I used to work with organizations to support their software evaluations, selections, and implementations. What regularly started as a desire for greater visibility into data, generally turned into a need for better management of data across their ecosystems. Basically, organizations cannot look at individual data and analytics projects without evaluating their needs in a cohesive manner. The reality is that selecting a new set of tools for data optimization requires a lot of effort. Organizations need to do the following - at the least:
- Evaluate their current infrastructure to make sure they have the components they need.
- Identify modernization needs that may exist, including how to structure a hybrid data ecosystem and what needs to be migrated to the cloud.
- Monitor their current data pipelines to identify gaps in data access.
- Evaluate the roles people play and how they interact with data.
What do these considerations have to do with support?
The more seamless an implementation is, the less technical support will be required over time. Also, organizations that conduct a thorough evaluation of their needs can better define their support requirements. Many solution providers offer tiered support, and companies need to understand how support options address their challenges.
Some companies have internal data teams that can support development, while others need to leverage professional services to get solutions up and running. As a company expands their toolsets, support needs can become more complex and may involve several providers. Consequently, understanding what an organization needs, what training is required, how people interact with technology, and support expectations, will influence how a business looks at and chooses their level of service.
It becomes important to ensure that a software provider meets those needs and provides dedicated service to ensure Customer success over time.