Companies need to make good business decisions to survive. In today’s world, that means data-driven business decisions. Yet according to Forrester research, companies analyze only 12% of the data they have, letting 88% of it go to waste. That’s like looking at the tip of the iceberg and ignoring the rest, and as we all know, that’s a very treacherous proposition.
Here’s the tough part: to stay competitive with top companies adept at navigating through oceans of information, your organization needs to evolve to incorporate data-driven decisions across every function, from marketing to human resources. Most business leaders are getting comfortable with this idea, but many are still having a hard time connecting data to the work going on in specific functional areas.
But here’s the good news: creating a data savvy workforce doesn’t mean that all your employees need to be data scientists. Let’s look at the three goals you should be pursuing to take advantage of all the data beneath the water’s edge.
Goal #1: Upskill your non-technical teams so they can analyze data relevant to their function.
The important thing here is that every employee gains a sufficient level of competency with data to make decisions in the best interests of the company. Are your marketing teams (to take one example) skilled enough with data to take advantage of marketing opportunities?
Let’s say your customer success team is looking through your CRM system, and the data within it indicates that most of your leads are coming through your website. Will they be able to see this in the data? If so, are they data savvy enough to go on to decide that optimizing the site’s SEO is more important than spending time at conferences?
Across all non-technical functions at your company, your people need to be able to make these kinds of decisions. After all, it takes an entire crew working in unison to keep a ship sailing.
Goal #2: Help your technical teams stay up-to-date on the latest developments in data science.
Any technical employee should be current in his or her field, and data scientists are no different. Do your data scientists have the opportunity to attend conferences and workshops to keep their skills honed? Do they know how to create the database infrastructure that can accommodate the huge amounts of data necessary for cutting-edge work?
One of the most exciting things about data science, as well as the power it holds for your company, is that there’s always something new on the horizon. Constant training is key to upskilling and retaining data scientists who can steer the data science agenda at your company.
Goal #3: Increase communication and collaboration between non-technical and technical teams.
This goal is harder to achieve than it sounds, as most data scientists don’t have practice in identifying business problems, translating them into data problems, and then translating solutions back to the business side. On the other side, non-technical people often don’t know how to set up data workflows to answer fundamental questions like, “Why are my customers leaving?” In short, data scientists need to be trained on how to answer business questions, and non-technical talent needs to be trained on how to leverage data science solutions. More specifically, both sides should be able to:
- Ask each other the right questions
- Assess available data sets
- Identify the most beneficial deliverables
- Manage expectations
- Talk about technical processes with one another
Without data and business savvy on both sides, you’ll be running a ship where the crew is speaking two different languages, frustrating your efforts to get where you need to go.
Working toward the three goals listed above are crucial for any organization, and it’s no surprise that leading companies are pursuing them. Now that you understand the challenge and how you can approach it, what will you do to drive data-driven decision-making at your business? It’s time to sink or swim.
About the Author
Sehreen NoorAli is vice president of business development and corporate partnerships for Metis, a data science training company. She is also the founder of EdTechWomen, a networked community for women’s leadership in education technology.
