Framework for Ecosystem Change (2): Evolution

Below I introduce a framework for Ecosystem Evolution, a collaboration-based process to achieve innovation in our social ecosystems, which includes complex spaces like Healthcare and Public Education.

Our thought process has been evolving since August 2009, and can be tracked in this stream.

This problem-solving approach is intended to be comprehensive in its objectives and capabilities, yet straightforward in its design. It is made possible by incorporating insights from complexity science, as well as the rapid evolution of the social media platform, which allows cross-disciplinary subject matter experts (“SME”s) to work together in an efficient, virtual manner.

Paradigms: the Way Things Work

At the core of this framework is a realization that there is a current way of doing things, and multiple, new, innovative ways of doing things better.

Using paradigms to frame and analyze developing ideas is important, especially in early stages, when the alternative solutions are still formative [1]. It provides an intuitive frame of reference for discussing ecosystems: boundaries, rules, behaviors, and outcomes, all important elements that describe the complex systems we will be tackling. This “way of doing things” (both current and improved) is often the source of significant debate. Semantic challenges abound. Traditionally, problem/solution scenarios are written down in many ways, ranging from pure text (popular in legislation) and napkin drawings all the way to complex diagrams and flow charts, using a multitude of formats and tools. We will need to keep the process focused on ideas and content, not tools.

Due to the complexities of our social ecosystems, the nature of changes involved must go far beyond any notion of incremental adjustments. Contemplating the “game changing” notion of a paradigm shift precedes any fundamental, structural changes in our current paradigms [2]. To innovate, we’ll need to challenge conventional wisdom in each domain, or subject area. This approach will help us achieve that.

Let’s take a look at my proposed Ecosystem Evolution model, which provides a collaborative overlay to the Current State view that I originated in my last blog post.

Ecosystem Framework pt 2

Ecosystem Framework pt 2

The over-arching characteristics of this new model are:

– All stakeholders will have opportunity for input
– Social media plays a critical role as “open collaboration forum” for idea exchange
– Invested producers with a financial stake will have more limited roles
– Consumers (most impacted by ecosystem outcomes) will have a voice in articulating outcomes
– Consumers will get final validation (via “rating”) of proposed solutions
– Several open-loop cycles ensure iterative improvements toward final innovation
– Multiple iterations or “feedback cycles” ensure consensus

There are a couple key points to take away from this.

(1) Actionable Scope (need to be realistic). A framework like this is a representation of a complex set of relationships, interactions, intermediate steps, and deliverables. The simplicity of the model should by no means imply trivial efforts or shallow treatment of the topics. Rather, considerable work is implied. This model creates the process backbone for a series of connected collaboration teams. Further details on “how” will be forthcoming.

(2) Adaptable, Scalable and Efficient. This approach creates the means by which the rigorous and appropriate discussions might evolve uninterrupted, through a “hub and spoke” model of work group replication. In other words, any number of problem-solving teams may be spun off from the core problem team within the ecosystem, to work on sub-issues, and report back. This makes the Ecosystem Evolution process adaptable, scalable, and via multi-tasking, quite efficient. Given the complexity of our ecosystem issues, this is perhaps the ONLY way problem solving could be meaningfully performed.

(3) Focus and Rigor. We will begin to ask the right questions, and record all viable answers.

(4) Meaningful Social Innovation (“disruptive”, and otherwise). Using this model, we can embark on a journey of discovery and social change that has heretofore been unsuccessful. It will be powered by people, connected using social media, supported (with further discussions) by both government and industry, and ultimately, embraced by all stakeholders. Clayton Christensen has made strong and insightful statements about the need for “disruptive innovation” to achieve change from outside ecosystem walls, and the many mechanisms required [3]. I think his vision is the right one, and this Framework intends to achieve it. However, with participation from producers and consumers alike, the degree of “disruption” can be minimized, and simply acknowledged as a working objective. After all, we won’t score a “win” if we create economic chaos. I believe the collaborative approach is the disruptive innovation that has been needed. The approach itself is an innovation in collaborative techniques imagined by Don Tapscott, but not (as yet) fully implemented [4].

(5) Who benefits? First and foremost, it will be the consumer, as this approach is designed to achieve their objectives. But in the end, all stakeholders will win, because we will have created a viable, optimal, balanced approach for delivering services.

This is clearly ambitious. Why am I so optimistic?

Because there are lots of smart people out there. We simply need to engage them to start solving the tough problems.

It’s time for our second test (and this is a non-rhetorical question): Can we make this work?

