Enterprise technology budgets now rival capital expenditures once reserved for factories, acquisitions, and market expansion. Many leadership teams still fail to evaluate technology initiatives as investment decisions — and that is where enterprise value quietly erodes. “Technology is not a support function,” says Harrison Allen Lewis, Founding Partner of Jacob Meadow Associates, LLC. “It is capital. And like any other form of capital, it should be deployed with a clear expectation of return.”
Lewis, a three-time CIO who has also served as Chief Data, Security, and Privacy Officer, has spent more than two decades inside complex enterprises across retail, grocery, and financial services. That experience has shown him that when technology is treated as capital allocation, organizations make sharper decisions, preserve flexibility, and generate measurable outcomes.
When Spending Lacks a Return Narrative
Throughout his career, Lewis has observed that large technology programs often consume substantial investment, move forward on schedule, and meet delivery benchmarks. Yet when executives probe the underlying financial logic, the connection to margin expansion, revenue growth, working capital improvement, or risk reduction frequently proves indirect or loosely defined. “Roadmaps were approved. Budgets were committed. Status reports were green,” he recalls. “Yet when executives asked how the investment compounded enterprise value, the answers lacked precision.”
Delivering on time and on budget matters, but it does not guarantee that capital increases future flexibility. When investment funds redundant capabilities or systems disconnected from outcomes, capital quietly stops working on behalf of the enterprise. Over time, the consequences surface in overlapping platforms, underutilized systems, and technical debt that constrains future choices. The issue is not execution discipline. It is capital allocation discipline.
Restoring Accountability to Technology Investment
The root cause is rarely underinvestment. It is misalignment. Technology enables capabilities, and capabilities produce outcomes. When that chain of accountability is unclear, spending drifts toward activity rather than value creation. Lewis has seen multiple platforms within a single organization serving nearly identical purposes, each justified at the time of purchase. Rarely were those decisions revisited as capital allocation choices. “It is not uncommon to find two or three systems supporting the same business capability,” he says. “Each one made sense in isolation. But no one stepped back to ask whether that capital was still earning its keep.”
Applying a capability and outcome lens frequently surfaces meaningful opportunity. In many mid-market and enterprise environments, organizations uncover 15 to 25 percent of technology expense tied to overlapping capabilities or underutilized systems. On a $50 million annual run rate, that represents $7.5 to $12.5 million in recurring capital that can be redeployed toward growth initiatives, balance sheet strength, or shareholder returns. This shift requires cultural change. Business leaders cannot delegate outcomes to technology teams while remaining detached from the systems that enable them. Likewise, technology leaders cannot operate solely as service providers. Shared ownership of outcomes transforms technology discussions into enterprise investment conversations.
Managing the Roadmap Like an Investment Portfolio
Lewis approaches modernization through a structured methodology, Define, Assess, Align, Execute, and Govern, or DAAEG, ensuring that each initiative is anchored to a clearly defined business capability before capital is committed. The first question is not which tool to select, but which constraint the business must remove to win. Every initiative must withstand a board-level inquiry: What constraint does this eliminate, and why is this the highest return use of capital available? Measurement follows the same logic. Adoption metrics and system uptime provide operational assurance, but they do not confirm that capital is producing durable returns. More meaningful indicators include margin expansion, cycle time reduction, working capital efficiency, lower risk exposure, and sustained revenue enablement.
Portfolio discipline demands governance. Some initiatives warrant additional funding as evidence of value strengthens, while others should be reshaped or stopped.
“Shutting down an initiative that is not delivering value should be viewed as disciplined decision-making, not failure,” Lewis says.
That discipline protects optionality and ensures that future capital remains available for higher return opportunities.
AI and the Speed of Capital Consequences
Artificial intelligence compresses timelines and lowers the cost of experimentation, accelerating both gains and mistakes. The margin for vague investment logic narrows. In an AI-enabled environment, misallocated capital compounds at algorithmic speed. As a result, data quality, governance discipline, and decision infrastructure become core capital assets. Organizations that continue investing in bespoke systems built around legacy processes risk institutionalizing inefficiencies at machine speed. “The leaders who get this right will stop asking what AI can do,” Lewis says. “They will start asking where it changes return on invested capital.” Leaders who treat AI as a capability multiplier, not simply a feature, will see its impact reflected in enterprise resilience, capital efficiency, and long-term value creation.
The conclusion for leadership teams is straightforward. Technology should be evaluated with the same rigor applied to acquisitions or major capital projects. Treated as intentional capital deployment rather than background spend, it becomes a mechanism for building capability, improving resilience, and compounding enterprise value over time.
Follow Harrison Allen Lewis on LinkedIn or visit his website for more insights.
