Cense

Innovation to Impact

Forecasting

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You might not have a crystal ball, but you can still envision the near-future by using a simple strategy called forecasting to plot your strategy for the coming months. Here is how.

Fundamentals

A forecast is a data-driven prediction of possible outcomes that can be used to generate scenarios. The first item required is data. This can be qualitative, quantitative, or mixed and from primary or secondary sources. Most often, forecasts are a combination of these.

Checklists have been found to be useful tools to help organize data that contribute to forecasts. Pull together those sources you have and then organize them in a manner that allows you to build a narrative — a story — of what has happened to allow you to better anticipate what might happen.

Forecasts work when there is some expectation of a linear progression from time to time (with some variation). Time series data — data gathered on the same topic/issue/item multiple times over in succession — is among the most popular sources of data. This will allow you to see patterns and spot trends that lead you to now.

Add Imagination

Once you’ve developed a model of the present situation, the next stage is to imagine what might happen in the near future. Forecasts are generally useful for predicting near-term (e.g., 3-, 6-, or 12-months) outcomes and are less useful for longer-term assessments.

Next match data from other sources — social trends, government policy documents, census data — to create scenarios. For example, seasonal trends can change the near term. ‘Seasons’ like ‘back-to-school’, holidays, flu trends, weather changes can all affect how present data can mislead us for future activities. The COVID-19 pandemic provided an example of the various ways in which an economy can re-open, a healthcare system can respond, and what ‘back-to-school’ looks like.

From these data points, work together as a team (this is always better done in groups because different people will see data differently) we can start to envision possible futures and outcomes.

Look for amplifiers and dampeners. What things might make an existing trend more pronounced and what might dampen that trend, or extinguish it altogether. In discussion as a group you can

Structuring Forecasts: Tips & Tricks

Begin your group work together with a few simple ‘rules’ to guide your discussion. Start with limiting any feedback or critique of ideas at the start. You want to explore why something could happen, not assess the likelihood of such activities at first. This opens our minds up to unlikely scenarios.

It’s helpful to have someone on the team who can play the role of the ‘black hat‘ – the person whose role is to illustrate why something won’t work. Edward DeBono’s ‘thinking style’ roles can be useful here in helping us structure a way to look at the data and ideas from different points of view. Building on these different perspectives, it’s important to build a variety of scenarios and attach a level of anticipated likelhood to them. (e.g., high, medium, or low) and timing (e.g., imminent, soon, long-term, etc..)

Build out as many scenarios as the data suggests might be useful. This is often three to five, but rarely nine or ten.

From these scenarios, ‘walk them back’ to the present using an approach of asking “what happened just before X” and repeating that of each answer until you find yourself at the present. This allows you to start building pathways of potential causality.

While it may be that none of the scenarios come into reality, there are likely to be pathways that resemble them. When you find these, your team can use those to examine the assumptions that you hold with each one of them and use that to develop a strategy around them to better increase your anticipatory awareness and adaptive capacity to learn and act.

Taken together, this method can help you to see what might be coming and plan accordingly. It is a powerful means to explore near futures and design your organization to be better suited to living in them rather than having to play catch-up.

To go even deeper, the Future Today Institute has developed this useful ‘Funnel’ model to guide forecasting that might be useful to you as well.

FTI-Funnel ToolDownload

If you want to develop forecasts, contact us. We can help you see what might be coming and design your team to better meet it.

Innovation Design Quality Control

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You want and need help in transforming your organization or business line and are seeking a consultant to help you. What should you look for? Let’s look at questions and issues you may want to consider when starting an innovation journey.

We break it down into three (plus) areas: Design research and foresight, service development, and evaluation.

Design Research

Design research is about exploring the problem or circumstance that you’re looking to intervene in through introducing a new product, service offering, or policy (which we’ll refer to as an innovation).

Design research is much more than ‘doing your homework’ and is meant to work with any marketing and financial studies you may have done. Design research is about exploring your end-user(s) — both identified and potential additional users. Responsible design research is also about looking at who else your innovation affects.

It will incorporate systems thinking into the process by considering the various ways in which your innovation affects and is affected by the various interconnections around it. For example, your service might be tied to other things (e.g., supply chain, regulatory issues, community norms) and good design research will help articulate these and allow you to map and model systems using visual tools.

Your innovation design team should have skills in design and research and understand a variety of methods and approaches such as quantitative analysis, qualitative data collection, sensemaking (for innovations dealing with complex situations), and behavioural science. The last point — behavioural science – is what allows you to understand what, why, and how an individual or group will choose to engage with your innovation and serves as a foundation for the next stage of work: service development.

But first, let’s go a little ahead into the future to look at the other part of design research: foresight.

Foresight

Strategic foresight is an approach to research that looks at the trends and drivers that influence specific domains of interest like your market, community, or social life as a whole. It draws on a variety of data sources such as published reports, publicly available (or privately held — if you have access) databases, as well as a series of exercises and activities that allow you and other stakeholders to envision what possible futures might look like.

The UK Social innovation agency Nesta has a useful, accessible primer on some of the methods that are used to envision futures.

Future-thinking is important because your innovation will always be applied to tomorrow, not today. Sustainable, effective innovations are those that meet emerging needs not just present ones. Foresight considers how and why things might change and, when combined with strategy and behavioural science, allows you to shape the design of your innovation to better anticipate and (hopefully) meet those changes as they emerge.

Service Development

Service development can include everything from exploring the physical space where your innovation will be deployed to undertaking usability research on digital platforms. The range of practices associated with what is more commonly called service design are many and when enlisting support to design your innovation it’s critical to ensure you have the right talent.

