About the Milgard Center for Business Analytics

“Know where to find the information and how to use it—That's the secret of success” -Albert Einstein


CBA co-creates value with/for




The Center for Business Analytics (CBA)’s core purpose: Inspiring innovation through the strategic use of data, analytics, design and service thinking.

In today’s very complex business world, organizations must find innovative ways to differentiate themselves from competitors by becoming more collaborative, virtual, accurate, synchronous, adaptive and agile. They need to be able to intelligently respond to market needs and changes caused by mergers, acquisitions, new regulations, rapidly changing technology, increasing competition and heightened customer expectations. Incorporating analytics with intuitive design thinking are becoming mainstream processes for companies to run smarter and more efficiently.

Vision, purpose, mission

Our vision is:

To be the premier inter-disciplinary university center for business innovation at the interface of data, analytics and smart machines.

Our purpose is:

The CBA’s purpose is to promote within individuals, organizations, businesses, and communities the ability to understand, manage, use big data to make effective and efficient decisions, and to innovate digital products and services. These decisions cross the wide range of stakeholder needs to solve existing problems, create new opportunities, and improve the performance of organizations.

Our mission is:

To help individuals, businesses, and our community grow and succeed in our global digital economy by gaining actionable insights from big data for data-driven business decision-making through an educational process that uses research-based knowledge focused on issues, needs, and opportunities.

 

Goals, strategies, key activities

Goals:

  • Increase impact and awareness through research, education and service
  • Drive engagement at the intersection of business and academics

Strategies:

  1. Create positioning in the business-relevant domain of data science and innovation
  2. Establish robust portfolio of offerings for academia, business and community
  3. Deepen business and academic relationships
  4. Leverage digital technology to deliver ongoing value

Key activities:

  • Student Education: T-shape analytical thinkers and adaptive innovators. The Center serves as a catalyst and provides access to knowledge related to the use of analytics and "big data" for students (undergraduate and Masters).
  • Executive and Professional Development: The Center develops and delivers a number of short courses for working professionals interested in business analytics, service transformation, and technology innovation.
  • Problem-Focused Research: The Center works with companies to address problems by conducting and supporting cutting-edge research in data science with a business lens.
  • Advisory Board/Corporate Partnership: The Center’s corporate partners represent a range of industry sectors and bring to the Center diverse business interests and problems to advance the science of data and innovation.


The approach

  • Business: What are the problems and/or opportunities? Create/amend business processes, create new businesses, close existing ones and enter new markets. Necessary skills for achieving organizational impact and competitive advantages with strategic thinking, service transformation and evidence-based decision making, (e.g. communication, project management, process optimization, business ethics, privacy, organizational culture change).
  • Data: What data and/or digital service could solve this problem? Core methods for acquiring, storing, handling and representing data, and how to convert that data to information, knowledge, and wisdom for desired outcomes, data modeling and databases.
  • Analyze: What models and methods can I apply to solve this problem? Descriptive, predictive, prescriptive, cognitive/machine learning, visualization/storytelling, core analytical, statistical and computational techniques, regression and related statistical methods, data and text mining and cognitive analytics, and operations research methods.
  • Revolutionize: How to apply these concepts to our business? Key insights that can be gained only through hands-on experience working with and implementing analytical projects in a business environment.