Many companies say technology is important. Then they manage it like overhead.
That is where the problem starts.
When IT is treated as a cost center, the discussion usually revolves around cutting licenses, delaying upgrades, squeezing providers, and tolerating workarounds for one more year. On paper, that can look disciplined. In practice, it often drives up labor, increases complexity, weakens service, and makes the business harder to scale.
The issue is not whether IT costs money. Of course it does.
The issue is whether leadership understands what technology is actually doing inside the business model.
At Narrative Group, we take a Financials First view. Before we talk about platforms, vendors, or architecture, we want to understand how the business creates value, where the friction sits, and where technology can improve productivity, reduce risk, and protect EBITDA.
That is the shift: technology is not just a support function. It is capital allocation inside the business.
I founded Narrative Group to bring that level of enterprise discipline to mid-sized companies. After more than 20 years across enterprise roles including PwC, Shoppers Drug Mart, Loblaw, and global pharma, I kept seeing the same thing. When leadership treats IT like overhead, the company makes short-term decisions and pays for them later.
False Savings Are Expensive
When IT gets pushed into the cost-center bucket, the discussion starts in the wrong place.
Which licenses can we cut?
Which refresh can we delay?
Which provider is cheaper?
Which workaround can we tolerate for one more year?
That may lower a visible line item for a while, but the hidden costs usually show up somewhere else.
Labor goes up. Complexity goes up. Service levels drop. The business becomes harder to scale.
I have seen companies cut software costs and quietly move the expense into human effort. People start saving emails by hand. They rekey data. They chase approvals in Outlook. They reconcile reports that should match automatically. The software line may look better temporarily, but the labor line gets worse.
One practical example was an older tool used to push emails into SharePoint to avoid broader Microsoft licensing costs. It looked like a cost saving move. Later, when broader upgrades were needed, including Windows 11, that old choice became a source of friction.
That is what hidden cost looks like.
The same thing happens when a company picks a low-cost IT provider that cannot scale, or lets a temporary contractor build cheap custom software that no one can support once the business grows.
Downtime and Drift
The downtime numbers are ugly. Global 2000 companies lose about $400 billion a year to unplanned IT downtime and 96% experienced an outage in the last three years. Those figures come from large enterprises, but the lesson carries straight into the mid-market.
New Relic found the median annual downtime from high-impact outages was 77 hours and costs reached as high as $1.9 million per hour. In financial services and insurance, the median cost of a high-impact outage was about $2.2 million per hour.
One serious outage can wipe out a lot of apparent savings very quickly.
There is also a less visible cost. When IT is judged only on cost, IT leaders become firefighters. They run from urgent problem to urgent problem, miss the strategic conversations, and then leadership wonders why spending keeps rising without a clear return.
Hero Syndrome may feel useful in the moment. It keeps the organization immature.
In some cases, I have coached overwhelmed IT leaders to stop masking poorly managed change so the business could finally confront the real consequence of weak governance. That sounds tough, but if leadership never feels the cost of disorder, it rarely fixes the root issue.
Start With Financials First
My approach is simple: Financials First.
Before I care about tools, vendors, or architecture, I want to understand the business model.
How does the company actually make money?
That conversation has two parts. First, the primary value chain: how the business sells, fulfills, delivers, collects, and retains. Second, the supporting cost structure: how finance, HR, reporting, security, infrastructure, and compliance help the business move.
In the value chain, I look for bottlenecks and low productivity. In the supporting functions, I look for ways to help the company do more work without labor growing at the same rate.
That is the shift executives need to make. Technology is not a side budget. It is capital allocation inside the business model.
If a technology decision protects EBITDA, improves throughput, reduces risk, or slows the rate of hiring while the company grows, you are looking at an investment decision.
Map the value chain
Then you have to map the work.
Draw it out. What systems are in play? Who is talking to whom? Where is the data moving cleanly, and where is someone stepping into a spreadsheet or inbox because the systems do not line up?
If your e-commerce platform does not talk to store inventory, do not begin with the integration tool. Start with the fulfillment model. If those flows are not mapped properly, the technology decision will sit on top of an operational problem that still has not been solved.
Then go and listen.
Show me the day in the life. Sit with the people doing the work. They will tell you where the friction is. In most cases, it comes back to role definition or technology not doing what the company needs it to do.
That is why I spend so much time on site visits. You see physical bottlenecks, workaround behavior, and visual clutter that never shows up in a deck. You also build trust. Once people show you the problem, you have to follow through.
