Data has already redefined the face of practically every industry, meaning even those without analytics-specific jobs must become data literate.

Practically everything modern consumers do — from what they eat and where they travel to what they read and where they socialize — produces data that is ripe for analysis. At times, this torrent of data can become overwhelming, but the companies that manage to find their bearings first in the emerging data landscape will be best-positioned to become the 21st century giants, while the rest will still be banging rocks together to see what happens.

Grounding Company Culture in Data Analytics

Even if a company’s leadership makes a concerted effort to integrate data analytics into the organization’s everyday operations, a lack of sufficiently data literate personnel can bring the whole effort to ruin. “Once [companies] have data,” explains Dan Portillo, a team leader at early-stage venture capital firm Greylock Partners, “they really need people who can manage it and find insights in it.”

The fact that 60 percent of corporate big data projects are abandoned after the pilot phase suggests that many companies don’t, in fact, have the people they need to transition to an analytics-driven business model. Part of this stems from an ongoing shortage of analytics professionals, a shortage that is only going to get worse in the near future. According to McKinsey, by 2018, the U.S. will experience a shortage of between 140,000 and 190,000 workers with “deep analytical skills,” as well as a shortage of 1.5 million management-level professionals with “the know-how to use the analysis of big data to make effective decisions.”

However, as troubling as this impending shortage may be, it isn’t the only reason that companies are, on the whole, struggling to build a workforce capable of leading them into the big data future. Formally-trained analytics professionals are the foundation of any robust big data operation, but the success and failure of an organizational transition often pivots on whether “non-analytics” employees in sales, human resources, communications and other seemingly less quantitative departments are on board, or if they’ve resigned themselves to lives separate from math and numbers.

As Gartner research director Lisa Kart points out, “A successful advanced analytics strategy is about more than simply acquiring the right tools. It’s also important to change mindsets and culture.”

The Broad Applicability of Analytics

In order to create unity, executives, managers, and analytics professionals must help every employee recognize — and accept — that data analytics bears upon everything that the company does. It’s not that everyone needs to “speak” data fluently — at least not in the near future — but everyone needs to be able to listen to data-speak with a baseline level of comprehension and apply analytics-derived insights in a rudimentary way, regardless of their position.

To this end, it’s important for non-analytics professionals — especially younger ones — to gain an understanding of the ways in which data can be used to improve operations in just about every department of companies in just about every industry, traditionally “technical” or not.

For instance, way back in 2014 — ages ago in data analytics years — San Francisco-based startup Evolv began helping human resources departments across the world analyze millions of “employee data points.” The idea was that applying standard analytics to data points like how long it took employees to get to work or how often employees interacted with their supervisors would enable HR departments to more easily optimize productivity.

A similar startup, Sociometric Solutions, helped Bank of America’s HR team analyze how their employees moved around the workplace, who they talked to, and what tone of voice they most frequently used. After implementing the insights derived from these analytics, “performance improved 23 percent and the amount of stress in workers’ voices fell 19 percent.”

Beyond HR, data analytics has proven to be a tremendous boon to everything from agriculture to manufacturing to healthcare, industries not traditionally noted for being tech-forward.

Soon, We’ll All Be Analysts

In today’s world, data is the one thing that companies in every industry have in common. The type and volume of this data may vary, but the fact that it exists and the importance of analyzing it does not.

According to research conducted by MIT faculty members Erik Brynjolfsson and Andrew McAfee for the Harvard Business Review, “Companies in the top third of their industry in the use of data-driven decision making were, on average, 5 percent more productive and 6 percent more profitable than their competitors.” In other words, data analytics are a must, and integrating them effectively requires a workforce in which everyone has a role to play.

At Saatchi & Saatchi Wellness, we believe that the future of marketing will be defined by the intersection of hard data science and compelling narratives. That’s why we strive to help our clients bridge the divide between data-driven insights and human storytelling to create meaningful consumer interactions. The data is all around us — we’re here to help you harness it.

Written by Tariq Hasan

I have been with the Saatchi and Saatchi Wellness Analytics team since 2015 within the Data Engineering group. Before joining SSW, I spent four years teaching English in Vietnam. During this time, I managed to teach myself programming and project management through a number of video game projects and collaborations. Upon my return to the US, I took an immediate liking to Data Science and have been growing ever since. Within the SSW analytics department, I am a driving force of the TrueTarget and SweetSpot product offerings for machine learning based predictive targeting and strategy optimization. On the rare occasion I am unable to solve a problem within the realm of SQL and Tableau, I can shore up any gaps with a liberal use of R and Python.

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