On the show today, Evan sits down with Isaac Collazo, Vice President of Analytics at STR. Isaac shares how he got started in the travel and hotel industry, and how he’s seen data analytics in the hotel space take off and advance over time. He discusses what type of data STR works with and how they strategize delivering key insights to their clients. Isaac and Evan also discuss what it takes to be a successful data analyst on these types of projects, highlighting crucial characteristics such as creativity, play, and drive. Finally, Isaac speaks on opportunities he sees in the hospitality industry and in his current role at STR.    Key Takeaways:  🛎️ How STR provides insights from data to inform hotel progress and strategy 🛎️ Opportunities for increased consumer understanding via hotel data 🛎️ The importance of creativity and perseverance as a data analyst 🛎️ How increased time and resources allow for long-term high-level analysis   Quotes:  💬 People who are on the data side have to be creative and have to just love to play with data because if you don't, then it's a pretty boring job. — Isaac Collazo 💬 I think there's a lot more space – not ability, but opportunity to do more with that data [in the hotel space]. — Isaac Collazo 💬 I'm looking for is someone who is very creative and who has more of a strategy mindset. Not only can they use data, but they understand that we've got to get to a decision or an outcome. — Isaac Collazo  Featured in this episode:  Evan Wimpey , Director of Analytics Strategy at Elder Research. Company website: www.elderresearch.com   LinkedIn: https://www.linkedin.com/in/evan-wimpey/    Isaac Collazo, VP of Analytics at STRAs a seasoned analytics professional, Isaac Collazo believes that data is not everything and understands the value of relationships when immersing himself in an industry to truly understand its people and experiences. He is the VP of Analytics at STR where he solidifies the company's analytical methodology, assists with integration into CoStar's digital platform, and unifies products and services to provide a single, reliable source of knowledge for the Hotel Industry. He is an expert in delivering meticulously curated insights based on industry knowledge and encourages others to make a personal investment in the insights they uncover. His easy-to-digest knowledge ensures recipients can apply it to their own business performance for an informed and successful future. LinkedIn: https://www.linkedin.com/in/isaaccollazo/  Chapters:  00:00 Introduction  00:57 Isaac’s background in the travel & hotel industries 02:52 How Isaac got started in data collection for hotel decision-making 05:35 The type of data and benchmarking that STR provides 11:55 What it takes to be successful on an analytics team 16:54 Insights from consumer data: seeking to learn more 20:05 Working with data in the hotel industry: the importance of time & resources 21:18 A new mindset Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Today we welcome to the show Eric Sims, Senior Analyst of Strategy and Analytics at LendingTree, an online lending marketplace. Eric and host Evan Wimpey discuss the process of getting projects off the ground, ways of making analytics accessible to business units and stakeholders, and gaining alignment on business endeavors. Eric also shares how he has been enriched by personal investigative data projects, and tips for others endeavoring on a side project. Finally, Eric speaks about the importance of understanding one’s clients and truly putting oneself in their shoes. We hope you enjoy this insightful episode!  Key Takeaways: 🌳 How LendingTree communicates and coordinates its projects amongst various teams 🌳 How to make analytics accessible to non-technical stakeholders 🌳 How M&Ms helped team members feel more comfortable with data concepts 🌳 Ways to truly understand and immerse oneself in a customer’s experience  Quotes: 💬 The most valuable thing to me, and I think to any company... is knowing your customer – and knowing not just your customers’ data, but knowing your customers’ voices and their problems. — Eric Sims  💬 I really like teaching and showing and sharing. Here's how you can do it. Ask me when you forget later. And we'll just keep practicing through it.  — Eric Sims  💬 The most important thing when it comes to you have a list of projects you want to do: pick one you like, just pick one that you're interested in. Because even if you are working on something you like, sometimes it's a slog. And so you gotta want it. — Eric Sims  Featured in this episode: Evan Wimpey Director of Analytics Strategy at Elder Research. Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey/  Eric Sims, Sr. Analyst, Strategy & Analytics Eric’s personal brand can be summed up in one word: originality. He’s always in search of new and interesting ways to approach learning and problem solving. He currently works as a Sr. Data Analyst at LendingTree, supporting the Small Business vertical, and in his free time he builds machine learning applications. He’s also interested in how recommenders can be used to connect social networks, and his latest project is a tea recommender system. Besides working and building side projects, Eric contributes to the LinkedIn data science community, plays paintball in VR, travels with his partner, and does normal home stuff (#RealLife). https://www.linkedin.com/in/ericsims2/  LendingTree is hiring! Check out current opportunities here:https://www.lendingtree.com/careers/jobs/Chapters: 00:00 Introduction 01:00 Eric’s background and how he got into analytics 03:12 Eric’s role and projects at LendingTree 06:47 How do new projects start? 09:52 Biggest challenges to getting projects from ideation to final product 13:54 Communicating data terminology: making analytics accessible  17:41 Lightbulb moments: making data make sense with M&M’s 21:33 Eric’s personal projects: learning new skills 28:33 Truly understanding the customerFind more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