Service design often seeks to develop models of your intended users based on the design research you’ve undertaken. This can result in tools such as personas that provide evidence-informed caricatures of your users that you can use to develop and test scenarios.

Service design methods incorporate visual thinking methods and tools and design thinking by exploring the research, developing ideas, testing and trying these ideas out in ways that inform strategy, and then deploying them into the world. Having a design team with skills in design methods, facilitation, and visual presentation will make this much easier.

Visuals can include everything from simple (but illustrative) maps like the image above to more sophisticated visual models, ‘gigamaps‘, and storyboards.

Evaluation

Last and certainly not least is evaluation. It’s one thing to design an innovation, it’s another to know whether it does what you think it does. Evaluation allows us to assess what kind of impact our innovation has on the world, what processes lead to that impact, and what aspects of our service, product, or policy are most likely influencing this impact.

It is through evaluation of our innovation that we are better able to fine-tune, amplify, or retract our offering to ensure it’s creating the most benefit and not doing harm. Evaluation also allows us to understand what hidden value our innovation might be offering, to articulate your return on investment (ROI), and to widen your perception of what your innovation does and could do.

Bringing in design firms that do not build in professional-grade evaluation to the project is like doing half the work. What good is your new product or service if you have little idea how or whether it works in the real world over time?

These are some of the things that anyone looking to develop an innovation in-house or with a consultant team needs to consider. We have a lot of resources on our learning page on some of these methods and tools as well as overall approaches to supporting groups in asking better questions prior to engaging a contractor.

This is what we do. If you want help with any of this and doing good, quality service design, design research, evaluation and foresight, please reach out and contact us. We’d love to hear from you.

What Went Wrong? A Question For Futures Insight

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In five years, what did we get wrong?

This simple question can be a powerful vehicle for understanding the way in which things in the future might — and might not — unfold. Foresight is a complicated process as we are asking to see into a horizon that hasn’t yet taken place. Rather than predict the future, strategic foresight is about anticipating possible futures.

What this means is that it is possible — indeed, quite likely — that what we think will happen won’t come to pass as we thought. However, we might also foresee certain things that allow us to prepare. For example, we might be correct to see the growing trend toward working remotely while being incorrect about the reasons that drive it and the timing (e.g., pandemic).

All of these are based on assumptions about what we anticipate happening.

Asking the question about “what didn’t go right” or “what did we miss?” begins the process of allowing us to ask more detailed questions about our assumptions. It can allow us to identify where the areas of friction might be, the critical and less critical uncertainties about our models of the world lie, and what might have been missed as we envisioned the connection between now and the future.

Asking what we might achieve is useful. Asking what might go wrong is prudent. Ask them both.

The Amazing Spidergram

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Illustrating action points within a complex system challenges evaluation users. Time to call on your friendly neighbourhood spidergram for help.

Visualizing complex systems is a challenge within strategy, foresight, and evaluation because each component of the system is interconnected with others. Influence on one of these is likely to influence others.

From an action standpoint, it’s easier to focus on one or two small parts of the system than tackle the entire system all at once. How do we reconcile this and provide a means to see the parts of the system without being reductionistic and neglecting the relationship with the whole?

One answer is: look to the spiderweb.

A spiderweb is a good entry-level metaphor for helping people see places they can take action within a system by creating distinctions between the parts (nodes, intersections) and the whole (branches, webs). There are two related, but different spiderweb models worth noting.

Spider Diagrams / Mindmaps

Spider diagrams (or spidergrams or mindmaps) are ways to connect ideas together through the branch-and-thread model akin to a spider’s web (hence the name). These are often called mindmaps and have been shown to facilitate learning about complex topics.

They enable the development of relationships between ideas and possible causal or associative pathways between ideas, concepts, or other data- or evidence-informed concepts. They also enable us to cluster related concepts together to identify sub-systems that may be more amenable to our intervention within the larger whole.

Spidergrams / Radar Diagrams

The other spider-related metaphor that is available to innovators and evaluators is the spidergram, sometimes called a Radar Chart or Spider Chart. These allow for the display of data collected along a scale presented alongside others that use a similar proportioned scale.

This hub-and-spoke model of data allows users to see a variety of performance indicators presented along a similar set of axes related to a common goal.

What this allows for is a view of performance across a variety of metrics simultaneously and can recognize how we make progress on one area often at the expense of another. Strategically, it can enable an organization to balance its actions and foci across a variety of key indicators at the same time.

This can be used with quantitative data such as the financial data above or social data, too.

Spidergrams/charts can also overlay data within the same domain (see example) providing even more depth into recurring or separated data points within the same topic or subsystem.

The web of engagement

What makes these tools powerful is that they display a lot of data at the same time in a manner that can facilitate engagement with a group of people tasked with making decisions. Visualizing data or systems brings the benefit of literally getting people’s focus on the same page.

People around a table can then literally point to the areas they are interested in, concerned with, do not understand, or wish to explore assumptions about.

Complex systems introduce a lot of data and a lot of confusion. Sensemaking through the use of visuals and the discussion that they encourage is one of the ways to reduce confusion and get more from your data to make better decisions.

If you’re stuck in the web of data and complexity, call on your friendly neighbourhood spidergram.

Want to learn more about how this can assist your innovation efforts? Contact us and we’ll gladly swing over and help (without the costume).

Photo by Jean-Philippe Delberghe on Unsplash. Spidergram by