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- Serco Realigns its Customer Facing Technology Organization
Serco Realigns its Customer Facing Technology Organization
Published: 30 Aug 2021
With the recent acquisition of WBB, Serco Inc., a provider of professional, technology, and management services, has greatly enhanced and added several technology capabilities to its portfolio. Serco’s strength in delivering advanced technologies, such as artificial intelligence, machine learning, data analytics, and cyber, has positioned Serco to bid on more complex Federal government programs. To take advantage of this and other critical differentiators, Serco is centralizing its customer facing technology solutions and capabilities architects into one organization within Serco’s Agile Staffing department acquired with the WBB acquisition. This reorganization will strengthen the development, maturing, and cross collaboration of these technology-enabled capabilities. It also aligns with Serco’s strategy on how it delivers technology solutions, and the establishment of this technology competency unit provides Serco’s IT professionals and systems engineers a solid platform to build and grow their careers. The organization will consist of 6 Competency groups reporting to Sharie Bourbeau, Vice President of Agile Staffing.
- Enterprise Solutions Architecture
- Analytics and Technology Solutions
- Acquisition Management
- Engineering & Logistics
- Strategy & Operations
- Machine Learning
Agile Staffing Background Info
Serco’s Agile Staffing organization is comprised of over 200 Studies, Analysis, Program Management, Contracting, Engineering, Logistics, Machine Learning/Artificial Intelligence and Technology (Cyber, Enterprise Solution Architects DEVCON) Subject Matter Experts who support multiple high-end projects simultaneously. The agile staff group provides strategic, enterprise-level experience that is responsive to time sensitive requirements through surge support, “episodic augmentation” or through the backfill of temporary gaps in the workforce saving hours/days of research effort and learning curve implications