Network Effects | On Digital Strategy

The Building Blocks of Digital Transformation: Community, Tech, Business Models, and a Change Platform

June 18, 2016 Leave a comment

I’ve been making the argument lately that the single largest obstacle in successful digital transformation is change itself. Surprisingly, the arrival of new technology is generally not the large hurdle to becoming more digital in a meaningful way, though it certainly represents a large and growing learning curve. Yet learning the new technology is manageable by most organizations in my experience, if they have the will to do so.

Finding the right business models can be a bit more of a challenge, but the process of discovering the best ones is increasingly well understood these days. One somewhat ironic lesson is that we’ve also learned that we usually have to build an audience first, often well before we decide on new digital business models, that are centered around some activity or capability of significant shared interest with the market, before we can experiment and find the right path forward in terms of generating value, such as revenue from sales, subscriptions, advertising, etc.

Online Communities Are the Business Construct That Create the Most Value

From my Enterprise Digital Summit 2016 Paris Keynote Deck

Why Digital Needs a New Mindset

It actually turns out the most important and challenging building blocks for digital transformation is people and the processes that can change them. Thinking in digital terms requires a significant shift in mindset, such as designing for loss of control, understanding the power laws of mass connectedness, the startling revelation that the network will do most of the work, and understanding how open participation is the key to unleashing digital value in scale to our businesses.

However, shifting the mindset en masse of the large number people that exist in the average enterprise (i.e. tens or even hundreds of thousands of workers) is not something that can be done to them, but can only be done with them as Euan Semple frequently likes to point out. So, what’s the single best venue in which to engage significantly in a time efficient and sustainable fashion? I now suggest that the most likely and cost-effective vehicle for this that we know today is online community.

The building blocks of digital transformation is a topic that I recently had time to study in depth as I prepared my closing keynote for the always terrific Enterprise Digital Summit 2016 (formerly the Enterprise 2.0 SUMMIT) in Paris this month.

Step 1: Gather Stakeholders into Communities of Digital Change

The fundamental building block of digital transformation is therefore not technology, but people, a much more challenging proposition. However, if we can somehow connect the collective workforce in the organization together in an effective fashsion to begin a shared and dialogue-based process of learning, understanding, experimenting with, and then carrying out the tasks of digital transformation across the enterprise as a much more aligned and self-supporting way, then we are much more likely to succeed. As I’ve discussed, we’ve even started to witness evidence that IT is shifting in this direction steadily, with the rise of empowered change agents and even unexpected source of pre-existing tech change using forces like shadow IT as a key resource for creating decentralized technology adaptation across the organization.

But it all starts with community, for which I believe the evidence is now clear is the most powerful way of organizing human activity and creating shared value yet developed.

Step 2: Assemble a Modern, Market-Facing Technology Stack

From there, we do need to look at the technology lens at what our business does and how it does it. We can no longer realize all tech change ourselves, as our competitors have already learned that the single greatest force for value creation is capturing and wielding community contributions of customers by the millions via mass co-creation, and business partners by the thousands (see APIs + hackathons). I recently summarized the many other emerging enterprise technologies we must consider all the time as well, but the most important ones are customer facing and involved in co-creation.

We therefore must instead now becoming highly competent in building strong and effective architectures of participation, as most digital leaders harness the vast capacity of the Internet to do most of the value creation:

Step 3: Create and Nurture Digital Experiments

From there we can combine people-led digital change at scale with a portfolio of digital engagement and experience technologies and processes — that must prominently include market-facing community — to begin creating, launching, and growing healthy and vibrant new products and services. Growing hacking in fact, has become an important new technique used by top Internet companies to ensure early lift and adoption, and has been a key subject of interest by top technology leaders like Microsoft CEO Satya Nadella. So grow the results of digital transformation this way, then generate revenue:

Step 4: Get Serious About Revenue Models

Finally, the last building block is digital business models, which one the service has a successful audience or community, can be experimented with and validated, though certainly some services, such as sharing economy ones, can monetize from the outset, though often at break even levels. Below is a representative list of some of the most common Internet business models, though by no means all the possibilities. For example, there are at least 18 separate known business models for open APIs alone. The high level Internet business models break down like so:

For a more complete exploration, please view the video of my closing keynote on this subject in Paris on June 2nd, 2016:

Or download a copy of the Slideshare deck that I presented with.

Additional Reading

How IT Can Change For the Digital Era and What Leaders Can Do About It

The digital transformation conversation shifts to how

Filed under Analysis, Digital Experience, Digital Transformation, Events, Network Effects, Online Community, Peer Production, Strategy, The Enterprise

The Long Game is Winning in Digital Ecosystems, and Other Global Tech Trends

March 16, 2016 2 Comments

I’ve traveled nearly 70,000 miles all over the world since the beginning of the year, talking with digital practitioners in the trenches. Most often these are passionate but often frustrated change agents, IT managers grappling with tech evolution, and corporate leaders on both the technology and business side looking towards their futures and feeling uncertain.

Where to best focus digital enablement efforts in their organization, while coming from behind, with scarce time and resources is question that is top of mind right now. Worse, leaders at the very top often don’t seem motivated to make the necessary moves.

From these conversations and many observations at conferences and events so far in 2016, it’s obvious to me at this point that we appear to be entering a new inflection point with digital: Those who began early, made the right decisions, and stuck to their Internet identity in terms of rethinking the future — as opposed to chasing traditional firms back into their own industries — are seeing outsized rewards in an increasingly winner-takes-all online marketplace. The rest of us are watching them pull away.

In short, the early entrants to the global digital business competition that were either a) lucky enough to discover the digital rules of success from the outset, or b) followed a positive market feedback loop to the same place are quite clearly sucking the air out of the room. Perhaps most importantly, they also had the ability to execute without the many constraints of our legacy organizations.

Of course, I’m talking about Amazon, Google, Facebook, and Apple — sometimes referred to as the Four Horsemen of the Digital Apocalypse, for good reason — on the consumer side as well as Salesforce, and now surprisingly Microsoft, on the enterprise side, the latter two which are making major new inroads to enterprises I speak to. Microsoft in particular seems to be suddenly winning a lot of enterprise-wide “Microsoft company” deals as their digital/cloud vision matures. As a whole, these technology companies are increasingly seizing broad swaths of digital territory as they move at near light speed compared to their non-digital native brethren, breaking into new category after category with with relatively high levels of repeatable success. Certainly, their track record is head and shoulders better and much more rapid than most Internet startups, or most traditional enterprises that is.

Using the Inherent Power of Networks and Sustained Tech Investment

Why this is has been the subject of endless analysis, scrutiny, and speculation about this very small cohort of tech companies eating the world, but I propose that the core reasons are actually fairly basic. To restate the above: There are certain fundamental rules to digital ecosystems and the businesses built on top of them. While it helped enormously to be early, organizations that understand these rules and can also execute and invest for a sustained period of time can still dominate if they understand a few crucial pivot points.

Networks effects, one of the most basic measures of a successful digital ecosystem, quickly become exponential yet look relatively minor at the beginning, fostering complacency in competitors at the worst time, when a new digital market seems small and uninteresting. It’s not until critical mass has been reached a little later on, that a digital platform grows very swiftly into a market dominating and self-sustaining force. Then it’s relatively easy to crush lessor players that aren’t utterly focused on k-factor and other measures of these effects.

Simultaneously, and harder to prevent, is the tendency of make basic subsequent design changes to online products that then impede the carefully built channels that have created the initial growth and scale. I’d argue that many digital contenders frequently make this last mistake, making simple but disastrous changes — often when turning over the product from the 1.0 team to the maintenance team — by not staying true to the inherent power laws of digital systems that got them there (patterns such as “enabling networks effects by default” or “anyone can participate.”)

Needless to say, the aforementioned tech leaders managed to navigate past all these obstacles, including shooting themselves in the foot later on as they had to bring on fresh talent to grow the company. The critical design parameters that enabled growth stayed in place, and long enough to provide returns. This also highlights the big difference between most of these organizations and traditional companies: They had venture backing that isolated them from the quarterly financial cycle of immediate and continuous returns. Some would argue that Amazon has been doing this anyway, despite being a public company, and reaping enormous rewards in the long game of digital, where increasingly it’s apparent the winners reside. As BCG has noted, “even sharp minds can fail to grasp the power of sustained exponential forces.”

