since more and more people would use this feature and all of a sudden … the endorsements become a beachhead into a very strategic product.
The other area that LinkedIn will probably step into is to catch the users young. Today it happens to be professionals; I will not be surprised if they start moving into the university/college space and what is a more effective way to bridge than to position a product that recognizes individuals against projects the individuals have collaborated on.
LinkedIn and Facebook are two of the great companies of our time and they are peopled with incredibly smart people. So what may seemingly appear as a great failure in fact will become the enabler of a successful product that will significantly increase the revenue streams of LinkedIn in the long run!
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!
Posted in Corporate Social Responsibility, Employee Engagement, Innovation, Learning Organization, Learning Process, Narratives, Social Causes, Social Dynamics, Social Network, Social Systems
Tags: connection, conversation, crowdsource, democracy, diversity, experiments, social network, social systems
Why Jugglestars? How will this benefit you?
Consider this. Your professional career is a series of projects. Employers look for accountability and performance, and they measure you by how you fare on your projects. Everything else, for the most part, is white noise. The projects you work on establish your skill set and before long – your career trajectory. However, all the great stuff that you have done at work is for the most part hidden from other people in your company or your professional colleagues. You may get a recommendation on LinkedIn, which is fairly high-level, or you may receive endorsements for your skills, which is awesome. But the Endorsements on LinkedIn seem a little random, don’t they? Wouldn’t it be just awesome to recognize, or be recognized by, your colleagues for projects that you have worked on. We are sure that there are projects that you have worked on that involves third-party vendors, consultants, service providers, clients, etc. – well, now you have a forum to send and receive recognition, in a beautiful form factor, that you can choose to display across your networks.
Imagine an employee review. You must have spent some time thinking through all the great stuff that you have done that you want to attach to your review form. And you may have, in your haste, forgotten some of the great stuff that you have done and been recognized for informally. So how cool would it be to print or email all the projects that you’ve worked on and the recognition you’ve received to your manager? How cool would it be to send all the people that you have recognized for their phenomenal work? For in the act of participating in the recognition ecosystem that our application provides you – you are an engaged and prized employee that any company would want to retain, nurture and develop.
Now imagine you are looking for a job. You have a resume. That is nice. And then the potential employer or recruiter is redirected to your professional networks and they have a glimpse of your recommendations and skill sets. That is nice too! But seriously…wouldn’t it be better for the hiring manager or recruiter to have a deeper insight into some of the projects that you have done and the recognition that you have received? Wouldn’t it be nice for them to see how active you are in recognizing great work of your other colleagues and project co-workers? Now they would have a more comprehensive idea of who you are and what makes you tick.
We help you build your professional brand and convey your accomplishments. That translates into greater internal development opportunities in your company, promotion, increase in pay, and it also makes you more marketable. We help you connect to high-achievers and forever manage your digital portfolio of achievements that can, at your request, exist in an open environment. JuggleStars.com is a great career management tool.
Check out www.jugglestars.com
Posted in Employee Engagement, Employee retention, Extrinsic Rewards, Innovation, Intrinsic Rewards, Leadership, Learning Organization, Learning Process, Motivation, Organization Architecture, Recognition, Rewards, Social Dynamics, Social Network, Social Systems, Talent Management
Tags: communication channel, conversation, crowdsource, employee engagement, employee recognition, extrinsic motivation, intrinsic motivation, learning organization, mass psychology, social network, social systems, talent management
JuggleStars launched! Great Application for Employee Recognition.
About JuggleStars www.jugglestars.com
Please support Jugglestars. This is an Alpha Release. Use the application in your organization. The Jugglestars team will be adding in more features over the next few months. Give them your feedback. They are an awesome team with great ideas. Please click on www.jugglestars.com and you can open an account, go to Account Settings and setup your profile and then you are pretty much ready to go to recognize your team and your colleagues at a project level.
Posted in Corporate Social Responsibility, Employee Engagement, Extrinsic Rewards, Gamification, Innovation, Intrinsic Rewards, Leadership, Learning Organization, Recognition, Rewards, Social Causes, Social Network, Social Systems, Talent Management
Tags: communication channel, connection, conversation, employee engagement, employee recognition, extrinsic motivation, intrinsic motivation, learning organization, organization architecture, social network, social systems, talent management, value management
Medici Effect – Encourage Innovation in the Organization
“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.