Talk is cheap. Actions speak volumes.
Invest where it matters
Decide what is actually unique
Mid-sized companies waste a lot of money pretending every process is unique.
Usually, it is not.
I advise leaders to classify processes into three buckets:
- competitive advantage
- point of parity
- commodity
Be specific. Be ruthless. For most companies, what makes the business distinctive is not the software. It is the expertise, relationships, customer experience, and judgment behind the operation.
That matters because the biggest barrier to scale is usually productivity.
If you want to grow over the next 24 to 36 months, you cannot keep adding people at the same rate. The first levers I usually pull are standardization and automation. Those are often the cleanest ways to create capacity.
Standardize the Rest
My preference is vanilla software and current platforms.
Stay current. Stay mainstream. Leave bleeding-edge experiments to somebody else.
Standard platforms bring built-in security, scale, robustness, and performance. They also force leadership teams to stop treating every local process as sacred.
I saw that clearly at Loblaw. We aligned more than $300 million in capital spend to the broader enterprise strategy and introduced infrastructure-as-software principles that reduced provisioning from six weeks to one day. That did not happen because we bought an exotic tool. It happened because we standardized the platform and governed the choices.
I also believe IT is effectively two departments. One part handles commodity operations such as desktop support, networks, and foundational services. The other should be learning the business and driving the technology that improves productivity and creates enterprise value.
Take the pieces that do not represent competitive advantage and outsource them.
At Shoppers Drug Mart, we reorganized the IT function through Project Symphony, moved to a portfolio-based model, and embedded specialized resources into each portfolio. Productivity improved by 40% year over year, based on output relative to total invested capital. That happened because the work was managed like an investment portfolio, with priorities, trade-offs, and accountability.
Measure Return in the Operation
Productivity and margin
If technology is an investment, the real ROI of IT investments should be visible in the operation.
Measure the time it takes to do the work. Use the client’s own business metrics. If a task drops from 20 hours to five, that is not a theory. That is capacity.
This matters especially in fixed-price businesses, where lower labor immediately improves margin. It also matters in growth businesses, where the first gain often shows up in the hiring curve. Revenue grows, but headcount does not have to grow at the same pace.
We have used that same logic in automation work. In one case, a five-week e-commerce product setup cycle went from roughly three weeks of manual setup time to about four hours. That changed the economics of the process and the staffing outlook.
Gartner reported that 75% of CFOs plan to raise tech budgets in 2026 and 48% expect increases of 10% or more. The same Gartner survey showed planned staff growth in the 4% to 9% range fell from 31% to 21%. Executives are already telling you where they think capacity will come from.
Self-checkout is another good example. At Shoppers Drug Mart, we designed a very simple user experience, piloted it in two stores, then rolled it out to 150 stores in the next fiscal year. That later grew to more than 400 stores. At Loblaw, the self-checkout experience had so many interventions that we had to rewrite the entire front end. The lesson is simple. Innovation is making the operation of a business model elegant. If the experience is clumsy, or the pricing and master data are wrong, labor walks right back into the model.
Stability and EBITDA protection
Stability matters just as much as automation.
You do not earn credibility by showing up with strategy slides while the basics are broken. Devices have to work. Networks have to connect. Meeting rooms have to function. You earn the right to talk about process once the foundation is solid.
We had one client with six offices where employees could not reliably connect when moving between locations. Their meeting rooms barely worked. Security had become the reason nothing could improve.
My view is simple: IT should be an enabler, not a blocker.
We assessed the infrastructure, replaced core switches and network gear, replaced outdated servers, put devices on a lifecycle plan, improved the meeting rooms, and helped build a new office. Three years later, the managing director joked that we had created a problem because now everyone wanted the rest of the offices to work like the new one.
That is operational credibility.
In another case, we helped transform IT for Canada’s largest provider of equipment for people with physical disabilities into a predictable evergreen model. Service became reliable. Spend became predictable. IT spend and headcount dropped from 3.5% of revenue to 2% of revenue while still supporting future growth. In a LogicMonitor survey, 80% called performance and availability critical. They are right. Uptime protects EBITDA.
Enterprise Value Shows Up Fast
The value story goes well beyond efficiency.