On today’s episode, Francisco Rius gives us an exclusive look into the data world of the ever-popular video game Minecraft. Francisco is the Head of Data Science and Data Engineering with a background in business economics and marketing. He and host Evan Wimpey discuss his journey to his current role at Minecraft and how data insights are used to improve each player’s experience. Francisco shares how a relationship-oriented approach that prioritizes social listening is crucial to the game’s long-term success. They discuss what it takes to have a strong data team in a creative field. Finally, Francisco wraps up by sharing his vision for the intersection of AI in video games. Tune in for an enlightening and inspiring conversation.  Key Takeaways: ⛏️ How data have provided insights to improve Minecraft over the past twelve years ⛏️ How Minecraft practices social listening to provide the best game experience possible for their players ⛏️ The different skills and expertise needed for a strong, creative data science team ⛏️ How AI opens new worlds of possibilities for the video game industry Quotes: 💬 A lot of times the relationship aspect of working in big corporations is multiplied times 10 when you're working in creative industries as well. So that relationship aspect is really important...[a new hire’s] ability to make friends and the emotional intelligence aspect of working shoulder-to-shoulder with folks that see the world in a little bit of a different light. — Francisco Rius 💬 I feel like data science and analytics teams are maturing to be subject matter experts alongside decision-makers. And we're seeing a little bit of a reduction in the number of layers of translation that happens between the data insight and the decision. — Francisco Rius 💬 The strategy for Minecraft really is: Hey, we want to create a relationship with our players that will last for the next 10, 20, 50 years. — Francisco Rius Featured in this episode: Evan Wimpey Director of Analytics Strategy at Elder Research. Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey/ Francisco Rius   Head of Data Science and Data Engineering, Minecraft at Microsoft Francisco leads the data science and data engineering efforts for one of the biggest video game franchises in the world.  He is passionate about the intersection of art and science, where video game makers can use data-driven insights to improve player experiences and outcomes.  Minecraft is one of the best-selling video games of all time, with over 120 million active players per month.  Before joining the Minecraft franchise at Microsoft, Francisco led the analytics group for Electronic Arts’ FIFA, NHL, and UFC franchises. LinkedIn: https://www.linkedin.com/in/franciscorius/Chapters: 00:00 Introduction 02:03 Francisco’s background and how he got to his role at Minecraft 06:01 How data has provided insights over Minecraft’s lifetime 09:44 Social listening at Minecraft 12:54 Partnerships in academia and Microsoft 15:26 Art & Science: fostering relationships between creatives and data scientists 19:46 A well-rounded data science team: working in tandem with subject matter experts 24:35 Balancing short-term and long-term change 28:41 Francisco’s vision for the future: AI in video games Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

On today’s episode, we welcome Rob Horrobin to the show. Rob is Pacific Life’s AVP of Data Science where he leads the Advanced Analytics Center of Enablement. You’ll hear Rob and Evan discuss the Center of Enablement and how it supports data science efforts across the organization. Rob describes their "Do-Partner-Support" strategy, which governs how they support internal clients while also creating possibilities for true transformation. We’ll also hear about the intersection between actuarial science, data science, and engineering, as well as the importance of varied skill sets and backgrounds in data science professions. Rob and Evan end by exploring the future paths of analytics capabilities. Key Takeaways:  📈How the Center of Enablement supports learning and transformation 📈How experience in multiple fields can build complimentary skillsets for successful data science projects 📈 How to successfully partner with clients to implement a data project 📈Tips for those currently in or seeking careers in data science   Quotes:  💬 I was a career-switcher, I was in pre-business school where I actually did mechanical engineering in the shipbuilding industry. — Rob Horrobin 💬 Starting with the end in mind — it's great to build a model, but you have to make sure that it's fit for its purpose. In the end, how are the folks gonna consume it? — Rob Horrobin 💬 If an actuary's a quarterback, a data scientist is a running back and an engineer could be a tight end — very complimentary skills, but not one-to-one. Where I get really excited is when an actuary and a data scientist and a data engineer rally around a problem and say, “how do we kind of make this thing work better?” — Rob Horrobin Featured in this episode:  Evan Wimpey  Director of Analytics Strategy at Elder Research.  Company website: www.elderresearch.com  LinkedIn: https://www.linkedin.com/in/evan-wimpey/  Rob Horrobin AVP of Data Science at Pacific Life LinkedIn: https://www.linkedin.com/in/robertmhorrobin/ Chapters:  00:00 Introduction  01:04 Rob’s background and how he got into data science 02:53 Rob’s role in the Center of Enablement: The Do-Partner-Support Model  05:47 Scope of the team’s work and how teams are structured 11:03 Actuaries, engineers, and data scientists: kindred spirits 15:04 Advice for those considering launching a data science effort 19:04 Advice for those interested in a career in data science  21:08 Standard certifications for data scientists in the future? 27:58 Rob’s vision: How can analytics create entirely different business models? Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

