You probably know that I am pretty passionate about the importance of Data Fluency as a skill set for Market Research & Insights professionals. I started writing about this in 2017, and then after the McKinsey article in HBR came out last year, the topic really picked up steam. BTW, if you missed the original Harvard Business Review article, do check it out and be sure to read the Comments (trust me)! The bottom line is that those of us in Market Research & Insights are now part of a diverse information ecosystem that serves data-driven decision makers. Thus, if we want to be truly consultative advisors, we need some level of “fluency” in the many types of data now available (including various 1st and 3rd party sources). The goal for those who choose to pursue advisory-level roles, is to be able to objectively recommend the best methods and data sources for our clients’ needs, from an informed awareness of the many available.
So, do you want to be perceived as a credible, objective “McKinsey Translator” who can manage the gap between business needs and optimized data source combinations? If so, you are probably already working on amping up your data fluency. Want an option for getting started on your data fluency journey? Please consider our upcoming course.
Data Fluency for Methodology Planning is starting in just a couple of weeks. We still have a few seats available, so if you’d like to save your spot, please sign up soon. How to sign up?
- If you are a Backstage Pass member: The course is in your dashboard. Just select and click to start the course.
- Not a Backstage Pass holder? Consider buying a monthly membership, and that way you can unsubscribe when you are done with the course.
Not sure? Here is a bit more about what you’ll learn:
In recent meetings, have you heard clients or colleague talk about 1st versus 3rd party data, data veracity, behavioral data, blended data or perhaps even DMPs? And when these topics come up, do you feel confident that you understand the terms and their relevance to customer insights work?
Today, the data-fluent researcher can choose from many types of data— including “big” and “small,” quantitative and qualitative, primary and secondary, financial and behavioral, and more. Know your options, and how to assess their reliability and suitability for different decision-making needs.
Students will learn about framing goals and needs, selecting data types and sources, selecting data analysis methods, and assessing data reliability.