Notes:
[1] Kuhn, Thomas, Structure of Scientific Revolutions. (1992).
[2] Meadows, Donella. Leverage Points (web, 2008).
[3] Christensen, Clayton. Disrupting Class (2008): McGraw-Hill, Ch.8, pp. 179-196.
[4] Tapscott, Don. Wikinomics (2006): Penguin, Ch.6, pp. 151-182.

Framework for Ecosystem Change (1): Current State

In my last post, I began to outline a new approach for innovation in complex ecosystems. Efforts to drive reform in Healthcare, Education, and Energy have routinely struggled, and progress has been elusive. My thought process was sparked, in part, by an analysis of complexity science written by Beth Noveck & David Johnson. But much of my energy was fueled by numerous examples where barriers to collaboration and silo-thinking have long served to stifle innovation in large-scale institutions and the ecosystems they serve.

The Challenge of Social Ecosystems

Though a great many provider professionals have, in practice, devoted entire careers to excellence, overall system outcomes can appear inconsistent and, in many cases, undesirable.

Why? As noted by Noveck and Johnson, system complexity itself introduces many dynamics that need to be investigated, among them, conflicting objectives of stakeholder “agents”. Another area for focus is money. While always a powerful motivator, in social ecosystems it serves as a double-edge sword. The same financial capital that’s driven breakthrough innovations can also motivate counter-productive results. To stakeholders in the pipeline, long-term outcomes are not always visible, actionable or prioritized effectively.

A Path Forward

To achieve an efficient system-level problem-solving process, I’ve developed a simple framework for Ecosystem Evolution.

First, let’s introduce Part 1 of this framework for the Current State, to ground our discussion and better define some key concepts like “ecosystems”, their “agents”, and their operating “paradigms”. The status quo is characterized by the following forces:

  • Closed-loop, mature transactions and processes
  • Heavy control exercised by producer and government stakeholders (“agents”)
  • Much investment (financial, emotional) associated with the status quo
  • Insufficient rigor in the definition of problems and possible solutions
  • Insufficient data to effectively prove viability of alternatives
  • Largely untapped sources of insight on complex (adaptive) system behavior

Ecosystem Framework Pt1 (Current State)

How would we move forward with this model?

For each ecosystem targeted, we’d document the current state paradigms (literally, “how things work”, represented above by the black box), creating light-weight process models that demonstrate a solid understanding of core challenges. We’d also break down the paradigms themselves into easily understandable components.

Rigor in developing models is critical. Stating problems fully and accurately is on the critical path to any meaningful change.

Then would come the work of articulating alternative paradigms using the above as a baseline, using a collaborative approach that leverages social media. Resulting ecosystem designs could give us (perhaps, for the first time) a detailed understanding of our fundamental, root cause problems, summarizing the changes that may be necessary to address them.

Next Steps

I’ll introduce Part 2, a collaborative solution framework for Ecosystem Evolution in my next post, building on the Current State model above. It will incorporate new, collaborative open-loop processes and the social media aspect. Comments and inputs are not only welcome, they are critical. We can only be successful if we tackle these problems with a mutual understanding and a resolve to work the issues to completion.

Our first test: looking at the model above, can we start to see the challenges more clearly?

Unraveling Complexity (the Missing Link): A new approach for solving problems in Social Ecosystems

For months I’ve been reaching out to colleagues to explore barriers to collaboration, a key tool in the social innovator’s toolbox. Among those queried (and in spite of diverse backgrounds), virtually all had experienced significant barriers to collaboration over the years including silo-thinking, dated and inefficient problem solving models, cultures of control, and a strong, prevailing lack of trust.

Consensus? The barriers to innovation seem to be as universal as they are frustrating.

So something is broken. What is the root cause?

Beth Noveck and David Johnson have published important research on how new Social Media collaboration technologies can change the game. Their perspective on a New Science of Complexity is summarized in this People & Place blog post and explained further in an excerpt from their research. Their focus was the U.S. EPA (including the Federal process for environmental research and legislation) but their conclusion, which I agree with strongly, is that the principles are applicable in business (#e20) and broader social venues (#gov20) as well.

My primary takeaway?  I now believe that INNOVATION IN COMPLEX ECOSYSTEMS will depend on an improved collaboration process – a new middle ground for problem solving – that balances large-scale central organizational approach with grass-roots contributions by individuals. It is about finding the “sweet spot” between rigid structure and adaptive, organic sourcing of ideas. In a new and somewhat uncharted public collaboration space, it means that the forces of organizational scale and leverage can be networked – connected – with discrete centers (or hubs) for contribution to produce more rigorous solutions.

