Join us on June 2nd for the MITX Data Summit! Advisory Board Members, Thomas Hubbard, who is the VP, Head of Global Marketing at Kaspersky Lab, has written a blog that provides us with a sneak preview of what we'll be talking about on stage at this event. Register for the Data Summit here.
Tom Hubbard is the Vice President, Head of Global Digital Marketing at Kaspersky Lab. He is responsible for UX, Media, SEO, Analytics and Web Development, among many other activities, in 200+ countries. Prior to Kaspersky Lab he was the Vice President, Online Marketing at Euro RSCG Edge.
It’s not exactly breaking news that there is a rapidly worsening gap between the demand for data scientists and the actual number of data scientists. The deep investment in a ”big data” across nearly every vertical has created a demand that the current labor force, schools churning out new graduates and even supplemental workforce from overseas cannot support.
Executives striving to build a data-driven marketing organization (and successfully complete the change management that goes along with) face a much more pressing problem: A shortage of available marketing talent that possess the analytical skills needed to integrate and apply data into day-to-day marketing activities.
Analysts are critical to any data-driven organization. They are responsible for integrating, organizing, structuring and analyzing data. Great ones can distill massive amounts of complex data into a few salient points. But because they lack ownership of customer-facing activities, they are often powerless to actually apply data or insights in the manner needed to truly transform marketing activities and customer experience based on data.
The key in any shift to a data-drive marketing organization really lies with the Marketing Managers and Program Managers responsible for concepting, developing and executing these marketing programs. Without their involvement, organizations will struggle with the changes necessary to successfully transform their operations.
Unfortunately, these individuals are frequently under-supported by their organizations. They lack the direct access to data, training and incentives that will help them begin to shift their approach to their work. Their exposure to data analytics is typically limited to analyzing program results. Those tend to be surface level metrics that show what happened, but lack the in-depth analysis required to understand why it happened and even better, to predict what will happen next time.
Organizations therefore must take seriously their responsibility to do a better job in both prioritizing analytics in hiring and nurturing and enabling existing staff.
Any marketing organization looking to become more data-driven needs to first look at its hiring practices. Often we prioritize other skillsets over analytics; the ability to analyze data and incorporate it into their daily work is easily placed secondary to other needs, particularly to things we consider “core” to the role.
Think about your last Marketing generalist hire. How much time did you spend talking about how they use data in their role? Did you ask them to share you data and walk you through it so you could understand how they move from data to insights? Did you ask them to complete an assignment that would demonstrate their ability to utilize data in their day-to-day work?
Many times we spend too little time talking about data, and generally assume they will be able to apply it in a way that meets our vision.
As we build out our teams, this approach is not good enough any more. A candidate’s ability to incorporate data into their work from Day 1 must be fully vetted in any hire. Making any assumptions related to this during the hiring process can set back or even halt your transformation process.
Hiring great people is a good start, but you need to be ready to support them. There are several key steps we must all take to nurture a data-driven team:
- Guide Them: Set a good example. Everything you do and say must show how it has been tied to data and not opinion. This creates solid expectations for how they should present their ideas and manage their programs.
- Enable Them: Provide access to all data sources, and train them on how to use them. It is remarkable how many companies who claim to want to move to a data-driven model still have siloed and protected data sources. Opening up access to the data to everyone is needed to truly become data-driven.
- Encourage Them: Don’t put constraints around their work and particularly how they use data. Encourage them to take chances, and to look at problems in a different way.
- Reward Them: Tie their use of analytics to their annual objectives, making it clear they will be rewarded for this type of behavior. This also clearly sets expectations by establishing how they will be measured.