Data science and data analysis skills were once (and to some extent, still are) a discipline unto themselves. Data science careers are in high demand, are likely to grow over the next few decades, and more people are studying data analysis fields in college and beyond.
But the future of data science in business isn’t just about hiring more dedicated data scientists. Instead, it’s about educating every member of your team, and every department, on how to gather, analyze, and use data in their positions.
The Universal Need for Data
All this stems from the universal need for more data. As our tools for gathering and analyzing data become more sophisticated, competition gets tighter; companies are practically forced to adopt better data mining and analysis techniques if they’re going to offer better products, better services, or more efficient operations. And with something like 2.5 quintillion bytes of data created each day, there’s no shortage of information to wade through.
Data can also apply to every department, and every position. Rather than merely informing high-level strategies, data can be used in customer service to help account reps make more educated decisions on how to proceed with customers. It can be used by graphic designers to create better ads for your target demographics. It can be used by salespeople to adjust their tactics on the fly.
Automation and Accessibility
We also need to consider the automation and accessibility of data analysis. In the coming years, our data gathering and analysis tools are going to be sophisticated enough that even someone without a degree in statistics or data science can interpret the numbers; for example, they could rely on data visuals or bottom-line analyses to inform their decisions.
This trend does two things; first, it tightens the noose on any company not already making use of data analyses as a central business function, since all their competitors are going to have even easier, faster access to data. Second, it puts data analyses in any critical thinker’s hands—and not just in the hands of people who made a specific profession of it.
Educating Your Team
With those considerations in mind, you’ll need to spend time educating your team on the basics of data analysis. To start, it’s a good idea to create a good learning environment—preferably a large room with adequately controlled lighting—and go over basic analytic techniques. If you have data analysis software in place for each department, this is a good time to go over the fundamentals. Ideally, the platform will be intuitive, and to some degree, self-explanatory, but it’s still a good idea to be proactive and make yourself available to answer questions your employees might have.
From there, it’s a matter of integrating more data-based responsibilities into the daily activities of your team. Ask your customer service team to check certain metrics once a day, or train them to run weekly reports, self-analyzing their own efficiency. This is especially important for leaders, managers, and any role that makes lots of decisions. In some cases, you may want to encourage your team members to attend formal data science classes, to further their own abilities independently and bring those skills into the fold.
SAP has dozens of platforms dedicated to data analysis in various industries and departments. If you’re looking to get your feet wet, consider using our customer data platform or our marketing analysis software—or upgrade your existing platform with one of our modern, user-friendly ones.