How Do You Use Data To Make Better Decisions? - With Some Of Our Favorite Guests - Making Better Decisions - Episode #26 Making Better Decisions: Leaders In Data podcast

50:56

What does AI consciousness mean? Today, Stephanie Shipp, Director of Business Analytics at Beacon Building Products joins to hash out this exact question, drawing from her background in philosophy and AI. Stephanie emphasizes the importance of balancing speed, insights, and accuracy in analytics. She talks about the need for setting clear expectations with stakeholders using accuracy scores and the importance of understanding the business context. The episode concludes with a discussion on the challenges of rapid technological advancements and the need for continuous learning and skill development in analytics. Key Takeaways: Balance Speed, Insights, and Accuracy: Emphasize the importance of finding a balance between speed and accuracy when analyzing data to make timely and informed decisions. Understand and communicate the trade-offs to stakeholders clearly. Set Clear Expectations with Accuracy Scores: Implement accuracy scores or similar metrics to manage stakeholder expectations better. By doing so, you can help set realistic expectations about the reliability and precision of data insights. Report Real-World Impact: Move beyond basic reporting metrics to provide insights that are actionable. Help stakeholders understand the broader implications of the data, rather than just presenting the numbers. Focus on Fair Metrics: Implement fair metrics in your analytics to account for variables such as seasonal changes, business days, and other relevant factors. This ensures more accurate performance evaluation. Embrace Challenges and New Discoveries: Foster an environment where new ideas and anomalies are explored. Encourage your team to be curious and to pursue insights that may challenge the status quo. Quote of the Show: “ Understand the business, understand changes in the business, and don't lose sight of that.” - Stephanie Shipp Links: LinkedIn: https://www.linkedin.com/in/stephanieshipp1/ Website: https://www.becn.com/ Website: https://www.unc.edu/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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The Art of Dodging Disaster - Sashi Tadinada - Making Better Decisions - Episode #50 34:42

9天之前34:42

34:42

How can we effectively manage risk? Sashi Tadinada, Vice President of Actuarial and Analytics at NFP joins the show today to hash out risk management and probability. Sashi dives deep into the importance of feedback in data modeling. Sashi and Ryan discuss the common misconceptions about data models, the role of iteration, and how to effectively communicate the range of outcomes to stakeholders. The conversation also explores how businesses can prepare for catastrophic events, although rare. This episode provides valuable insights for business leaders on making informed decisions using data analytics. Key Takeaways: Prioritize Real-World Feedback: Constantly incorporate feedback from real-world data and stakeholders to improve and iterate on models and solutions. Educate Stakeholders on Model Limitations: Ensure that stakeholders understand the probabilistic nature of models to prevent misconceptions about their accuracy. Focus on Risk-Adjusted Decisions: Make decisions by weighing the potential benefits against the risks, considering both average outcomes and extreme possibilities. Educate About Probability Misconceptions: Raise awareness about common misconceptions in probability, such as underestimating high-probability events and overestimating low-probability, high-impact events. Foster a Learning Culture: Share books and resources on probabilistic and statistical thinking, like Nassim Taleb's "Black Swan," to deepen understanding among team members. Quote of the Show: “ I spend my entire time modeling the real world in some way, trying to predict something. The main important thing for me always is how useful it is.” - Sashi Tadinada Links: LinkedIn: https://www.linkedin.com/in/sashi-kanth-tadinada/ Website: https://www.nfp.com/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Navigating Data Tides - Parag Shrivastava- Making Better Decisions - Episode #49 37:37

16天之前37:37

37:37

“ The focus is on driving the business outcomes and the last mile delivery.” Ryan welcomes Parag Shrivastava, the Global Director and Head of the Data and Analytics Portfolio at Hewlett Packard Enterprise. With nearly 25 years of experience in the field, Parag discusses his journey ranging from electrical engineering to roles in major companies like Sama, Deloitte, and McKesson. They discuss the importance of turning raw data into actionable business outcomes, focusing on last-mile delivery, balancing data infrastructure, and the human element involved in data storytelling and adoption. Parag also touches on crucial aspects of change management and shares practical applications of traditional machine learning, LLMs, and AI in improving supply chains and optimizing healthcare systems. Key Takeaways: Focus on Business Outcomes and Last Mile Delivery: Ensure that data initiatives include clear plans for implementing and using insights to drive productivity and performance improvements. Balance Infrastructure with Actionable Insights: While keeping infrastructure robust and modern is crucial, the emphasis should be on actionable insights that directly benefit the end-users. Data Storytelling and Simplicity: Ensure the data insights are presented in a simple, consumable format. Dashboards and reports should be easy to understand and actionable to facilitate better decision-making. Implement Incremental Changes: Embrace an agile approach to data projects. Deliver value in incremental steps rather than trying to roll out everything at once. Change Management Across All Phases: Effectively manage change by involving users early in the ideation, execution, and operational phases. Use design thinking and continuous feedback loops to improve the adoption and usability of data initiatives. Quote of the Show: “ It's a data-driven decision. It's not based on emotions.” - Parag Shrivastava Links: LinkedIn: https://www.linkedin.com/in/pshr/ Website: https://www.hpe.com/us/en/home.html Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Building Trust and Frameworks in AI - Catalina Herrera- Making Better Decisions - Episode #48 44:51

