Laying a firm foundation

High-spend and inconsistent standards for Business Intelligence (BI)

A leading manufacturer of medical devices, pharmaceuticals and biotechnology was plagued with low efficiency and high cost for BI across global operations. Lacking a centralized analytics strategy and delivery approach, each division within the company managed its reporting and analysis independently. Measurements were defined differently by country, region, or division, making it difficult to conduct meaningful performance comparisons region by region. Analytics teams were not strategically organized and deployed, leading to lack of focus, reporting delays, and excessive BI labor cost.

Offering—Software, standards and staff

The organization had undertaken a two-year global ERP implementation that resulted in the generation of a vast amount of business data that could be used for improved decision making. Deloitte worked with the organization to implement an enterprise business intelligence environment that captured this new ERP data and additional data sources moving forward.

However, the real value came with the evolution of the delivery model from a project-based model to a factory model. The factory model offered an effective way for the organization to develop, standardize and disseminate its own analytics strategy and structure across the globe. Usable data is now consolidated and standardized into formats that can be used to conduct analysis across supply chain, finance, transportation, patient metrics, spend analytics, bill of materials, and many other core business processes.

Managed by a highly skilled and certified Deloitte Project Management Office, the Analytics Factory has global reach, currently employing 70 onshore and offshore resources who possess both business and IT skillsets. The Analytics Factory helps the company to balance cost, accountability, risk, and ownership of analytics initiatives through the following capabilities:

• Single point of program/project governance
• Shared delivery model across a portfolio of projects
• Standard and consistent/repeatable method project delivery
• Managed resource pool scalable on demand
• Performance metrics tracking and reporting, including cost improvement

More functionality, lower cost, quicker turnaround

A model of structured growth, this analytics initiative evolved from a data warehouse, to multiple BI projects, into an ongoing analytics program that has launched an operational COE. With a consistent, scalable infrastructure, and the right people and processes in place, the company now experiences faster turnaround for its analytics needs.

This year, the company has enjoyed lower overall spend for BI. Using an efficient blend of onshore and offshore analytic talent, bill rates have been reduced by 55 percent for the Analytics Factory team. Furthermore, the ability to retain top talent on its “bench” (ETL developers, project managers and architects), has allowed experienced teams to ramp up quickly on new projects. This creates further economies of scale, as demonstrated and tested resources can migrate between projects without excessive downtime. As a result, productivity has improved. In 2013 alone, ten major projects have been completed, compared to two or three in years past.