Organizations worldwide are trying to make more effective use of data, analytics, and AI, but many continue to struggle to adopt a data-driven culture. A survey of large U.S. firms conducted by NewVantage Partners found that 92.1% of companies say they are achieving returns on their data and AI investments (a marked increase from 48.1% in 2017). Yet, only 26.5% have created a data-driven organization, and only 19.3% have established a data culture. The greatest barrier to organizations becoming data-driven? Ninety-two percent of survey respondents identified cultural impediments as their most pressing challenge.
So, how do we continue to find, capture, and analyze data while also making it accessible to the people who need it to make decisions quickly and effectively? The answer lies in data democratization.
Creating an internal data-driven culture necessitates data democratization—the ongoing process of empowering all employees to have an easy way to access, understand, and apply data to expedite informed decision-making, uncover opportunities, and build customer experiences powered by that data. The ultimate goal is to allow the employees closest to the decision to use data effectively without any barriers to access or understanding. By knowing where your data is and making sure people can understand it, your organization will be better equipped to scale and deliver value through empowerment.
Do we need a team of data scientists in order to democratize data?
Many organizations begin their data science journeys by hiring data scientists to analyze big data sets. Naturally, a data scientist brings a wealth of specialist expertise and value (along with a hefty price tag). However, truly transformational data science is democratized data science. Restricting data science to experts only limits its potential, and does little to create a widespread data-driven culture. On the other hand, democratizing data provides significant opportunities for better insight and implementation. Not only do employees already understand the business and its challenges, but involving them in data science transformation encourages them to engage with the data and buy-in to its benefits.
How to democratize data in your organization
The idea of an organization-wide data science transformation may sound overwhelming, but there are some simple ways to start. One of these is using simulations to develop your employees’ comfort level with data analysis.
The CEO of a large bio-sciences company we work with announced an initiative to make data accessible to everyone in the organization in order to improve the speed and quality of decision-making at all levels. To accomplish this, they needed to figure out how to provide usable data and meaningful analytical skills to decision-makers at all levels of the business.
Their first steps were to begin building self-service data portals and to make basic data-literacy programs accessible to all employees. Subsequently, they partnered with our team to create a series of simulations. These were tailored to each business function to develop the skills and confidence of employees at all levels to use data to enhance decision-making. These simulations were designed and delivered through Blueline’s ExperienceBUILDERTM digital design platform.
These custom learning simulations created a safe space for employees to learn to apply data analytics by working through real-life scenarios. Learners were tasked with identifying the problem or question, finding the right data source, analyzing that data, and making a good data-based decision.
It’s important to acknowledge that there can be gray areas in data interpretation and decision-making. Despite having access to data sources to inform decision-making, finding the best possible solution may not be clear-cut. Access to data moves us forward in the quality of decision making, but it’s still a mix of art and science. The power of ExperienceBUILDER simulations is that they model complex challenges with multiple feasible solutions—where right and wrong are often gray. In ExperienceBUILDER’s collaborative, team-driven learning environment, selecting the best answers often requires meaningful dialog and deep dives into data interpretation best practices:
- Are we answering the right question?
- Are we getting the right data source to answer that question?
- When we choose the right data source, are we analyzing it correctly to have the best chance of making the right business decision?
- Are we ignoring outside influences on the datasets?
Teasing out the best possible answers helps employees develop their data-driven decision-making skills.
Data science is for everyone
Data science is about people. Rather than requiring highly paid data scientists to do it all, organizations that strategically and broadly bring people and data together are likely to realize better results.
Blueline Simulations has first-hand experience designing simulations that help your employees make the most of your data. Reach out to Blueline to learn more about how we can help you develop your team’s data-driven decision-making.
