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
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.
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?