We’re kicking off the new year with Rick Hinton, founder and CEO of Valerius Consulting. Valerius provides adaptive change management services, especially for data analytics organizations. Rick and Evan discuss what change management looks like in the analytics world and why it’s necessary for growth. We learn about the importance of the words “trust”, “deliberate”, and “gradual” as they relate to implementing effective change. Rick wraps up by teaching us the CALM process for change management (Communication, Alignment, Learning, & Measurement) and providing practical advice for businesses.  Key Takeaways: 📈How change management is synonymous with continuous learning 📈Common barriers to change and how to foster an environment of trust 📈The pacing of effective change within an organization 📈The CALM process for change management and how to apply it to your business (Communication, Alignment, Learning, Measurement)  Quotes: 💬 Trust is not an initiative that you plug in. It's the way you operate every day.  — Rick Hinton  💬 The business folks, the technical folks, and the data science and analytics folks - the challenge has always been them speaking the same language…The change challenge is they don't understand each other…That language barrier is a big impediment to change.  — Rick Hinton  💬 We’re not just changing for change’s sake. We're trying to improve, we're trying to learn, and that ties in really well with what people in the data science realm and analytics realm do. That's what they do every day, to try to interpret output and make decisions and learn from it.  — Rick Hinton  Featured in this episode:  Evan Wimpey Director of Analytics Strategy at Elder Research. Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey/   Rick Hinton  Founder and CEO at Valerius Consulting  Valerius Consulting: http://www.valerius.us/  LinkedIn: https://www.linkedin.com/in/rfhinton/  Chapters: 00:00 Introduction 01:16 Rick’s background and why he founded Valerius Consulting 03:05 What is change management in analytics?  05:19 Change in data analytics, past and present 10:41 Analytics team structures and communication barriers 14:18 Building trust 17:54 Too much too fast? Pacing of change 21:42 The CALM process 29:12 Conclusion Transcript & Show Notes: https://bit.ly/myob14Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Today’s very special guest joins us all the way from the North Pole. Elf is the Head of Data and Analytics at Santa’s Workshop. Elf and Evan discuss how the elves got into data analytics to solve complex problems, from toy manufacturing to efficient delivery routes. Elf describes how data analytics has changed over the centuries that he’s worked at Santa’s workshop. He also provides insight on increasing buy-in from key stakeholders. Evan and Elf wrap up by discussing Elf’s vision for the future of analytics to increase the amount of joy and cheer spread throughout the world. Tune in for an exclusive look into the magic of Santa’s Workshop! Key Takeaways: 🎁 How to ensure buy-in from stakeholders by centering them in the process 🎁 How Santa’s workshop tackles route optimization 🎁 Why data is needed to adapt to evolving business challenges, from chimney shortages to toy demands 🎁 Current challenges that Santa’s workshop faces and how they hope to solve them   Quotes:  💬 “If we're not able to measure some improvement in what the data and analytics are able to do, then it's really hard to get that buy-in from the stakeholders.”  💬 “And it's really the data that we collect year over year, and we also do some third-party data acquisitions to understand some of these changing trends, but the data is really helping to drive those delivery decisions.”  💬 “I would really like to focus on that last mile, the most difficult children to deliver to, to make sure that every child that is hopeful of a Christmas gets something under their Christmas tree, something that they can open to have a little bit of magic there on Christmas morning.”  Featured in this episode: Evan Wimpey Director of Analytics Strategy at Elder Research. Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey-40469b47   Elf Head of Data and Analytics at Santa’s Workshop Elf is the Head of Data and Analytics at Santa's Workshop and is passionate about using data to spread joy and cheer. He has extensive experience leading his team at the North Pole location for the past 1,145 years. He has a background in retail management and carpentry. In his free time, he enjoys collecting vintage candy canes and watching Lord of the Rings. 00:00 Introduction 01:02 Elf’s background in data analytics 03:37 Scope of data analytics in the business model 05:54 How have data analytics problems evolved over centuries of work? 08:03 Ensuring buy-in from stakeholders: creating analytics champions 12:07 Do freezing temperatures affect computing? 14:08 If Elf could tackle one analytics question, what would it be? Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Joining us today is Selma Dogic, Senior Manager of Analytics at Carter’s. Selma discusses strategies for the implementation and adoption of data solutions in a large multi-brand business. Selma and Evan also talk about how data teams coordinate with the business side of Carter’s to deliver solutions. Finally, Selma discusses future directions for data analytics at Carter’s, which includes the importance of building a healthy data culture and data literacy at organizations. Tune in to hear more of this informative and thoughtful episode! Key Takeaways: 🍼How teams are structured and projects are prioritized for optimal results 🍼How data science effectively operates in the retail space to provide crucial business insights 🍼Who Carter’s markets to and how they build customer trust 🍼The importance of a healthy data culture and data literacy for all Quotes: 💬“Not only are we doing the data engineering and feature engineering to help train better models... but we're also learning ourselves.” - Selma Dogic  💬“When you identify a champion, somebody who gets it just as much as you do, but they're on the other side of it, that can transcend your analytic strategy and really drive adoption.” - Selma Dogic 💬“I'm really interested in building out well-structured and well-maintained data domains for the organization and having the business users equipped to leverage those data domains to make their business decisions.” - Selma Dogic Featured in this episode: Evan Wimpey Director of Analytics Strategy at Elder ResearchCompany website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimp... Selma Dogic Senior Manager of Analytics at Carter’sLinkedIn: https://www.linkedin.com/in/selmadogic Chapters: 01:12 Selma’s background and how she got started at Carter’s 03:33 What is Carter’s? 04:45 Selma’s role at Carter’s 06:43 Business team structure and strategic decision-making 11:37 How are data results delivered to businesses? 14:59 How to implement data strategies – identifying champions 19:18 Carter’s data sources 22:47 How Carter’s gets creative with marketing 24:40 Promoting data literacy and data cultureFor more info and podcast transcript: bit.ly/myob12cFind more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

In this episode, we are joined by Zach Wasielewski, Senior Data Scientist at General Mills. Evan and Zach discuss Zach’s role in strategic revenue management and how data science teams operate cohesively in a large multinational company like General Mills. They discuss change management strategies and how General Mills has grown as an established company. Zach also shares about his background in financial services and discusses his transition to consumer product goods.  We recommend enjoying this episode over a bowl of Cinnamon Toast Crunch. Tune in for an entertaining and informative conversation! Key Takeaways: 🥣How various business units across the company strategize together through knowledge-sharing 🥣How an established company like General Mills has incorporated data science strategies and grown over time🥣What strategic revenue management looks like and what challenges they work to solve🥣How data teams interact with the supply chain and future directions for data science projects in supply chain shortages Quotes: 💬“We're learning as we go and building on top of what we've got in place to make sure that anything that they could be using and testing and looking at historically is what we're also incorporating into our models.” - Zach Wasielewski 💬“The data science group, especially in the SRM space, is all very interconnected... we are all very much one team, even if we work in different things, different products, different stores.” - Zach Wasielewski 💬“We are one giant cohesive organization...What I learn in my day-to-day job is something that is important for them and what they learn is equally as important for us.” - Zach Wasielewski Featured in this episode:Evan Wimpey Director of Analytics Strategy at Elder Research Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey-40469b47  Zach Wasielewski   Senior Data Scientist at General Mills  LinkedIn: https://www.linkedin.com/in/zachary-wasielewski/  Zach’s athletic accomplishments: https://datacolumn.iaa.ncsu.edu/blog/2019/04/25/intramural-softball-winners-2019/   Join General Mills’ team: https://careers.generalmills.com/careers   Chapters:01:51 Zach’s background and how he got started at General Mills 04:00 Zach’s role at General Mills 08:55 Data flows at General Mills 10:41 How are data teams organized at General Mills? 15:48 How change is implemented at General Mills 18:36 From finance to consumer goods – how did Zach get up to speed? 24:34 What data science project would Zach like to tackle in the future? Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Joining Evan on the data science slopes is Gus Kaeding, Senior Manager of Data & Analytics at U.S. Ski & Snowboard. Gus shares how his background in professional skiing, coaching, and the U.S. Olympic Committee informs the work he does today. He discusses the types of challenges athletes use data to solve and the tech infrastructure for sharing insights with coaches. Gus also explains some of the challenges with data collection and how he envisions data collection in the future. Gus and Evan wrap up by discussing the future of the U.S. team. Tune in for an invigorating episode on sports analytics!   