Past Webinar Recordings-A Guide to Data-Driven Decision Making Webinar

Video Transcription

Video Summary

Caleb Fitzgerald of Black Aena Consulting presents a webinar on data-driven decision-making for businesses. He explains that growth comes not from having more data, but from defining clear objectives, asking the right questions, and using data to validate assumptions. He opens with the WWII “bullet hole” case study to show the danger of misreading data and emphasizes that the most important step is properly defining the problem.<br /><br />The talk distinguishes data work from decision work: data work focuses on gathering and analyzing information, while decision work turns insights into business action. Caleb outlines a three-step framework: define the problem, brainstorm alternatives, and implement the best option. He highlights common traps like confirmation bias and confusing correlation with causation.<br /><br />He then introduces decision matrices, including weighted matrices, as practical tools for comparing options based on criteria like cost, time, impact, and gut feeling. Examples include marketing and operations decisions. He also stresses the importance of interviewing customers, using open-ended questions, and maintaining clean financial and customer data. The session ends with Q&A on customer interviews, weighting criteria, and adapting matrix attributes to each business context.

Asset Caption

Companies that successfully use data to grow don’t do this because they have more or better data, but because they define clear targets, success criteria, and they know how to ask the right questions. In this webinar, we'll discuss how to define clear targets, how to determine your success criteria, and how to ask the right questions. We'll explain why this process works, how you can use data tools to help the process, and walk through case studies to see how to apply this to your organization!

Hosted by Caleb Fitzgerald, Principal, Black Gallina Consulting

Keywords

data-driven decision-making

business growth

problem definition

decision matrix

confirmation bias

correlation vs causation

customer interviews

weighted criteria