Elder Research’s Post

Hey Leaders, Is training a priority for your team? 💡 In this blog, Veronica Blackburn, our Director of Learning and Development, shares why building in-house AI and data science expertise is so important ... Especially with technology evolving so rapidly. ⚙ 𝗔 𝗳𝗲𝘄 𝗿𝗲𝗮𝘀𝗼𝗻𝘀 𝘁𝗼 𝗶𝗻𝘃𝗲𝘀𝘁 𝗶𝗻 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴: ✅ Empowers employees to effectively use data and gain insight ✅ Helps employees build skills that directly impact their work ✅ Fosters a sense of ownership, loyalty, and pride in work 𝗙𝗶𝗻𝗱 𝗼𝘂𝘁 𝗺𝗼𝗿𝗲 𝗶𝗻 𝗩𝗲𝗿𝗼𝗻𝗶𝗰𝗮’𝘀 𝗯𝗹𝗼𝗴: https://lnkd.in/gQTSh-kp #DataScience #AI #Empowerment

This photo was taken during our 20th anniversary celebration in 2015. Since that time our team has grown from about 60 team members to more than 160. And that’s not the only growth we’ve seen. We’ve witnessed team members grow sharper in their skills, grow as leaders, and grow as colleagues and friends—all while serving our clients to the best of their ability. Looking forward to what’s next and looking forward to even more talented lifelong learners joining the team! If you’re interested in joining our team or know someone who might be, check out our Jobs tab: https://lnkd.in/gpPJUkTT

If you work with customer data, you know it comes with a lot of complexity. Find out how a leading consumer packaged goods (CPG) company partnered with us to gain better insights. 💡 𝗧𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 The client was dealing with the challenge of aligning customer growth and retention goals with diverse data. They didn’t have a clear way to integrate historical customer data with future strategies, making it hard to set clear goals and optimize resources across accounts and brands. 𝗢𝘂𝗿 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 📊 Immerse ourselves in their business to understand strategic objectives and KPIs. 🧩 Apply advanced segmentation to categorize customers by performance and product objectives. 💭 Deliver insights to directly inform their strategic planning and trade strategies. 𝗙𝗶𝗻𝗱 𝗼𝘂𝘁 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗰𝗮𝘀𝗲 𝘀𝘁𝘂𝗱𝘆: https://lnkd.in/ewnGNxcV

Work in hospitality or know someone who does? 👀 We’re excited to announce the release of our latest guide, “Hospitable Data,” designed for hospitality leaders looking to take their data strategies to the next level. 📈 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗲𝘅𝗽𝗲𝗰𝘁 𝗳𝗿𝗼𝗺 “𝗛𝗼𝘀𝗽𝗶𝘁𝗮𝗯𝗹𝗲 𝗗𝗮𝘁𝗮”: ☑ An analytics assessment to identify roadblocks and opportunities ☑ Real-world examples to illustrate effective data use ☑ Tips on how to grow your organization’s level of analytics maturity ☑ Helpful questions to ask ahead of data projects 👉 𝗚𝗲𝘁 𝘁𝗵𝗲 𝗴𝘂𝗶𝗱𝗲 𝗵𝗲𝗿𝗲: https://lnkd.in/eugCN9Kc In the fast-paced world of hospitality, it’s not just about gathering data; it’s about using it to make better, faster, and more confident decisions. Explore our guide for some helpful tips and share it with your friends in the industry! #DataAnalytics #HospitalityIndustry #DataStrategy #CustomerExperience #BusinessGrowth

