A modern data strategy is critical to the successful execution of an analytics program.
David Dadoun, chief data officer at Bombardier Recreational Products (BRP), outlined the dos and don'ts of building a modern data strategy in a session on Sept. 21 during Real Business Intelligence, a virtual conference hosted by Dresner Advisory Services,
Dadoun joined BRP, a Canada-based maker of snowmobiles, jet skis and other recreational vehicles, just six months ago.
Upon his hiring, he was tasked with overhauling the enterprise's analytics operations. Before taking any steps to modernize BRP's data strategy, however, he conducted meetings with almost 80 different data employees in both local and international offices to find out as much as he could about BRP's existing analytics operations and what changes he might accomplish.
He then tailored BRP's data strategy based on what he discovered. Any organization needs to tailor its data strategy to its individual needs, he emphasized.
But there are general best practices, beginning with a cloud-based data platform. On top of that, however, is implementing what he termed a domain federated data strategy.
Domain federation is a strategy that centralizes the architecture, governance and security of an organization's data operations but creates flexibility beyond that centralization by establishing domain teams. Those teams then develop data assets that enable knowledge workers across multiple departments to access and use data to drive the decision-making process.
"In domain federation, we look at eliminating bottlenecks, scaling our ability to deliver value across data products, those products are interoperable, and the fact that those products are interoperable creates a network effect that drives the value of data," Dadoun said.
Typically, organizations have developed either centralized, decentralized or federated data strategies, according to Dadoun.
A centralized data strategy puts a single data team in charge of all data-related matters, meaning that regardless of whether an analytics project is for the human resources department or finance department, among others, the data team undertakes the project and turns over a finished product when it's done.
Advantages of a centralized strategy include a guarantee that best practices will be enforced and a common data architecture for all projects. Cons, however, include the loss of business proximity to the project, bureaucracy and an inflexible structure.
A decentralized data strategy, meanwhile, gives each department its own data team with those teams reporting to department heads rather than a chief data or chief analytics officer. Advantages are proximity to the business -- the data teams and data consumers work closely together -- and flexibility, but disadvantages include the absence of common standards and development of data silos.