The primary lesson here: Deeply understand the rules of digital ecosystems and build one that solves a real pain point for a lot of people. Optimize the results relentlessly and pour the returns back into growth. Don’t stumble along the way.
This is a playbook that is simple enough to understand, but that most industrial era organizations fully embrace in a meaningful way, despite all the marketing talk — and I’m guilty as many of us in this regard — about digital transformation.

What does this have to do with the conversations I’ve been having? To person, almost everyone thinks their organization is moving too slowly, tentatively, and uncertainly towards becoming effective digital organizations that can compete, what I’ve called a next-generation enterprise. As SAP’s excellent Sameer Patel — and fellow Enterprise Irregular — once famously said, businesses have digitized quite a bit, but they haven’t really transformed.

Getting Past the Digital Innovator’s Dilemma

The real obstacle is one which I’ve been exploring in various forms over the last several years: Most organizations have accumulated and/or designed in enormous amounts of legacy culture, process, mindset, and infrastructure that got them where they are, but now has to be undone to a large extent to be fully realized and effective digital organizations. The world of agile, lean startup, OKRs, open APIs, devops, relentless A/B testing, and growth hacking are all words or phrases sometimes heard in the halls of the average classical business, but they just don’t lie at the heart of them, and won’t any time soon.

Worse, we’ve greatly over-centralized technology enablement so that it’s become a profound chokepoint in many organizations. CIOs and CMOs feel this acutely when this is the case, and yet a few are now reaping the benefits of going in the opposite direction. There are indeed solutions, but they require more ideas that traditional organizations aren’t good at: Open innovation, Kickstarter-style ideation programs, app stores, customer co-creation, change agent programs, hackathons, employee incubators, BYOT, enterprise architecture that’s designed for loss of control, and more.

The second big observation from my travels this year is that the technology world is maturing in some interesting ways. These trends too tend to favor those that invested early or invested big, or both. One is the realization that digital success stories aren’t coming from very many places. The United States and Asia dominate the top of the list, arguably having an unfair advantage through better investment policies for startups and very large markets that make it easy to take advantage of power laws. Larger markets, even ones relatively undeveloped, seem better to attract both talent and the numbers required to build market presence that can’t be ignored.

So what are organizations to do? I’ve suggested some digital transformation blueprints for both boards of directors as well as for the C-Suite that can help develop and grow true digital native lines of business in a sustainable way. But I also think that there is now a very steep curve to climb to respond to the network effects that Internet startups have created in many new and existing industries.

Become a Network Orchestrator and Harness the Market

The reality is that there is really only two ways for companies behind the digital maturity curve — which is still almost all of them right now — to catch up: a) Invent new industries that are irresistible in terms of the value and utility they offer b) employ the latest lessons learned on how to play to the strengths of the digital marketplace and turn the knob all the way to the right, beating the existing players at their own game by more purely and deeply plumbing the inherent factors that make digital ecosystems such an uneven playing board. Most digital contenders fail to understand even the most basic concepts of digital, such as the network itself is the single biggest resource you can and must use to digitally fuel your ecosystem to transform. It will do almost all the work, as long as you have a vision, a value proposition, and a platform which truly embodies and orchestrates both. Network orchestrators, in fact, are at the top of the Internet food chain. Organizations must live there, or become fodder for those that are. As Forrester’s Dan Bieler noted recently:

Digital ecosystems empower the CIO [Dion: and other internal tech leaders, official and unofficial] to become a critical business enabler by providing a technology platform to redefine approaches toward innovation, knowledge management, supply chain optimization, product development, and sales and marketing. In particular, traditional firms put survival at risk due to slow innovation cycles. CIOs who define a clear strategy to exploit the possibilities that digital ecosystems offer for their organizations position themselves as powerful change agents.

I’d only add that it’s not just about defining a strategy, but leading and executing on it sustainably. I’ll be exploring more about my travels and lessons learned on the emerging edge of digital shortly. In the meantime, your insights on this challenge are very welcome in comments below.

Additional Reading

Going Beyond ‘Bolt-On’ Digital Transformation

Is it IT’s last chance to lead digital transformation?

Filed under Analysis, Network Effects, Strategy, The Enterprise, The Web

Why the Underlying Laws of Cloud, Social, and Digital Business Matter

May 25, 2015 1 Comment

I’ve spent much of my Memorial Day Holiday here in the United States pondering the Red Queen effect vs. network effects, seminal laws of technology and business both, that are often held as gospel by their adherents who believe they are the natural and intrinsic properties of their operating environments (digital ecosystems in this case.)

Both hypotheses apply to any connected, relatively closed environment of some kind, which very much includes everything from traditional marketplaces, online communities, app stores, cloud services, SaaS, enterprise social networks, social media, and cable/video networks to e-mail, telephones, and package delivery. I cite these, as many practitioners don’t even consider system concepts when trying to figure out why they aren’t succeeding as hoped, despite those very ideas defining the rules of the playing field they’re working upon.

Both Red Queen and network effects have years of rigorous research and thinking to back them up, and as far as they go, they make real sense of the modern world as explanations for why things are the way they are in various places. This includes how organisms compete, survive, and thrive in the natural world or how networked products and services grow and maintain dominance on the Internet, respectively. These combined environments will ultimately lead to what I’m currently calling the 4th Platform.

The issue here is looking at why there are so many so-called ‘winner-take-all’ players at the top of the technology industry, especially on the Internet. In the shadows, nowhere near as successful, there are usually hundreds — sometimes thousands — of also-rans, depending on the sector, who struggle mightily, but usually fail. Rarely are the winners dethroned, though it does occasionally happen (see: AOL, MySpace, Friendster, RIM/Blackberry, all top digital players in their day.)

What triggered this line of thinking was Gartner’s fascinating new report on the Magic Quadrant for Cloud Infrastructure, which makes the stunning claim that Amazon now has 10 times more cloud computing capacity in use than the entire total of all the other 14 providers combined. The company is deeply wired into over a million customers’ ecosystems, and thousands of online products. By any estimation it is uncatchable.

Sidebar: Interestingly, this hasn’t stopped technology leaders such as Staples CIO Tom Conophy from stating last week that they’re going after Amazon “in a big way.” This despite the fact that both organizations aren’t even playing on the same digital meta-level.

Or is Amazon uncatchable? Don’t we just need to go ‘up the stack.’ As it turns out, not if it just leads to commoditization.

If traditional enterprises — and yes, more likely, startups — can only understand the fundamental rules by which the Amazon, Apple, and Facebook et al became leaders, the reasoning goes, we should be able to use those very rules against them. We should then be collectively able to out-innovate, out-invest, out-maneuver our competition and get to the top of an increasingly shallow but very, very steeply inclined pile of winners.

Deep thinkers in this space like my industry colleague Simon Wardley note that network effects create enormous inertia for change that make it very hard for a new player to get started, even if they’re much, much better. Worse, this is true even if you realize this and try to organize and optimize for it. You are simply spitting in the wind. Market-leading network effects, in fact, nearly always easily trumps the seemingly-powerful Red Queen Effect.

None of this is a new discussion of course, and the power laws of digital networks, such as Reed’s Law, have been relatively well-understood for at least decade. But their effects are now inexorably felt in the traditional business world like never before.

Using Networked Relationships Built on Enduring Digital Values

Ultimately, as organizations increasingly perceive the imperative to put a digital layer over their entire organization, even completely re-imagine it for the new models of digital business, there are some key fundamentals that we have to remember to close the gaps:

Count on nearly everything in the ecosystem to eventually drop to effectively zero cost. Do not build your digital business along the commoditization axis. Only the underlying properties, like network effects, are exempted from this rule and this is a potent realization. We will eventually get the cost of nearly all technology to nothing, making replication and competition both easy and rampant. This isn’t where most businesses would like to be. However, network relationships like communities, total aggregate API integrations of partners, total daily users contributing value, these cannot never be copied whole cloth on an increasingly low cost scale. When people are involved, commoditization is not possible, and real, meaningful human relationships then become the strategic coin of the digital realm.
Use differentiated models for commodity elements of digital business, versus the methods you employ for the innovative (and most important) elements. Social business, bi-modal IT (actually, tri-modal), devops, and even agile, are still the mantra here. These methods have been discovered to operate on the scale, speed, and collaborative dimensions required of today’s rapid digital cadence. Even better, they connect people the best way — that we know of so far — with how modern technology profoundly alters and — mostly — improves the way we work.
If you are a large organization, you’ll have to operate in sometimes truly unexpected new ways to deliver well on digital. In particular, this means powerful new network models of organization structure — in IT and everywhere else — as well as new widespread digital workplace skills to be able to change at a sufficiently high and sustained rate.

