“These days, if you just get a quarterly report or a monthly report, you’re kind of looking in the rear view mirror.” – Marc Zionts, CEO
Over the next three weeks, you’ll be getting the inside scoop at Automated Insights. From company vision and market approach to value positioning and product development, you’ll get a 360-degree view of what makes Automated Insights the industry leader in natural language generation.
First, I sat down with our CEO, Marc Zionts, to discuss the vision and goals of Automated Insights and what they mean for the future of business intelligence. As CEO, Zionts is responsible for the strategic direction of the company and execution of the business to accomplish short-term goals while constantly working towards long-term objectives necessary for driving the company to new heights.
Q: When you talk to prospects and companies around the world, what gets you the most excited about NLG and how might Automated Insights help drive that excitement?
A: What excites me is the fact we’ve found that by adding in a narrative to visualization platforms with our Wordsmith software, our customers can expand the number of people in an organization that can get the data, understand it quickly, and then process it correctly. They’re able to run their organization more effectively, to be more agile and, ultimately, more successful. Wordsmith helps increase data literacy by explaining what the data means interactively and in real time. So, when people start associating a visualization or dashboard with a narrative explanation, it increases their data literacy skills. At the same time, it helps democratize data, meaning more people in the enterprise can have access to that real-time information.
Q: You talked about making better decisions and touched on the cost of misinterpreting data. What are those consequences of misinterpreting data?
A: There is a real cost to organizations if they actually misinterpret data. Someone could be looking at data and think they know what it means but really don’t, and then make a decision based on their understanding or misunderstanding. That could cost an organization millions of dollars. This is just one of the costs associated with not having natural language generation as part of your data understanding through BI dashboards. There are two other costs associated with misinterpretation. The first often comes when people admit they don’t know what the data means. As a result, they reach out to an analyst to help them understand what the data means, which is costly in time, money, and resources. The second cost we know our customers experience is when they head into an hour-long meeting and spend 50 minutes of the meeting arguing about what the data means. Then, in the last 10 minutes, try to decide what they need to do about it. We think it makes more sense that everybody’s on the same page; everybody understands the data correctly and understanding is democratized across the enterprise. In that case, you now have a more valuable meeting dedicated to discussing action steps to further grow the health of your organization.
Q: Looking ahead at the outlook of NLG, where do you see Automated Insights and natural language generation heading into the next 5-10 years?
A: We give customers a tool that enables them to write with data. When I think about our roadmap and where I see NLG heading, specifically with Automated Insights, I see us going towards making that tool faster, better, higher-quality, and accessible to more people. That’s where we’re focusing our energy. For example, we’re increasingly adding in more machine learning and artificial intelligence capabilities. If you can just start selecting a few pieces of data and we can start suggesting the narrative that you’re interested, we’ve now sped up the time it takes you to deploy as well as decreased the time it takes to get to the value. At the same time, what makes us unique is our ability to do that and still allow you to edit our suggested narrative. We’ll learn off of what you say, but we’ll also allow you to control the language and narrative so it’s specific to your brand, your domain, and your industry jargon. Looking ahead, we see a combination of artificial intelligence and machine learning partnered with a deterministic system–a blend of both worlds.
Q: If you had to define Automated Insights in three words, which would you choose?
A: The three words that come to my mind are innovative, agile, and passionate. First of all, it’s all about having an innovative, product-oriented company. We’re a pioneer in this space. We were one of the leaders in coming up with the concept and implementing it in an open manner and a way that nobody else has using essentially any language that you choose. As I move onto agility, life is never exactly what you think. The markets aren’t exactly what you think. You need to be agile while still having a strategy that you’re trying to follow, but that means you have to be able to zig and zag a bit. Finally, I think it gets down to passion. Do you care about what you do? Do you enjoy what you do, who you do it with, the people you work with, the people you work for, the company and the culture? The product, do believe in it? Do you truly believe that we bring value to customers? I believe our team does.