Collaborative foresight – two proven models to get people involved
One of the most common questions we hear from foresight managers looking to develop foresight in their company is the following: How do I involve more people in our foresight work?
These companies usually have a dedicated person or team scouting future trends and making sense of future developments in their industry. However, they’re struggling to spread the efforts past the core foresight team – even if they already know they’d be better off with more people involved.
If this sounds familiar to you, there are clear measures you can take. Getting people involved in foresight rarely happens by accident but as the result of developing a specific organizational structure that favors collaborative foresight work.
What is collaborative foresight?
Collaborative foresight is the practice of involving a large number of people in an organization’s foresight work.
In collaborative foresight, you might have hundreds or even thousands of employees looking for interesting weak signals and emerging trends as well as elaborating on their potential impacts. By doing so, they support your organization’s overall foresight work.
Only a fraction of these people are trained in foresight, let alone consider futures work their primary job. Instead, these people participate in foresight along with their main duties and responsibilities, which can be anything from sales to service design to customer support.
The alternative to collaborative foresight is having only a small number of people to collect signals and make sense of them, such as a team of corporate futurists dedicated to foresight. Actually, such a team is needed to take foresight collaborative in the wider sense, too.
Benefits of collaborative foresight
The benefits of crowdsourcing your foresight work are numerous. the most obvious one having to do with getting more eyes and ears around the organization.
When people with different roles and responsibilities take part in your foresight process, you will automatically get a more diverse collection of ideas, perceptions, and observations.
This will help you build a richer picture of changes taking place in your operating environment, and better serve strategy, R&D, and innovation at your company.
The perspectives of, say, someone working in product development or customer service may be vastly different, but just as valuable for foresight.
A lesser spoken benefit of collaborative foresight has to do with using the acquired insights. The more people are involved in gathering signals, the larger a crowd has a touchpoint to the foresight work you do at your organization.
What follows is that these people are more likely to use the fruits of foresight work in their planning and decision-making. Away goes the futurists’ pain of doing lots of work for nothing.
Thus, by embracing collaboration in your foresight process you might find that you get inputs that are of higher diversity, but you might also experience a surge in overall interest towards future topics at your company.
What’s not to like?
The two most common models to make collaborative foresight work
Involving people in foresight work doesn’t happen by accident. Getting people to participate is a challenge similar to any organizational change where you want to get people to work towards a common goal.
From what we’ve seen, most organizations who succeed at collaborative foresight, employ one of two organizational models to make it happen: the centrally-led model or the centrally-inspired model for foresight.
Model 1: The centrally-led model for collaborative foresight
In the centrally-led model, foresight work revolves around a central team of foresight or innovation professionals.
The central team tracks and analyzes domains the company holds valuable as part of their daily work, such as new technologies or customer behavior. In many cases, the team's input could better be described as foresight for innovation rather than strategic foresight.
The central team is aided by a larger number of people who would be primarily expected to contribute by bringing in new inputs and opinions related to a certain pre-named topic. For example, such a setup might be implemented to run global scouting over a specific technology domain.
It is then up to the central team members to ultimately analyze the gathered information, and to connect the dots between findings collected by the organization.
New information and findings can then be fed directly to people, projects, and further teams who already work with development related to the specific domain in question. Thus, crowdsourced inputs and insights get directly where they are needed for taking action: into the daily work and decision-making of R&D and innovation, for example.
The companies that successfully implement this model often seem to have a somewhat hierarchical structure and culture. A foresight model that is similarly structured is just natural to them.
Model 2: The centrally-inspired model for collaborative foresight
In the centrally-inspired model there’s also a central team, typically consisting of foresight professionals. However, their role is more to facilitate than to control.
Instead of running the entire sense-making process, the foresight professionals may only summarize some of the fundamentals. A lot more of ad-hoc and domain-specific interpretations are being continuously made by other individuals and teams working with strategy, R&D, innovation, road mapping, branding, or something else altogether.
In the process, ultimately everybody ends up contributing to foresight: taking initial summary-level inputs and enriching this information for their own purposes. By doing so, they not only help themselves in their daily tasks but automatically contribute back to the higher-level summary understanding, too.
Thus, the foresight professionals may again facilitate connecting new findings with the larger pool of futures knowledge for the whole organization to use. Not a vicious cycle but a highly valuable loop for everyone!
This type of collaborative foresight work seems to fit best in organizations with a transparent and flat working culture, with distributed decision-making authority.
5 requirements for collaborative foresight
Regardless of your optimal model, organizations going towards collaborative foresight face a standard set of challenges:
There are at least these four basic requirements you simply must meet in order to succeed:
Requirement #1: Having a continuous process
Going collaborative practically means going continuous with your foresight work. Building a process, engaging the organization, getting valuable inputs, and seeing actual business benefits do not happen overnight. You rarely are able to gain the best value out of such collaboration if you only run standalone foresight projects.
Requirement #2: Having someone in charge
Someone has to be in charge of your continuous foresight process, usually a foresight, strategy, or innovation manager. This person should not only carry the flag for foresight but also actively take part in the daily foresight work – someone who knows the true nature and details of this work. Sad to say, but we can only wish you good luck if no one has true ownership of such a continuous process at your company.
Requirement #3: Using the acquired insights
You have to have a use case for foresight. If people don’t see a point in the work they do, it’s pretty tough getting them involved. The gathered inputs need to be used where they are supposed to be used: typically your strategy updates, R&D projects, innovation endeavors.
Requirement #4: Having a shared repository
You have to have a way to collect inputs from people, organize those inputs, and make sense of them collaboratively.
Spreadsheets and presentation software fall short when hundreds of people are involved. This is also why most companies start looking for a purpose-built tool for foresight early on in the process of aiming to go truly collaborative.
Collecting findings in spreadsheets or shared drives simply won’t do when you’re trying to expand the efforts past a core team of foresight professionals. Making sense of the findings is even harder without a purpose-built tool for collaborative foresight, like FIBRES.
Making foresight collaborative is a tricky task. Since you read this far we assume the following: you already know that wisdom lives in the masses, and want to make use of that knowledge. That’s a great starting point.
Picture source: Martin Reisch, Unsplash.
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