Difficulties of a Nascent Big Data Platform
To develop intuition around the knowledge challenges facing ADP, user research was conducted including over 20 interviews, two workshops, a community survey, and countless whiteboard diagraming.
Distinct user groups
The community survey revealed distinct user groups within ADP, each of which had their own data needs, technological proficiencies, and preference for learning.
Articulating User Needs
Interviews with data engineers, data analysts, product owners, and team leads suggested that knowledge needs varied significantly across teams. Whereas individual contributors commented on the need for step-specific, detailed instructions, teams spoke of the need for high-level value proposition – how can they build a project around ADP?
“My biggest complaint about ADP is that no one knows what data is in there.”
– Data Analyst
“Understanding the process and contact points would have cut the time in half.”
– Data Engineer
Identifying Resource Gaps
An audit of the existing ADP knowledge bases was conducted to target most troublesome areas. While knowledge gaps were discovered throughout the entire ADP process, it was the uncertainty at the beginning stages of engagement – when a business team investigates capabilities of the data platform – that offered the most potential. A team cannot use the platform if they don’t know what it can do.
The value of ADP needed to be communicated more clearly and technical support needed to support individual contributors throughout the process. Improving the overall user experience of the platform would therefore require a two-fold solution:
Non-technical users don’t understand how ADP can deliver unique value to their teams
Technical users need standardized process documentation in order to create meanginful value for their team