At the core of this thinking? A realization that traditional large-scale organizations (with their central thinking, hierarchical layers, and silos of functional experts) are generally ineffective when dealing with complex situations. Quite literally, they are too rigid. Without the ability to adapt to new variables or to coordinate across silos, grid-lock ensues. And complex social ecosystems are impacted, since “sending in experts” is how we tend to attack these issues. On the list? The well known structural challenges in energy, sustainable food and water sources, public education and healthcare.

What’s needed is an outright paradigm shift in problem solving models that are fundamentally more interactive and cross-functional. And focusing on complexity theory is key, because it begins to unlock some new doors. For one, there must be an organic aspect that allows solution teams to learn, self-correct and grow. And to meet the requirement of connecting people more dynamically, Social Media is the ideal technology. Some examples? Think about experts engaged in live chat. Acceleration of thought synergies. Tools to merge and re-mix knowledge. Ability to leverage and extend dynamic repositories.

With focus and coordination, we can work to find the elusive “sweet spot”.

In terms of naming and framing the problem, the above research makes significant strides. The next step is critical as well, and is just as exciting: in pockets across the internet, the new collaboration is already starting to appear.

Are you seeing it too? Let’s talk, I’ll show you where and how.

Organization Change: the ‘Organic’ POV

In times of dramatic change and crisis, executives (perhaps in line with human nature) revert to known formulas .. tapping structured, controlled and seemingly “safe “solutions. In Stephen Billing’s blog “Organizational Change is Not a Relay Race” he warns against relying on formal & rigid decision processes in times of crisis. Most dangerous: hand-offs between executives, consultants and HR .. passing the baton of responsibility from runner to runner.

We’ve all seen this happen. If you’re leading an organization in crisis, it is no time for hand-offs. It introduces delay, dilutes both message content and ‘signal strength’ .. and in the end, serves to diminish trust. But to really get at the core of the disconnect, we need to understand how change works.

I frame the issue as two contrasting views: the organization as machine vs. the organization as living organism.

In the latter view, change brings in an organic element. Transformations take place in every cell.  Granted, there are communication and control processes present in the organism too; each cell plays a vital role, as in a machine.  But in a living organism, just as within an organization, success (survival and adaptation) depend on symbiotic adjustments from every minute part of the system.

No doubt the industrial age has influenced the thinking of executive management.  But we must now choose our relational paradigms more carefully, especially at times of crisis when time is short and emotions are running high.

Machines excel at repetition. Living organisms excel at change.

Take a good look, there’s plenty of change and crisis to go around.  What kind of organization do you need to be?

Downside of Scale in the 21st-Century (re: Agility)

Recently came across a good post by Oliver Marks (@OliverMarks) covering a brief CNBC interview w/ Deloitte’s John Hagel.  The topic was the cummulative economic impact of large scale operations, and the ever-declining Return on Assets (ROA) across industry over the last 40 years.  The conclusion derives from basic business economics.  As assets get ever larger, returns from those assets, ROA, will trend to zero. Incremental productivity gains lose their impact.

The implications of this are important.

As you watch the Hagel video, you’ll hear him say “no back to normal”.  Complacency, especially  in corporate America, seems to have clouded our long-term economic view.  As Hagel alludes, executives seem to be waiting for the next economic cycle to bring us back to the good old days.  But when we continually build ever larger companies with ever more complex infrastructures and systems, we lose our ability to get meaningful value for that investment. 

The operational implication is even more problematic.  Due to scale, it becomes increasingly difficult to make strategic or even tactical adjustments.  Progress becomes gridlocked.  We lose our ability to compete. 

Look around your own company.  Are you seeing this happen? 

The flattened knowledge economy drastically cuts transaction costs, bringing global and niche competition head to head with the traditional market giants.  Where scale once provided muscle to fend off competition, that muscle has effectively turned to fat.  The extra weight prevents the agility needed to adapt to new demands, upstart competition, and wholly transformed markets. 

How can we hope to make money, when the answer to every problem is to buy and/or build more infrastructure?  Large scale operations require maintenance and up-keep, care and feeding.  It’s a problem that doesn’t go away.  A viscious circle.

It’s no longer enough (if it ever really was) to try to ‘think entrepreneurial”.  Small and nimble companies are developing a clear advantage in the new global marketplace. They lack the bureaucracy that blocks collaboration, that shields executives from shifting market paradigms, that strands innovators in organizational silos.

If your company is large and getting larger, it won’t be a question of competition.   The more important question:  will you be lean and agile enough to survive?