In this episode of Mining Your Own Business, Data Scientist Xhoana Laska shares how she and her team are bringing data innovation to the field of industrial paint and coatings, an industry that became prominent in the late 1800s.

With her background in mathematics and statistics, Xhoana’s knack for numbers has come in handy in her role at National Coatings & Supplies | Single Source, Inc. She has spearheaded projects to save thousands of labor hours, optimize inventory processes, improve demand forecasting, and more.

Join us as our podcast host, Evan Wimpey, chats with Xhoana about interesting projects she’s worked on and insight she’s gained along the way!

In this episode you will learn:

⛛ The importance of identifying areas where data analysis can drive significant efficiency improvements
⛛ Why effective communication is crucial for stakeholder buy-in
⛛ The need to prioritize projects based on business-critical needs
⛛ The importance of creating a culture of learning that empowers employees

Quote
💬 “I enjoy working on problems that involve bringing solutions that can potentially save money or optimize and be efficient at the end of the day.”

Featured in This Episode

Xhoana Laska, Data Scientist, National Coatings & Supplies | Single Source, Inc.
From process optimization to demand forecasting, Xhoana Laska enjoys creating data-driven solutions for complex business problems. And that’s at the heart of her work as a data scientist for National Coatings & Supplies | Single Source, Inc. (NCS SSI).

With over three years of experience in the field, Xhoana has a knack for numbers and strong background in mathematics. She specializes in business process automation and statistical and machine learning modeling for procurement, sales, and marketing. She’s also a proud member of the Wolfpack at NC State University, where she received her Master of Statistics degree.

LinkedIn: linkedin.com/in/xhoana-laska

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction
00:50 Xhoana shares her journey into the field of data science.
01:56 Evan shifts the conversation to discuss Xhoana’s first project at NCS SSI.
06:31 Evan discusses the importance of stakeholder involvement in the project.
07:27 Xhoana explains the support provided by the IT team for data quality and accessibility.
10:08 Evan and Xhoana discuss data quality and tools used at NCS SSI.
13:41 The discussion shifts to the process of prioritizing projects at NCS SSI.
22:17 Evan invites Xhoana to share her ideas for future data science projects.
25:33 Evan wraps up the conversation with Xhoana.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

Explore the dynamic world of retail data analytics with Sravan Vadigepalli, Senior Director of Products and Engineering at Lowe’s. In this episode you’ll learn about the unique analytics challenges and opportunities in the home improvement space and how Lowe’s approaches product development.

During the chat Sravan also shares his thoughts on the future of data-driven innovation in retail. Grab some coffee and join host Evan Wimpey as he delves into the intersection of technology and customer-centric solutions. We hope you enjoy the conversation!

In this episode you will learn:

⛛ The importance of recognizing and adapting to the diverse needs of customers
⛛ Why data initiatives should be aligned with broader business objectives
⛛ How Sravan’s team uses a unique framework to streamline decision-making processes
⛛ The need for a balance between building internal tools and leveraging external solutions

Quote
💬 “For data folks like us, you need to get into the weeds of the business.”

Featured in This Episode

Sravan Vadigepalli, Senior Director of Products and Engineering, Lowe’s
Sravan Vadigepalli has spent the past decade building and curating data analytics teams in the retail industry. He specializes in translating data into insights and applications of Machine Learning/AI models to the ever-evolving retail space. Sravan did his MS in MIS from Oklahoma State University and an MBA from the University of Illinois Urbana-Champaign. Outside of work, Sravan is a self-proclaimed long-distance endurance runner.
LinkedIn: linkedin.com/in/sravanvadigepalli/

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction of the podcast and the guest, Sravan Vadigepalli.
00:45 Sravan Vadigepalli shares his background and career path.
02:53 Discussion on the differences in data challenges between various retail sectors.
8:24 Discussion on the process of developing data products and analytic products.
12:52 Explanation of the prioritization process for projects.
15:49 Discussion on the frameworks used for project prioritization.
19:31 Conversation shifts to evaluating internal versus external solutions for product development.
22:17 Sravan shares some ideas for the future.
25:10 Evan wraps up the show.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

When considering evaluation metrics for classification models, is it possible for one metric to rule them all? Join us for a lively debate between Aric LaBarr, Associate Professor of Analytics at NC State's Institute for Advanced Analytics, and Robert Robison, Elder Research Senior Data Scientist.