In other words, most organizations must rapidly evolve their operating models to adapt to the rules of the digital networks. A few have, but most still have not. There’s still time in a few industries however, but not a tremendous amount. For most, however, it’s now later than they think.

Filed under Analysis, Enterprise Architecture, Network Effects, Social Business, Strategy, The Enterprise

Defining the Next Generation Enterprise for 2014

May 12, 2014 Leave a comment

Many of you know that over the last several years I’ve tried to make the case that most organizations are currently falling behind the advancing pace of technological change. That business is so centered around technology today is the reason why addressing this has become a top competitive issue. Becoming better adapted to tech change is even tied to the medium-term survival of many organization as I recently explored in my look at digital transformation.

But to say that technology alone is what is disrupting traditional businesses would be inaccurate. We ourselves have changed — have co-evolved — along with technology. Our mindsets have become expanded by the new possibilities of super-connectedness, new models of working, and pervasive data-based insight that today’s networked revolution has wrought.

That’s not to say there aren’t important pros and cons to these advances as well. Along this journey of global, open, and social digital networks, we’ve also encountered enormous challenges in grappling with issues such as individual privacy and equal access, as well as the inherently large inequalities that emerge from the gaps between the digital haves and have-nots. This is precisely because technology is a profound force multiplier of just about everything it touches. There are other potential worries as well.

As The Economist fretted over recently, most technology revolutions have created more employment, not less. We hope that this is true for the next generation, but we’ll see, given how current models show that producer power is generally moving outside of traditional organizations to external networks that have less well-defined employment models:

Everyone should be able to benefit from productivity gains—in that, Keynes was united with his successors. His worry about technological unemployment was mainly a worry about a “temporary phase of maladjustment” as society and the economy adjusted to ever greater levels of productivity. So it could well prove.

Yet to most of us, it’s quite clear that digital channels combined with engagement at scale within them amongst all our stakeholders is at the core of the future of business. But what does this actually mean? What does it look like to most organizations? How can we articulate the changes to structure, process, and management of our organizations in a deeply digital age? It’s my belief we need a comprehensive yet eminently understandable model of how all this reshapes our organizations.

I’ve come to realize we’re trying to hit a fast-moving target with poorly aging models for service delivery and IT governance when it comes to digital transformation. The reality is that it usually takes several years for a large organization to achieve large scale change. By this I mean three to five years, and often more, and that’s just for an individual enterprise-wide initiative.

In today’s operating environment of yearly — sometimes quarterly — waves of highly disruptive enterprise technologies and products, that’s just too long. We need a clearer and more updated sense of where we need to take our organizations, and it must also show us how to increase our technology metabolism as well. This model should include the broad strategic outlines as well as specific adaptations to the latest powerful new digital capabilities such as big data analytics, omnichannel customer engagement, the Internet of Things, social business, and so on. These subjects are all highly strategic to the future of our organizations at the moment, yet they are also interrelated and must fit together relatively well in this model somehow.

Motivation for an Infinitely Renewing Model of Tech & Business

Over the last few years, I’ve adopted a term known as the next generation enterprise or NGE for short. It’s the idea that we can maintain an up-to-date strategic model when it comes to digital transformation. The vision for the next generation enterprise is different from one year to the next and has specific technological phases as well as overall strategic themes at any given time. This vision has its own management theories as well, such as shifting from organizational hierarchy to networked community or reorganizing how we operate to the three new top-level modes, to name just two examples.

In other words, the idea of the next generation enterprise is a relatively complete view — including both business and technology — of the target that typical organizations should be aiming for in their objectives for digital adaptation and growth. For the moment, let’s put aside whether there even is a typical organization, since many of the most important technology innovations are usually agnostic to your particular industry or unique company attributes. In other words, most major technology advances will derail your boat if you ignore them long enough, no matter what business you’re in.

To give us a shared roadmap and a point of reference, I’d like to start putting a clearer definition behind what we think is meant by a next-generation enterprise. Early this year, I mapped out the most important strategic new enterprise technologies, but it was a purely technology view and included a good many tactical elements that aren’t that important when it comes the big picture.

Instead, I’d like to have a more enterprise-centric view that includes the most important advances in business that technology has directly enabled. Some would say that the advent of being digital connected to every human being on the planet at all times (at least in the developed world) is one of those advances, and I agree. This realization is that communities are moving increasingly to the center of our businesses. But it’s more than that. The enclosing strategic conception is really one of ecosystem, whether that’s inside a segment of the enterprise with a single networked team, an external customer community, or a full-on developer network of thousands of application development partners who have welded your digital supply chain to their apps. All of these are ecosystems that must be created (or identified), grown, cultivated, managed, secured, and governed.

In fact, one of the largest issues we have in digital transformation today is that we look at business in a far too simplistic traditional model. In this legacy view, there are functional silos with workers combined with management hierarchies that together actually make decisions and operate our organizations. Then there are suppliers, business partners, and customers, and that’s about it for the big moving parts.

Today’s next generation enterprise plays on a much larger and more complex chessboard. There are thousands of relevant ecosystems that now exist for most businesses, most informal, and across thousands more channels, all with a long tail structure.

This means that while the head of the distribution consists of big channels you’ve heard of — from major social networks and call centers to traditional media and Amazon’s cloud — there are thousands you haven’t heard of and will never be able to deliberately consider and plan for. Business architecture has thus moved from simple planned models to complex and highly dynamic emergent networks across every business function we have. We’ve gone from a few dozen groups of stakeholders to ultimately tens of thousands that we must still manage to somehow. Ultimately, our org structures must adapt to reflect this.

I’ve previously proposed a set of enterprise strategies which have a good chance at addressing many of this issues, which were originally brought forth by the channel fragmentation, scale, and decentralization that we saw greatly exacerbated by IT consumerization a couple of years ago. But I now see that bring-your-own-device was just the forefront of a wave of grassroots led network-enabled change, including bring-your-own-application, bring-your-own-community, and soon, even bring-your-own-workforce.

The Element of The Next Generation Enterprise for 2014

So I’d like to put a stake in the ground and define what I think the next generation enterprise for 2014 should look like. There are several views here, but I’ll start with the more business-centric view of ecosystem and expand to other views as I’m able. In this ecosystem view we have the following components:

A more network-centric enterprise. Less hierarchical and consisting much more of online communities for achieving cost-effective outcomes at scale. This will happen within and amongst the workforce (network/social collaboration), business partners, customers, and the marketplace. Management and leadership through networks will become an essential skills and will require knowledge of the concepts and operation of digital and social businesses.
Workforce communities. While we’ve had a primitive model of team in the legacy workplace, it becomes much more fluid, dynamic, and high scale in the networked world, often directly supported by powerful new collaboration capabilities. Teams-based, project-centric, and — still evolving — process-based work conducted by communities will increasingly become the norm. Why? Because the data has consistently supported that the network/community model provides better business results.
Business partner communities. One of the least developed models of networked communities, there are however good examples that can be pointed to. Strategic partners, affiliates, and suppliers can be engaged together in operations, in particular — as John Hagel famously pointed out — with exception handling scenarios.
Customer communities. This is one of the strongest and most easily started models for strategic community. The evidence for business value is strong enough that I’ve wondered if the window is already closing on customer communities in certain industries. Certainly in my research I’ve found that customer care communities can reduce costs by 30% in the first year alone over traditional approaches. Social support also at the very top of Ray Wang’s social business use cases.
Marketplace. The single most scalable asset that businesses have is networked access to their customers and the broader marketplace. While this constituency also includes regulators and influencers, two groups that can be hard to manage, it also includes online advocates, crowdsourcing participants, software developers, and other interested parties. If you’re surprised to see developers in this list, then don’t be: Developers have become one of the single most important new constituencies as their innovations can drive primary growth and network effects. This is a very different view of business than before, where companies directly engaged their stakeholders.
New channels. The next generation enterprise will still have some legacy aspects including physical offices/stores — just smaller and more virtual — it will be the Web and especially on mobile devices that value is primarily created and captured, both. Social business environments (communities of all functional types and audiences) and the application as the new CRM will be key channels here as well. Ultimately, however, APIs — which I define as open digital supply chains — will be the most strategic channel for many industries because it scales faster and creates far more robust outcomes for very little investment.

