Data analysis has seeped into more professions and more aspects of business. No longer is number crunching relegated to “quants” or “geeks.” Even if data analysis isn’t part of your job description, understanding and applying basic concepts of data analytics has become a necessary skill in most every business communications position.
Many highly educated communications professionals still fear data – and dread having to perform data analysis tasks. PR professionals are not alone in their dislike of numbers. Although data and analytics tools are plentiful, ability to organize and interpret data is in short supply, especially in business communications.
Being able to work with data has become an increasingly important skill for PR, as PR measurement progresses into standard practice to validate PR’s contribution to the corporate bottom line. Remaining fearful and avoiding data-crunching tasks can harm a career, even in a field like public relations.
Fear of data can also harm entire organizations, warns Thomas C. Redman, president of Navesink Consulting Group, who’s known as the data doc. If uncomfortable with data, people may be reluctant to share information or may complain that data is inaccessible or incompressible, Redman writes in an article for Harvard Business Journal. Fear can even prevent people from expressing their thoughts and trying new ideas.
Data analytics experts offer these suggestions for managers to help them control fear and harness the power of data. Although written for business managers in general, they apply particularly well to public relations and other communications professionals.
Study the topic. Read articles online as well as books, remembering to focus on what data means for you on your department. Redman recommends “Competing on Analytics” by Thomas Davenport and Jeanne Harris, “Data-ism” by Steve Lorh, “The Signal and the Noise” by Nate Silver and his own book “Data Driven.” It may also be worthwhile to take an online course on data analytics.
Understand the basic concepts. Although you may not perform a regression analysis yourself, understanding such concepts and the difference between causation and correlation will help you become more comfortable with data analysis.
Practice. Practice assembling and analyzing data on something that interests you — meetings start time, your commute time, your exercise program or sports statistics. Aggregate the data and create some simple plots, such as a time-series plot, and compute some statistics, such as the average and the range. PR folks may want to start with measurement of media clips.
Think about it. Consider what that data means. Construct graphics to visualize what you’ve uncovered.
Apply data concepts to work problems. As your knowledge and comfort level grows, apply what you’ve learned to work and involve your team in data analysis projects.
Open relationships with data analysts. Accept that you can learn from them and treat them with respect rather than dismissing them as “geeks.” Expose them to the organization’s challenges and include them in the decision-making process. When hiring, put some emphasis on seeking job applicants who have an appetite for working with data to clarify business issues.
Don’t be overwhelmed. Identifying limited number of key metrics rather than 10 or 20 can help prevent becoming overwhelmed with data.
Question assumptions. Thomas H. Davenport, a professor at Babson College, suggests asking: What assumptions are being used to build the model? Under what conditions might those assumptions become invalid? And, how well do the sample data represent the population?
Respect the data. The goal of data analysis is to deliver objective perspectives. Pressuring analysts to reach conclusions that support an executive’s intuition defeats the purpose of data analysis and may sour relationships.
Understand the different types of data. Small data is manageable enough to fit on a single server, is already in structured form of rows and columns, and frequently comes from an organization’s transaction systems. Despite its name, it’s extremely useful, Davenport explains in an article for Harvard Business Review. Big data is too big to fit on a single server and is probably from outside your business transactions and in an unstructured format such as what customers are saying on social media. Big data offers great opportunity, but is challenging to analyze.
Bottom Line: For PR and other communications professionals to advance their careers, developing understanding of data analytics concepts and being able to work with “data geeks” has become a must-have skill. All PR pros need to become more comfortable with data analytics, even if they don’t necessarily do the number crunching themselves.
William J. Comcowich founded and served as CEO of CyberAlert LLC, the predecessor of Glean.info. He is currently serving as Interim CEO and member of the Board of Directors. Glean.info provides customized media monitoring, media measurement and analytics solutions across all types of traditional and social media.