During the debate Robert champions AUC’s comprehensive measure of model performance, while Aric advocates for a broader perspective, emphasizing the importance of business context in metric selection. Tune in as host Evan Wimpey moderates the discussion, and gain valuable insight on what really matters when it comes to machine learning model evaluation. We hope you enjoy the conversation!

In this episode you will learn:

⛛ The importance of exploring various metrics to evaluate model performance

⛛ Why metrics should align with business objectives

⛛ The need for data science teams to invest time in feature engineering

⛛ Why a model's success relies not only on its performance but also on stakeholders' ability to understand and trust the insights it provides

Quotes
💬 “There's a difference between communicating the value of a model and distinguishing between which models are better.” –Robert Robison

💬 “If you can't explain the model to your stakeholders or business users, then it's not going to get implemented.” –Aric LaBarr

Featured in This Episode

Aric LaBarr | Associate Professor of Analytics, Institute for Advanced Analytics

LinkedIn: https://www.linkedin.com/in/ariclabarr/

Robert Robison | Senior Data Scientist, Elder Research

LinkedIn: https://www.linkedin.com/in/robert-robison/

Evan Wimpey, Director of Analytics Strategy, Elder Research

LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Evan introduces the debate topic and guests, Aric LaBarr and Robert Robison.
01:37 Robert begins his argument by defining AUC (Area Under the Curve) and its significance as a metric for classification models.
06:11 Aric begins his rebuttal, challenging the notion that AUC is the only metric to consider.
09:26 Robert provides a rebuttal to Aric's points.
11:48 Aric starts his rebuttal, focusing on communicating models to business users.
14:41 Robert responds to Aric’s points.
16:18 Evan asks Robert if certain cases may require metrics other than AUC.
17:03 Robert responds to Evan’s question.
17:53 Aric weighs in on the question.
19:37 Evan asks Aric if focusing solely on AUC may save time and costs.
20:30 Aric responds to Evan’s question.
22:20 Evan gives time for the debaters to ask each other questions.
25:30 The debaters share closing remarks, summarizing their positions.
29:14 Evan wraps up the show.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

In this episode Evan Wimpey sits down to chat with Nirmal Budhathoki. A seasoned data scientist at Microsoft, Nirmal has extensive experience in both cybersecurity and the tech industry.

During the conversation Nirmal discusses his unique career journey, from unexpected detours, including serving in the Army, to becoming a data scientist. He also talks about applications of machine learning in cloud security, emphasizing the need for proactive defense strategies. Additionally, Nirmal offers advice for aspiring data scientists and highlights the ongoing advancements in the field.

In this episode you will learn:

⛛ How individuals from diverse experiences can excel in data science

⛛ The importance of proactive defense strategies in cybersecurity

⛛ The need for community engagement and mentorship in the field of data science

⛛ How Large Language Models (LLMs) can be used to enhance cybersecurity measures

Quote
💬 “Security is never a compromise.”

Featured in This Episode

Nirmal Budhathoki, Senior Data Scientist, Microsoft
Nirmal Budhathoki is a Senior Data Scientist at Microsoft focused on cloud security. He has over 12 years of experience in the IT industry, including more than 5 years in data science. A dedicated learner, Nirmal holds master's degrees in information systems, business administration, and data science. He enjoys sharing his knowledge with others and has provided hundreds of free mentoring sessions to aspiring data scientists. He also conducts mentored learning for MIT’s Data Science and Machine Learning certification program in collaboration with Great Learning.

Nirmal also has experience working with the military—both as a security data analyst and through serving four years in the Army. He’s also passionate about solving data science problems aligned with product strategy and business outcomes. And in his free time, he enjoys applying his skills to sports analytics.

LinkedIn: https://www.linkedin.com/in/nirmal-budhathoki/

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Evan introduces the show and Nirmal Budhathoki.
01:01 Nirmal talks about his unconventional path into data science.
04:48 Nirmal shares how data science supports security and mentions specific use cases.
11:00 Discussion on proactive approaches in security and the role of machine learning.
14:40 Nirmal emphasizes the need for a proactive defense strategy in cybersecurity.
15:11 Discussion about the use of large language models (LLMs) in Microsoft's work.
21:05 Nirmal talks about his active involvement in the community.
22:27 Nirmal reflects on the positive impact of mentoring.
24:24 Evan asks Nirmal about his ideas for the future.
28:17 Evan wraps up the show.