Using this model, we can also baseline the various states of maturity of each part of the modern enterprise ecosystem for comparison, as in how far along are we? The essential point here with this view of the next-generation enterprise is that it’s the current target model, not what you should look like today. It’s what you should be aiming for, although you should certainly have some elements of it in place today (see figure 2.)

What do you see as other essential views of the next generation enterprise? What else needs to be added?

Filed under Analysis, Crowdsourcing, Enterprise Architecture, Network Effects, Social Business, Social Media, Strategy, The Enterprise Tagged with NGE2014

How We Gave Up Control Over The Social Web

November 13, 2013 1 Comment

A short but pithy piece over the weekend by Dave Winer titled “Why the Web 2.0 model is obsolete” got me thinking about where we’ve ended up with social media after nearly ten years. Blogs, wikis, and other tools of easily shared self-expression from the early days have given away in recent years to a much less diverse social media monoculture. A few large social networks now control our social identity, content, and behavior, and through their terms of service, often literally own our online existence legally and de facto.

This evolution was perhaps inevitable given the rules through which networks operate and certainly the result has its strengths. It’s far easier for consumers and businesses to adopt a hosted service than set up their own social presence, with all the complicated bits it requires to set up a fully functional social identity on your own these days. It’s also probably more secure, safe, and reliable long term. It’s certainly the shortest route to connecting with the vast captive audiences that the leading social networks now wield.

Yet in the process of making many short term decisions in the name of reach and convenience, many of us have given away our social capital, and along with it much of our online autonomy and freedom. I’ve long since stopped advising companies to drive their traffic to Facebook (disclaimer: I am a shareholder) and build their own online communities and digital ecosystems if they are intending to be strategic about things like social business and open APIs.

The impressive thing is that we’ve largely achieved the original vision of Web 2.0 and it’s just how we do things now. We share by default. We use social media more than any other digital activity. Social media is now woven into so much of what we do today. Yet the majority of all of this user generated content and online community is now centralized in a few large social silos that can no longer talk to each other.

Even worse, if we go the opposite direction that might seem better long term, we’ve discovered issues with that model too. For example, we’ve learned that when we create many smaller, self-controlled, and more autonomous social environments we then create fragmentation. We can’t easily communicate or collaborate with each other across these social islands. Thus, for as many downsides as the monolithic social networks have, they do achieve one important thing: They create a very large single social universe that we can all communicate across.

So what should we collectively do? Should we cave in and trust that the corporate owners of the social world will be benevolent, even when they clearly have business models that are very often at cross purposes to our needs and desires? Or should we find a way to solve the problem of creating our own social corners on the Web and then connecting them together, all while making it very easy to do so? Personally, I’m hoping it’s the latter. Certainly I’ve explored previously how open social standards have a genuine shot at helping with this, even if it might be a bit of a long shot.

The reality is that social media silos are now holding us back, both as individuals and as businesses. We can do much better if we want. But getting there requires a little long-term discipline and plenty of widespread demand. That makes it pretty unlikely in the face of the enormously strong network effects of the largest social networks today. But perhaps there’s a third option to regaining control over our social lives. In fact, I predict the next big breakthrough in social media is likely to come from the need to resolve this tension between the unfortunate long term consequences of centralized social media and the benefits of a much more federated and user controlled model. Unfortunately, recent history has been a steady march towards the former.

So until then, we all need to mull over where our collective decisions are taking us, for as social media is perhaps the greatest communication revolution in history, its intrinsic power cuts both ways.

Filed under Analysis, Network Effects, Social Business, Social Graph, Social Media, Social Technology & Standards, Strategy, The Web, Trends and Statistics, Web 2.0

Enterprises and Ecosystems: Why Digital Natives Are Dethroning The Old Guard

February 26, 2012 2 Comments

Why is it that so many traditional companies with an enormous wealth of assets largely fail to transform them for the digital era? By assets here, I mean established customer base, closely held relationships with trading partners, mountains of data and IP, as well as their bread and butter, the actual products and services they offer. For large organizations, these assets typically represent many billions in long-term investment and accumulated value that is being stranded beneath a digital ceiling they cannot seemingly break through. The lesson has been a hard one: It’s been surprisingly difficult for many companies to make a genuine transformation to digital.

For those just joining this conversation, this transformation is about opening up and digitally enabling the strategic assets of our organizations for better consumption and participation, with as low a barrier as possible. It’s also means doing so in a way that continually maximizes their value over time in today’s deeply networked marketplace. Achieving this triggers the primary engine of growth for digital ecosystems, namely network effects. This is how Apple, Facebook, Google, Amazon (new guard), and Microsoft, IBM, SAP, Oracle, and many others (old guard) eventually built hundreds of billions in combined value. They tapped into the relevant power laws of networks by carefully and deliberating cultivating and then closely managing them by harnessing peer production over the network.

How exactly was this accomplished? They did it by digitally platforming their businesses in specific ways: Enabling self-service on-boarding, viral adoption, open participation, best-of-breed data capture, ownership and control, and took advantage of the fact that relationships — and therefore, ultimately transactions — must take place on the network with as little friction and cost as possible. They realized that we are now all connected together continuously in a single global network and then designed their organizations around this central fact of the digital age. They are now reaping the results of this mindset:

Networked ecosystems must be a core focus and competency of modern business.

This begs the increasingly urgent question: Why then are a large number of older organizations neglecting their digital ecosystems, often failing to meaningfully cultivate them at all for many of their most valuable assets?

This is a key question that fellow Enterprise Irregular Vinnie Mirchandani recently asked in an internal EI mail thread and later posed on his blog:

But for every Apple which has gone one way, I see so many others piss away this huge asset that is their ecosystem. I hear about musicians and filmmakers auditing, even suing studios for accounting disagreements. I hear SAP mentors complain about legal issues getting licenses and other access to new technology. It’s easy to dismiss Joe Konrath’s litany of complaints against book publishers as one from an unhappy author, but the 230+ comments it has drawn shows a deeper angst about how poorly publishers are managing their author ecosystems.

Ecosystems, communities – call them what you want. They are a vibrant organism which deserve far more ink from all of us. And they need professional managers at the companies at the middle who nourish them and not just treat them as railcars to be hustled away whenever inconvenient.

As companies remain inadequately connected to their customers, partners, and workers via digital ecosystems, many of which they do not control, they are missing a rapidly narrowing opportunity. That’s because it’s very, very hard to disrupt a well-established network effect, which is much more powerful than the equivalent notion in the pre-digital era: traditional market share. Network effects are primary focused on pull distribution, while marketshare is heavily based on push, which is much harder and much more expensive to sustain. As digital natives sew up more and more industries and lay down network effects years ahead of their traditional brethren, any chance to reclaim the throne will be very unlikely.

For leading examples of potent digital ecosystems, see open APIs, social customer care, and app stores.

Why is this? There are a number of reasons but a few are particularly significant. What I wrote in the EI thread in response to Vinnie’s original question was this:

I find that in general, the farther you are from the tech business, the less native skill or familiarity there is with system thinking, which is perhaps the critical capacity to have in order to regard your business in ecosystem terms. This is something that in tech is standard fare with constant discussion and focus on platforms, network effects, SDKs, open APIs, app stores, etc.

Traditional publishers are typical of the technically challenged industries that are being blind-sided by newer, much savvier, techno-centric, network-oriented new digital businesses.

Business leaders that can’t deeply see the way forward for their organizations as flexible, highly dynamic, and organic digital networks of customers, partners, workers, and other (likely and unlikely) participants will ultimately fail. But this isn’t the set of skills or mindset that made them successful in the first place, so they don’t value it and don’t think in these terms. They literally throw off digital rethinking like a sort of corporate immune system. Surprisingly, from my talks in the C-suite the last few years, everyone individually seems realizes they have to change, but collectively they are resistant, it’s fascinating to watch.

A big part of the problem boils down to this: Companies are inherently designed to perpetuate the problem they were invented to solve. It’s a particularly thorny instance of the Innovator’s Dilemma, which ensures that a company is unlikely to aggressively re-invent itself until it’s in the process of being disrupted. Unfortunately, this often means it’s already too late.

