Podcast Summary
Getting started with Enterprise Data Management (EDM) can feel overwhelming, but the key is starting small and focusing on business outcomes. In this episode, we break down where to begin, how to align your data strategy with business goals, and why governance is essential for long-term success. Learn how clear data processes, stakeholder buy-in, and incremental progress can turn chaotic data into a valuable business asset. Whether you’re just starting or refining your approach, this episode provides actionable insights to help your company unlock the power of data-driven decision-making. Listen now to transform your data into a competitive advantage!
Podcast Transcript
**Jocelyn 00:00:**
You’re listening to Infoverity’s *Trust Us* podcast, where you can gear up for your data management journey with bite-sized discussions on industry trends and thought leadership. On each episode, we feature industry experts to help you navigate your path to mastering your enterprise data.
Today on the podcast, we’ll be talking to Taylor Beckt about where to begin your data-driven journey, what that journey looks like, how to get started, common use cases, and guiding principles along the way. Welcome, Taylor. So glad you could join us today.
**Taylor Beckt 00:33:**
Thank you so much for having me, Jocelyn. I’m really excited to be here.
A little bit of background on myself: I am based out of Columbus, Ohio, and I’m one of our architects here at Infoverity. I work primarily in the product domain with a variety of our PIM and MDM solutions. I’ve done everything from high-level data strategy to the nitty-gritty configuration and actual development of specific solutions. In my previous life, I worked for a large automotive manufacturer here in Ohio, where I gained classical training in manufacturing, logistics, and supply chain management.
**Jocelyn 01:17:**
It’s great to have you here, Taylor. I’m excited to talk about how our listeners can get started on their journey.
There’s a lot to unpack in enterprise data management. I think a good place to start is defining what we mean by enterprise data management. This term can have different meanings for different people, but in my mind, it really boils down to one thing—making the most of the data you already have.
**Taylor Beckt 01:45:**
That’s a great question and really the first place to start. Enterprise data management is a broad landscape, but at its core, it refers to a business’s ability to identify, integrate, master, and enrich critical data—such as information about customers, suppliers, products, and locations—for both internal and external operations.
**Jocelyn 02:09:**
All of the data.
**Taylor Beckt 02:10:**
All of the data, exactly.
**Jocelyn 02:13:**
Thanks for that explanation. Given how broad this topic is, can you talk about what a typical journey through the enterprise data management landscape looks like?
**Taylor Beckt 02:26:**
Every company’s journey looks a little different and can start in different places, depending on business priorities, company direction, past investments, organizational structure, and appetite for change. Typically, there’s a business goal that necessitates diving into the company’s data and determining how to leverage it more efficiently to achieve tangible results.
For example, if a B2B company shifts to selling directly to customers, they must evaluate their product data’s accuracy and the tools they use to manage it. They may find that their first step is improving data governance processes, or they may realize they have the right processes in place but need better tools to master, enrich, and syndicate their data. Similarly, many companies modernizing their ERP systems must take a broader look at their entire data ecosystem.
The best place to start is where you can deliver the most immediate and meaningful business results. The journey is never truly complete—it evolves continuously. Demonstrating quick progress and incremental results is key.
**Jocelyn 03:48:**
That makes sense, Taylor. But from what you’re describing, this sounds like an effort that could span an entire career. How can our listeners orient themselves and determine exactly where to start their journey?
**Taylor Beckt 04:08:**
It comes down to asking a few key questions. Determining how to begin your enterprise data management journey can feel overwhelming, but not all progress needs to be lengthy or expensive. There are many low-cost, low-effort solutions you can implement today to get started.
**Jocelyn 04:29:**
Like what?
**Taylor Beckt 04:31:**
Well, that depends on how listeners answer certain questions, such as:
– How can I consolidate my customer and product data following a merger or acquisition?
– How can I justify having ERP, PLM, and PIM tools?
– How can I pivot my business to sell directly to customers?
– How do I choose a data platform?
– How do I enable supplier onboarding?
– How can I increase the speed of product time to market?
– How do I improve customer experience with personalized content?
– How can I demonstrate ROI on my data investments?
**Jocelyn 05:25:**
That sounds like a great way to begin evaluating which problems to solve. Can we discuss some of the most common use cases for enterprise data management?
**Taylor Beckt 05:41:**
Absolutely. There are several common catalysts for companies embarking on an enterprise data management journey, including mergers and acquisitions, ERP modernization, and moving to SaaS-based platforms. Each of these scenarios typically necessitates consolidating data systems and processes.
There are also industry-specific use cases. For example:
– **Manufacturing:** Transitioning from B2B sales to direct-to-consumer often requires an Amazon-like e-commerce experience.
– **Retail:** Customer data platforms and personalized product experiences are essential for competitive success.
– **Sustainability:** Some industries focus on traceability, ensuring customers have confidence in product origins.
– **Healthcare:** There is a need for a holistic patient view across all care providers.
**Jocelyn 07:00:**
That’s a great point—regardless of industry, making the most of your data is essential. The key is aligning data strategy with business goals, whether enterprise-wide or for individual teams. Success starts with defining what outcomes you want and building an actionable roadmap to achieve them.
**Taylor Beckt 07:52:**
That’s exactly right, Jocelyn. I can break this down into a few steps:
- **Focus on business outcomes** – Align on specific, measurable business goals.
- **Find the right-sized solution** – Infoverity offers tailored solutions for different stages of the journey.
- **Plan your transformation** – Select tools, outline a roadmap, and establish governance processes.
- **Implement your transformation** – Start showing ROI quickly with phased implementation.
- **Mature your transformation** – Continue refining and optimizing your approach as business needs evolve.
**Jocelyn 10:01:**
That’s great insight, Taylor. Getting started is often the hardest part.
For those ready to begin, Infoverity offers a right-sized approach leveraging decades of experience to help businesses realize the value of their data and drive meaningful transformation. Our **FlexiFrame implementation methodology** blends waterfall structure with agile flexibility, ensuring long-term sustainability while incorporating user feedback throughout the process. Additionally, we develop connectors and accelerators to address common business challenges, such as product configuration and large-scale data distribution.
That wraps up our discussion for today. Taylor, thank you so much for sharing your insights on starting a data management journey.
**Taylor Beckt 11:23:**
Thank you for having me, Jocelyn.
**Jocelyn 11:26:**
For over a decade, Infoverity has been a trusted leader in enterprise data management consulting. Our experts are located worldwide, with headquarters in Columbus, Ohio, and Valencia, Spain.
To learn more about how we can help you, visit [infoverity.com](https://www.infoverity.com). We’ve also included additional contact details in the show notes.
