Wolf&Grayson EditorialHarrison Allen Lewis is the Founding Partner of Jacob Meadow Associates, a boutique consultancy helping organizations unlock their “X Factor” through data governance, AI, and business-IT strategy. He’s seen firsthand how unclear ownership in data migration strategy can derail multimillion-dollar programs.
Enterprise Resource Planning (ERP) transformations are among the most ambitious milestones in a company’s digital journey. They demand years of preparation, significant investment, and impact nearly every part of the business, from workflows to financial reporting to customer experience.
When done right, ERP transformation empowers leaders with real-time insights and the confidence to act decisively. But as Lewis notes, success depends less on technology and more on clarity around data governance and accountability during data migration.
“Our approach begins with reframing who is truly accountable for success and then working with customers to equip them with the right tools, frameworks, and guidance,” says Lewis.
The payoff is compelling: a unified system that boosts productivity, streamlines operations, and provides real-time insight across the enterprise. However, the path to go-live is less about technology and more about untangling the responsibility for migrating data from old systems into new ones.
When Data Becomes the Deciding Factor
As a three-time CIO and former Chief Data Officer, he’s rescued large-scale transformations at major retailers and financial institutions, giving him a front-row view of why so many implementations stumble.
“Most of the time when I step into an ERP implementation that has gone bad, it is because of the data,” he shares. AI-driven data quality issues and unclear ownership of migration tasks often leave customers stranded.
The vendor tells the business that it must prepare, clean, and migrate all of its own data, even though most companies have never done such a task before; it’s like asking someone to pack and label every item for a house move without ever having moved before—it is an unrealistic burden without expert help.
Some insist data is solely the customer’s burden, while others acknowledge shared roles without clarifying how accountability works in practice. It creates a paradox. “From the customer’s standpoint, they’ve never done this before. ERP implementations happen once every eight or ten years. They don’t have the expertise, but they’re told they’re fully responsible,” says Lewis.
Building a Better Way Forward
Lewis founded Jacob Meadow Associates on the lessons learned from both successes and failures. “I took everything that worked and why it worked, everything that didn’t work and why it didn’t work, and said there has to be a better way,” he says. That “better way” became Data Governance as a Service, a practice that places his firm in an active, collaborative role during data migration, through its strategic partnership with Promethium.
Promethium is an open data fabric that connects all enterprise data sources in real time, identifies authoritative sources of truth, and aggregates context for migration to the new ERP system — creating an AI-ready data foundation that enables self-service data access and supports future AI initiatives.
“It’s not about shifting responsibility. It’s about walking through the risks together, ensuring clean, complete data moves into the new system,” says Lewis. Through its partnership with Promethium, Jacob Meadow Associates delivers Data Governance as a Service—helping clients establish ownership and accountability across every stage of transformation.
Eliminating the “Gray Areas” in Data Governance
For Lewis, responsibility divides are not just inconvenient. They represent real risk. He describes the traditional contractual model of data migration as a landscape of black, white, and gray.
“The gray is where confusion and disruption live. Customers don’t always realize the gray exists until it is too late, which leads to change orders, delays, and added costs,” he says.
Instead, Jacob Meadow Associates defines programs around explicit business outcomes, aligning every role to those outcomes. With data governance frameworks in place, accountability is transparent, and every party is equipped to succeed.
Oversight ensures accountability is transparent across the customer team, the system integrator, and the advisors. “It’s cruel to give a customer what represents an impossibility, telling them to own data migration without the knowledge or tools to succeed. Our brand is focused on business outcomes, so collaboration is the only way forward,” Lewis says.
AI as a Built-in Advantage
Artificial intelligence is foundational to this model. By combining AI data quality monitoring with human judgment from data stewards, organizations gain visibility into data issues long before cutover. “We are an AI-first organization. Where many see AI as a bolt-on, we embed it from the start,” he says.
To make benefits tangible, Jacob Meadow Associates applies a “business benefit realization matrix” that links technical capabilities to business capabilities, then to business outcomes.
This helps quantify both tangible and intangible returns while clarifying who is accountable for delivering them. “Ultimately, ERP is an investment. AI makes it possible not just to deliver on the business outcomes requested, but to elevate that outcome with measurable value,” Lewis says.
Defining Success on Customer Terms
The consequences of neglecting data migration strategy highlight exactly what is at stake. Lewis recounts joining a century-old company mid-project, only to discover the system integrator had delivered infrastructure and training while leaving the client responsible for data migration. The result was a six-month delay and an unplanned investment. “Everyone thought they were ready to go, but they had nothing because the data wasn’t there,” he recalls.
Lewis encourages organizations to treat ERP transformation as a shared journey. With strong data governance and AI data quality monitoring, companies can approach transformation with confidence, clarity, and a focus on true business outcomes.
Because when accountability is shared, success is defined by what the customer achieves—not just by what is delivered. “If I do my part and the customer fails, that is not success. Success is what the customer defines, and our role is to deliver collaboratively on that.”
Follow Harrison Allen Lewis on LinkedIn or visit his website to learn more.
