Most executives and managers say adopting AI and analytics is their top priority, however, only 1 of 3 of these projects succeeds. Further, the lack of analytics costs businesses some $242 billion annually from under optimized planning. Implementing AI has been elusive due to a lack of vision, voice, and clarity on the value of analytics, and how to achieve a culture of data-driven decisions. Module 1 of the Analytics Academy follows the book, “Implementing an Analytics Culture for Data-Driven Decisions”, to crystallize and articulate the Roadmap to implement an analytics culture and to give clarity to the four main components of Mindset, People, Process, and Systems. These components when aligned encompass a successful implementation path.
In Module 1 you’ll learn each of the four components of the analytics culture, then the assembly of these components into a Roadmap for how to implement analytics. You’ll conclude with an exceptionally enlightening use case where a highly successful analytics proof-of-concept project ended without its implementation, and where and why on the analytics Roadmap misalignment can cause a derailment.
Reviews much of Module 1, Class 1 (Digital Transformation) for repetition that’s essential to learning and covers the partnering evolution and roles of business partnering along with the capabilities ladder of analytics and the value creation. Masters the three I’s . . . Insight, Influence, and Impact to tell the business something it does not know with Insight that Influence decisions and Impact strategic direction.
Reviews much of Module 1, Class 6 (Systems) for repetition that’s essential to learning and covers a wide-ranging examination from reporting to analytics, the need to go beyond Excel, distinguishing between data visualization and analytics tools, followed by the strengths, weaknesses, and applications of those tools, as well as best practices, and introduces the concept of Systematic Intelligence™ to explore data to find insights.
Teaches the rules for analytics storytelling, benchmarks that make a “good” vs “bad” story, best practices for storytelling, and the form and format for storytelling. Using examples, you’ll learn about presenting to the audience, their characteristics, and see an example for the creation of an analytics presentation and its story.
Is critically important to build an analytics culture as you need to know the gap between your analytics aspiration from where you currently are on the analytics Roadmap. This class teaches what benchmarking is, why it’s important, and the benchmark framework to assess the three areas of Are You Ready, Are You Capable, and Are You Creating Value. The class concludes with reviewing an actual comprehensive benchmark.
In this workshop several students across multiple companies put together their plans for Benchmarking in their companies. Learn how they would approach Benchmarking from concept to justification to project plan.
Is a use case in operations in a large high-tech manufacturer where a senior director started with a concept of digital transformation but learned that was wrong. How he learned about analytics and rebuilt his analytics journey is enlightening in dispelling the misconceptions of digital transformation, the importance of the analytics benchmark, and the next steps to building an analytics culture for data driven decisions.