In fact, it may be too late for a growing number of industries to fully make the transition to being ecosystem-centric. This includes media, publishing, telecom, retail, and many software companies. Under looming threat is real estate, higher education, financial services, professional services, accounting, and even venture capital. In each of these categories, ecosystem-centric firms are building network effects with open network-based products increasingly built by worker/open communities and delivered to customer communities. Those products are in turn built upon by hundreds or thousands of loyal 3rd party partners to bring their own customers and ecosystems to the table. This is an embarrassment of riches that only a few companies, again mostly digital natives, seem interested or able to tap into.

As Fred Wilson once said, the Web (and therefore digital business) is all about “building networks on top of networks“, which leads to even more powerful outcomes, like 2nd order network effects.

Fortunately, the force multiplier of the ecosystem model can be stated in a simple, fundamental way: It allows one to tap into the vast size and strength of the external network to drive growth, innovation, and revenue for your own ecosystem. As Peter Kim and I wrote in our new book, the fundamental principle of business in the ecosystem era must be to let anyone participate in every aspect of the business, primarily by inverting the facilitation process of driving shared value (i.e. network effects by default.) Being able to elicit the network (Internet, community, shared data, whatever) to maximum effect to fuel and growth your ecosystem is thus the core competency of the digital era. Unfortunately, this lesson is being lost to most organizations that were built well before this next-generation business model was understood. It will be a great loss that doesn’t necessarily have to happen in my opinion, but will ultimately result in the needless disruption of a large number of companies that just aren’t able to become digital natives.

For additional reading see:

4 Ways to Create Sustainable Business Ecosystems

Why Information Power Is The Future of Business

What Will Power Next-Generation Businesses?

A View of Digital Strategy in the Ecosystem Era

Are We Building Businesses Or Are We Building Platforms? Yes.

How Digital Business Will Evolve in 2012: 6 Big Ideas

Filed under Analysis, Enterprise Architecture, Network Effects, Peer Production, Strategy, The Enterprise

Transforming the Enterprise As We Know It

October 31, 2011 6 Comments

As I was reading David F. Carr’s latest piece on The Brainyard today, it drove home again for me some of the practically insurmountable challenges that many organizations have in avoiding the growing forces of digital disruption. David’s piece talked about Don Tapscott‘s proposition that we have to fundamentally remake the way our organizations engage with the world and produce useful work. The very-near future of business consists of new methods that are effective in today’s world, not for the era they were created in:

“When most people think of Enterprise 2.0, they think of the use of collaborative tools,” Tapscott said. “I’m arguing that something much bigger is happening than the application collaborative tools within the enterprise–it’s a profound transformation of the enterprise as we know it.” Basic principles of organization that have been established over the last 100 years are being upended, leading to “huge changes in how we orchestrate capabilities to create goods and services,” Tapscott said.

Like Tapscott, I’ve long been a proponent, along with thought leaders like John Hagel, that there’s a deep and profound Big Shift taking place as we get deeper into the 21st century. To survive, we must think in deeply networked, decentralized terms now, not in the rapidly receding business concepts of an age bygone. This means platforms instead of products, ecosystems instead of businesses, peer production instead of central production, and networks instead of hierarchies, to name just a few of the more significant aspects of the shift.

But how can traditional organizations get there? Web companies have a hard enough time getting there themselves, as digital natives. Most of them certainly don’t become the next Amazon or Facebook, two companies that virtually embody much of the changes taking place. Instead, I see many traditional firms engaging in the cargo cult mentality, hoping that by adding window dressing like social media, a few APIs, and perhaps some user-generated content, that they too will suddenly have a healthy, sustainable future.

Well, it’s not going to happen that way. The changes required are deep and sometimes painful. In fact, the more I examine the issue, successful transformation to a new mode of existence that naturally avoids the disruption inherent in these shifts boils down to a surprisingly few number of key changes. But those changes, though not generally that complex in and of themselves, are almost impossible to drive deeply into many organizations by virtue of their existing structures and processes. As they say, culture eats strategy for lunch.

Many of you know that I’ve been exploring how to foster social business approaches in large organizations for a number of years. When I see successes, they seem to have much in common with what made things like social media so successful. Yes, that’s network effects but also, and more to the point, about enabling an environment where emergent change can actually take root and thrive. A network effect can’t take hold if everything about the traditional way a business operates is to lock everything down into fixed transactional processes. That just doesn’t work in a fast changing new era where the value is in sustaining dynamic relationships and not fixed transactions.

As JP Rangaswami recenty wrote, it’s now all about “The capacity to change. Designed as an integral function. Native.”

How then can businesses “fundamentally remake” themselves? What critical changes are at the heart of moving from regular business to things like social business? I’ve been exploring the answers to that question recently in quite some detail, but I’d start with these three things:

Local autonomy. Effective, resilient response to business change can’t only be driven by top-down, hierachies. It’s far too slow, low in innovation, and far from problems on the ground. Restructure the organization so that change along the edge is not only possible, but well-resourced, common, and effective.
Freeform collaboration. Going beyond Enterprise 2.0 to reinventing the way business models scale and provide value. I’ve previously written about the orders of magnitude cost reductions that are possible and the things they enable, plus how to get there.
A culture of experimentation. Of the three, this is the hardest. The first two are different; it’s always possible to create a startup culture at the edge of organizations and it’s also possible to drive mass collaboration. We increasingly see it done all the time in large companies, though it takes time to really establish itself in a transformational way. But to get an organization to be fundamentally more accepting of innovation is very difficult to instill when it does not already exist. Some of it is a skill problem, but a lot of it is more systemic. Solving this is going to be one of the great generational challenges of the social business era.

There’s a lot to consider when undergoing the large-scale transformations that businesses must undertake today, but a focus on these core issue will go way towards getting started.

Filed under Analysis, Network Effects, Peer Production, Social Business, Strategy, The Enterprise, The Web

Exceeding the Benefits of Complexity? A Fractal Model for the Social Business Era

September 12, 2011 10 Comments

Over the weekend my friend and industry colleague JP Rangaswami wrote an insightful post that pondered how we have gone about delivering on customer experiences as connected to our back-end capabilities. Specifically, he explored an issue that is increasingly challenging many of the large-company CIOs I speak with these days: That the present rates of change demanded of the accumulation of 20-30 years of legacy business systems is greatly exceeding the ability of our enterprises and associated software “stacks” to deliver on them, particularly as cloud, social, and mobile dramatically transform computing today.

The problem lies in our classical views of enterprise architecture and business architecture both. But JP puts it more poetically:

Development backlogs are endemic, as the sheer complexity of the grown-like-Topsy stack slows the process of change and makes it considerably more expensive to change. The stack has begun to fossilise, just at the time when businesses are hungrier for growth, when the need to deliver customer-facing, often customer-touching, applications is an imperative.

Which makes me wonder. What Tainter wrote about societies, what Shirky wrote about companies, are we about to witness something analogous in the systems world? A collapse of a monolith, consumed by its own growth and complexity? As against the simpler, fractal approach of ecosystems?

This fractal aspect of user systems, Web 2.0, and SOA is one that I deeply explored in the 2005-2007 timeframe, and my ideas on this even made the cover story of the SOA/Web Services Journal at one point. This is when we began to see successful, composite systems sprouting up “in the wild” that were eminently natural and highly successful, such as Amazon’s, Flickr’s, and many others. Innovative new open API-based businesses had definitively emerged and shown us — in fact, virtually proved to anyone willing to observe — that business/technology ecosystems could be routinely produced that were far more successful than the ones virtually any traditional business had managed to produce for itself internally with methods like SOA. It was clear something important and new was happening and we tried to learn from it.

The signature lesson in this time period was that being “in the business” of ecosystems, at multiple levels, was the key to resilience, growth, and sustainability. It’s still a far cry from how most organizations are structured today, but I do see the first hints that this is starting to change. Companies like Best Buy and Sears have been getting the message among the old guard firms and looking at integration, partnership, and engagement as an open network activity.

The Web has also shown us that complexity, as important as it is to address and resolve the many inherent vagaries of dealing with the real world, is largely the enemy, whenever it exists needlessly. Our assumptions of where the complexity should be, in the transports for example, was wrong. It was in the ecosystem itself and we paid dearly for half a decade (and running) based on that misapprehension. But we’ve learned. SOAP usage has almost completely shifted to REST, complex WS-* stacks have largely moved on to simple standards and methods like Web-Oriented Architecture.