Key Takeaways  How data benefits athletes and team development and creates champions How data insights are delivered to coaches and athletes Challenges in data collection and how new innovations are addressing them Insights into the future of the U.S. Ski & Snowboard team  Quotes  “It's about growing those sample sets - whether they are in the gym or at home, during recovery, or on the slopes - as much as we can. And solving for “how do you create those results?” whether good or bad, and incrementally improving those.” - Gus Kaeding “Anytime you're talking about an analytics kind of project, whether it's in business or whether it's in an MBA program, buy-in's always tough and there's a number of different stakeholders you have to address. So, most of the projects that I work on are sourced from a question that comes from the coaches” - Gus Kaeding “Now we really want to make sure we're scaling. And when we identify some of those [young] athletes, to support them in a way where they're bringing their friends, their community, and the sport along with them as well.” - Gus Kaeding  Featured in this episode  Evan Wimpey  Director of Analytics Strategy at Elder Research.  Company website: www.elderresearch.com  LinkedIn: https://www.linkedin.com/in/evan-wimpey-40469b47  Gus KaedingSenior Manager of Data & Analytics at U.S. Ski & Snowboard LinkedIn: https://www.linkedin.com/in/kaedinggus/   Chapters  01:40 – Gus’s background and how he got into ski & snowboard data  03:49 – What types of data is collected for ski and snowboard?  06:23 – Video tracking for data collection: challenges and benefits 09:10 – How are analytics efforts prioritized?  13:38 – How are data insights delivered to coaches and athletes? 16:22 – Challenging conventional norms  20:03 – Does ski data change the way you ski? 22:47 – What’s one data question you aspire to answer? 27:12 – For the fans of U.S. Ski & Snowboard: what to look out for  Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

In this episode, we hear from April Wilson, Head of Career Services at the Institute for Advanced Analytics. April’s ten years of career expertise inform the insights she provides on hiring in the analytics world. She shares the most desirable skills companies look for when hiring, the importance of having equal expectations, and the benefits of having an open mind when evaluating candidates – the skills they have may be beneficial in unexpected ways. Evan and April wrap up by discussing three tips for teams looking to hire.  Key Takeaways  The primary skills that employers are looking for when hiring  How companies and prospective hires can manage their expectations The surprising truth about industry experience The importance of an open mind when hiring  Quotes  “I want you to know the technology, I want you to understand it, but I need for you to be able to talk about it and explain it as well.” - April Wilson   “[The skills employers are looking for are] like a three-prong: it’s that technology, that communication, and that ability to present to stakeholders. And be able to present the right information to your stakeholders.” - April Wilson   “Remember, there's no such thing as unicorns. It takes a team, a data science team to do well.” - April Wilson  “[Employers] don't care if you're straight outta undergraduate or if you've been a college professor for 15 years, as long as you have the skills that they need, you fit the organization, and you feel like you have something to contribute.” - April Wilson     Featured in this episode  Evan Wimpey  Director of Analytics Strategy at Elder Research.  Company website: www.elderresearch.com  LinkedIn: https://www.linkedin.com/in/evan-wimpey-40469b47     April Wilson Head of Career Services at Institute for Advanced AnalyticsIf you are a company interested in learning more about recruiting analytical talent you can email April at april_wilson@ncsu.eduIf you are an individual that wants to hone the skills you need to get the job you want, email April at clearpathcs@gmail.comLinkedIn: https://www.linkedin.com/in/april-wilson-8125a55/   Chapters  01:09 April’s background and the work she does in career services 02:27 The skills sets individuals need when entering and exiting a master’s program 05:10 How the demand for certain skills has changed over time 09:46 Commonly overlooked skills and company expectations when hiring 15:12 Importance of accurate job descriptions and equal expectations  16:44 Prospective hires with much vs. little experience – should they take different approaches? 21:09 Does industry experience make a difference?  26:13 Three tips for teams looking for candidates Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Today’s episode features Nick Wan, Director of Analytics for the Cincinnati Reds Baseball Team. Evan and Nick’s conversation covers the value sports analytics provides to everyone involved, from hiring personnel to coaches to players. You’ll hear about how specific baseball rule changes affect analytics and the accessibility of sports data to analysts and fans alike.  You’ll also learn how Nick’s work landed him on the front page of the New York Times and what he envisions for the future of sports analytics.     Key Takeaways  The breadth of analytics usage in the sports world The demand for data that is applicable and actionable How public research can add value to the analytics world The importance of critical thinking to ensure sound methodology  Quotes  “The goal is really to produce work that is not just strong statistically, but also applicable.” - Nick Wan  “Everyone's reading FanGraphs in the industry. It truly is a bastion of the analytics community, not just in baseball, but in sports in general.” - Nick Wan  “You do have to be a pretty sharp, critical analyst or analytics contributor to recognize when the methods are off a bit.” - Nick Wan  Featured in this episode  Evan Wimpey  Director of Analytics Strategy at Elder Research.  Company website: www.elderresearch.com LinkedIn: https://www.linkedin.com/in/evan-wimpey-40469b47  Nick Wan Director of Analytics, Cincinnati Reds Baseball Team Twitch: https://www.twitch.tv/nickwan_datasci  YouTube: https://www.youtube.com/c/NickWan  Twitter: https://twitter.com/nickwan  LinkedIn: https://www.linkedin.com/in/realnickwan/  Check out Nick’s front page NYT article feature: https://www.nytimes.com/2015/02/14/upshot/how-arizona-state-reinvented-free-throw-distraction.html   Chapters  01:17 How Nick got into sports analytics from a neuroscience background 05:49 How sports data analytics teams are organized functionally 08:28 Who are the end users of sports analytics? 12:00 Demand for applicable data 13:56 Accessibility of sports data  18:21 The value of the public research field of sports analytics 24:18 How do rule changes in the game affect analytics?  29:33 Neuroscience: the future of sports analytics?  Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

