The Execution Gap : Bottom Up and Top Down is a False Paradigm

Over the last 16 years I have spent a lot of time with people who have committed their lives toward social change.  Historically these people were architects in rust-belt cities and then aid workers in refugee camps.  Later I worked with lawyers and government officials in government offices. Today I continue the same work, but work with electrical engineers and data scientists. As I continue to engage the same kinds problems but across wildly different disciplines, it has become clear that many of the deeply entrenched beliefs of one group are completely foreign or irrelevant to another. 

For most of the 100+ year history of urban planning, the cannon of planning theory describes top-down vs bottom-up processes. Various terms are used to describe this such as "centralized vs decentralized" or "rationalist and grass roots." A few other sub-models of planning have emerged, such as Advocacy Planning and Participatory Action models. What has been less dominant is a recognition that our technologies are a big part of the planning process. Consideration of the technology as an equal force throughout the process opens many new directions for exploration. More importantly, technologies such as machine learning, when applied to dormant low-tech economic sectors, are far more powerful change agents than people. 

A critical question that has been consistently absent from planning theory concerns use of the appropriate technology relative to the complexity of the problem and idea. Why spend a million dollars, engage hundreds of people, conduct dozens of technical studies, and then document a robust vision for the future in only a book or a website? How do these technologies advance the implementation of the vision? These technologies increase risk because the translation of a complex vision from written text into built form or economic process is a massive leap.

There are other ways of course. Through small scale pilots, rapid trials, online Wikis, collaborative mapping sessions, partnerships with local technology companies (big and small), one can always find a way to create new experiences.  A classic example is from the Czech Republic; after the fall of communism a process was needed to rapidly educate the public on the history of their nation which had been suppressed under totalitarian rule. Rather than merely release a book, the city of Prague presented a living timeline of Czech history. Maps, photos, documents, and didactic panels lined the main streets so that citizens can walk through the history of their nation and learn how one era informed the next.  Woven into the architecture, the city itself functioned as the core technological platform to engage citizens and enhance thinking on the needs and futures of the nation-state.  As a robust experience, it also created stakeholder buy-in for the next logical step.

Design as a Process of Optimization

To develop a concept and not implement as part of the ideation process is high risk. Working at the EPA, for example, I find it very hard to convince leadership and scientists that a particular organizational or technical change is possible. For many decades, people have made suggestions and introduced new visions, but rarely have these been successful.  In contrast, I find a way to rapidly prototype every idea. Should we create a new division? Lets get some people to volunteer and test how this division might operate. Should we purchase an enterprise solution?  Lets get the 30 day free trial and see how we might need to also change if we buy it. Rapid prototyping any kind of solution will always give more information and reduce risk.

Planning and Design as Synthetic Futures

As Herbert Simon pointed out, the scientific method is an excellent way to understand the natural world that is around us, yet when faced with creating something new in the world - and thus artificial - we turn to design. The more we understand the design process, and how it is similar or different from the scientific method, the better we can design and introduce new things into the the world.

The role of design as an additional demand - to not only stretch and reveal what is possible in the future - but to help us get to what is preferable future. Empowered with the ability to make something new, design is a means to consider multiple future realities, and equipped with the ability to implement them, each idea on a  possible future exists in a state between idea and reality. Consequently, mindfully experimenting with a material process to test implementation measures and reduce the risk, one develop synthetic futures and transform them into new realities.

Impact Any Problem Like a Designer

This morning I was asked if I approach design management (the emergent term for the application of design to organizations to engage complex problems) as an architect or as a communications designer. It was a little hard to answer is because the answer squarely falls into the domain of neither and both. While I believe whole heartedly in a non-disciplinary approach to design, if it is necessary to specify a form of design practice and theory, it is important to recognize that these fields exist on a gradient. Over the last 15 years of research and practice in design and urban planning, I have developed a systematic approach to structure problems and interventions across this gradient and have developed a simplified conceptual model in response to demands.

Illustrated above, I look at all problems as fitting somewhere within the above structure - wherein a problem might be defined by thought and language (sign), by tangible products and interfaces (object), by spatial context (environment) or by large scale invisible systems such as formal law and culture (culture can be considered another expression of law).  So for example, if you are attempting to solve a big problem like poverty, it exists in all sections because poverty is contextual, has artifacts, and there are many existing specific words and images that are used to communicate the idea of poverty. Whereas a problem that is very well defined, like the design of a toaster, will most likely sit squarely in the domain of objects.