But technical discussions obscure the very important truths about what we’ve learned in the interim between the “aha” moment when we realized that what was happening so successfully “out there” was something that would make us just as successful inside our organizations, for internal and customer-facing needs both. After all, this holistic ‘integratedness’ — usually triggered via our connections to the Internet — was a part of our businesses increasingly and we simply had to realize this and engage as Internet natives. But back then, Andrew McAfee worried that focusing on the plumbing was the wrong emphasis to have on the exciting changes taking place, and he was largely right from a communication perspective.

However, building fractal architectures that addresses the old and the new isn’t as easy as just deciding to cast off the old, less effecive ways, as JP notes:

What I’d established in my own mind was a growing belief that the issue was to do with rates of change and costs of change. Vertical integration paid off when the rate of change was low. Networked small-pieces approaches paid off when the rate of change was high.

We are clearly living in times of much greater rates of change. Unfortunately, the old systems, the old architectures, the old business “stack” is often running the core of the business. It’s usually deeply vertically integrated, and not made of small networked pieces, loosely joined that are truly agile, deeply harness innovation on the edge, and turn IT into a profit center instead of a cost center.

So, while I have a lot more to say about this, because I believe that social business context will be at the root of the future of our how we design our products, services, processes, and workplaces, below are a few basic rules you can take away that if you stay true to, can indeed help you make the transition to the future. Note that customer and worker experiences are outside the scope of this, this has more to do with the new business stack below the social layer:

4 Ways to Create Sustainable Business Ecosystems

If resilient, networked, recomposable, open business capabilities are the future of business and IT architecture, getting there then requires a substantial change in stance:

Open Your Business Stack. To everyone, internally and externally, generally in the order of the systems and data that are most often requested for integration. Make it easy for anyone to onboard themselves and use the simplest and most egalitarian technology possible to deeply connect the world to your business. Self-onboarding is crucial because it enables the killer asymmetric business advantage of systems that respond to external engagement best: Export most of the change effort to outside your organization and impose it on those that wish to participate and integrate with you. Enterprises that close the “clue gap” with Big Data will have an enormous advantage.
Go Into the Business of Ecosystems. Stand behind your open supply chain: Invest in it for the long term, market it, evangelize it, support it, and stand behind it like your customers — again, internally or externally — will be building world changing products and services from them (if you do this, the track record is that they will.) Be fair and generous with your IP and enterprise data; you are under-utilizing it by several orders of magnitude until you do this, leaving much or even most of the potential of your business on the floor. Worse, until you treat it like a business, you won’t get external contributions to enrich your ecosystem that will drive down the cost of change while greatly increasing the velocity of new solutions and local adaptations.
Begin Fractal Reconciliation of Your Classical Systems. While hanging a trendy Web API off an ancient COBOL accounting system might be a step in the right direction, long-term success will mean going well behind the API. The existing business/IT landscape must be converged and rationalized so they themselves are made of “networked small pieces” that are faster to change as well as more resilient and responsive to being so much more connected (and therefore useful and valuable) to the world.
Spin Up New 21st Century Business Models. All new possibilities, many of which will be foreign to non-digital native firms, are reachable once you have created a fractal enterprise stack. Dominating classes of data, metered business knowledge, all new monetization methods, and more become possible once the three transformations above have started.

Unfortunately, after having advised and directly assisted many large companies in doing much of what I’m describing here over the years, it’s clear that most organizations are at a major disadvantage in making this transformation. The organizational will required is actually quite low, since most of this is fairly easy to do now with cloud technologies, increasingly capable technology partners, and the latest development stacks. Instead, it’s the understanding of how important it is to kill excessive complexity and focus on ways of thinking about business and technical architecture that will propel companies into bright futures.

We must leave behind vertical integration and radically collapse the size of our seams (APIs) in our businesses, while radically increasing the number of useful endpoints such that we look at them as the very fundament of our enterprises. The benchmark for success is how many others are depending on your ecosystem for their own success. Starting now, the activity in your organization must be focused on optimizing for growth of this number. That is the only way we’ll ensure we’re building businesses that are the most relevant, meaningful, and valuable to us going forward. The enterprises that don’t simply won’t survive in their present form. I believe that much is at stake here. Unfortunately, the “cultural gap” John Hagel wrote of back when this conversation started between the enterprise crowd and the Internet crowd is still much too large and is still hindering the move forward for many organizations.

I look forward to continuing this discussion and exploring just how much we’ve recently learned about the future of business and enterprise architecture.

Filed under Analysis, CoIT, Enterprise Architecture, Network Effects, Strategy, The Enterprise, The Web, Web 2.0

The K-factor Lesson: How Social Ecosystems Grow (Or Not)

January 5, 2010 1 Comment

Recently for some work that I’m doing I had to revisit the techniques for creating successful online social environments. This is a surprisingly deep and nuanced topic that we as Web application architects or enterprise social computing practitioners are just now fully beginning to grasp. The subject matter itself runs the gamut from key conceptual underpinnings — esoteric topics like systems theory and network effects — to the daily grind of understanding and managing the needs/expectations of an often difficult-to-control community of actual, live people.

In general, I’ve found that the ideas behind social systems themselves are clean and elegant while dealing with their practical realities can definitely be messier and many find them annoyingly unpredictable as well. In the end, online social ecosystems are invariably a fascinating mix of the classic vagaries of technology and people. However, despite the apparent science, making them grow into something undeniably successful is still very much an art form.

Interestingly, there’s no real name for this skill yet and it’s an important — even vitally strategic one — for any organization that has to engage with a lot of people over a network. And that’s increasingly most of us in these days of the ever-present Facebook news feed, Twitter microblog, and workplace Enterprise 2.0 environment. It also means that creating a workable online community requires a good dose of hard-nosed engineering as well as highly effective “soft” skills in UX design, social architecture, and community management. For it to really work — to have a vibrant and growing community — you have to seamlessly connect both of these worlds: a well-crafted social environment together with the people that will use it. The rewards for doing it successfully speak for themselves: Ultimately, businesses and communities are groups of people, and if they produce more value for each other together than they can individually, then there is something in it for everyone. And the online world lets us create these entities far easier, more quickly, and with larger populations than ever before in history.

Related: Network effects are just one of several dozen “power laws” that social architects must know today.

We used to call this process “founding a business” or “creating an organization”. We would call the people that did this entrepreneurs or occasionally philanthropists if their goal was non-commercial. But this terminology doesn’t seem to apply as much to what’s happening now. For one thing, communities are organized differently and frequently have other motivations for participation than the usual one for traditional businesses: the worker/employer relationship. Second, the output of large distributed online communities — especially when focused on discrete outcomes — can greatly exceed the results produced by densely concentrated single institutions. While we are certainly in the very early days of this phenomenon, I’ve frequently pointed to numerous examples of these new models for creating shared value.

So putting aside the socialism vs. capitalism arguments for now (they are increasingly brought up in this discussion, though why they don’t seem to apply here is the subject of a future post) the 21st century networked economy — powered by people and knowledge connected together globally at virtually no cost — has set free fundamentally new ways of innovating and collaborating for mutual benefit. Specifically, it’s the rules for how these new mechanisms thrive and create value that is the object of discussion here.

For my own part, I’ve been fortunate to encounter ways to reduce the concepts for creating growing social ecosystems to a short list, the key ones which I’ll present here. Please be warned, some jargon is necessary, but I will explain it along the way.

How To Create Self-Sustaining Social Ecosystems: The K-factor Lesson

Like my 50 Essential Strategies for Web 2.0 Products, this overview cannot possibly be exhaustive. It does however highlight the central idea behind all successful communities: They are either busy growing or they’re busy dying. Gaining critical mass early on is another important lesson that we’ve garnered from the early Web 2.0 pioneers. Finally, the aforementioned and mysterious K-factor is introduced and explained below.

