Mike Carroll

VP, Corporate Transformation, Strategy Development and Innovation Georgia Pacific

In 2010, Mike left retirement to join GP as VP Innovation, where the MBM® philosophy and Mike’s mindset of innovation were in alignment. In 2019, he was named Innovator of the Year by ASPI, the Association of Suppliers to the Paper Industry. He also received the 2020 Visionary of the Year award from Smart Industry Magazine. He is involved in numerous innovations and transformations across GP and Koch Industries, and continues to be a frequently feature keynote speaker at industrial and manufacturing events around the world. He is recognized for his knowledge and experience in Leadership, Innovation, Organizational Transformation, and Intellectual Honesty.

Day 1: Americas

9:00 AM Digital Transformation Is An Evolution Of Decision Making: Identifying The Intersection Where Corporate Decisions Should Occur

Technology is an enabler of decision making. Who makes the decisions is usually reliant on reporting structure. Decisions are mostly made over the course of an extended period of time. There is nothing unreasonable about this construct. But this construct can only provide limited growth. Changing the dynamic of how decisions are made is the key to growth which can keep pace with competition and disruption. Mike shares his thoughts.


  • Understanding true actionable insights are identified at the plant level where value is created
  • Identifying how that front-line insight can inform support
  • Instilling a metric set into the entire end-to-end enterprise that respects that key insight
  • Asking 'what needs to get done,’ ‘what do you need to know to get that done’ and 'what is there to know that I don’t know,' to identify the facts and context to bring you key perspective
  • Realizing that who you work for depends on the problem being solved
  • Understanding that digital transformation has nothing to do with digital- it’s the transformation of how you think and make decisions 
  • Graphing the decision-making process with good Bayesian analysis