Cense Ltd.

Inspiration, Innovation and Impact

Innovation Like An Epidemiologist

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What if innovation was like epidemiology? What if we wanted to understand the source, scope, scale, and spread of an idea or product?

That’s one way that we think about the innovation process.

Innovation – like a virus — is similar to infectious disease epidemiology. Both of these areas look at the development of something, its effects, its spread, and how it scales over time. Both innovation and epidemiology require evaluation as well.

Viral Innovation

The parallels between infectious disease epidemiology and innovation are many. The first of these parallels is between a virus and an innovation.

A virus develops and mutates as it has more exposure to hosts. A virus ‘learns’ from what it does and adapts to fit a changing context. Innovation does the same thing only with an idea, product, or service. For innovators, the aim is for healthy development and the creation and distribution of the product or service. This is what research and development and marketing is all about.

Innovation and epidemiology are also both interested in the spread and scale of things. If an innovation works well in a context we might want it to spread to other contexts. Innovators often want their products to scale as far and as wide as possible. Sometimes innovations scale and sometimes they don’t.

The way we know this is through conducting detailed, systematic monitoring and evaluation.

Epidemiology, like innovation, is driven by evidence from the laboratory and the real world together.

Stages of Development

At Cense, we also look to another parallel between the two areas: research and development.

Innovation develops in four stages that are similar to phases of research trials.

The role of design and evaluation is different for each stage. At Stages 1 and 2 the emphasis is on working with innovators to align their intentions with their design to explore what it (the innovation) does and how it does it. This is where design thinking and strategy are most prominent.

At Stages 3 and 4, the aim is to build an evidence base and strategy to spread and scale the innovation. At these stages, the focus is on marketing, distribution, and amplification. Evaluation in these stages focuses on the larger impact and the means by which the innovation is implemented and adopted for use across contexts.

Like an epidemiologist, its important to collect data to support moving the innovation from each stage. It’s also important to explore what kind of effects — positive and harmful – are generated at each stage.

At Cense, we work with our clients to design the right evaluation and strategy for each stage of development. There are no ‘one-size fits all’ approaches to innovation. Much like with a virus, an innovator must know what their innovation does and what will change at each stage and scale of its development.

What is key is designing data collection and strategy that is fit for purpose.

Viruses aim to spread and survive just like innovations. By thinking like an epidemiologist you can help your innovation to survive and thrive like the best kind of virus.

Photo by Bill Oxford on Unsplash

Surfacing Invisible Rules

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What often can hold our change initiatives back are mental models about how or why something happens. Historically, many innovations and discoveries were held back or failed outright because people were unable to see or believe what was in front of them. By asking a set of questions at the outset and throughout your project you can avoid many mishaps.

The scene below from Men In Black illustrates what happens when our mental models about the world get upended and ask a simple question about what we know*. (*Just prior to this scene, Will Smith’s character confronts alien life forms for the first time — something that Tommy Lee Jones’ character already knows and lives with.)

One way to surface these hidden assumptions is through an exercise we might call ‘Invisible Rules‘. This three-part exercise can help you surface and uncover those ‘hidden’ rules we live by that might be holding us back from what we are seeking to change.

The exercise involves asking a series of questions in three stages:

1. Assumptions

  • What assumptions am I operating under?
    • Consider things like people (populations, characteristics, traits, knowledge, skills, preferences), time and timing, the likelihood of success, resources required.
  • How did these assumptions come about?
    • Is the evidence based on fact or folk knowledge?
  • What evidence is there to support that these assumptions are true?
    • Is this evidence still valid? (e.g., is it based on a historical or current position? Has something changed considerably since the evidence was first generated to prompt questions about its relevance?)

2. Design

With these answers, we move to a new set of questions tied to the design of your innovation (project, product, service, etc..)

  • Can I modify any part of the design (e.g., remove, reduce, amplify, or replace) that might make it better?
  • What can I learn (borrow, modify, adapt) from other designs addressing similar issues?

3. Future-casting

Lastly, it is useful to ask yourself three “How might” questions about your innovation.

  • How might this project fail?
    • For whom? Under what conditions?
  • How might we learn about what we’re doing while we’re doing it?
    • The evaluation and reflection metrics, measures, and processes in place to learn what works and doesn’t as you go.
  • How might things change beyond our control?
    • Possible surprises that might sidetrack your plans (e.g., pandemic, government change, policy change).