At Carnegie Mellon University, I was introduced to Richard Buchanon's theory on the Four Orders of Design, which was very similar to my own model, but we maintain very different objectives and I found his model is harder to operationalize.  Buchanon does have other variations,  and additional work on operationalization has been pursued by Golsby-Smith.  There are additional models out there and while I find it validating and interesting to look at their models, my own approach emerged from the field. It is not informed by these other works, I point them out merely because they exist, and I find these other frameworks are missing a critical component, the people.

Within my framework, the most important characteristic is the recognition of dispositions held by people who occupy each conceptual frame. Without people - there is no framework.  There are no objects or contexts without people - there is also no design or strategy - people are the scaffolding of everything.  Consequently, I do not consider this framework as universal, but is thus far, a model that has arisen organically through various design interactions with people, technologies, and spaces.

Yet people are highly complex. I cannot manage to engage all people in every project on every level, and therefore I have created over the years a simple heuristic to note critical attributes of people within a project which will determine the project outcome.  All stakeholders in a project have, want, or lack resources (for their interest or mine), they likewise all hold a unique vision for their lives and the project outcome, along with specific objectives, beliefs, expectations, and baggage from prior experiences. I cannot juggle all these balls for every person at one time, but I do attempt to establish an sense of organizational structure between different actors and their unique attributes.

The Difference of Design in Organizations
Lets imagine an international company hires me with a big problem phrased as a simple request, "how do we become the leader in our industry?"  When companies have approached me before, they have already conducted many of the preliminary SWOT assessments and strategy planning sessions. Perhaps they have utilized a more traditional business management strategy, but found the problem too sprawling to meet the discrete demands... for example, it is impossible to identify and validate appropriate benchmarks if the problem itself is poorly defined. Driven by market research, they believe they should offer the same technologies or assets as their competitors. Yet it makes no logical sense to mirror competitor if you want to be the industry leader. It is important to do something new - but what and how?

Using the Framework to Generate the Big Picture
As a complex problem, I will work at all levels of the framework. In the case of robotics, I will take this problem and build a detailed understanding of their robots (the object).  I will look at all documentation, branding, communications, and language used in relation to their robots (sign). I will go into the facilities where the robots are used and spend time understanding the relationship between the robots and the Environment. I will also look at sales trends, labor laws, social movements, international trade agreements, and latent technology trends (perhaps also concerning language, objects, environments) to capture a big picture understanding of the robots in relation to some invisible systems that shape the future of the company.

Digging Deep into the Social Terrain
In this process, however, I have left out the most important component: the people.  Who is talking about the robots? Who is listening? Where are they? When customers purchase the robots, what are they saying? How do they represent their needs?  In the environmental context, who works with the robots and how?  How do those people exchange information about the robot in that context?  More importantly, how does the robot relate (or not) to the resources, objectives, histories and so on, of every person at every level?  If I go to the capital and talk to the people shaping policies that inform the outcome of robotics markets - congressmen and lobbyists for example - what can I learn from them?

Insight by Emergence
Working through this framework to understand the problem is only the first step. Yet the more I can build knowledge at each level of interaction, the more flexibility I have to craft and test interventions. Perhaps the corporate strategy is something simple like a branding campaign or promoting a national policy - yet perhaps it also requires manipulation to the technology to better facilitate how other companies train their employees? If that is the case, what language should be used and by what device should it be communicated? By means of this approach, the key insights and opportunities will emerge and do not need to be invented - nor can they be predicted.

Impact by Design
The final outcome of such a problem will rarely consist of one single action.  Rather, it will require many small interventions choreographed across the system.  Some interventions are more important than others. To describe the processes on design for wicked problems deserves more attention than I can provide right, yet with this framework, one is equipped to better understand any kind of problem to get going in the right direction by doing the following:

1. Get away from the tunnel vision of a personal discipline or expertise
2. Build an integrated and fluid systems understanding of a problem 
3. Identify many points of intervention across scale/scope and points of view
4. Leverage the most powerful yet high-risk asset of any problem, the people.
5. Uncover new opportunities for exploration and testing