When data democratization efforts are all said and done, 87 percent of efforts don’t deliver on the original goals.
There are many reasons for that. A lack of buy-in. A lack of resources. Skill gaps.
But succeeding with data democratization doesn’t have to be challenging. In fact, it can (and should) start with one use case.
That’s exactly what happened at UBS, where the challenge of improving a reporting process became a successful transformation. Here are 4 lessons Nick Bignell, Director at UBS Investment Bank, learned while spearheading democratization for a company operating in a highly complex and regulated space.
Lesson #1 — It’s okay to start small.
Democratization often starts small, solving a common, time-consuming problem such as reporting or transparency.
Bignell wasn’t looking to transform the entire analytics approach of UBS. He wanted to speed up time to insight.
Except, he didn’t have the tools to do it.
Some roadblocks included multiple data sets, manual and repetitive processes, and ad-hoc analysis — problems any department in almost any company faces. He automated key processes and was able to show how money was being allocated while providing transparency the company hadn’t seen before.
Lesson #2 — It’s a grassroots effort.
Democratization needs both alignment and buy-in from all departments — but it often starts with a small team of dedicated people. After Bignell showed success with his initial project, the number of people automating analytics grew to four. It then grew again to seven in six months.
It was the start of a movement.
The bank had a lot of data, but most of it wasn’t being used. Some of it was hidden. Some of it was siloed. And some of the data wasn’t as useful without knowing what it meant.
At the same time, UBS wanted to implement a new, centrally managed data science capability within the organization to increase analytic capabilities.
When an email went out asking for people who wanted to be involved, Bignell responded. After all, he didn’t want to lose access to his analytics automation tools. The result was the beginning of a democratization project that grew the user base from seven to nearly 3,000 users.
Lesson #3 — It’s a bumpy, bumpy road.
There are many barriers along the way to democratization, including:
- Access to tools and data
- Proving ROI
- Supporting growth
As he stepped deeper into democratizing analytics at UBS, Bignell knew that each barrier carried the potential to derail the initiative.
First, he needed to automate the activation of licenses so people could be up and running on their machines. The easier it is for someone to use something, the more likely they will adopt it.
After that, he had to prove to IT that people accessing the data could be trusted with direct access to a database. That required a scalable and governed approach to their data, starting with slow manual downloads, then advancing to RPA, and finally direct access.
As everyone got on board, he had to make sure they had support to encourage growth and learning. He grew internal champions and support groups for specific departments and purposes. UBS provided training, a centralized site with FAQs, and a community.
Lesson #4 — It’s a long but exciting journey.
Democratization doesn’t happen overnight. Even when a company has successfully scaled analytics, maintaining that success is still an ongoing process.
The journey for UBS started in 2015. While most of the democratization efforts have been completed, the goal now is to maintain the culture of excitement around the improvements.
What Bignell has found is that people are happier. They’re more excited about their work.
They’re not stuck in the weeds repeating processes, asking permission for data, and waiting for reports. They’re asking big questions, providing value, and seeing results from the work.
The result is more productivity and satisfaction in the work everyone does. And it all started with solving the issue of reporting.
Not everyone starts their data democratization journey in the same place — but they can all arrive at the same destination. To assess how far along the journey you are, take the Analytics Maturity Assessment and get a report that shows you what you need to do next.