Fiat and network effects are the two primary ways that social ecosystems grow. The first is based on an explicit or implicit mandate of some kind. An example of a fiat is when an organization requires participation in a particular social group, perhaps a committee or online community. The second, a network effect, is when a social group has more value the more that other people are involved in it too (which is usually, but not always the case.) Keep in mind that the degree of value in each new member, or their contributions, is based on the structure or design of the social system and will vary greatly. Also note that the fiat approach that is common in business today is a top down effort to “push” participation, while network effects are a “pull” method and tend to be more bottom-up and organic. Background: Read more about push vs. pull systems. Critically, the degree to which a network effect is realized can be influenced by many factors not the least including the intrinsic nature of the social ecosystem itself and how it is connected to the rest of the network (the Web or your intranet.) In general, network effects will ultimately be more successful than fiat for most purposes, especially since the use of social systems are so often made optional, even in business environments.
Network effects can be encouraged by promoting self-sustaining growth via feedback loops (aka virality). One of the myths of the online world is that viral growth can’t be engineered. While it’s sometimes not straightforward, it can indeed be created intentionally. While cynical uses of virtuous growth cycles won’t produce results for long, the basics work best: letting any user improve the community by contributing knowledge, often to a lightly structured data set or encouraging them to invite their friends and colleagues. In fact, any good social ecosystem will make it easy and rewarding to do so, such as allowing users to discuss, converse, jointly edit, or otherwise work together on common goals. Stated another way, the future of software applications that don’t provide more value when more people are present in an interaction is probably going to be fairly short. A good place for more background on the lifecycles of systems (social or otherwise) is William Varey’s Unlimited Growth.
Measure your K-factor and keep it above 1. The K-factor of an ecosystem is a statement of whether your network effect is self-sustaining or not. A K-factor of less than one means that your organic growth level is falling (exponentially) and a K-factor of greater than one means that it’s growing naturally and again, exponentially. How to increase your community’s K-factor? There are literally countless ways but allowing users to contribute to hard-to-recreate data set, adding user distributable widgets that provide useful offsite functionality, as well as integrating meaningfully with 3rd party social networks through their application model are a few of the more popular and effective ones. I explored some of these distribution approaches in more detail a while back in my overview of the new distribution models of the Web.
The higher the social feedback loop intensity, the higher the breakthrough factor. Feedback loops are created for example when a user invites another user to the community and then that user invites their friends and so on. However, the quality of the feedback loop is a measure of how often it reaches outside of the community and how effective that outreach is (often stated as k = e * i, where “e” is the efficiency of the feedback loop and “i” is the average number of invites per user.) An individual user’s ability to affect the quality and intensity of the feedback loop is usually a measure of their social surface area, which I generally consider to be the size of their social graph x the number of online channels they use x the frequency of participation x the amount of influence they exert. If you have a social ecosystem with a lot of influencers or users that are very active online, they will clearly fuel the response to your feedback loops more effectively. The design of the social environment itself also has a major effect depending on whether it makes it easy to invite others or otherwise create feedback loops. A breakthrough factor is achieved when the feedback loops rise above a certain threshold of attention, such as when multiple invites come from multiple persons over a short interval of time. When this threshold is crossed for a prolonged period, the K-factor increases much more rapidly. This rise can be self-sustaining (the so-called virtuous cycle) and can lead to a permanent and dramatic growth climb as evidenced by many of the popular social networks early on, such as MySpace and Facebook.
External “high impulse events” can be used in the short term as a catalyst to reach the breakthrough factor. This was famously the case with MySpace which used a database of 50 million e-mail addresses to drive initial users to the site, whereupon their feedback loops soon created a particularly strong breakthrough factor. Traditional marketing is often used as the seed to drive the initial population of communities, but unless the K-factor soon rises above 1, the long-term cost of this approach is usually prohibitive. It’s worth noting that it all my research, I’ve never encountered a community that was successful long-term without naturally self-sustaining growth. This is the K-factor lesson of this post’s title: You can grow any community in the short term using artificial means but it will only last and continue to grow on its own because of the inherent quality of the people and the knowledge that has accumulated. That said, you must get your community growth primed in some way. High impulse events can include (by no means exhaustive) traditional marketing, paid incentives (expensive but Paypal was very successful with this model in its early days), and — particularly for business communities — seeding initial high value content.
Growth in a social ecosystem is not endlessly exponential and eventually hits a ceiling. Plan for it. Typically described by the S-curve, it is encountered when you either fight an existing network effect or when resources are exhausted on the network. While hitting the upper bound of the S-curve is desirable and denotes a successful system (Facebook is just hitting this now), it can also be an indicator of a failure or a bottle-neck in the feedback loop design. A false S-curve is most often evident in my research when a community undergoes a major UX redesign and users have to find their way again, often unable to find and use the features that drive growth and sustain the community. Be aware of this and guard against the potential causes of premature S-curves.

I’ve written in the past about deliberately creating emergent phenomenon and then capturing some kind of value from it. Like most efforts on a fixed scale of zero to the maximum possible result, there is a reverse bell curve effect, meaning that most people will get middling results, some will get very poor, and some will hit it out of the park. From the projects I’ve been involved in, I find that the most successful social efforts are ones that are highly agile and willing to capture lessons learned early and often and then make changes quickly and do it all over again the next week. The Web favors those who experiment, adapt, and evolve and thus should go your social ecosystems.

Good luck with your social media and Enterprise 2.0 efforts. Please don’t hesitate to ask questions below or contribute your own wisdom.

Filed under Network Effects, Social Media, Strategy, The Web Tagged with "network effects", growth, k-factor, marketshare, social architecture, UX, viral

Building Modern Web Apps? Better Have A Deep Competency in Web 2.0, Open APIs, Widgets, Social Apps, and More

August 24, 2008 Leave a comment

The Web has an interesting property that those building Web applications and online businesses usually encounter soon after they first launch: It has its own unique and unforgiving rules for success and failure. Appreciating them requires a certain level of understanding of the intrinsic nature of the Web and how it works. Actually leveraging those rules requires an even deeper and more profound understanding of the Web. The challenge these days? The Web competency bar is climbing fast.

To drive the right decisions in what they do product designers, marketing teams, software architects, developers, strategy officers, and other key roles in today's generation of online businesses need to have a solid handle on an extensive array of Web topics. This ranges from appreciating why plain old HTTP is so good at underpinning the Web to more sophisticated topics like modern application architecture, the latest in online user experiences, next generation computing models (grid/cloud/utility/SaaS/PaaS), cost-effective scalability, user identity, network effects, Jakob's Law, analytics, operations, user community, as well as the many compelling new distribution models that are nearly mandatory in the first release of most products.

This extensive set of competencies is what's required nowadays to deliver a credible online product to a receptive user base and it has dramatic implications for both uptake and overall cost/time-to-market. Worse, this body of knowledge has become extensive enough that many Web startups frequently fall far short of what they need to know in order to be successful with these far flung practice areas.

Does this complex body of knowledge mean the era of the two-to-five person Web startup is coming to a close? Not at all, at least not yet. The productivity level of the latest tools and techniques remains almost astonishing though the level of knowledge required of these teams is creeping up and up. And as we'll see, new models for product distribution are pushing the capability envelope of the typical Internet startup team to the point we may very well see the day soon that they won't have all the skills necessary to deliver a fully-scoped modern Web application. It is also one reason why fewer and fewer Web startups have the goods to be all around hits out of the gate.

Certainly, varying depths in subject matter are required depending one's exact role in a Web business, but Web-oriented products are fundamentally shaped the vagaries of the network itself. Tim O'Reilly himself still has the best quote on the subject: "Winners and losers will be designated by who figures out how to use the network." And as we'll see, the Web is driving the evolution of a major new generation of online distribution models.

Why Adopting New Distribution Models Is Crucial

As an example of this, I've been tracking some of the latest discussions around the hot topic du jour in the Web world: Social networking applications. Specifically, it's been interesting to watch the surprisingly low level of industry attention around the titanic competition brewing between social networking application formats from Web giants Facebook and Google. Why is this? Some might say it's because these applications still have largely unproven business models. Others, like Nick O'Neill at the Social Times recently observed (rightly in my opinion) that the struggle may have to do with a deficit in understanding why these new types of Web applications are so important. Nick notes that these widget and social networking style models for packaging and distributing Web apps often "have more eyeballs looking at their products than television channels have" and the challenge is that too many people just "don’t know what any of this means", despite the major players divvying up the online pie for themselves. With the size of these next generation distribution audiences, ignorance has an extremely painful price: failure to produce results and growth, poor engagement with the marketplace, and loss of market share.

