No matter what an organization sells, data needs to tell a story. For Brian Moore, Director of Product Management at Salesforce, data serves as the roadmap for building intuitive products, smarter strategies, and lasting customer value. Before leading data-driven initiatives at one of the world’s largest enterprise technology companies, Moore spent his early career inside retail branches and corporate support centers at Saks Fifth Avenue, Wells Fargo, PNC, and Home Depot, where he uncovered a significant structural blind spot.
“I started realizing that teams had no idea what happened after reports were submitted. None of the data was connected like it should be,” says Moore. This disconnect between the daily activity in stores and what executives saw at headquarters became the catalyst for his focus on connecting data dots. Today, Moore shapes enterprise solutions that create clearer insights, coordinated execution, and measurable business outcomes.
Why Analytics Still Struggles to Deliver Value
Embedding analytics into enterprise systems is essential for creating that alignment. “Analytics helps departments build KPIs together. If you’re not building them together, that’s a red flag,” says Moore. Still, moving from understanding the need for analytics to actually integrating it across an organization is rarely straightforward. Cultural barriers often overshadow technical challenges. Many leaders remain uneasy when conversations turn to data logic, daily reports, or measurement frameworks. “You have legacy leaders who freeze up when asked what decisions were made from a report. When that happens, you lose out on key insights that would help move the business forward,” he says.
Retail, in particular, faces a double bind: entrenched legacy systems and large-scale transformations from on-prem to cloud. In these environments, strong product managers become essential interpreters. Their role is not only to gather requirements but to explain how analytics can streamline workflows, reduce risk, and unlock faster decisions. “Leaders love dashboards and insights,” Moore says. “Getting there is the challenge.”
A Practical Path to Analytics Integration
Rather than pushing enterprises toward expansive new platforms, Moore offers a grounded approach for building an analytics foundation. He describes a three-step process that applies to organizations of all sizes.
- Assess what already exists. Moore advises leaders to begin by reviewing their current tools and data sources. “What does your team use today? What can it actually tell you? Start there.”
- Integrate analytics into planning cycles. Every new initiative should include one key question: How do we measure this? Moore stresses that measurement should be baked into planning, not added after the fact.
- Match measurement needs to existing tools before buying new ones. Organizations often overspend on systems they are not ready to use. “You avoid the bandwagon effect by understanding your gaps. Otherwise you end up with analysis paralysis,” says Moore.
This structured approach sets the stage for meaningful impact. Moore highlights workforce analytics as an example. By tracking employee output, speed, and task value, retailers can determine staffing needs with precision. “You may realize you don’t need five people on a workflow. You can do it with three. That creates cost savings that scale nationwide.” Such insights move organizations away from gut decisions and toward operational clarity.
Where AI and Predictive Analytics Are Taking Enterprise Systems
Moore sees the future of enterprise solutions defined by cleaner data, stronger guardrails, and expanding predictive capabilities. “When your data is clean coming in, you get clean outputs that help you make quick or long-term decisions,” he explains. However, he stresses that AI does not eliminate the need for human expertise. Data scientists and architects remain essential to ensure inputs are structured logically and outputs can be trusted.
One trend Moore believes will transform the next five years is the rise of agentic marketing. These systems enable automated but personalized user journeys triggered by real-time engagement. “We’re seeing more direct, personalized conversations between consumers and brands. That’s never happened at this scale before,” he says. Moore points to Salesforce’s leadership in marketing automation as a sign of where the industry is heading. As companies adopt AI-driven personalization and predictive insights, the competition will hinge on who can maintain data trust, protect customer privacy, and still innovate quickly.
Building Smarter Solutions Starts With Data People Can Trust
With a saturated landscape of AI tools and vibe-coded applications emerging, Moore believes enterprises must return to the basics. Data should be trustworthy, accessible, and aligned with customer needs. “If your data isn’t giving you what you need, you need to find the people who can get it for you,” he says. The organizations that succeed will be those that stay customer-first, leverage their internal data intelligently, and build guardrails that support long-term reliability. For Moore, connecting data, people, and technology is the foundation for smarter enterprise solutions that deliver measurable impact.
Connect for Brian Moore on LinkedIn or visit his website for more insights.
