Building a Culture of Data at Your Organization

We know that data is fundamental to making smart decisions at all levels of the company, and yet creating a culture of data that leads to this is mystifying to many organizations. 

Sadly, there’s no quick and dirty way of building a strong culture of data.

We’re talking about a huge shift in mindset and behaviors, and those don’t happen overnight. To create new processes, update the tech stack, and hire and train staff is no mean feat. It takes time, effort, and trust. But it is achievable with smart planning and the right champions. 

Building a culture of data is a crucial part of maturing within digital consumer intelligence (DCI). It’s one of the six key pillars set out in the DCI Maturity Model, and something we ask about in our DCI Assessment to help organizations identify their strengths and weaknesses.

In this guide, we’ll show you how organizations of different maturity levels behave in relation to the culture of data pillar, and give advice on how your organization can advance. We’ll also be digging into the subject with insights advocate and Brandwatch’s VP Solutions Consulting for Europe Joakim Nilsson, who has over 15 years of experience in helping brands grow using insights.If you haven’t already, we’d encourage you to check out our DCI Assessment to see where your organization stands. 

Building a culture of data: 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 a culture of data looks like for organizations at each stage of maturity. 

1. Monitoring

In this early stage, there is perhaps no culture of using data, or as Joakim Nilsson puts it, “decisions are made based on where the wind is blowing – think senior leaders making decisions based on their own opinions. This isn’t a good culture of data, per se, but it’s at least somewhere to start. There's a lot of room for improvement, and that’s a good thing – an opportunity.”

These organizations are likely to make decisions solely based on instinct, from the top down and without scrutiny. 

We’ll often see a lack of trust and confidence in data in these businesses. This can be a real stumbling block, explains Nilsson.

2. Developing intelligence

A developing organization will have the building blocks for a culture of data in place but will often falter when it comes to actually acting on insights. 

There will be, says Nilsson, “a clearly outspoken will to be data-driven and make decisions based on data, but it’s likely that the big ideas are more ambitious than the actual actions taken. This is also the stage where we tend to see some decent investment in analytics tools, and we see budget put towards truly becoming digitalized.”

We might see, for instance, consumer insights being presented to leadership to help influence decisions. 

But, ultimately, this cultural shift does need to come from the top down, and at this stage we may not see senior leadership driving the data culture.

To reach a higher level of maturity, senior leadership need to be both flag-waving for data and analytics and also empowering and emboldening their departments to do so.

3. Digital consumer intelligence

At this advanced stage we see leadership champions using consumer insights data in decision making, say, being integrated into the recruitment process, or the company website. Analyzing data will likely now come naturally to key areas of the business. 

“In the ‘advanced’ category, we are hearing not only stories of ambitious ideas, but stories of what they’ve actually done. We’re hearing how data has and will inform decision making in the company, ie we’re going from ideas to real execution,” Nilsson explains. “There’s also a common language and understanding of data – a data literacy – across the organization, but it’s important to be mindful that this culture of data is unlikely to look the same throughout each area of the business.”

We put to Nilsson the billion dollar question: How do organizations move to being mature? 

“At this point in the maturity journey we’re still likely to see some teams lagging behind – access to the data is incredibly important. A culture of data is not functional unless everyone in the organization has easy access to data, information, and insights.”

An important point, and one oft-overlooked, is to avoid the temptation to silo Data Scientists – data does nothing for the business if it’s siloed. Be sure to make these key data champions and their crucial work visible across the organization. 

4. Embedded digital consumer intelligence

A digitally mature organization is where we see a real culture of data across the whole business. 

Here, consumer data is visible and truly meaningful at every level of hierarchy, with experimentation and innovation with data being encouraged. And it’s not just big decisions being influenced and made using data, but the smaller everyday ones too. For instance, we’d see frontline members of staff using analytics to solve customer queries multiple times a day.

In these organizations, data is king – and importantly, it’s democratized. 

“It’s not that we just see proficiency and literacy in data, but data is hard currency. Data is seen as the organization’s largest asset – for example, with Google and search,” says Nilsson. “Employees are expected to be data driven - they’re expected to justify their actions and decisions with data. There may even be a Chief Data Officer whose job it is to build a clear bridge between how the company harvests and exploits data, and how it connects it to business value.” 

How does the culture of data pillar relate to other pillars?

There are five other pillars in the DCI Maturity Model. To mature in digital consumer intelligence, an organization must focus its efforts on all six areas. That said, some pillars more closely entwine than others.

Insight expert Evelyn Castillo, Account Director for EMEA at Brandwatch, explains how the speed to insight pillar is linked with culture of data. “Speed to insight essentially means understanding and acting quickly on consumer feedback. This enables organizations to act fast and outpace their competitors, but a strong culture of data is needed for rapid and widespread action that drives change.” 

‘Insights flow’, which is about getting the right information to the right people across the organization, is also an obvious fit with building a culture of data. Joakim Nilsson explains: “Information flow and culture of data go hand in hand. When every person in the company understands how crucial information sharing is, the act of sharing becomes second nature.” 

He continues: “Performance is consistently measured and insights are shared to connect the dots and gain a holistic vision of overall performance. This has multiple benefits. Ultimately, a culture of data is a culture of decision. Embracing data and insights in the company culture allows for crucial decision making at all levels of the organization.”