23天之前44:51

44:51

“It’s not just about the cool shiny tool.” Today Ryan welcomes Catalina Herrera, Field Chief Data Officer at Dataiku. She discusses her extensive background in engineering and AI, emphasizing the importance of data governance, trust, and frameworks in achieving data-driven success. She explains that effective data use involves seamless organizational collaboration, clear roles, and responsibility. She touches on challenges faced by both large and small organizations in deriving value from data, highlighting the need for digitalized processes and AI literacy. The two also dive into the necessity of holistic frameworks for maintaining data integrity and avoiding negative outcomes in AI deployments. The episode highlights the essential balance between technical infrastructure and human factors in leveraging data for better business decisions. Key Takeaways: Foster AI Literacy: Ensure that your team and leadership are well-versed in AI and data concepts. This includes understanding the basics of machine learning, data governance, and how data-driven decisions can benefit the organization. Break Down Silos: Eliminate data and team silos to promote collaboration and integrated data pipelines. Enable Proactive Maintenance: Don’t just focus on the shiny new tools. Regularly maintain and update your data infrastructure. Ensure your systems are resilient and capable of delivering accurate insights over time. Measure and Communicate ROI: Regularly measure the ROI of your data initiatives and communicate these metrics clearly to stakeholders. This helps demonstrate the tangible benefits and justifies continued investment in data and analytics. Adopt a Framework for Data Integration: Use integrated frameworks to connect various data assets and analytics tools. This approach helps provide a holistic view of data and ensures that insights are generated within a consistent and controlled environment. Quote of the Show: “ Without trust, you don't have a group of people making better decisions, and that trust doesn't happen if you don't know that behind the scenes you have a framework.” - Catalina Herrera Links: LinkedIn: https://www.linkedin.com/in/herreracatalina/ Website: https://www.dataiku.com/ Paint by Numbers: https://thetasteofbalance.com/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Dissecting the Ocean of Data - Yin Warner - Making Better Decisions - Episode #47 40:53

30天之前40:53

40:53

We’re going all-in on a customer-centric mindset! Ryan welcomes Yin Warner, Senior Director and Head of Enterprise Data Management at First American to discuss a range of topics, including the balance between data accuracy and speed in the financial sector, risk management, the challenges of enterprise data management across different reporting pipelines, and the importance of data literacy and effective communication. Yin also discusses her curiosity-driven approach to problem-solving, her research interests outside of work, and the value of ongoing learning and networking. Key Takeaways: Instill a Customer-Centric Mindset: Encourage your team to apply a customer-centric approach when using data for decision-making. Understanding customer behavior and needs helps break down silos and maximizes data value. Emphasize Business Context: Make sure your data initiatives are closely aligned with business objectives. Data should be used to drive business outcomes and solve real business problems. Start with Focused, Iterative Projects: Avoid trying to solve all data challenges at once. Start with focused projects that deliver tangible business value and build from there. Balance Decentralized and Centralized Data Functions: Depending on the organization’s size, consider whether to decentralize data analytics functions for greater agility and efficiency or keep it centralized for consistency. Manage External and Internal Data Reporting Needs: Understand that different stakeholders will require different types of reports and data contexts. Create systems that can handle both internal performance metrics and external regulatory reporting smoothly. Quote of the Show: “ I believe data really is the footprints that we left behind through what we do, how we interact business-wide.” - Yin Warner Links: LinkedIn: https://www.linkedin.com/in/yin-warner/ Website: https://www.firstam.com/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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The Human Touch in Analytics - Bhupi Arora - Making Better Decisions - Episode #46 44:57

