Ask the Expert: Does My Company Need an Analytics Translator?

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Drew Sheehan of FTI Consulting’s Data & Analytics practice reviews the role of this relatively new position that is becoming critical in our data-driven business world.

Today’s organizations have a veritable ocean of data at their disposal. Data is a resource that can either drown companies that struggle to manage it or, if leveraged strategically, provide actionable insights and unearth unique business advantages.

Managing big data is a primary reason for the explosion of in-house data teams. Some of the roles are well established, including data architects, data engineers and project managers. Other positions are relatively new, like machine teachers and data hygienists. One thing these professionals tend to have in common is a data science background.

Among the new positions is the analytics translator, a role that has only emerged in the past few years. The translator’s primary responsibilities are to democratize, interpret and analyze data for organizations, with the ultimate goal of helping them achieve real business transformation and manage the ocean of data to make better-informed and data-driven business decisions.

As leading firms increasingly shift toward artificial intelligence and adoption of robotic process automation as part of operations, the analytics translator can be a critical addition to the team. The growing embrace of big data — and the volume and speed at which it is generated — demands the kinds of skills a translator can offer to keep a firm informed and operating efficiently.

7.5 SEPTILLION GIGABYTES

Quantity of data generated worldwide every day*

What differentiates analytics translators from their fellow data teammates? They may not necessarily have a data science background. Instead, they combine analytic and classic soft skills that help them serve as the connective tissue between the non-data and data worlds. Analytics translators have the technical skills to work closely with IT, business intelligence and data science teams, but they also possess the business acumen that engenders credibility with the finance, accounting and operations teams within an organization. Effectively bridging the gap between technical and financial/operational teams enables the translator to understand a company’s enterprise-wide strategic priorities and the process for providing the critical data to support those priorities.

Simply put, analytics translators help contextualize data and unearth business trends, challenges and opportunities by bringing big-picture perspective to the data analytics. They find the narrative within the data — what a business is doing well (and not so well), what the behavioral trends of a target customer base are, etc. — that they use to forge actionable insights. These insights can help leaders make the best business decision at the best time while adhering to company priorities.

The analytics translator works to interpret and express an enterprise-wide view to end users while also uniting all teams — business, data and sales, among others — to ensure successful delivery. Analytics translators can decipher when data is “good enough” or directionally correct to support the required business analysis. Determining when the data can support decision-making in a fast-paced environment without waiting for perfect data can help the business move forward while taking into consideration current limitations. Analytics translators can simultaneously work with technical teams to improve the data and supporting architecture over time, leading to continuous improvement.

The ability to “speak data” is highly touted in today’s business world. Perhaps more so is the ability to translate data into language that colleagues and clients can understand.


* https://lucidworks.com/darkdata/

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