Will a data scientist shortage hurt Big Data’s promise?
Through a special arrangement, presented here for discussion is a summary of a current article from the blog of LiftPoint Consulting.
Data scientists are a new breed on the marketing team, with expertise across a diverse collection of areas, each of which can have a positive impact on marketing initiatives, separate and combined.
Yet the McKinsey Global Institute predicted that "by 2018 the United States could face a shortage of between 140,000 to 190,000 people with deep analytical skills, as well as a shortage of 1.5 million managers and analysts who know how to use the analysis of Big Data to make effective decisions."
A survey by Robert Half Technology concurs, suggesting that "most companies aren’t maximizing their data collection and don’t have the people in place to do so."
These hard-to-find people can be your tour guides through the complexities of data. They combine computer science, statistics, math, and business skills with creative problem solving and clear communication to help you make marketing sense of all that data.
In recognition of their value, marketing and analytics are already merging in the C-suite, with CMOs increasingly aligned with their CIOs. In 2012, only 36 percent of CMOs said their CIO was a critical partner; by 2014, that percentage grew to 51 percent, according to "The Evolved CMO In 2014," a joint research project by Forrester Research and Heidrick & Struggles.
There is urgency too. Forrester Analytics’ State of Customer Analytics 2014 report concluded that analytics is no longer an option, but a necessity for any organization to compete. Every organization in every industry needs a senior-level data specialist on their marketing team.
Data scientists can translate all the analytic mumbo jumbo into concepts and theories that non-analytic marketers can understand. They recognize that a given business question exists inside the context of a given company and industry, and the nuances those outside influences play on the technical work of solving the business problem.
Many firms outsource their data scientist needs if they can’t afford or can’t find the correct skill set. The benefit that an external data scientist brings is a perspective on marketing from outside your company ("best practices") that can be leveraged to save time and improve results for your team.
The days of marketing as a "creative" fraternity are over. Today’s marketers need a data translator to help question, discover, interpret and, ultimately, succeed in today’s data world. The era of data scientists has arrived.
How important is it for retailers and brands to leverage data scientists? What are the barriers that can prevent a data scientist from succeeding on a retail marketing team?