In data-intensive businesses, information needs across the organization are high. Teams supporting analytic initiatives often struggle to achieve strategic analytic goals while managing day-to-day tactical requests. A formal demand management mechanism helps balance tactical and strategic delivery. An important component of prioritizing the analytic initiative lies in understanding its value to the organization. While some companies may set aside budgets for innovation projects, most organizations need to balance innovation with other work at hand. Value- and financial-based prioritization methods help teams quantify and qualify that value.
Organizational Value of Analytics
Most analytic teams provide a “free” service to their organization, making it difficult to quantify the value of the team and to effectively prioritize the analytic requests that come into the team. Analytic teams have long resisted the business chargeback models employed by IT because they believe that it gives them agility and flexibility in supporting their business partners. The upside is that this is true; the downside is that this can result in chaos—since there is no effective cost to a project or ways to identify trade-offs in completing one project over another, the team lacks any ability to prioritize their work and ensure that their resources are deployed on high value projects.
An inability to say no to business customers also results in resources ...