“Do you use robots to write your stories?”

No, not unless you count laptops and the expertise of human hands as “robots.”

Yes, we’ve been asked this question before. In fact, it’s one of the questions we respond to quite often. Part of our job as industry leaders in an emerging field is to educate the public on what natural language generation technology can do and, on the flip side, its limitations. Natural Language Generation, or NLG, is evolving faster than most casual observers can follow. We operate in an industry where terminology and labels are continuously being defined and redefined. Analysts are still rushing to fully understand and map out the various offerings that make up the NLG landscape. So, as you can see, it really is no wonder we receive so many questions.

This blog post series is intended to expose some of the myths infiltrating the market. Below, we debunked the first of four of the biggest misconceptions of NLG technology.

Myth: NLG is coming for your job

Reality: NLG Empowers the Human Workforce

The “automation is costing jobs” storyline has become a popular media topic in recent years, yet we’re still waiting for it to carry any weight. There’s been a steady drumbeat of articles and news segments warning us those entire industries are quickly turning to automation in lieu of a human workforce. Whether it’s self-driving trucks transporting goods or robots overseeing an assembly line, automation will continue to permanently alter jobs that humans have held for generations. With much change coming from an industry that relatively few people fully understand comes much ambiguity and, ultimately, fear. It’s true that we are in a fourth industrial revolution, and it will dramatically change the way we live, work, and relate to each other. We’re rapidly adopting and implementing digital strategies and connected machines throughout the workplace. The changes are profound, and at the root of the innovation is the desire to improve the quality of life in every way.

This is where NLG is having an impact on jobs; it’s is augmenting the roles of employees by freeing up their time to focus on higher value, ROI-generating tasks. Even traditional content-generating roles like copywriters, analysts, and journalists are expanding their roles because of their ability to generate narratives and stories with a reach, depth, and speed not possible by hand. NLG streamlines repetitive, time-consuming tasks like internal reporting, mass personalized communication for marketing, and content at scale (for example, e-commerce product descriptions or data-driven content generation), so staff can focus on tasks that utilize

NLG isn’t taking away people’s jobs—it’s helping people do more in their roles. For instance, Automated Insights’ Wordsmith platform allows the Associated Press to publish 4,400 corporate earnings stories per quarter, up from 300 manually-written stories. Automation simply allows these writers to highlight 4,100 more organizations than they ever could before.

“Internally, the reaction has been positive from staff, largely because automation has freed up valuable reporting time and reduced the amount of data-processing type work they had been doing.” – Philana Patterson, Assistant Business Editor at the Associated Press

“Visualizations contextualized and enriched by easy-to-understand narratives, either analyst or NLG-created, accelerate the time to insight. They also improve the accuracy of insights and conclusions made from analytic content delivered to, and shared with, an expanded set of users who may have limited analytics skills.” – Gartner, Technology Insight for Modern Analytics and Business Intelligence Platforms, September 2017

NLG is also having a positive impact within industries where extracting insights from massive amounts of data is vital to the success of a company. NLG produces valuable, easy-to-understand narratives that provide insight for anyone, regardless of their level of data expertise, making critical business decisions. Allstate, a leading insurance agency, understands exactly how important it is for team members to be able to effectively understand, communicate, and act on data. Adding NLG to their Tableau dashboards gave the company’s data analysts the power to move beyond dissecting and translating data for reporting to focusing more on their plans for action derived from their insights.

Allstate’s analytics team relies on Tableau to share valuable data and sales information to this group; however, even leveraging Tableau, working to support the entirety of the Allstate field agents can be a challenge. The sheer amount of data, insights, and end-users provides analysts the near-impossible task of supporting each and every individual user of their dashboards. Where the field agents ran into problems was knowing exactly what to do about it because the amount of data was too overwhelming for them. As a result, Allstate’s analytics team noticed low adoption and engagement with their dashboards.

By integrating the Wordsmith for Tableau Extension with their existing dashboards, Allstate was able to automatically turn their data into clear, easy-to-understand language directly within Tableau. Instead of creating a dashboard with visualizations to broadly support thousands of different people, Allstate now leverages the Wordsmith for Tableau Extension to create that same dashboard to individually support each agent, field sales leader, and territory sales leader with role-based insights and action items tailored to their specific performances and goals.

Enhancing their Tableau dashboards with Wordsmith increased adoption and engagement of their Tableau dashboards. Sales users across the nationwide enterprise at every level, from field sales agent to chief revenue officer, could finally interact with and utilize powerful data visualizations to drive ROI-producing next steps.

“There’s no way Allstate could produce what we’re doing today, having analysts spend time manually writing reports. We thought Wordsmith was a novel idea and wanted to jump on it.” – Ryan Dunn, Director at Allstate

Natural language generation isn’t a mystical, robotic machine that is coming after your job, replacing the workforce person by person. The purpose of NLG is to refine processes so you can do what you do best, the skills you’ve spent so much time developing. If you’re a marketer, NLG streamlines mass communication so you can focus your energy on building creative storylines that will hook your audience. If you’re an analyst, you get to spend more time truly analyzing what’s happening in a given dataset and forecasting outcomes to further the health of a company. NLG empowers you to go further with your passions and not be stuck performing time-consuming, repetitive tasks. Your expertise can now be scaled to grow your company, team, or client base.