An excellent summary of the truly massive, but largely underappreciated scale of these new Web application models was last week's TechCrunch piece on the progress of Google's OpenSocial, an increasingly successful model for creating portable social networking applications that will run on any OpenSocial-compliant site. Erick Schonfeld reported that OpenSocial now has a total reach of an astonishing 350 million users and it will soon be 500 million. There are over 4,500 OpenSocial apps today, a healthy number for the application format but a small drop in the bucket compared to the number of Web sites in the world. But the key is that these applications are integrated much deeper into the social fabric of an engaged audience, interjecting themselves into the daily personal and work habits of the "captive" users of social sites and even have access to the personal habits and data of users of these sites. Facebook's story is impressive as well with over 37,000 applications that have been installed over 700 million times.

And social networking applications are just one of many news ways that applications have to be packaged and distributed, yet far too many organizations persist in a very 1990s view of Web experiences, namely that Web sites themselves are the center of online product design. Many even think that some of these other new distribution models are interesting but not part of their core online product. Unfortunately, that's very much a parochial view in the present era. Federated applications, atomized content and functionality, 3rd party product ecosystems through open APIs, and much more are required to establish a strong and resilient network effect which fends off competitors that are themselves bringing these potent new competencies to bear.

In fact, one of the things we emphasize over and over again in our conference workshops and in Web 2.0 University is that having a Web site is usually the least interesting things about new products. Worse, it makes the customer have to find you amongst tens of millions of other sites. Instead, these new models tend to focus on going to the customer, instead of making them come to you which is a much harder proposition. This can instantly give you the ability to reach millions of potential people with dramatically lower effort and cost, as long as you have something interesting to offer.

Unfortunately, the number of capable practitioners of these new distribution models remains relatively small compared to the large body of experts in traditional Web product development. Demand is also low for these new skills as most organizations have been painfully slow to appreciate how much online product development has changed. A quick search of the job aggregator SimplyHired tells the tale: Nearly a thousand Web designer positions are available while only 36 OpenSocial and 40 open API positions are open, for example. This despite the the latter skills being able to project a product across the Web into hundreds of social sites or create an API that allows the product to be incorporated into countless other products for far less cost per customer than traditional methods.

The lesson here is that these new models still have a lot of fertile, unclaimed territory and many otherwise fierce competitors have not yet become fully aware of these new opportunities. Get your piece of the pie while there's still time.

I also find that the Web development industry has been slow to change, particularly outside the valley, and there is depressingly scarce information on how to deliver well on things like widgets, open APIs, social networking applications, and even syndication. To help with this, I've put together a short primer and some good references for those that want to get started.

Because the good news is that there remains tremendous opportunity for growth and success — for both startups and traditional businesses — if they will actively begin incorporating these new product delivery models into their own online capabilities.

Overview of Online Product Delivery Models

Web sites. This the classic model for Web presence. During the early Web, creating a Web site was just about the only option for engaging with those online (e-mail being the other.) Most early Web sites were used for publishing and not for user participation or peer production. These days, Web sites are still important, though by no means mandatory, and have their content syndicated via RSS and ATOM (pushing the content to where it's wanted), provide an access point to obtain widgets, and maintain user identity, and create communities of users. Upshot: They've evolved a lot but Web sites are only part of an extensive set of capabilities that must be brought to bear in the Web 2.0 era.
Syndication. It took ten years for the Web community to figure out a workable syndication model. Now RSS and ATOM are now the expected models used to distribute content off a single site and across the Web. Countless aggregation services now exist that make a site's information embedded in their services as well as a way to offer users a method for pulling information from a site and experienced in a means of their choosing, from Google Reader and Newsgator to the innovative Yahoo! Pipes. Most sites still heavily underutilize syndication even for notifications and pushing out frequently changed information to draw attention to it much less the strategic ecosystem and integration opportunities it affords.
Web 2.0 applications. You might argue that Web 2.0 itself is not a product distribution model but a set of design patterns and business models and that would be a true statement. However, in this context we're referring to the fact that Web 2.0 apps package up the 3rd major type of networked value: user participation. Before then, Web sites and syndication primarily had only centrally produced content or functionality that they could expose over the network and offer to the marketplace. In other words, user participation its purest form — sometimes known as peer production — ultimately results in products like Mechanical Turk and Predictify that provide direct networked access to user participation, but there are many fine gradations to this. The bottom line, Web 2.0 applications plug the user into the network like never before and are a critical rung in the distribution ladder since it offers access to the largest set of content and information by harnessing collective intelligence.
Open APIs and Web services. This is one of the most important long-term decisions most online businesses can make. Offering an open API lets anyone take the online components of a business, from its data and functional capabilities to the users themselves, and makes them open and accessible over the Web to be incorporated into other products and services, sometimes in the form of mashups and sometimes in the form of entire online products. Amazon, one of the first Web companies in existence and is hence far downrange in terms of the experience curve, has been using this distribution model with notable success recently. So have hundreds of others. The real challenge has been how foreign this model is to the original Web model and thus to the various management and development competencies in most organizations. It's much more an a way to OEM a product and leverage the customers and investments of hundreds of other partners. However, overall, it affords the potential for much larger business outcomes than could ever be created with point Web presence. It's now considered a significant oversight not to have an open API available for the typical online product.
Web widgets. Selecting parts of a Web site and it's data and packaging it up to make it run inside a portable, user distributable widget has been growing more and more popular over the last few years. For example, WidgetBox currently distributes 74,000 different kinds of Web widgets from its partners to over 1.2 million other sites. Widgets lets users distribute a Web site to other places on the Web at no extra cost and it also creates an ecosystem effect, where other Web sites users become the users of the new site. The YouTube badge is a notoriously well-known example of this that also helped drive the extraordinarily fast growth of the site. Like APIs, widgets are now considered a mandatory must-have for new and existing online products. But unlike APIs where it's up to the API users, figuring out users want out of your site's widgets is still an art form.
Social networking applications. Sometimes viewed as an extension of the Web widget model, social networking applications are applications designed to run inside of popular social networking environments and usually have capabilities that tap into and make use of the social graph information resident in a user's social network account. This is an amazingly fast moving field as you can see from a recent post on the latest happenings on the OpenSocial blog, to the extent it's hard even for well-funded companies to keep up. However, despite skepticism that large businesses can be built exclusively through a social networking application, it's become ever more essential for a site to make its capabilities accessible usable in these environments. Not only will users help distribute online products in these formats to their contacts but it also increases the overall usage of the your application including participation and its consequently growth of a site's network effect. While not yet considered mandatory for online products, the ease with which these social network applications can be created and the large numbers of users they make available makes it a smart distribution option for most Web businesses. Like widgets, however, figuring out what users will find engaging in a social networking application featuring your online product takes some research and experimentation. However, the results can be very rewarding and some social networking applications have millions of daily users. See the Plaxo Pulse story on Mashable for the details of how OpenSocial drove a 5x improvement in traffic in only 3 weeks.
Semantic Web and Web 3.0. The Semantic Web, one of the original visions for the World Wide Web, has taken a while to arrive but it's beginning to look like it may hit critical mass in the next 12-24 months. Combined with Web 3.0, which takes the architectures of participation at the core of Web 2.0 and drives it through a lens of Semantic Web capabilities. The benefits can be profound and can greatly increase the value and leverage of information on the Web. While this is very much not prime time yet, unlike #1-#6 above, it likely will be and smart organizations can get ahead of the learning curve and get an early market lead using these techniques. For now, however, I recommend that most organizations focus on executing well on the first six items before tackling this and waiting for the technologies to finish emerging and maturing.

The list above should provide good guidance for starting move into the potent new models for distribution on the Web. I'm seeing, however, that because of the major shifts in strategy and product design emphasis these techniques demand, most organizations take an inordinately long amount of time to become effective with them. The lesson here: Start small now and build core competency. Small investments now can pay off later in terms of valuable experience made from early experiments and pilots. When done right,
these new distribution models can become the dominant channels that the world uses to interact with your business, like they already have with Amazon and Twitter.

I'll be talking about these and other strategic online product design topics in my upcoming Building Next Generation Web Apps Workshop at the inaugural Web 2.0 Expo 2008 NYC next month. I'll have more details about this deep-dive session in an upcoming post.

Filed under Network Effects, Social Business, Social Media, Social Technology & Standards, Strategy, The Web Tagged with distribution models, Jakob's Law, Semantic Web, Web 2.0