In this episode, we are joined by not one but two data science and analytics leaders from Home Depot: John Carroll and Jon Weininger.You'll hear them discuss their past and present roles at Home Depot as experts on analytics on different teams.They offer insight into coordinating with different teams across the organization and how their respective backgrounds inform the way that they communicate with both technical and non-technical individuals about data.You’ll also hear them talk about prioritization when it comes to project management and the ways they’ve learned from and adapted to challenges over their careers.Finally, they share the “why” behind their work and their role in creating value and impact for the company as a whole.Key TakeawaysHow the data science and analytics teams have evolved over time, responding to company needs The dynamics of the data science team and how they communicate their ideas with other data teamsStrategies and approaches to prioritizing projects in a complex environment Common roadblocks and how to prioritize the problems that need to be solved  QuotesMy role  is more strategic and supporting the good works and making sure the roadblocks are gone and our leadership understands the value of what our data science teams are working on - John CarrollPeople are asking for analytic support. Therefore, more people want analytic support - EvanMarket timing is like organizational interests and kind of the likelihood of getting a strong adoption from somebody who can help to focus attention and resources - John Weininger Featured in this episodeEvan WimpeyDirector of Analytics Strategy at Elder Research.Company website: www.elderresearch.comLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47 Jon WeiningerData Science Manager, Home DepotLinkedin: https://www.linkedin.com/in/jonweiningerhttps://careers.homedepot.com John CarrollSenior Manager MET analytics and Insights, Home DepotLinkedin: https://www.linkedin.com/in/johncarroll652 https://careers.homedepot.com  Chapters01:34 Jon Weininger and his work background02:31 John Carroll and his work background05:03  How does Home Depot structure their data analytic capability? 09:12  Communicating technical work to other teams 15:09 What are the roadblocks?21:17  How to set priorities with stakeholders 25:59 Given an ideal scenario, where do you want to focus your analytics effort?Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this episode, we are joined by Olga Sazonova, Director of Data Science at NutriSense. Through her work as a data scientist and her own personal experience, Olga offers insight on how having access to one’s personal health data can empower individuals to take charge of their wellbeing.  You will hear about how their data analytics team is structured to work efficiently with their clients’ data, and how data analysts of different backgrounds complement each other. Olga also discusses the importance NutriSense placed on developing meaningful data since being founded in 2019 and how insights from the data work alongside professional insights from subject matter experts.  Evan and Olga wrap up by discussing future possibilities Olga sees for this type of work, especially in accurately predicting health outcomes.  Key TakeawaysWhat NutriSense does and how they use data analytics to help personal health The value in building a team with complementary skill sets How to create text data that enable meaningful insights How personalized data can be a powerful motivator for lifestyle change  QuotesWithin our company, we're very aligned on the idea that you want to practice a holistic approach to someone's well-being. - OlgaThe hope was that if we teach people about their genetic risk and tell them what they can do to mitigate that risk, they will be motivated by that information to do it. - OlgaI think for every individual there are so many other factors that will impact the results for a given meal, so it's wrong to expect the same results every time. - Olga Featured in this episodeEvan WimpeyDirector of Analytics Strategy at Elder Research.Company website: www.elderresearch.comLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47 Olga SazonovaDirector of Data Science at NutriSenseLinkedin: https://www.linkedin.com/in/olga-sazonova-0328124 Company Website: https://www.nutrisense.io  Chapters00:00 Intro01:26 Olga’s background 05:00 What NutriSense does 09:31 Potential challenges faced by breadth of data collection 11:44 Organization of a data analytics team 13:44 How personalized data can lead to change 16:27 What to do when professional advice clashes with the data 19:49 Data results are unique to each person 23:01 One burning question that Olga would like to solve 25:25 ConclusionFind more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this episode we are joined by Jay