Posted in Chaos, Employee Engagement, Innovation, Leadership, Learning Organization, Model Thinking, Motivation, Order, Organization Architecture, Social Dynamics, Social Network, Social Systems
Tags: boundaries, chaos, communication channel, creativity, crowdsource, discipline, diversity, employee engagement, experiments, intersection, learning organization, medici effect, social systems
Viral Coefficient – Quick Study and Social Network Implications
Virality is a metric that has been borrowed from the field of epidemiology. It pertains to how quickly an element or content spreads through the population. Thus, these elements could be voluntarily or involuntarily adopted. Applying it to the world of digital content, I will restrict my scope to that of voluntary adoption by participants who have come into contact with the elements.
The two driving factors around virality relate to Viral Coefficient and Viral Cycle Time. They are mutually exclusive concepts, but once put together in a tight system within the context of product design for dissemination, it becomes a very powerful customer acquisition tool. However, this certainly does not mean that increased virality will lead to increased profits. We will touch upon this subject later on for in doing so we have to assess what profit means – in other words, the various components in the profit equation and whether virality has any consequence to the result. Introducing profit motive in a viral environment could, on the other hand, lead to counterfactual consequences and may depress the virality coefficient and entropy the network.
What is the Viral Coefficient?
You will often hear the Viral Coefficient referred to as K. For example, you start an application that you put out on the web as a private beta. You offer them the tool to invite their contacts to register for the application. For example, if you start off with 10 private beta testers, and each of them invites 10 friends and let us say 20% of the 10 friends actually convert to be a registered user. What does this mean mathematically as we step through the first cycle? Incrementally, that would mean 10*10*20% = 20 new users that will be generated by your initial ten users. So at the end of the first cycle, you would have 30 users. But bear in mind that this is the first cycle only. Now the 30 users have the Invite tool to send to 10 additional users of which 10% convert. What does that translate to? It would be 30*10*10% =30 additional people over the base of 30 of your current installed based. That means now you have a total of 60 users. So you have essentially sent out 100 invites and then another 300 invites for a total of 400 invites — you have converted 50 users out of the 400 invites which translates to a 12.5% conversion rate through the second cycle. In general, you will find that as you step through more cycles, your conversion percentage will actually decay. In the first cycle, the viral coefficient (K) = 2 (Number of Invites (10) * conversion percentage (20%)), and through the incremental second cycle (K) = 10% (Number of Invites (10) * conversion percentage (10%)), and the total viral coefficient (K) is 1. If the K < 1, the system lends itself to decay … the pace of decay being a function of how low the viral coefficient is. On the other hand if you have K>1 or 100%, then your system will grow fairly quickly. The actual growth will be based on you starting base. A large starting base with K>1 is a fairly compelling model for growth.
The Viral Cycle Time:
This is the response time of a recipient to act upon an invite and send it out to their connection. In other words, using the above example, when your 10 users send out 10 invites and they are immediately acted upon ( for modeling simplicity, immediate means getting the invite and turning it around and send additional invites immediately and so on and on), that constitutes the velocity of the viral cycle otherwise known as Viral Cycle time. The growth and adoption of your product is a function of the viral cycle time. In other words, the longer the viral cycle time, the growth is significantly lower than a shorter viral cycle time. For example if you reduce viral cycle time by ½, you may experience 100X+ growth. Thus, it is another important lever to manage the growth and adoption of the application.
So when one speaks of Virality, we have to consider the Virality Coefficient and the Viral Cycle Time. These are the key components and the drivers to these components may have dependencies, but there could be some mutually exclusive underlying value drivers. Virality hence must be built into the product. It is often common to think that marketing creates virality. I believe that marketing certainly does influence virality but it is more important, if and when possible, to design the product with the viral hooks.
Posted in Chaos, Financial Metrics, Innovation, Product Design, Social Dynamics, Social Network, Social Systems, Virality
Tags: beta users, invites, K, product adoption, product design, referrals, social network, social systems, viral cycle, viral hooks, viral loop, viral tools, virality
Standing Ovation Problem and Product Design
When you seed another social network into an ecosystem, you are, for the lack of a better word, embracing the tenets of a standing ovation model. The standing ovation model has become, as of late, the fundamental rubric upon which several key principles associated with content, virality, emulation, cognitive psychology, location principles, social status and behavioral impulse coalesce together in various mixes to produce what would be the diffusion of the social network principles as it ripples through the population it contacts. Please keep in mind that this model provides the highest level perspective that fields the trajectory of the social network dynamics. There are however a number of other models that are more tactical and borrowed from the fields of epidemiology and growth economics that will address important elements like the tipping points that generally play a large role in essentially creating that critical mass of crowdswell, which once attained is difficult to reverse, unless of course there are legislative and technology reversals that may defeat the dynamics.
