Keith Aumiller, Director of Advanced Analytics at AmeriGas joins the podcast today to discuss automation within the data field. Keith shares the insights he’s gained from a career spanning financial services, aerospace manufacturing, and the energy sector. They discuss the importance of data quality, the limitations and hype surrounding generative AI, and the role of advanced analytics in business automation. Keith also delves into the philosophical implications of full automation and offers practical advice on implementing and understanding large language models. This episode is packed with thought-provoking discussions on the future of analytics and its impact on business decision-making.
Key Takeaways:
- Educate on Data Limitations: Ensure your organization understands the limitations of data analytics tools like generative AI. Emphasize that they generate text, not ideas.
- Focus on Data Quality: Reinforce the importance of data quality. Implement robust data collection and cleaning practices to avoid the "trash in, trash out" problem.
- Balance Complexity with Simplicity: Use advanced analytics and automation tools where they add value but don’t neglect the power of simple, descriptive analytics for everyday decision-making within teams.
- Automate Wisely: Identify clear business cases for automation and ensure they have a solid ROI before proceeding to enhance efficiencies without causing undue disruptions to existing processes.
- Customize Data Practices by Industry: Understand that data quality and processes vary significantly by industry. Tailor your data governance and analytics strategies to fit the specific needs and realities of your industry.
Quote of the Show:
- “ You can have the best algorithms in the world, and if you don't have good data to base them off of, then you're not going to get good results.” - Keith Aumiller
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