Predicting failures before they happen is what predictive maintenance is all about, but it’s not always easy. In this whiteboard video, Ramon Perez, AI Solutions Portfolio Director, shares why predictive maintenance can be so hard and some ways to address those challenges. 𝗦𝗼𝗺𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗞𝗲𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀: 🔎 𝗟𝗮𝗰𝗸 𝗼𝗳 𝗟𝗮𝗯𝗲𝗹𝗲𝗱 𝗖𝗮𝘀𝗲𝘀: Trying to predict rare events with sparse data is like finding a needle in a haystack. 🏭 𝗦𝗶𝗴𝗻𝗮𝗹-𝘁𝗼-𝗡𝗼𝗶𝘀𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀: The large amounts of data generated by equipment create a lot of data noise that can be hard to sift through to pinpoint potential failures. 💭 𝗜𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗶𝗻𝗴 𝗥𝗲𝘀𝘂𝗹𝘁𝘀: It’s not just about predicting; it’s about guiding maintenance teams on where to focus their efforts. 𝗛𝗼𝘄 𝘁𝗼 𝗧𝗮𝗰𝗸𝗹𝗲 𝗧𝗵𝗲𝘀𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀: 🧩 𝗥𝗲𝗱𝗲𝗳𝗶𝗻𝗲 𝗙𝗮𝗶𝗹𝘂𝗿𝗲: Are there any unusual patterns in the data that can potentially be redefined as early warning signs? 🔄 𝗖𝗿𝗲𝗮𝘁𝗲 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗟𝗼𝗼𝗽𝘀: Introducing human expertise into the loop helps refine models. By feeding back insights from the field, you enhance the model’s accuracy over time. ⚙️ 𝗨𝘀𝗲 𝗗𝗶𝘃𝗲𝗿𝘀𝗲 𝗠𝗼𝗱𝗲𝗹 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: There’s no one-size-fits-all model. Combining local and global models, anomaly detection, and subject-specific insights builds a robust predictive framework. 🧑💻 𝗔𝗶𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗠𝗮𝗸𝗶𝗻𝗴: Visual tools and summary stats help decision-makers act quickly and decisively. Ultimately, it’s about combining human expertise with machine intelligence to tackle predictive maintenance problems effectively. Interested in learning more? Check out elderresearch.com/blog.

Fun Fourth of July fact: In July 1776, there were 2.5 million people living in the newly formed United States. 🇺🇸 In July 2023, the U.S. Census Bureau estimated there were 334.9 million people living in the nation. This holiday, we hope you have an amazing time celebrating with your favorite people. Happy Fourth of July from all of us here at Elder Research! 🎆 #FourthofJuly #4thofJuly #DataDriven #PeopleCentered

Hey Data Leaders, Don’t let perfect data be the enemy of progress. “In our experience the mistake of ‘waiting for perfect data’ probably kills more projects than any other,” says Jeff Deal, our president and COO. Here’s a typical scenario. 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝘀𝘁𝗮𝗿𝘁𝘀 𝘀𝘁𝗿𝗼𝗻𝗴: Goals defined ✅ Potential ROI calculated ✅ Project plan developed ✅ Budget approved ✅ Team assembled ✅ Project launched ✅ 𝗧𝗵𝗲𝗻 𝘁𝗵𝗲 𝘁𝗿𝗼𝘂𝗯𝗹𝗲 𝘀𝘁𝗮𝗿𝘁𝘀 ... The desire for “perfect” data creeps in. Unrealistic expectations about data preparation time and costs delay projects. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆? Even relatively clean data requires significant preparation. And of course you need engineers to parse, cleanse, and transform data into a format suitable for analytical modeling and visualization. Also, experienced data scientists expect to work with imperfect data, and they have tools and techniques to get around the most challenging data problems. The truth is no organization has perfect data. And your data doesn’t have to be perfect to deliver valuable insights. 💡 Jeff shares more in this blog: https://lnkd.in/ekpktvex #DataScience #DataAnalytics #DataPrep

Today is #InternationalJokeDay and we couldn’t miss sharing a joke from our very own Evan Wimpey. 😂 𝗤: How many data scientists does it take to screw in a light bulb? 𝗔: Just 1, but he needs thousands of already-screwed-in light bulbs for training. 😆 Keep the laughter going by sharing a joke below! 👇 Check out Evan’s book, “Predictable Jokes,”  at predictablejokes.com, and be sure to catch his interviews with data leaders on our Mining Your Own Business podcast.

The difference between effective analytics solutions and ones that miss the mark: The time invested in change management. 🎯 Analytics solutions work best when everyone is on board. But real change only happens when people are ready for it. Change management is a structured way to help teams plan for and adjust to change. It involves a lot of communication, getting everyone aligned, providing learning opportunities, and measuring the impact of the change. That way new analytics solutions don’t just end up collecting dust—they transform the way teams work. If you’re not sure where to get started with change management, our team is happy to chat. You can also check out the change management resources on our website. #DataDriven #PeopleCentered #ChangeManagement