So I will focus, in this post, the importance of standing ovation model. The basic SOP (Standing Ovation problem) can be simply stated as: A lecture or content display in an audience ends and the audience starts to applaud. The applause builds and tentatively, a few audience may members may or may not decide to stand. This could be abstracted in our world as an audience that is a passive user versus an active user in the ecosystem. The question that emerges is whether a standing ovation ensues or does the enthusiasm fizzle. SOP problems were first studied by Schelling.
In the simplest form of the model, when a performance or content consumption ends, an audience member must decide whether or not to stand. Now if the decision to stand is made without any consideration of the dynamics of the other people in the audience, then there is no problem per se and the SOP model does not come into play. However, if the random person is on the fence or is reluctant or may not have enjoyed the content … would the behavioral and location dynamics of the other participants in the audience influence him enough to stand even against his better judgment. The latter case is an example of information cascade or what is often called the “following the herd” mentality which essentially means that the individuals abnegates his position in favor of the collective judgment of the people around him. So this model and its application to social networks is best explained by looking at the following elements:
1. Group Response: If you are part of a group and you have your set of judgments governing your decision to stand up, then are you willing to reserve those judgments to be part of group behavior. At what point is a person willing to seed doubt and play along with a larger response. This has important implications. For example, if you are in an audience and a member of a group that you know well, and a certain threshold quantity in the group responds favorably to the content, there may be some likelihood that you would follow along. On the other hand, if you are an individual in an audience, albeit not connected to a group, there is still some chance of you to follow along as long as it meets some threshold for example – if I can see about people stand, I will follow along. In a known group which may constitute you being a participant among five people, even if 3 people stand, you may stand up even though it does not meet your random 10 people formula. This has important implications in cohorts, building groups, providing tools and computational agents in social networks and dynamics to incline a passive consumer to an active consumer.
2. Visibility to the Group: Location is an important piece of the SOP. Imagine a theater. If you are the first one in the center of all rows, you will, unless you turn back, not be cognizant of people’s reactions. Thus, your response to the content will be preliminarily fed by the intensity of your reaction to the content. On the other hand, if you are seated behind, you will have a broader perspective and you may respond to the dynamics of how the others respond to the content. What does this mean in social dynamics and introducing more active participation? Simply that you have to again provide the underlying mechanisms that allow people to respond at a temporal level ( a short time frame) to how a threshold mass of people have responded. Affording that one person visibility that would follow up with a desired response would create the information cascade that would culminate in a large standing ovation.
3. Beachhead Response: An audience will have bias. That is another presumption in the model. They will carry certain judgments prior to a show – one of which is that the people in front who have bought the expensive seats are influential and have “celebrity” status. Now depending on the weight of this bias, a random person, in spite a positive audience response, may not respond positively if the front rows do not respond positively. Thus, he is heavily inclined to discounting the general audience threshold toward a threshold associated with a select group that could result in different behavior. However, it is also possible that if the beachhead responds positively and not the audience, the random person may react positively despite the general threshold dynamics. So the point being that designing and developing products in a social environment have to be able to measure such biases, see responses and then introduce computational agents to create fuller participation.
Thus, the SOP is the fundamental crux around which a product design has to be considered. In that, to the extent possible, you bring in a person who belongs to a group, has the spatial visibility, and responds accordingly would thus make for an enduring response to content. Of course, the content is a critical component as well for poor content, regardless of all ovation agents introduced, may not trigger a desired response. So content is as much an important pillar as is the placing of the random person with their thresholds of reaction. So build the content, design the audience, and design the placement of the random person in order that all three coalesce to make an active participant result out of a passive audience.
Posted in Leadership, Learning Organization, Organization Architecture, Ovation, Social Dynamics, Social Gaming, Social Network, Social Systems, Virality
Tags: applause, audience, copy, emulate, group, leadership, motivation, product design, recognition, social dynamics, social network, social networks, social normns, virality
Walled Garden: Mirage or Oasis?
A walled garden in the context of the internet relays to full control of the user experience. In other words, it is a methodology that is deployed to ensure closed or exclusive content for consumption by a set of users.
One of the prime examples of the walled garden in the technology world is the Apple ecosystem. This constitutes the interplay or hardware and software intricately tied in a manner that precludes any legal way to contaminate the harmony of user experience. Well, at least that is what Apple has vociferously claimed over the ages. They have argued that adopting the walled garden has served to be a bedrock of innovation, and the millions of applications on the Appstore bears out that fact. But the open source folks argue otherwise.
Posted in Chaos, Innovation, Order, Social Network, Walled Garden
Tags: Android, ecosystem, innovation, iOS, open source, order, pay to play, walled garden