Lanterman, Senior Manager, Operations Performance Analytics & Insights at InterContinental Hotels Group (IHG).In this podcast, Jay shares how data analytics is being applied in the hospitality industry to create operational efficiencies. Evan and Jay discuss some of the specific project areas where analytics can be applied and how teams can work together to across the business to ensure lasting impact.They also discuss the impact COVID had on everything from customer experience data to demand data and how they think about forecasting moving forward.Key TakeawaysHow data analytics is being applied in the hospitality industryHow teams can work with other functions, across business units, and with franchisesHow to convey insights to non-technical stakeholders to encourage implementationHow to think about forecasting as we come out of COVID QuotesThat's what analytics is for, it is to guide the business and help them focus rather than tackling everything all at once. - Jayif I had a magic wand, it would be great if we all use the same system and we could get the cleanest data and everyone would operate on it and set it perfectly - Jay Featured in this episodeEvan WimpeyDirector of Analytics Strategy at Elder Research.Company website: www.elderresearch.comLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47 Jay Lanterman  3rd degree connectionSenior Manager, Operations Performance Analytics & Insights at InterContinental Hotels Group Linkedin: https://www.linkedin.com/in/Jay-lanterman-36641b86 Company Website: https://www.ihgplc.com/en/  Chapters00:00 Intro01:16 Jay’s background03:06 Projects and types of data in hospitality06:00 Challenges of accessing data from franchises08:30 The value of the data architecture team10:04 Collaborating with teams across the business11:58 Putting the recommendations into action15:01 The challenge to conveying insights to non-technical stakeholders20:06 Getting data from the "front lines"22:38 Forecasting post-COVID25:57 If there was a magic "analytic success" button, where would Jay use it at IHG? Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this episode, we are joined by Liping Wu, a Senior Manager of Data Science at Advance Auto Parts.Liping and Evan discuss how the many applications of data science that the enterprise analytics team is deploying at Advance Auto Parts, how the enterprise team achieves success with the different business verticals, and the advantages and disadvantages of having an enterprise data science team vs a team embedded within a business function.You will hear how the the pandemic has impacted their data, the models the use, and the initiatives they work on. Liping specifically discusses the opportunities in improving supply chain demand forecasting.Key TakeawaysWhere Advance Auto Parts is applying analytics in their businessHow the enterprise analytics team achieves success working with the different business functionsAdvantages and disadvantages of having an enterprise data science team vs embedded teamsThe impact of the pandemic on their data, models, and analytic initiativesThe opportunities for using analytics in supply chain forecasting QuotesFolks like us who have similar skill sets find it easier to cross-pollinate the technologies as it evolves because the design is changing and we need to keep learning every day. - LipingThe auto parts industry had record high DIY sales after the dip in March and April In 2020 - LipingWe did find that simplicity is the virtue in these changing times - LipingFeatured in this episodeEvan Wimpey Director of Analytics Strategy at Elder Research.Company website: www.elderresearch.comLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47Liping WuSenior Manager, Data Science at Advance Auto PartsLinkedin: https://www.linkedin.com/in/liping-wu Company Website: https://shop.advanceautoparts.com/  Chapters00:00 Intro01:50 Liping’s background03:34 About Advance Auto Parts06:12 How the enterprise analytics team works with the different business functions09:33 How the Advance Auto analytics team is structured13:27 Pros and cons of enterprise data science team vs teams embedded in verticals19:31 The impact of the pandemic on their data science efforts26:02 If there was a magic “analytic success” button, where would Liping use it at Advance Auto Parts?Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this podcast, we are joined by Korri Jones, A Senior Lead Machine Learning Engineer and Innovation Coach at Chick-Fil-A. He discusses his background and his career journey that lead him to be a Machine Learning Engineer working at Chick-Fil-A.he also talks about what it is to be a Machine Learning Engineer and what are the usual works and tasks every day. He also shares how he manages his teams such as the Data Science Team and the Data Engineering Team to be more productive and dynamic with each other. He also answered the big question in this show, given an ideal scenario, what would you focus on? Lastly, Korri describes what it looks like working with Chick-Fil-A.Key TakeawaysWhat is a machine learning engineer and when they get involved in a projectThe value that an innovation coach brings to a teamWhere project ideas originate & how they are decided uponHow they operationalize projects at Chick-fil-AThe unique culture of the Chick-fil-A team QuotesI want people to do what they are hired to do and really just crush it. I don't need a data scientist doing all of the engineering work. I don't need the engineer doing all the data science work. - Korri Some people talk about thinking outside the box. We help to make sure that there is no box in the first place. And so you don't have to try to think inside