Issue link: https://read.uberflip.com/i/1365400
It's not just about having the latest tools in the belt; it's about making it easy for your customers to get what they need. Start with an analytics Center of Excellence To go from strategy and intent to meaningful progress, one of the first steps is to identify and choose a leader and a team to spearhead the change, and to set up an analytics Center of Excellence (COE). The team typically starts small, with a few cross-functional roles to bootstrap it; the team will then grow to service more and more needs. Many large enterprises already have established shared services organizations that handle business intelligence or reporting. Those organizations can seed the analytics COE with technical and business roles. Similar to IT infrastructure organizations, they should not only supply the talent, but also be a key driver and sponsor for the effort. Because over time, these reporting shared services organizations will need to evolve to either adapt or become part of the analytics COE. The starter roles are often data engineers and architects, business intelligence analysts, and data scientists. The group needs to be led by someone who can work across multiple organizations, business units, and back-office groups, such as Finance and IT. Serve all your customers' needs One of the primary mental shifts that organizations need to make is moving from an attitude of "you must use our reporting solution and you will like it" to "what are your analytics needs and how can we help enable you?" Shared services reporting organizations are often report pushers and are not positioned to answer the difficult questions that come from employees, business leads, and customers. Therefore, when establishing a new analytics COE, it's important to establish tenets for the group which will set expectations for how the group acts and makes decisions. The analytics COE will need to service two types of customers: • The data and analytics consumers: The decision makers, data scientists, business intelligence (BI) analysts, and developers. These customers typically care about the ability to quickly access insights and data and the quality of the tools and services available to them to process and present data. • The data producers: The owners of applications, infrastructure, and devices who will supply the data into the platform. These customers need services like the ability to easily publish their data into the analytics platform and define a data contract. This includes the domain model of the data, frequency of refresh, and definition of policies, for example, a security policy outlining who can access their data.