Just came across this article (below) on balancing “reflexive” and “reflective” decision making. Since #codedataio started on #codaai to build it as a recommendation system for business decision making, my interest has always been piqued by decision making models people use in their businesses. Interesting closing statement by Marshall Goldsmith in the article: “what got you here won’t get you there.” Don’t you learn from “what got you here” to “get you there”?
I am curious:
What is the percentage of “reflexive”s vs. “reflective”s vs. ones with a “mixed” style?
How do you fit in data driven decision making with your decision making style? Are you making data driven decisions most of the time?
And with your businesses getting complex, I assume decisions are often based on several parameters that either didn’t exist before or did not contribute significantly in past situations. How do you consider the entire gamut of parameters and their impact on your decision making? Factors like Supply Chain irregularities, changing labor laws, seasonality – how are these incorporated in your data driven decision making?
To continue the discussion, are you using BI tools to make data driven decisions? Are these mostly reports and dashboards? Or self-service analytics? How much time are you spending daily on doing self service analytics? And are you making your decisions based on reports and dashboards? Do you know how your decision making affect the downstream decisions in your business? How do others know how your decision affected their decision?
We at #codedataio think that data driven decision making can be made better.
No reports. No dashboards. No isolated networks of decision making. Only recommendations that takes decision making in your business to the next step.
That’s the motivation behind #codaai. #codaai is a Decision Automation System powered by #codamind – our AI platform that powers decision making for Plant Performance (#codaline), Service Excellence (#codacare) and Workforce Utilization (#codaforce).