We are in the midst of a data-driven revolution and exploding quantities of data are affording many companies with massive transformational value. Despite that, the value enterprises generate from their data is still underwhelmingly low, with only 32% of companies being able to realize tangible and measurable value from their investments in data. This begs the question - where is the investment in these capabilities going?
Usually, the investment goes to the technology and data itself instead of the integration between data, technology and the people who use it. This can perpetuate issues like the one we saw with a materials science client, where many managers and engineers are still spending 60% of their time gathering data to keep operations running. In other words, much of their time is spent working on the data versus working with the data. What’s preventing these companies from converting new data into new value? The answer lies in data culture – the meaningful integration of data, insight, and the experience of work.
Why is Data Culture Important?
Research has shown that organizations with a strong data culture have nearly 2x the success rate and 3x the return from AI investments than companies without. A strong data culture puts people at the center of any data transformation. It ensures they’re empowered to consume and use data in ways that make sense for them, and it aligns (and even evolves) with their level of data maturity. Along with strong data and AI capabilities, this kind of culture can help businesses to think about data more strategically and use it more broadly, helping them optimize operations, understand customers better and ultimately unlock new revenue streams through new products and services. It’s a compelling proposition as companies race to improve across all performance KPIs while reducing speed to market.
So, how can leaders get data culture right?
Opportunity 1: Focus on changing behaviors rather than ‘culture’
Aristotle said, “We are what we repeatedly do”. This brings to the fore the importance of observable behavior and habits around data; they are what shapes culture. To understand these behaviors, organizations can start by capturing the experiences and interactions people have with data, mapping some of the roadblocks they encounter when making effective decisions and listening to what they find most meaningful about their work.
For instance, Accenture worked with a materials science company to map the attitudes people held towards the use of data and analytics in their decision-making process. Many harbored negative attitudes towards data due to past experiences with it, but they still understood the value of data. We also discovered that many people were tackling even the simplest problem as if it were a big innovation problem. This was happening because the company was incentivizing highly innovative behaviors, and while innovative behaviors should be rewarded, they should not exist in an innovation vacuum. Unaccompanied by some form of data governance or value prioritization, this meant the organization struggled to unlock the full value of data because there lacked a clear path to implementation.
Solution: Adopt a behavior-led framework for change
By regularly understanding which behaviors exist and to what extent, organizations can measure behavioral change over time. We call this an organization’s Data Pulse and it is meaningful for two reasons. First, organizations can use it to track the existence of a data culture in an organization at any point in time. Secondly, it provides measurable evidence of those interventions that increased data adoption and those that did not.
The Data Pulse is a survey designed with behaviors at its core. We define the behaviors we need to see in relation to the way data is treated as an asset, how it is trusted as the basis for action and how data is used in the context of driving business value. In relation to these dimensions, we ask people to articulate the prevalence of certain observable behaviors in the environment around them. For example, whether people share insights they've discovered, making them accessible for others through to the way data and insights are used to create novel and valuable solutions for an organization.
By forming a clear understanding of people’s needs, challenges and values, organizations can use these as the basic design principles on which future data solutions are based. Mapping these principles over time paints a more accurate picture of an organization’s data maturity and the behaviors displayed.
Opportunity 2: If you want people to do something, make it easy
When it comes to changing behaviors, there is a universal truth: if you want people to do something, then make it easy for them. When we examine the technologies or processes many organizations use to make data-driven decisions, more often than not, people find it hard to do the things they need to do with the tools that they have. Data solutions are usually challenging to access. For instance, there might be too much friction or sometimes an overload of information with a limited amount of time to process that information. In the same materials science organization mentioned in our previous example, the lack of data governance led to poor data management, and siloed data sources discouraged many from leaning on data to generate better ideas. All the above act as restraining forces to data adoption, as these unintended forces end up overwhelming the user.
Solution: Solution-driven Behavioral Change
People are motivated to learn and change their behavior when a changing context demands new behavior Focusing on the environment in which people make decisions is key to understanding their experience with data, which is exactly what we delivered for a financial services client. We setup a room designed to enable the team to physically move across different areas as they mentally walk-through various stages of the decision-making process. Essentially, a guided physical movement acts as a nudge for following a lean and value focused decision-making process. At the same time, the environment is underpinned by data displayed on digital dashboards. Participants interact with real-time portfolio data resulting in more engaging and data-driven discussions in the room.