The sheer amounts of data that organizations have access to today can help them better interact with their customers and provide an improved experience. However, limited funds mean that several organizations are scrambling to find enough money to finance their analytics endeavors.

The trick, according to experts, is to align different departments and encourage them to share both the data they have access to as well as their budgets, allowing the entire organization to invest in projects that wouldn't be affordable by a single department. "One of the most significant obstacles to turning raw data into actionable intelligence is the fundamental lack of effective data sharing across departments and divisions of the enterprise," notes Scott Schlesinger, head of business information management at Capgemini North America.

However, the first step is for business leaders to choose the organizational model they want their company to evolve into. Zubin Dowlaty, head of innovation and development at Mu Sigma, explains that most organizations choose one of two models: a purely decentralized model where analysts and data scientists are employed by specific departments with very little visibility and communication with their peers in other sections of the organization; or a centralized model which allows the whole company to leverage the resources of a central analytics team. But Dowalty notes that some organizations are opting for a more advanced federated model, which finds a balance between the two extremes by building a network of analysts in different departments, giving them visibility into different data resources and access to a shared budget. While the latter is more complex to implement, Dowalty says this is the way forward, especially for bigger organizations which want to make sure their analytical resources are made the most of.