Logging a ticket with Information Technology (IT) to look into a problem or request a service can be cumbersome. It often results in long waits, not to mention a seemingly endless game of back-and-forth.
Now imagine having to request IT to develop a model you can use to help drive business decision-making from a variety of data points and sources. It’s a tall order, especially when having to translate the unique nuances of IT and business needs.
Marina Vassiliev, Lead, Self-Service Analytics with Questrade, describes having limited visibility into the various requests business units had submitted to IT. The discovery of this shared pain point ignited the creation of Questrade’s Enablement Program.
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Marina recalls how getting user buy-in to simplify the request process started with a targeted awareness campaign across various programs and services. Participants shared a desire to be able to develop self-sufficiency, while getting data insights more quickly and easily.
Once the team reached critical mass for support, a training program was launched. The program’s goal was to share information while also lending the support of a data scientist to deliver one-on-one support to key functions.
Data governance, particularly in relation to data privacy, was paramount. Marina notes that this focus served as “a key component to catalog data assets to help uncover how to link disparate things together safely and securely.”
“Our team managed to find a balance between stakeholder needs by splitting imagined prototypes from trusted workspaces,” she adds. This approach lent itself to the development of a checklist which paved the way for quality criteria to launch an internal certification program.
This certification program rewards trained super user contributors by exposing their work to environments which are highly visible across the organization. These contributors demonstrate a higher level of data ownership, and help set expectations for maintaining results and performance.
The success of the project rests in enabling IT teams to continue focusing their efforts on developing the robust data capabilities they are used to, including the oversight of regulatory and client-facing reporting. For business units, they have the flexibility to quickly and securely connect to source data to develop prototypes for their own modeling.
This approach has reduced re-work, source data misrepresentation, and isolation between departments — while informing better decisions.
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