Armstrong World Industries has completed 13 acquisitions since 2020, while also migrating to S/4HANA and modernizing its 20-year-old analytics environment. The company integrates two to three new businesses annually; with customized integrations impossible at that scale, Armstrong needed something most acquirers don’t: a playbook it could run 13 times consistently.

“At that pace, you can’t treat each acquisition as a one-off, or you’ll end up with many different ERP systems,” said Julie K. Walker, Senior Director Enterprise Applications and IT Strategy. “The most important thing is to have a strong, reusable foundation with core SAP modules, consistent data, and clear integration.”

Walker started at Armstrong in finance, where technology meant accuracy and efficiency—getting the numbers right and the processes fast. She became a subject matter expert during Armstrong’s initial SAP implementation, moved to IT development, and eventually took over leadership of all enterprise applications.

Her progression through finance, development, and application management shaped how she thinks about transformation today. Technology, as she sees it, is no longer supporting the business. It’s driving it.

New customer experiences, new operational models, and the ability to absorb acquisitions without slowing down are what technology enables at Armstrong now.

The 3-Step Playbook

Armstrong treats SAP as the hub of its entire digital architecture. Every downstream integration, from analytics to process intelligence to customer-facing tools, flows from that core. Getting an acquired company onto SAP unlocks the full platform ecosystem; leaving them off it cuts them out entirely.

The integration sequence is the same each time.

1. Stabilize the new entity and implement cybersecurity tools to bring it up to Armstrong’s security standards.
2. Connect the entity to Armstrong’s SAP instance and core platforms.
3. Only after that connection is secure does Armstrong layer in modernization and optimization.

Walker considers skipping that integration “leaving value on the table,” weakening the business case that justified the acquisition in the first place.

“Integrating acquisitions is important because it’s how we unlock the full value of what we’ve bought. Integration isn’t just combining operations; it’s creating a stronger, scalable Armstrong.”

She frames common platforms as a collaboration enabler. When employees across acquired entities share the same systems, they know who to call and how to work together—a dimension of integration gets lost when the conversation focuses only on system consolidation.

The playbook standardizes the technology. But each acquired company arrives with its own workflows, its own process logic, and its own way of doing things. SAP alone doesn’t reveal where those differences lie.

“When you’ve done 13 acquisitions, you quickly realize that you need a common way to see processes and to compare them, and to decide where we standardize versus where we allow flexibility,” explained Walker.

Signavio, SAP’s business process intelligence platform, will fill that gap. Armstrong plans to use it to map how each acquired business operates, identify gaps with its core SAP model, and prioritize what needs to change first.

Walker sees it as far more than “just a documentation tool.” It’s the mechanism that makes the integration playbook repeatable, giving her IT team a consistent methodology for evaluating acquisitions rather than starting from scratch.

Looking ahead, she’s particularly interested in automating routine process analysis and building integrations that scale. Her goal is to move Signavio from a diagnostic tool to one that accelerates action.

What Finishing S/4HANA Made Possible

The discipline behind that standardize-then-build playbook traces back to Armstrong’s S/4HANA migration, which finished in 2022, five years ahead of the 2027 deadline.

Walker calls it her favorite initiative Armstrong has undertaken, one where IT and the business were “rowing in the same direction” from the start, with complete support from senior leadership. Completing the migration early gave Armstrong something most companies still working toward 2027 don’t have: room to maneuver.

“We knew it was behind us, and that it opened the doors to optimize anywhere we wanted to,” noted Walker. “We didn’t have to worry about a looming deadline.”

That freedom let Armstrong pursue supply chain optimization, advanced analytics, and the M&A integration capabilities the company now depends on.

But the modernization that followed has brought its own challenges. Armstrong is migrating an analytics environment that accumulated over more than two decades in SAP BW toward platforms like SAP Datasphere and Databricks while introducing AI tools.

The sequencing is critical: Armstrong isn’t simply replacing one analytics platform with another, but shifting how it models data, how teams access insights, and how quickly the organization can move from question to answer. That requires new skills and mindsets as much as new tooling.

“One of the biggest challenges is simply the weight of history,” said Walker. “We’re modernizing more than 20 years of BW—decades of reports, custom logic, and ways of working that people are deeply familiar with. Helping teams let go of the old while building confidence in the new takes time and a lot of communication.”

Armstrong’s approach has been to let people experience new platforms before asking them to commit. The company ran proofs of concept extensively in 2025, giving teams hands-on time with new tools so they could see the value firsthand.

When people understand the reasoning and can see steady progress, “the complexity becomes manageable,” she noted.

AI Measure by Outcomes, Not Hype

When asked how Armstrong measures AI benefits, Walker doesn’t see the need for a new framework.

“We haven’t changed how we measure benefits. It’s exactly the same. This allows us to stack up those AI initiatives against all our other initiatives,” she explained.

Armstrong evaluates every project—AI included—on whether it reduces time spent on manual tasks, improves decision speed, or surfaces insights not previously visible. Consistency enables apples-to-apples comparisons when leadership allocates resources.

While evaluating projects, a clear pattern surfaced: AI projects stalled when data wasn’t ready. Legacy data structures and uneven data quality across systems meant that some areas of the business could support AI immediately, while others couldn’t.

Armstrong now conducts a data readiness assessment before approving any AI initiative, evaluating quality in relevant source systems, and identifying what needs cleansing or restructuring before a model can deliver real value.

“We’ll actually create a data cleansing project before we even start the AI initiative,” explained Walker. At the same time, Armstrong pursues AI in areas where data is already clean, delivering visible wins that sustain executive support while longer remediation work proceeds elsewhere.

Internally, the company’s Data-Driven Decisions Committee became the AI Committee after the team noticed a shift. Engagement had been difficult to sustain when the focus was purely analytics, but it surged once AI entered the conversation.

The committee expanded beyond analysts and IT leaders to include governance, legal, HR, and business unit representatives. Walker sees no contradiction in the rebrand: “AI starts with good data,” she said, so stakeholders understand that analytics remains the foundation.

Managing the Gap Between Ambition and Readiness

Across every front of Armstrong’s transformation, Walker applies the same principle: pair transparency about constraints with visible evidence of progress, and never let either honesty or optimism crowd out the other.

“The hardest part isn’t the technology,” she said. “It’s managing the expectations that come with modernizing something the organization has relied on for decades.”

Foundation work, she emphasized, almost always takes longer than the “appetite for results.” Her advice to peers is direct: explain early and often why certain steps take time, where data readiness is a barrier, and what’s needed to unlock the value everyone is eager to see. Armstrong has tried to bridge what Walker calls “the art of the possible” with operational reality.

The company hosted an AI Day where vendors demonstrated capabilities, then paired those demonstrations with honest assessments of what would be required to implement similar solutions.

Armstrong is also expanding its use of SAP Business Technology Platform (BTP). Walker sees BTP as a way to streamline project delivery, with code generation as one area of focus. The company is still early in evaluating the AI credits included in its Signavio contract, working through SAP’s published use cases to determine where those credits can deliver practical value.

When Walker presents at SAP Sapphire this year, she’ll cover S/4HANA, analytics modernization, Signavio, and AI—representing the full span of Armstrong’s transformation agenda. That breadth reflects how Armstrong approaches transformation: not as a set of discrete technology projects, but as a single discipline applied consistently across every initiative.

The company focuses on building repeatable playbook for M&A integration, holds AI to the same benefit metrics as every other investment, and communicates transparently about why foundation work takes time. As Armstrong continues acquiring two to three companies a year, that discipline is what prevents growth from creating fragmentation.