These simple set of questions can produce an enormous amount of data for you and your team. In just a few hours you might save years of pain and problems and see beyond the fence into the pool of opportunity beyond.

Want help in seeing things differently and asking better questions in your work? There are some simple steps that can help your team see things that others can’t. Contact us. This is what we do.

we’d be happy to help.

Innovation Value Hidden in Plain Sight

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Evaluation is more than just a means to measure impact; it reveals hidden value within the innovation process and destination.

Evaluation is often considered to be something that is done to or of something when it is completed. This is the innovation’s destination. For some, evaluation is about understanding the process — what happens along the way to developing a product. This is innovation’s journey.

But what if there were products (and outcomes) in the journey? This is where evaluation can provide deep insight into the true value of innovation.

The reasons to consider bringing evaluation more fulsomely into the entire innovation process from end-to-end are many.

  1. It increases your organization’s mindfulness about what it does, what it is doing, and what it seeks to achieve.
  2. Through paying attention to the process more systematically and with discipline (which is what evaluation is all about) it’s easier to spot patterns in the use, development, or understanding of your product by different audiences involved in the innovation process. This allows you to better see different perspectives.
  3. It documents the small accomplishments that are part of a larger whole by recognizing the work that is done in pursuit of innovation (and not just the final product). Doing this ‘shows the work’ of innovation, rather than leaving it to a final, finished product to do that.
  4. It engages your innovation team by showing progress measurably and keeping them engaged, particularly when the development cycle might take a long time and have periods of uncertainty associated with it.

Pulled together, evaluation can also tell the story of your innovation. When we consider that upwards of 80 percent of innovation efforts yield no viable product, it is easy to dismiss the work that goes into it as inefficient, wasteful or having low value. Evaluation captures the value that is in the innovation process, documents it, and provides insight to help drive the direction of innovation.

One final value point is that many solutions might exist within that ‘80%’ failure space, but haven’t been fully articulated or for which the value isn’t apparent until later. Often we see a design process yield many possible directions for action that get prototyped only to see that the best option is in one of the un-chosen options afterward.

This happens not by chance, but through designing an evaluation system to accompany and even integrate with your innovation development process. By adding evaluation into the process throughout, you’ll find much more value in all of the work that you’re doing.

It’s all hidden in plain sight (if you know how and where to look).

Interested in learning more? Contact us and we can show you how to develop the systems to get more value from your innovation efforts.

Photo by Ewan Robertson on Unsplash



Why human systems innovation is social innovation

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Is it social?
An innovation may be more social than you think

Social innovation is described as a specific type of innovation that meets social goals. The Stanford Graduate School of Business defines social innovation this way:

A social innovation is a novel solution to a social problem that is more effective, efficient, sustainable, or just than current solutions. The value created accrues primarily to society rather than to private individuals.

We like this particular definition largely because it includes the role of social justice into the definition along with an emphasis on social impact. Social innovation is becoming more than a niche as human systems are becoming more entwined through collaborations, partnership, strategic alliances and the mass of interconnections of people from around the world. In an increasingly globalized world made possible through transnational trade, global policy, mass human migration and the digital networks of knowledge and media created through the Internet the process and outcome of innovation is increasingly social.

The reasons for this is that there is no longer a standard client or patient or person or customer or…

The diversity in human systems means that it’s increasingly problematic to apply ‘standard models’ to populations. That’s not to say that we can’t make assumptions or that certain generalizations don’t work at all, but they aren’t the same as they once were. What we need to do is design for each condition and setting in which we seek change.

This process of design, when done well, includes the involvement of those who are the beneficiaries or stakeholders in the innovation. By excluding these relevant stakeholders there is a genuine risk of designing something that might either miss something critical or worse, unintentionally create something that exacerbates social problems rather than addresses them in a satisfactory manner. For that reason our approach to innovation design is one that assumes that nearly any human system intervention is a social innovation on some level.

By approaching a problem context as a social innovation we bring together not only the design considerations, but also the social ethics and values associated with social innovation. It also ensures that innovations are made social and translated beyond the originators of the innovation into the wider world, thus increasing exposure and improving access and overall knowledge translation.

Next time you approach an innovation problem ask yourself if what you’re doing is social or not. You might be surprised where it lands you.

And if you need help with that, we’d be happy to help.