Considerations

Data Team Organization Structure: Before initiating a new data program, you may benefit from reviewing how your data flows across the whole organization, and how members of the data teams provide analytical services. As Irina Sedenko, Research & Advisory Director at Info-Tech Research Group, suggests:

“I would always like to understand the organizational structure and operating model of the data science practice. Does the organization have a central data science team or are data scientists embedded within business units? Centralized or decentralized model?”

Regulatory and Compliance Demands: Knowing the regulatory and compliance structure you should adhere to will affect the data governance you need and how auditable those controls must be.

Define Your Success Criteria: Create the success metrics you would like to see throughout the life cycle before you embark on setting up the program. What do they expect to get out of the program 12, 18, and 24 months down the road? How will they know if the program is successful?

Toolsets and Skills: What tools do you have already? What do you need to procure? Are you going to perform any sort of application rationalization and/or standardization of tools? Or will your individual CDSs decide what works best for them?