or outside of a box. - Korri Featured in this EpisodeEvan Wimpey Director of Analytics Strategy at Elder ResearchLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47Website: www.elderresearch.comKorri Jones Senior Lead Machine Learning EngineerInnovation Coach at Chick-Fil-A Linkedin: https://www.linkedin.com/in/korri-jones-mba-780ba56 Chapters00:00 Introduction01:39 Korri's Background04:00 Korri's Career as a Senior Lead Machine Learning Engineer07:01 Balancing the technical side and business side09:01 What is an innovation coach?11:36 Getting the ideas from the data science team or others14:02 When does a machine learning engineer get involved16:44 How are projects decided upon19:11 If there was a magic "analytic success" button, where would Korri use it?22:51 Working With Chick-Fil-A 25:10 OutroFind more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this episode, we are joined by Alex Cunningham, Manager of Advanced Analytics at Church & Dwight. Alex and Evan have a thought-provoking discussion about how to drive analytics successes, build momentum, and develop partners. He also discussed their strategy to develop a good product and the team's secret to integrating that process. Alex also touches on what makes the analytics team at Church & Dwight special and the most important traits they look for when growing their team. Key TakeawaysWhat the analytics center of excellence group of Church and Dwight is.How to build momentum and develop partners early on.How to prioritize projects and implement them into production.What traits they value in their analytics team.Where Alex would use a "analytic success" button if he had one. Quote TakeawaysWe went out to folks and invited them to join the circle as partners. Then, once we've established ourselves, it gets better. We don't need to do much to attract people; they're drawn in because they've heard about our successes and achievements and want to be a part of it. - AlexEmpathy and humility. Two closely related traits are what allow us to become those good partners to folks in the business in that internal consulting type capacity. - AlexBeing a lifelong learner is one of the qualities I believe is essential for a successful data scientist. The learning component is something that strong data science groups truly value. - AlexSpeakers of this Episode Evan Wimpey | Director of Analytics Strategy at Elder Researchwww.elderresearch.comLinkedin: https://www.linkedin.com/in/evan-wimpey-40469b47Alex Cunningham | Manager, Advanced Analytics at Church & Dwight Co., Inc.Churchdwight.comLinkedin: https://www.linkedin.com/in/alex-cunningham-297a8a39Timestamp00:00 - Intro01:43 -  Alex's background and career history 04:50 -  How Church & Dwight structures their analytics capability 06:06 -  How the analytics group has integrated in the business & built momentum 11:33 -  How they prioritize & implement projects 19:05 -  The important aspects of their team 23:43 -  If there was a magic "analytic success" button, where would Alex use it? Find more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/

Welcome to Mining Your Own Business Podcast. Each episode will bring in data and analytics gurus from around the world as they regale us with their data analytics stories and enlighten us with their secrets for how to turn data into actionable insights.In this episode, we are joined by Gerhard Pilcher, the CEO of Elder Research. He is also the author of the book titled Mining your Own Business. In this episode, he talks about his book and the possibility of a second edition. He also discusses the challenges of the new analytics approach, as well as how it compares to previous models. Gerhard underscores the key components needed to drive change and adoption. He also discusses the similarities and differences between successful and failed projects that he has seen in the past. He then ended the conversation by answering the question, “If there was a magic button, where would you use Analytics?”Key Takeaways-Discovering what the book "Mining Your Own Business" is all about-The possibility of a second edition-What are the  challenges of the modern model of analytics-The commonalities of successful and failed projects-What Gerhard hopes to learn from future episodes of this podcast-If there was a magic "analytics success" button, where would Gerhard use it?Quotes From The Episode"Success is when the team is willing to be have their norms challenged." - Gerhard"Exploring why the analysis is counterintuitive can lead to some of the most significant breakthroughs. However, I believe that people who are unwilling to be questioned may miss out on a tremendous chance." - GerhardBooks Mentioned in The EpisodeMining Your Own Businesshttps://www.elderresearch.com/resource/books/mining-your-own-business-how-to-use-analytics-in-your-business/ Amazon ->https://www.amazon.com/Mining-Your-Own-Business-Understanding/dp/0996712100 📌Speakers of this EpisodeEvan Wimpey | HostDirector of Analytics Strategy at Elder Researchhttps://www.linkedin.com/in/evan-wimpey-40469b47Gerhard Pilcher | GuestChief Executive Officer at Elder Researchhttps://www.linkedin.com/in/gerhard-pilcher-a3583122/Timestamp[00:00] Intro[01:24] Gerhard’s Background[06:32] Gerhard’s Book, Mining Your Own Business[06:15] Making the 2nd edition of Book and What is the Goal of the Book[10:47] Challenges for the New Model of Analytics[18:02] Commonalities on Successful and Failed Projects[20:03] Topics to Expect in Future Episodes[24:51] If there was a magic button, where would you use Analytics?[29:03] ConclusionFind more show notes, transcripts, & more episodes at: https://www.elderresearch.com/resource/podcasts/