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

Kicking off Season 3 of Mining Your Own Business, Evan Wimpey sits down to chat with Bill Shube. A supply chain analytics expert with over 11 years at the LEGO Group, Bill is also the founder of Supply Chain Watchtower. Through his company Bill’s goal is helping small businesses effectively manage their inventory.

Grab a chair and tune in as he shares his story. Bill talks about how his team has successfully leveraged citizen development to gain actionable insights from data, saving thousands of hours and much more. Plus he shares how citizen development can impact on data tasks, governance, and scalability within an organization.

In this episode you will learn:

⛛ How citizen development can be used to empower business teams to play a more active role in data analytics

⛛ The need for governance initiatives to manage potential risk and ensure citizen developers stick to best practices

⛛ How no-code and low-code tools can complement existing systems, boosting collaboration rather than creating silos

⛛ Why a mindset change is crucial for all teams to be empowered to make the most of data

Quote
💬 “That's what citizen development is about; it's empowering the average user.”

Featured in This Episode

Bill Shube, Founder, Supply Chain Watchtower
Bill Shube, founder of Supply Chain Watchtower (SCW), has over 11 years of experience in supply chain management and analytics at The LEGO Group, where he and his team have saved thousands of hours and spotted millions of dollars worth of planning errors through analytics automation.

His goal in founding SCW is to bring these big-business experiences and techniques to small and growing businesses, helping them understand their demand and supply. This empowers businesses to right-size inventories, avoid stock-outs and overages, and ultimately improve cash flow and profitability.

LinkedIn: https://www.linkedin.com/in/bill-shube/

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction
00:35 Talking about Bill’s experience with the LEGO Group and his company, Supply Chain Watchtower
01:48 Discussing Bill’s work in the supply chain
02:26 Sharing the team’s evolution to citizen developers
05:10 Talking about the challenges of siloed data
06:31 Breaking down what citizen development is and its benefits
08:52 Discussing how citizen development is implemented
12:28 Sharing the need for data governance
13:22 Talking about putting good practices in place
14:55 Discussing how user communities can foster collaboration
16:17 The importance of being on the same page
22:05 How citizen development can impact multiple areas of a business
25:06 Discussing how Bill’s team is using data tools to support daily operations
27:54 Talking about Bill’s dreams for the future
30:33 Wrapping up the show

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

In this episode Evan Wimpey chats with Mike Arney, founder of PB Vision, a company helping pickleball players gain game-changing insights. Tune in as he shares how his company got started and how his team is applying AI, machine learning, and computer vision in new ways.

Mike also shares why it’s important to value the thoughts and ideas of end users and how that collaboration makes a difference. Whether your team is embarking on a new analytics project or seeking data-driven inspiration for existing ones, we hope this episode will be insightful!

In this episode you will learn:

🔹 How analytics can be applied in diverse ways and lead to innovative solutions

🔹 The importance of considering end users with any project

🔹 How asking for feedback from end users can help refine an analytic tool

🔹 The need for balancing technical optimization with maintaining a positive user experience

Quotes
💬 “I [saw] the amazing things [AI was] doing and said, ‘How can I actually get my toes in the water and understand how this works from a functional perspective?”
💬 “Here's a problem that we can solve. What would a possible solution look like? … Let's do a little bit of research. Let's experiment.”
💬 “Some people are super passionate about certain things and their voice can be pretty loud. It's great to have that passion, but you have to be very careful that does not drown out the silence or the quiet majority.”

Featured in This Episode
Mike Arney, Founder, PB Vision
Mike Arney is the founder of PB Vision, a company combining the power of AI, machine learning, and computer vision to transform video analysis in pickleball. With his background as a UI/UX designer and his love for pickleball, Mike embarked on a journey to transform the game with AI.

Through PB Vision, Mike’s team is providing insights and data-driven coaching to help pickleball players improve their performance. The platform leverages analytics to offer an in-depth level of game analysis, enhancing both training and overall playing experience.

LinkedIn: https://www.linkedin.com/in/mikearney/

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters
00:00 Introduction
01:04 Talking about the focus of PB Vision
02:35 Sharing the story behind the launch of PB Vision
04:57 Vetting the solution and delving into computer vision
07:54 Discussing the different ways to approach a challenge
10:54 Talking about the downside of being locked into a solution
12:00 Sharing the importance of building technical skills
12:30 Discussing why UI/UX can’t be an afterthought
15:28 Evaluating user feedback
18:35 Inviting the pickleball community and developers to the table
19:47 Delving into the need for user buy-in
22:46 Looking to the future of PB Vision
30:31 Wrapping up the show

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

In this episode of Mining Your Own Business, Evan Wimpey chats with Eric Siegel, bestselling author and founder of Machine Learning Week. Tune in as he shares why businesses need to focus on machine learning projects that work in the real world.

