Tableau

Tableau has evolved from nothing to where we are today because people want to use it. We put Tableau on our robust customer data sets…to quickly ask questions like ‘how many customers have a Freedom and a checking account and use the mobile wallet?’

We were early adopters of Tableau with version 4.0. Today we have three servers globally and 67 active instances, supporting 25,000 people globally. Tableau is an integral part of how we operate.

Tableau is so great because it talks to all these different softwares. And for us, this was a big milestone–tying them together and getting text mining into a dashboard. Our analytics staff strives to perform advanced analytics and build predictive models and machine learning solutions that enable the business to move forward.

Insights from our dashboards help us optimize call center operations to reduce the need for customers to call us multiple times. Monitoring these timely dashboards shows us that as the resolution rate and satisfaction index of customers go up, volumes for calls and dispatches–which are key cost drivers–go down

In three months, we not only had dashboards, but we had staff actively using this data, actively getting insights, actively taking action, and really making a difference for customers in each of our restaurants. Tableau was the ticket to take all metrics and understanding to that next level.

I think where Tableau has been most helpful with respect to our growth is creating simplicity in scaling. Once data is organized, it’s very easy to add another small multiple in our stack of visualizations related to a specific region.

By building one single network of Tableau dashboards that allows a user to see at the system level how are we doing, how are all of our hospitals doing, and to very rapidly drill down to the individual hospital and nursing unit, and down to a list of the affected patients in that unit, has been helpful for communicating and collaborating around improving many of our KPIs.

We went from inaccurate reports to a single data source, a single Tableau solution that allows people to go deep or provide high level information. It’s been an incredible way to help us achieve our goals at Schwab.

Tableau provided ARC’s customers the deep insights, advanced analytics, detailed performance intelligence and competitive benchmarking needed to enhance industry partnerships and operational success. Being able to easily track patterns and trends in sales and analytics embedded into their daily processes delivered a unique solution for our customers.

Airline BI offers a nice mix of data visualization and raw numbers … It’s the best of both worlds. Airline BI helps us stay on top of trends with a weekly analysis of agency performance and better understanding of how our O&Ds are performing, as well as monthly cost-of-sale metrics including market share and booking class.

Our enhanced BI product set was very well received. We now deliver highly valuable information that customers need, give them time to act on it, and cut down on a lot of the noise that interferes with the value inherent in the data.

Our Tableau deployment went viral. In less than two years, we have 20,000 users. And the reason for this success is because we’ve been able to strike the right balance between empowering the business, enabling better visibility, and instilling trust and governance in the data.

Adoption has been awesome. We had one user who literally danced when she accessed the dashboard… We helped her put words, ideas, and drawings to life in Tableau that meet her needs.

To really align the product–the end result–with what the end users needed, Tableau was the only thing that would offer the flexibility we were looking for.

Tableau has amazing data visualization and excellent customer support. It can be low cost at first, but this is mostly to get users in the door. Plus we feel Tableau is really only beneficial if you have your data in Excel or a CSV file, which can be uploaded to Tableau very easily. If you need connection to a database, you’ll need to have an IT staff skilled to create the SQL query to pull the dataset.