Optimize your Big Data investments, decision making, and performance.
Big data analytics can provide an efficient and rapid way to explore customer preference and actions, and enable individuals and teams at all levels within the enterprise to make decisions that continuously inform enterprise strategy.
This one-day interactive workshop focuses on the capability development of two key Lean practices — Value Stream Analysis and Disciplined Problem Solving — as applied in a Big Data ecosystem. Your teams will engage in a series of structured, hands-on exercises, and will end the day with solutions specific to your organization’s unique challenges.
What you’ll gain:
A deeper understanding of Value Stream Architecture — engaging individuals at all levels within the enterprise with the virtual voice of the customer (Value stream discussion may be introductory, intermediate or advanced, based on the knowledge and practice level of workshop participants.)
Improved skills in Value Stream visualization and analysis — enabling faster identification, evaluation and prioritization of problems and opportunities
Experience in in Disciplined Problem Solving methods for four distinct Big Data scenarios: 1) Data-first breakthrough innovation, 2) Problem-first breakthrough innovation, 3) Problem-first incremental improvement, and 4) Data-first incremental improvement — all of which help teams sense and respond to emergent problems and opportunities.
Why Steve Bell and Karen Whitley Bell?
Cutter's Steve Bell and Karen Whitley Bell have championed the convergence and collaboration across technology communities (including DevOps, Agile, Scrum, ITIL, and others) through shared Lean principles and management practices in order to help enterprises simultaneously achieve operational excellence and rapid innovation.
For more details on how to bring Steve Bell and Karen Whitley Bell to your organization to help you maximize your return on your Big Data investments, complete the form below, or send an email to your Cutter Account Executive, or call +1 781 648 8700.