From Sales to Finance to CS: Building Company-Wide Analytics at DocuSign
If you’re hoping for company-wide adoption of your business intelligence (BI) initiative, a one-size-fits-all approach won’t get you there. You’ll face different learning styles, staff reluctant to change, and unique workflows you hadn’t anticipated. But there is a better way.
Over the past three years at , we've seen tremendous success in our BI adoption. It wasn't always easy, but we’re now seeing data-enabled thinking as a widespread phenomenon across the company. Here’s how we’ve done it.
Tearing Down Data Silos
DocuSign is well-known as being an e-signature company, and there's a good chance you've interacted with our product in the past. If you've ever signed a mortgage or an apartment lease online, you've likely come across us. Today, nearly everything is signed electronically because paper documents are quickly becoming a thing of the past. But as our company has grown over the years, we’ve begun to expand into handling every part of that contract experience.
Before we started this BI initiative, our data analysis and visualization were fairly decentralized. Left unchecked, this will only lead to siloes in your company. Employees have no idea of their colleague’s work or how it might complement their efforts. We needed centralized data processes to tie everything together. We had to get a proper business intelligence (BI) solution and a data warehouse.
Before I started at DocuSign, they began building a data warehouse and chose a BI solution. Unfortunately, that BI platform proved to be inadequate. The platform couldn't even handle the data they threw at it. It took forever to load and would constantly crash. Keep in mind this was also a few years ago, when our data volumes were a fraction of what they are now.
By the time I joined DocuSign, they had switched from that failed BI platform over to . I had experience with Qlik in the past, although always in a consultancy capacity. I would go to a client's business, implement Qlik, build new dashboards, and help with general implementations.
That work was enjoyable, but joining DocuSign would be a chance for me to build a BI implementation that would last. I could grow the program and see its impact at the company. It was an exciting opportunity.
Our First Case of Adoption
As I mentioned before, a one-size-fits-all approach to adoption just won’t cut it. To be successful, you need to meet people where they are. That’s why we began by building dashboards for salespeople in the place where they lived: Salesforce.
Immediately, the sales teams loved that they didn't have to go anywhere else to use the solution. All of that insight and actionable intelligence was at their fingertips from a single screen. If you want to drive adoption quickly, build dashboards that make life easier for your sales team.
After this early momentum with QlikView, we expanded our efforts with . Our approach here was different. With QlikView, it made sense for my team to build the dashboards for others, since there’s a bit higher learning curve. But with Qlik Sense, we wanted a self-service model. That’s when things took off.
Our team serves largely a supporting role with Qlik Sense. We give users access to data sets—or sometimes they bring their own data—along with training and guidance. For the most part, our Qlik Sense users have become self-sufficient.
To put this into context, before Qlik Sense, about 90% of the dashboards across the company were built by my team. Now, that number is down to between 10% and 20%. We’ve completely flipped development on its head. It’s exciting to see users taking data into their own hands and building solutions that fit their needs. And we’re seeing this happen across the company.
If a business analyst is given a data model, they can build out charts and visualizations on their own. Even if they’re not a technical person. If a salesperson is trying to close a deal, they can see how customers are using DocuSign. Are they using what they purchased? What part of our solution are they loving the most?
A customer success person can use that same data to gain more insight into DocuSign's impact on a client. Are they underutilizing us? Why is that the case? What can we be doing better? These are the types of question that data helps us answer. Even the financial department uses this data to close the books every month. It’s refreshing to people in different roles finding value in these solutions.
Snowflake and Qlik
Over the past year, we've moved from our original data warehouse over to Snowflake and we've been exceedingly happy with the results. The entire infrastructure is not only scalable, but you also don't have to worry about things like indexing that shouldn’t be on our mind.
Qlik just sees Snowflake as another data source. For an end user, it’s the same seamless experience whether the data is from Snowflake, Salesforce, or SQL server. Qlik loads it in-memory and the users interact with the data through their dashboards. For DocuSign, about 95% of the data we’re serving users comes from Snowflake.
The primary difference we’ve seen switching to Snowflake is performance. Our old data warehouse was painfully slow. Overnight reloads were started at 1:00 a.m. and we were lucky if they finished by 9:00 a.m. Often, it would take longer. And these times are Pacific.
That meant someone in an east coast office might not get that data until noon their time. But with Snowflake and some Qlik transformations after the fact, that whole process takes maybe two or three hours. That up-to-date data is ready to go when people walk in the door.
Engaging for Engagement
Flash forward to today, and 80% of DocuSign's 4,000 employees are using QlikView or Qlik Sense monthly. But we never would have been able to get to that point if we were chasing some mythical one-size-fits-all solution.
Instead, we started by building a dashboard specifically for the people who needed it and we put it in the place where they would use it the most. Those early dashboards are still running—our sales team uses them constantly.
That's a piece of advice I would give to anyone looking to go through a similar transformation of their own: Get out there and talk to people. Ask them what they need. Build a solution that matches the actual, real-world requirements that they have. We made sure we captured their needs immediately and were able to present them in an easy-to-use manner.
When I look at what we’ve built over the past few years, I’m proud to have enabled so many people. Whether it’s sales or CS, teams can make better-informed decisions because they have reliable and consistent data at their fingertips. That’s the only place data should be.