We helped a financial services technology provider improve the quality and stability of its environment, which added more than 25 basis points to gross margin. We worked with Canada’s leading reverse mortgage lender to improve project execution, and one project materially contributed to enterprise value and to a valuation at a five-times multiple in a transaction with a major private equity fund. We also helped a start-up insurance distributor put an enterprise IT structure and investment governance in place ahead of a $100 million USD raise.
Deloitte found that 95% of companies say digital initiatives lifted market capitalization or return on equity, and leading firms attribute more than 40% of enterprise value to digital initiatives. Boards care about value creation. Technology has a direct line into that conversation.
AI Still Needs Adult Supervision
AI is the newest version of a tool that promises to do everything.
I am optimistic about AI, but cautious. It is still immature. It does not know what it does not know. And much of what gets pitched today is not ready for prime time.
That is one reason Gartner predicts 30% of generative AI projects will be abandoned after proof of concept. Poor data, weak business rules, fuzzy ownership, and unclear ROI are usually the cause.
You cannot codify broken business processes.
Find the boring foundational functions first. Document the process. Set the business rules. Clean the data. Then use AI where it can help in long-running workflows, data quality, and repetitive, detail-heavy work.
That is where the value becomes practical.
What I Want CEOs and CFOs to Do Next
If you are a CEO, CFO, or COO, start with a few blunt questions.
How do you actually make money?
What did downtime cost last year?
Where are people doing work manually because a system is weak, old, or disconnected?
Which processes truly make you different, and which are commodity operations wearing an ego?
Then get board-ready about the numbers.
Look at IT spend as a percentage of revenue. Look at total IT spend versus revenue and expenses. Look at the ratio of IT labor to non-labor spend. Look at service levels, uptime, and the time required to complete key business processes.
What gets measured gets managed.
If the board cannot see how spend connects to uptime, capacity, risk, and growth, the spend will always feel discretionary.
At Narrative Group, we start with a Financials First discovery assessment. We look at how money is spent on IT, how capital is deployed, how data moves, and how the value chain is executed. Then we organize the work into three to five strategic themes and Then we organize the work into three to five strategic themes and build a technology investment roadmap. Quick wins matter because they build credibility. Big-bang programs usually create pain.
Leadership still has to own the change. The goal is to give senior leaders enough information to make decisions and then follow through on them.
I built Narrative Group to bring that level of enterprise discipline to mid-sized businesses. Some companies need advisory support. Some need fractional CIO or CTO leadership. Some need us to act as the IT department. The objective stays the same. Focus on the things that actually drive enterprise value.
Final Thought
IT reaches far beyond servers, licenses, and tickets.
It sits inside your value chain. It touches revenue, labor, margin, resilience, and valuation.
Treat IT like overhead and you will keep getting reactive spend, weak prioritization, hidden labor cost, and frustrated people.
Treat it like an investment strategy and you give the business room to grow, absorb change, and perform with less friction.
Every company has its own narrative. Follow the money, understand the work, and use technology to make the business model more elegant.
Frequently Asked Questions
What is the true financial risk of managing IT strictly as a cost center?
The risk is serious operational disruption plus hidden labor cost. Underfunding infrastructure increases the likelihood and impact of outages. Treating IT solely as overhead can directly threaten EBITDA, continuity, and growth.
How does an IT investment strategy affect exit valuation?
Strategic technology can increase scalability, improve margin, and support a stronger valuation story. Buyers pay for operational capacity, resilience, and growth leverage, not just reduced spend. Deloitte found that leading firms attribute over 40% of their enterprise value to digital initiatives.
If we pivot to an investment strategy, how should we benchmark IT budget increases?
Do not benchmark against someone else’s legacy debt. Benchmark against your growth goals, operational bottlenecks, and risk exposure. The right question is whether technology spend is creating measurable capacity and protecting value. A 2026 Gartner survey reports 75% of CFOs plan to raise tech budgets, with nearly half increasing them by 10% or more.
How do we evaluate AI investments without turning them into expensive experiments?
Demand clear ROI, clean data, documented process, and real business ownership before piloting. Without that discipline, AI is just another shiny project. Gartner predicts roughly 30% of generative AI projects will be abandoned by the end of 2025 due to unclear ROI and poor data quality.
Will shifting IT to an investment strategy reduce labor costs immediately?
Not always immediately. More often, it changes the future labor curve by creating capacity so the business can grow without adding headcount at the same rate. That is often where the biggest return shows up first. A Gartner report noted the share of CFOs planning significant staff growth fell year-over-year, reflecting a direct shift toward automation-driven efficiency.