Eric also dives into the importance of measuring the impact of machine learning projects, the need for business professionals to understand the technology, and the potential challenges associated with overhyped AI expectations.

In this episode you will learn:

🔹 The importance of deploying machine learning models in real-world business operations to capture value

🔹 Why metrics are key to getting the most out of machine learning projects and impacting business decisions

🔹 The importance of a structured end-to-end practice that enables business stakeholders to collaborate closely with data scientists

🔹 Why tools like generative AI need to be assessed by how they are helping organizations capture real value

Quotes
💬 “Measuring the value is just as fundamental as developing the model. And it goes hand in hand.”
💬 “Measuring the value is just as fundamental as developing the model. And it goes hand in hand.”
💬 “We're trying to improve business operations. We're trying to provide actual business value by implementing change.”

Featured in This Episode
Eric Siegel, Bestselling Author & Machine Learning Week Founder
Eric Siegel, Ph.D. is a consultant, former Columbia University professor, and founder of Machine Learning Week. He’s also an instructor for the “Machine Learning Leadership and Practice” course, executive editor of The Machine Learning Times, and a sought-after keynote speaker. Eric authored the bestselling book “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die” widely used in university courses. His latest book, “The AI Playbook,” is now available at bizml.com.

Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award teaching graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.

LinkedIn: linkedin.com/in/predictiveanalytics


Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters

00:00 Introduction
01:02 Diving into analytics use case examples
05:56 Measuring the effectiveness of analytics efforts
06:49 Discussing Eric’s new book and using metrics to drive decisions
11:37 Talking about best practices around end-to-end processes
14:13 Discussing the need for useful ML models and change management
16:26 Exploring the need for stakeholders and data professionals to understand each other
18:28 Talking about the Machine Learning Week conference
22:58 Delving into Eric’s predictions for future advancements and generative AI
27:24 Chatting about Eric’s dream analytics project and current projects
32:00 Wrapping up the show

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/

Tune in as host Evan Wimpey chats with PayPal Data Science Lead Gulrez Khan about the art of data storytelling. With over two decades of experience, Gulrez has discovered how data storytelling can be an effective tool to bring clarity to the complex.

In this episode he shares lessons he’s learned and creative ways he's helping children and adults build data literacy.

Key Takeaways
🔹 The importance of truly understanding a business problem before starting a data science project
🔹 How data storytelling can help bridge the gap between business stakeholders and data science teams
🔹 The creative approach Gulrez Khan is using to help both children and adults grow in data literacy
🔹 How data scientists can become agents of change by not only fulfilling requests but also identifying alternative solutions based on their domain knowledge

Quotes
💬 “So you become a change agent—not just do what has been asked of you but understand the business and say, ‘Hey, you know what, there is another way we can do it.’”
💬 “Data is very powerful, and with a good heart, you can make change.”
💬 “I've got a few principles that I apply in terms of data storytelling … start with the problem formulation. What is the question being asked?”

Featured in This Episode

Gulrez Khan, Data Science Lead, PayPal
With almost two decades of experience under his belt, Gulrez Khan is a data-wrangling extraordinaire, who has a knack for turning boring numbers into captivating stories. When he's not busy working, you can find him digging through open datasets like they're buried treasure or passing on his data visualization skills to the next generation in the hopes of creating a world of data-literate children.

Gulrez is on a mission to improve the way people make sense of data. He's known for delivering corporate workshops that are equal parts informative and entertaining and has recently written “Drawing Data with Kids,” a book to cultivate data literacy in children and adults alike.

LinkedIn: linkedin.com/in/gulrezkhan-data

Evan Wimpey, Director of Analytics Strategy, Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey

Chapters

00:00 Introduction
01:09 Working as a data science leader at PayPal
02:17 How and why PayPal started a data science community
03:41 Creating sparks in data science projects
09:08 What it means to become a change agent
09:55 Discussing the principles of effective data storytelling.
11:27 How data storytelling facilitates better communication
15:02 Data storytelling as a marketable job skill
18:09 Gulrez’s book, “Drawing Data with Kids,” and data literacy
24:45 Using data for good
25:59 Wrapping up the show

Find more show notes, transcripts, & more episodes at:
https://www.elderresearch.com/resource/podcasts/