There’s no “I” in data.
Despite the inarguable importance of data and analytics in today’s marketplace, our country’s demand for analytical talent has quickly outpaced the supply of talent. In other words, although the value and volume of data continue to grow, we’re facing a significant shortage of people who know how to work with and deploy it in the workplace.
There are a number of factors contributing to this shortage, but foremost among them is the unfortunate reality that people — especially students — simply don’t understand what a career in “analytics” entails. Furthermore — the breadth of skills required by analytics organizations today spans multiple academic disciplines and areas of domain knowledge — it’s nearly impossible for a single analytics professional to “do it all” with a high degree of excellence.
At Saatchi & Saatchi Wellness, we’ve built an analytics department grounded in teamwork, complementarity, and comprehensive, forward-looking insights. Located at the intersection of healthcare, marketing, math, data, and computer science, an effective healthcare marketing analytics team is comprised of players with diverse talents capable of mastering every facet of this dynamic field.
To the uninitiated, differentiating among the various positions that fall under the “analytics” umbrella can be challenging. Like any great football team, we believe that a team built on diverse, complementary skillsets is invaluable in driving disruptive insights for our clients:
The Quarterback: Data Strategist
Data strategy is the art of translating business problems into the language of analytics. They are responsible for identifying and defining key performance metrics across a variety of marketing channels, tactics, and sources — a job that requires a nuanced understanding of the relationships between real-world outcomes and quantitative analyses. In short, whenever a company assigns its analytics department a project, it’s the data strategist’s job to orchestrate the project from beginning to end and guarantee that the team produces any and all required deliverables. Just like a quarterback, a data strategist touches the ball during every play.
The Tackle: Data Engineer
Data engineers are in charge of everything related to data integration, automation, and manipulation, and are thus the sine qua non of analytics as a whole. They use complex set theory and statistics embedded within programming languages like SQL to make sense of voluminous raw data and make it usable for everyone else on the analytics team. Not only do data engineers have to consider how to most efficiently store massive consumer datasets, but they also have to optimize code in order to reduce database computation times and costs. They function as the tackle of the analytics team by deftly bearing the significant weight of massive raw data sets and empowering their teammates to do their jobs.
The Wide Receiver: Data Visualization/BI Expert
Data visualization experts “catch” whatever structured data and insights their team members produce and organize it in an aesthetically pleasing, compelling, interactive way. Their role is essential to bringing clients, consumers, and stakeholders into what can often be an esoteric, data-based conversation — whether through the development of an intuitive dashboard or the design of engaging infographics.
The Middle Linebacker: Digital Analyst
Typically found in marketing and advertising agencies or digital-first companies like Facebook and Google, digital analysts are responsible for gauging how consumers utilize and engage with digital platforms. Every company has their own definition of a “conversion” — a product purchase, a registration action, a white paper download — that represents a successful consumer interaction.
Digital analysts work closely with creative teams, UX designers, and media buyers to transform clickstream data into a conversion-driving digital experience. Just like middle linebackers function as the “quarterback of the defense,” digital analysts respond to and interpret engagement activity in order to improve consumer-facing processes.
The Running Back: Data Scientist
Usually responsible for a team’s predictive and prescriptive analytics work, data scientists simulate an array of likely business outcomes using statistical modeling and artificial intelligence tools grounded in machine learning. Data scientists take a company’s historical data — and the ongoing insights offered by the company’s data analysts — and use them to predict future consumer engagement, both in concrete terms like tendency to purchase and in more abstract terms like consumer loyalty. Like a running back who takes handoffs, blocks for the quarterback, and catches passes out of the backfield, a data scientist must creatively combine insights about past behavior with other environmental data points to strategically — and successfully — anticipate what’s to come.
At Saatchi & Saatchi Wellness, we guide clients through significant and complex business decisions — decisions that demand a multifaceted and sophisticated approach to analytical problem solving. To that end, each of our team members plays an essential role in creating meaningful, long-lasting value for our brands.