5 weeks之前44:57

44:57

Today we discuss the human touch in analytics with Bhupi Arora, VP of Business Data Analytics and Insights at Hitachi Vantara. The discussion delves into the challenges of using data to inform decision-making in an era of overwhelming data abundance. Bhupi shares insights on connecting fragmented data, ethical AI use, and the importance of maintaining a narrow focus on business outcomes. They also explore the future of analytics, the role of change management, and the human elements essential to navigating the evolving landscape of data and AI. Throughout the conversation, Ryan and Bhupi emphasize the need for a strategic approach to data and analytics, balancing technological advancements with empathetic leadership. The episode wraps up with reflections on the optimistic potential of AI to drive positive change across diverse sectors and regions. Key Takeaways: Focus on Strategic Objectives: Clearly define what your organization aims to achieve with data and analytics. Empathy in Change Management: Use empathy to understand stakeholders' motivations and resistance. Scaling Analytics: Create a coherent, unified vision for data across the organization to improve decision-making. Blinders for Focus: In the face of overwhelming data and tools, focus on the most critical business questions and use cases. Then, gradually expand your scope rather than attempting to address all at once. Promote Analytics Internally: Address the "marketing problem" for analytics by clearly defining and demonstrating its value within the organization. Quote of the Show: “ Making sense with the data that we have today without drowning in its chaos is what matters the most.” - Bhupi Arora Links: LinkedIn: https://www.linkedin.com/in/bhupindersarora/ Website: https://www.hitachivantara.com/en-us/home/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Driving Data-Driven Change - Robin Sutara - Making Better Decisions - Episode #45 46:39

6 weeks之前46:39

46:39

What happens when technically inclined people work with non-technical individuals? Robin Sutara, Field Chief Data Strategy Officer at Databricks, says that is where the most valuable contributions come from. Robin shares her journey from repairing Apache helicopters in the U.S. Army to holding prominent roles at Microsoft, and her contributions to the field of data strategy and AI. She discusses the importance of using data in everyday decisions, the challenges of implementing data-driven transformations in organizations with legacy systems, and the crucial role of data engineering. Robin also emphasizes the need for greater diversity in data roles and highlights her involvement with Women Leaders in Data and AI, an initiative aiming to increase gender representation in the field. The conversation provides valuable insights on the evolving landscape of data and technology and the importance of bridging technical capabilities with domain expertise. Key Takeaways: Recognize Everyday Use of Data: Understand that data is already a part of daily decision-making processes. Encourage organizational members to see data usage as a natural extension of their current habits. Rethink People, Process, and Operations: Emphasize the role of people and processes in successful data transformation. Foster Domain Expertise Integration: Use diverse perspectives to enrich data solutions and spark innovation. Articulate the Value of Data Engineering: Communicate the ROI of data engineering efforts by referencing cost savings, productivity gains, and unique insights. Establish Clear Data Governance: Define and enforce policies for data quality, metadata management, and lifecycle management. Quote of the Show: “ I really wish people would come to the realization that data is not this outlier thing. It's not a new or novel concept. It is something that you're already using today.” - Robin Sutara Links: LinkedIn: https://www.linkedin.com/in/robin-sutara/ Website: https://www.databricks.com/ Check out our SubStack! https://substack.com/@makingbetterdecisions1 Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Embracing Human Elements in Data - John Giaquinto - Making Better Decisions - Episode #44 41:55

7 weeks之前41:55

41:55

Biases are the setback to human involvement in data-driven decision-making. This episode with John Giaquinto, VP of Loyalty, Personalization, and Analytics at Rite Aid, discusses the intricate dynamics of human behavior and data-driven decision-making. John shares his extensive experience in marketing, advertising, and customer analytics, emphasizing the importance of interpreting data correctly and challenging preconceived biases. Throughout the conversation, John and Ryan explore the concept of proactive vs. reactive data analysis and the significance of exploratory efforts. They delve into the specifics of loyalty-based marketing, discussing long-term incrementality, consumer behavior, and the challenges faced in a constantly changing business environment. Key Takeaways: Understand the Difference Between Data and Insights: Ensure that your team and stakeholders understand that raw data is not inherently insightful. It needs to be analyzed and contextualized to extract actionable insights. Balance Reactive and Proactive Analysis: Determine an effective balance between reactive reporting (answering specific business questions) and proactive analysis (exploring new opportunities). Foster Exploratory Analytics: Allocate resources and create an environment that supports exploratory analysis. This can help uncover new avenues and opportunities that would otherwise remain hidden. Human Element in Analytics: Acknowledge and address the biases and cognitive limitations. Train your team and stakeholders on fundamental behavioral economics concepts to improve decision-making and reduce bias. Leadership Buy-in: Strive for top-down support and belief in the power of data. The data culture has to be endorsed from the executive level to permeate effectively throughout the organization. Quote of the Show: “ You need to do things to make sure you're taking your own bias out of it and that you're actually providing information with that data.” - John Giaquinto Links: LinkedIn: https://www.linkedin.com/in/johngiaquinto/ Website: https://www.riteaid.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Navigating the Last Mile - Nachiket Mehta - Making Better Decisions - Episode #43 47:28

