The pace of innovation never rests: How lessons from our past still influence us today

Everyone is talking about the need for innovation these days, but there are a lot of questions about the best ways to move forward. Even before the Covid-19 crisis hit, McKinsey found that 92 percent of company leaders thought their business models wouldn’t stay viable at the then-current rates of digitization, and the pandemic has only accelerated this need for rapid innovation in the digital world. 
 
As we’ve helped several customers navigate the uncertainty and find solutions, we always go back to what’s at the core of innovation at Tableau. A recent event was the perfect opportunity to pause and look at how we’ve also weathered uncertainty and increased our pace of innovation throughout the history of Tableau—and how these lessons still serve us today.
 
The IEEE VIS conference is the premier forum for academic and applied research in visualization, bringing together an international community to share ideas and celebrate innovation every year. It also hands out the Test of Time Awards honoring work that has endured and remained relevant for at least a decade or longer after its initial publication. This year, Tableau co-founders Chris Stolte and Pat Hanrahan, with their former colleague Diane Tang, received the 20-year Test of Time Award for their groundbreaking research underlying Tableau, a paper titled Polaris: a system for query, analysis and visualization of multidimensional relational databases.

The Polaris paper laid out several key ideas: Interactive specification of the visualization using a drag-and-drop user interface; the VizQL query language that described both the visualization and the data query; and the ability to live query relevant data directly from its database, eliminating the need to load data files into memory.

In 2003, Chris Stolte, Christian Chabot, and Pat Hanrahan founded Tableau based on this work, and developed Polaris from an academic prototype into the company’s first product—Tableau Desktop. Of course, academic prototypes are usually intended to demonstrate an idea not scale to market. To become viable, they had to transform their prototype into a product that could withstand daily use by many different people with various needs, data, and environments. Transforming a prototype into a product that could be shipped was not a trivial undertaking as many technical and product challenges stood between our founders and building a successful company.

When I joined Tableau in 2004, I was Tableau’s seventh employee jumping back into a developer role after leading engineering teams at another California-based startup. As a young company—even with an incredible new product—we had to constantly knock down technical challenges and think about how to be to be different. We focused on giving people new ways of asking and answering questions they couldn’t easily address with the existing tools they had on hand. That pushed us to figure out how to extend the original technology we had built around VizQL with even more new capabilities, including maps and geocoding, building statistical models, and supporting multiple data sources through blending and federation. This enabled us to leap ahead and show customers there were different and vastly improved ways of working with their data.
 
These early lessons in innovation still impact and inform everything we do in engineering and development at Tableau today. Early on, we learned to listen to what our customers were trying to accomplish, but we never stopped with only delivering what they asked of us. We also became customers of our own product by running our development team and the entire company on data analyzed with the product we were building. We didn’t want to miss any opportunities for improvements or just build what our customers needed right now. We wanted to reinvent how we could all work with data, then do it again and again, taking ourselves and our customers on a journey past how we were working with data today to a place we thought would be more powerful.  
 
In addition to being our own customer and critic, we knew that as a young, small company we had to demonstrate how Tableau worked and do it fast. We did this by often demonstrating our product using data that our customers provided. This turned out to be a highly effective way to see the almost immediate impact of connecting people to the meaningful insights in their data. In fact, on one sales engagement our former CEO Christian Chabot gave a demo to about 40 people at a customer site. The demo went well, but the group was distracted. Chabot wondered what it could be and asked for feedback. He was told, rather excitedly, that the team was distracted from his demo by the insights Tableau revealed in their data. We learned early on that giving people new ways to do things opens their eyes to better ways of understanding their businesses.
 
Today, we continue the search for new and better ways to work with data. Whether we are helping customers analyze their data using natural language with Ask Data, or helping them surface outliers and explain specific points in data by leveraging the power of AI in Explain Data, our work in AI only continues to grow now that we’re a part of Salesforce. We recently announced that we are bringing together Tableau with Salesforce’s Einstein Analytics to deliver the best analytics platform out there. This new platform will create even more ways for people to make the most of their data, from improving the quality of insights, to helping them act faster, to enabling smarter data prep and easier sharing. This is just the beginning of our innovations to come with Salesforce as a partner.  
 
Additionally, we are even more committed to making analytics accessible for everyone with our initiatives around becoming a data culture, where data is embedded into the identity of the organization. The World Economic Forum just released a report on the future of jobs with the main message that Covid-19 is accelerating the need for companies to scale remote work, speed up automation, and expand digitization. Old jobs will be lost and the newer ones will demand more advanced digital skills, including using data. In fact, the WEF listed the top in-demand job of the future will be for data analysts and scientists. Establishing a data culture is not an overnight process, but it’s a worthwhile and essential one and we hope our work—especially in programs to promote data literacy—can help everyone explore, understand, and communicate with data.
 
All these recent efforts build on what we’ve strived to do since the beginning of Tableau—give people new ways of working with their data. The original VizQL work is still the heart of our product and the work we have done since, including building new data platforms and applying good design principles to create highly engaging products. Everything we work on is to build on our mission to help people see and understand their data. We owe a great deal of thanks to the original groundbreaking work in VizQL that has truly stood the test of time.
 
We’re excited to continue to take that same focus, dedication, and excitement for innovation into the future. Today, as Tableau’s CTO, I’m focused on examining future technologies and product ideas that we can leverage to push our customers’ abilities to work with their data to new heights. And our R&D team remains steadfastly focused on pushing forward with new ideas and how to best turn those into the innovations that will continue to improve Tableau. If you’d like a more in-depth look at our research and development work, please follow our engineering blog.