How to Encourage a Culture of Experimentation Across Your Organization

Essentially, starting to experiment looks like asking a series of questions of your organization. For example, what methods of research do your teams use for consumer research, and how often, if ever? 

These questions – and, crucially, answering them honestly – will start you on your journey to becoming a truly innovative organization.

In this guide, we’re going to talk through what this means, why it matters, and how you can successfully mature in this pillar. We’ll also show you how it connects with the other five pillars in the DCI Maturity Model to help demonstrate the areas that experimentation can impact, and what can impact on your organization’s experimentation. 

Throughout we’ll be calling on the knowledge of Senior Solutions Consultant at Brandwatch, Tristan Learmonth. Tristan holds a distinction in Information Systems, and has spent his career thus far mapping out solutions on how organizations can use data and research to learn more about their customers and potential customers. 

Note: If you haven’t already, we’d encourage you to take our DCI Assessment to see where your organization stands. 

Why does experimentation matter?

“Investing in research experimentation will make your business more agile,” says Tristan. “It’ll open you up to new perspectives, and potentially allow you to acquire priceless knowledge and experience along the way.”

The point Tristan makes here about becoming more agile is often a huge draw for senior leaders and those holding the budgets, and with innovative research methods tending to be speedier than traditional methods such as focus groups and surveys, it’s a win-win situation. 

Another benefit that comes along hand-in-hand with becoming more experimental as a business is that you’re likely to become much more adaptable to change. 

Tristan explains: “A recent example to look at here is how many businesses recently had to dramatically change their business models due to the Covid-19 pandemic. Those who were already experimenting and innovating were ahead of the curve and more resilient to this change.”

When we discuss experimentation, we often also veer into the subject of digital transformation. This is because, explains Tristan, “digital transformation is a cultural change that requires organizations to continually challenge the status quo, experiment, and get comfortable with failure.”

There we have the word that many leaders balk at, and therefore don’t press ahead with experimentation boldly and without fear. Failure. To experiment, you must be open to failure.

Different types of research methods to help your business experiment effectively

Let’s briefly touch on traditional research methods, and how you can switch them up to be more experimental and innovative.

Focus groups, surveys, and market tests are proven to be extremely useful in validating theories and really drilling down into specifics.

However, they tend to be manual, slow, limited geographically, and expensive.

Bringing in new technologies and methods such as campaign performance tools, social media management tools, and digital consumer intelligence solutions means you’ve now got access to global, unprompted, scalable, cost-effective research that is done digitally and insights are often generated immediately. 

“Experimenting with these methods gives you a wider choice of research methods adapted to your business needs,” says Tristan. “Both approaches – traditional and experimental – complement each other, but you’re going to learn so much more, and become more agile, by bringing in these more experimental methods.”

Building a culture of experimentation: The four stages of maturity

DCI Maturity can be measured across four key stages. We call the earliest stage ‘Monitoring’ and the most advanced stage ‘Embedded digital consumer intelligence’. Here’s what building an experimental culture looks like for organizations at each stage of maturity. 

1. Monitoring

We should start by saying that some of the challenges will be around actually being able to undertake this experimentation in the first place and breaking out of usual routines.

Right at the beginning of an experimentation journey, we often see resistance to change. The fear of failure is halting the process before it’s even started.

There may not be reviews of current sources, methods, and workflows at all, and if there are, they are likely to be few and far between. ‘Stick to what you know’ is likely to be a subconscious mantra in these businesses.

Tristan suggests how to begin. “Here you want to start by freeing up a bit of time – perhaps adopt the 10% time model borrowed from the engineering world. This means allowing your teams time to break away from their day to day work and use this time to explore new ideas.”

2. Developing intelligence

The next stage in the growth curve sees incremental improvements to current sources, methods, and workflows following reviews, which are more regular and thorough.

“Next you’ll want to get out into different parts of the organization and get some differing points of view on what you’re doing,” says Tristan.

3. Digital consumer intelligence

Following these incremental improvements, we see that businesses are understanding the benefit of allowing experimentation and are now actively encouraging it. We may see deliberately designed ‘safe spaces’ for acceptable risk, and new ideas are celebrated and rewarded based on their outcomes.

“To mature further, you would now be likely to break out and head further into parts of the business you don’t normally deal with regularly and source some new research questions and hypotheses to test,” Tristan says.

4. Embedded digital consumer intelligence

When an organization is mature in this pillar, we are pleased to see that new ideas are celebrated based on originality. There will be novel applications of existing sources, and early adoption of new CI methods.

“Collaborate with ‘non-digital’ parts of the business to see if there are ways you can use their data,” says Tristan. “These might be manufacturing, or parts of customer care that you don’t ordinarily have contact with, such as people who might have more face time with the customers themselves.” 

“And one general tip for all maturity levels in this pillar is to try and spend an equal amount of time presenting your ideas as you do researching them, even if it’s just within your own team,” continues Tristan. “This time will give you new ways to tell stories and share insights."

How does the experimentation pillar relate to the other pillars?

When we talk about the different pillars that make up DCI, and as you explore the other guides in the series, it should become apparent that these pillars do not work in isolation.

Tristan explains: “I speak to many customers every day and often they have different maturity in different pillars – for example, they are developing intelligence in the data governance pillar but have a deeply embedded voice of the customer. Ultimately all of the pillars should work alongside each other to achieve the ultimate goal of DCI maturity.

“Let’s take the insights flow pillar, for example. Experimentation will plug into insights flow, as the learnings from experimentation will be distributed throughout the organization for everyone to learn from.”

Tristan also highlights the speed to insight pillar as being closely related to experimentation. 

“Hopefully through the experimentation process you’ll come across new ways to access data and insights more quickly. Trying out new tools, processes, and data points regularly will considerably improve your speed to insight.”

This pillar also links strongly also to the culture of data pillar – experimentation is only possible in an organization that prioritizes data based decision making. 

“Experimentation is an investment that companies need to embrace fully to give space for innovation to thrive, and learnings to be applied,” Tristan says.