8 weeks之前47:28

47:28

Nachiket Mehta, the Head of Data and Analytics Engineering for Global Operations at Wayfair joins today to discuss navigating the last mile of data decision making. Nachiket shares his extensive experience in software development, consulting, and data engineering. They also discuss the importance of translating data into actionable insights and the best practices in data governance and AI application. Nachiket emphasizes the importance of stakeholder alignment, data contracts, and automated governance. He also explores upskilling employees for AI and the role of data in making better strategic decisions. Key Takeaways: Focus on Business Impact: Always start with the question of what business impact you're trying to achieve. Data Contracts and Governance: Implement a solid governance model with data contracts. This could include defining roles, maintaining clear ownership, and using a versioned repository for data contracts to avoid miscommunication and errors. Handling Ad Hoc Requests: Differentiate between ad hoc and long-term data use cases. For urgent, short-term needs, use scrappy solutions temporarily but ensure anything productionalized meets governance standards. Balancing Speed and Governance: Develop a balance between the need for quick answers and the adherence to governance policies. Establish a flowchart or decision tree that guides staff in correctly prioritizing tasks. Structured Planning Processes: Link your data initiatives to the company’s strategic planning processes. Make sure data-related goals are clear and aligned with the company's larger objectives. Quote of the Show: “ Don't try to overcomplicate it and add a lot of additional layers, middlemen, middle steps.” - Nachiket Mehta Links: LinkedIn: https://www.linkedin.com/in/nachiketmehta/ Website: https://www.wayfair.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Diving Into Data: Beyond Lakes and Swamps - Mark Brady - Making Better Decisions - Episode #42 52:09

9 weeks之前52:09

52:09

Mark Brady, Deputy Chief Data Officer for TRMC at KBR joins the show today to hone in on data knowledge and management best practices. With an extensive background in mathematics and computer science and experience in various industries, Mark discusses the essential elements of effective data management. He critiques common data science practices, such as the flawed concept of the data life cycle and the misuse of terms like 'data lake.' Mark emphasizes the need for rigorous, structured approaches and outlines the four levels of knowing in data science. He also introduces the notion of next-generation data management and models like the Active User Model and the Notified User Model. This episode is packed with insights on how organizations can improve their data practices to make better, more informed decisions. Key Takeaways: Adopt Next Generation Data Management Principles: Focus on structured, well-defined data management practices rather than relying on buzzwords like "data lakes." Ensure your data is integrated and not siloed to avoid "data swamps." Emphasize Data Structure: Use structured data models to enable automation and ensure accurate and consistent data processing and analysis. Understand the Four Levels of Knowing: Having the data, knowing what data you have, understanding the data, understanding the data in the context of other data. Clarify Terminology: Make sure everyone involved has a common understanding of key data management terms like "data lake," "data warehouse," and "data mesh." This avoids confusion and ensures everyone is on the same page. Focus on Rigor and Precision: Adopt a rigorous and precise approach to your data practices. This will lead to more reliable outcomes and better decision-making capabilities. Quote of the Show: “ It turns out that we don't actually manage data in a data life cycle, nor should we manage in a life cycle.” - Mark Brady Links: LinkedIn: https://www.linkedin.com/in/mark-brady-18274321b/ Website: https://www.kbr.com/en Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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The Automation Conversation - Keith Aumiller - Making Better Decisions - Episode #41 43:25

10 weeks之前43:25

43:25

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 Links: LinkedIn: https://www.linkedin.com/in/keithaumiller/ Website: https://www.amerigas.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Knowing the Data’s Purpose - Charles Link - Making Better Decisions - Episode #40 50:28

