Why does most of what we read about innovation resemble very little of what our work life actually looks like?
It is rare to find a profile of an innovation initiative that speaks to the everyday experiences of business, government, healthcare, or non-profit life. Instead, we read cases where there was leadership, time, focus, drive and commitment that perseveres through challenges and that comes together to bring an idea to light. Of course, there are barriers to overcome in these stories, but they are overcome and the characters live happily ever after with year-over-year growth or a product that transforms the market.
These stories might be inspiring to a few, but they hardly reflect what most everyday innovation looks like.
It might explain why so many struggle with innovation practice in their work and why innovation activities continue to show little growth or depth at a time when they are highly needed.
Best Practices or Real Practice?
Much of what passes as corporate innovation best practice is predicated on a model of scaled operations using a standard model. In plain speak: it’s about standardization. That’s a reasonable way to go when you have a closed system where the influence of the organization on the activities is high, the degree of variation and randomness in the system is low, and there is an ability to use past practice to predict future outcomes with the right data. Innovation here can be done ‘at a distance’ using plans, reports, and data from the field with limited information about the context required to understand the systems themselves. Innovation here can be done more easily using models, forecasts, and small data-intensive experiments.
If human agency is involved, this changes the calculus a great deal. If these humans act independently and interdependently with influence from others then the same practices described above won’t work. They will make choices that will differ based on a variety of factors (other people, environment, situation, preference, mood, psychological safety, choice of resources) that will create a context. Context matters greatly and the ability to extrapolate lessons from one setting to another is reduced. These situations are often what we call complex and are immune to the rules that shape more simple arrangements.
These are open systems.
These domains can be understood by using the Cynefin Framework (below, for example) that outlines the characteristics of these kinds of situations and the type of practices that reflect each domain and system form.
Real practice is about recognizing complexity within these systems and designing for it, not ignoring it or trying to design around it.
Real Innovation Practice
What I call real practice (as opposed to best) are those based on the situations that people are more likely to be presented with and we see in everyday life. It may be emergent, but could operate in an open system with the conditions above and reflects changing conditions and realistic, practical constraints.
These are situations that feature some or all of the 7 conditions below:
- Leadership is variable. Leadership involves setting the agenda, clarifying and communicating a vision for the project (and any goals associated with it), providing necessary support to those in the organization tasked with innovating (design, research, strategy, and implementation), and maintaining the appropriate focus. Leaders that lose focus, fail to support the team, change the deliverables or terms or vision – – or fail to articulate them clearly, or those that introduce arbitrary distractions into the process are all possible.
- Followership is variable. Good leaders can’t lead unless people are willing to follow, share in leadership, and follow through. Innovation requires those involved in the innovation process to be reflective on their skillsets (knowing their strengths, weakness, and gaps as individuals and teams), willingness to learn and the ability/willingness to work constructively with others.
- Psychological safety, risk and creativity. Those involved in innovation work must feel safe to share their ideas, fears, and work through issues tied to innovation. Leaders need to allow themselves to be vulnerable and express that vulnerability in not knowing and teams need to feel safe in speaking out, challenging ideas and offering suggestions. Collectively, everyone must feel comfortable with wrestling with uncertainty and the inability to predict, control, and shape the outcomes (including the freedom to ‘fail’). Without this, ideas will be conservative, willingness to implement will be low, and fear of change will be high. Organizations need to allow themselves to be ‘fearless’.
- Limited ability to leverage resources in a timely manner. We see this often in small businesses, non-profits, and government for different reasons. Take financial resources as an example. Small businesses are often beset with issues of cash flow. Non-profits face similar issues with an extra layer of regulation (e.g., limits on what or how funds or resources are spent). Governments are affected by bureaucracies and the often poor compatibility between the perspectives of policymakers, political leaders, and those closest to the problem so that even simple decisions are made complicated, limiting the ability to flow resources from one body to another. All of these will limit what’s provided in supporting or constraining the innovation context.
- Limited perspective. Often organizations are unable to see the bigger system(s) they are acting on and with — meaning that they miss opportunities to frame the work in ways that will make a real difference and also be less susceptible to external factors that can undermine the success of the initiative. They don’t have the means or tools available to gain insight into what’s going on within their industry, neighbourhood, or even their own business. Perspective-taking is not a given for organizations, it requires attention, focus and methods.
- Timing. For any organization operating with ‘seasons’ of activity, innovation activities are often curtailed because of time, attention, and the ability to follow through and implement plans. Trying to innovate in the busy season might be necessary, but may mean an entirely different approach to managing projects, generating buy-in, and prototype/testing cycles than if done when innovation can be brought front and centre.
- Data. Are we making decisions based on ideas, hunches or real data? Do we have the data and is it enough, the right type, or accurate in a way that enables us to learn, make sense of the situation, and draw useable lessons from it? Data can come from a variety of quantitative and qualitative sources, but without good data, we create additional uncertainties to our innovation and strategy.
Each one of these issues can shape the way innovation activities are practiced or approached — if at all. As the stakes go up, trepidation comes with it.
In over a quarter century of work in innovation in human services I’ve rarely ever seen moments — never mind full projects — that didn’t have at least one of these issues present and visibly affecting the innovation process at some point. These issues are a part of the fabric of what innovation looks like. It’s why ‘innovation labs’ or ‘teams’ are usually poor examples to follow, because they are designed for contexts that rarely exist in most human systems, organizations, and contexts.
While it would be ideal to resolve each of these, real practice is about designing an innovation process that accounts for all of these as possible contributors. It’s about doing what designers know and do well: work with constraints.
So the next time you seek to innovate, ask yourself if these factors are in play and consider how to design an innovation process that recognizes them. In doing so, we shift our expectations from best practice to real practice and maybe achieve something better as a result.
If this describes your situation and you want help in designing for this real innovation practice (honestly), contact me. I can help (this is much of what I do).