11 weeks之前50:28

50:28

Today, Ryan Sullivan is joined by Charles Link, Senior Director of Data and Analytics at ReWorld Waste. Charles shares his extensive experience spanning marketing, financial analysis, IT, and data management. They discuss the importance of understanding the purpose behind data creation, the significance of having clear data definitions, and the value of conversations with both data creators and stakeholders. Charles also emphasizes the importance of artificial intelligence as a tool that needs to be understood properly and integrated thoughtfully. This episode brings practical strategies for balancing data accuracy with practical business processes, securing sensitive data, and embracing AI for future business enhancement. Key Takeaways: Understand the Purpose of Data: Data is created for specific purposes. It's crucial to ensure that you understand the context and intended use of data before acting on it. Balance Sales and Data Quality: Organizations need to find a balance between minimizing sales friction and maintaining clean data. This can be achieved by integrating data requirements into the normal workflow of sales activities. Adopt a Process-Oriented Approach: View data as an integral part of business processes. Engage with data creators and stakeholders at the beginning of any project to ensure clear data definitions and requirements. Implement a Data Dictionary Incrementally: Start with the immediate data needs of current business initiatives and build out your data dictionary graduall. Focusing on what delivers business value will provide compound returns over time. Enhance Human Communication: Use advanced technologies to augment rather than replace human interactions. Quote of the Show: “ Look at everything as a matter of process and think of data as the blood cells that flow through the veins of those processes.” - Charles Link Links: LinkedIn: https://www.linkedin.com/in/charles-a-link/ Website: https://www.reworldwaste.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Crafting Narratives for Data Storytelling - Jeff Nieman - Making Better Decisions - Episode #39 44:36

12 weeks之前44:36

44:36

Today, Ryan interviews Jeff Nieman, Senior Director of Data Strategy and Visualization at Best Buy. Jeff shares his extensive experience in data governance, data literacy, and AI's role in improving data cataloging and storytelling. He emphasizes the importance of trust in data, creating accessible data catalogs, and achieving balance in data strategy to ensure ROI. Jeff also sheds light on the concept of proactive data analytics and predictive modeling, underscoring the need for strong business partnerships and a thorough understanding of business contexts to maximize data utilization effectively. Key Takeaways: Prioritize Data Trust and Accessibility: Develop an easy-to-navigate data catalog to make data sources easily searchable and accessible. Harness AI for Efficiency: Use AI tools to automate and streamline data cataloging and metadata creation processes. Utilize Storytelling Techniques: Develop data visualizations and dashboards that not only present data but also tell compelling stories that are easy to understand. Cultural Change from the Top: Ensure executive leadership is educated on the value and potential of data analytics. Quantify the Value of Analytics: Tie predictive models and analytics projects directly to business outcomes and financial performance. Quote of the Show: “ It's not just enough to get good data. You have to know how to understand the data. How to better tell the story, how to better help people become literate and fluent in the area of the data.” - Jeff Nieman Links: LinkedIn: https://www.linkedin.com/in/jeffreynieman/ Website: https://www.bestbuy.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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The Trifecta for Better Business Decisions - Nikhar Shah - Making Better Decisions - Episode #38 47:27

13 weeks之前47:27

47:27

In this episode of Making Better Decisions, host Ryan Sullivan speaks with Nikhar Shah, VP of Data Analytics and Forecasting at LPL Financial. Nikhar shares his academic background in computer science, management information systems, and data science and recounts his extensive experience in the data industry. He discusses crucial skills for making data-driven decisions, emphasizes the importance of combining technical skills, problem understanding, and communication, and delves into the differences in working in data analytics between India and the United States. Nikhar also touches on current challenges in the field and the impact of AI and ML on business processes. Key Takeaways: Develop a Balanced Skill Set: Emphasize the importance of technical skills, problem-understanding, and communication in your team. Embrace AI and ML Applications: Leverage your company’s internal data to create personalized GPT models to enhance decision-making and productivity. Foster Mathematical Intuition: Provide resources for team members to develop these skills, which are crucial for making better decisions using data. Implement Forward-Looking Analytics: Move from historical BI reporting to integrating forecasting and predictive analytics in your business intelligence tools. Promote a Culture of Learning and Adaptation: Encourage curiosity and the exploration of new technologies and methodologies relevant to data science and analytics. Quote of the Show: “ It's fundamental to have a quantitative mindset and outlook to any problem. If you have that, I think you will be better equipped with making better decisions using data and having a little bit of more foresight on what you're trying to solve.” - Nikhar Shah Links: LinkedIn: https://www.linkedin.com/in/nikharshah/ Website: https://www.lpl.com/ Ways to Tune In: Spotify: https://open.spotify.com/show/6PpvYXoXjAYl8auDpmShYi Apple Podcasts: https://podcasts.apple.com/us/podcast/making-better-decisions-leaders-in-data/id1739178505 Amazon Music: https://music.amazon.com/podcasts/5e2ec300-0c66-4e24-8b01-0586af60235c/making-better-decisions-leaders-in-data Podchaser: https://www.podchaser.com/podcasts/making-better-decisions-leader-5672586 Transistor: https://www.makingbetterdecisions.live/episodes YouTube: https://www.youtube.com/@MakingBetterDecisions/podcasts…

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Data Predictions and Strategies for 2025 - Ryan Sullivan - Making Better Decisions - Episode #37 25:35

14 weeks之前25:35