Cory McNeley is a Managing Director at UHY Consulting.
In today’s day and age, digital transformation has never been more accessible, but in my opinion, it has also never been more disappointing. Organizations are investing heavily in ERP platforms, AI tools, massive data lakes, analytics, automation and modern applications while simultaneously failing to gain measurable business outcomes from those investments.
The problem seems to be the lack of alignment on how technology is actually operated across the organization. In my experience, most transformation efforts do not fail at the strategic or technology levels. Instead, they fail at the operationalization level.
The Missing Layer
There is a missing layer in how the business actually runs.
Technology can only be as effective as the system it supports. Too often, organizations tend to implement new tools while leaving the underlying issues unchanged. Finance, IT and operations continue to operate in silos. Data remains fragmented. Ownership of systems is unclear. Success is measured by project completion instead of actual business impact.
The results are predictable. Organizations become more tech-rich but remain outcome-poor. Without an operating model that connects strategy, execution, accountability, data, people and measurable outcomes, even the best initiatives typically fail.
Common Failure Points Across Industries
1. Technology transformation is usually coined as an IT initiative. In reality, it is a business initiative that requires shared support from IT, finance, operations and leadership. Without clear accountability, decisions tend to stall, adoption may suffer and IT can become a support mechanism instead of a driver of the business.
2. Organizations continue to struggle with data silos. Many companies are investing heavily in analytics and AI before developing consistent data definitions, taxonomy, clear ownership and governance. This can lead to mistrust in reporting, AI hallucinations and a limited ability to scale and grow with the tools they have already invested in.
3. There is often no connection to measurable business value. Projects are typically measured based on milestones, timelines and budgets. But how often are they measured based on outcomes?
If an organization cannot tie a new system or transformation to margin improvement, cash flow, efficiency, cycle-time improvement, revenue growth, customer-base expansion or reduction in DSO, momentum starts to fade dramatically and quickly. And at that point, you have to ask: Did you really focus on the right project? Change for technology’s sake does not necessarily bode well. There needs to be a measurable outcome.
4. Change management and people are treated as an afterthought. Training does not drive adoption. Training does not drive buy-in. Without embedded change management throughout the entire process, the platform and the implementation are doomed to fail. Super users need to be developed. Systems need to be trained upon. People need to understand how the process changes so they do not revert to old habits.
The Modern Operating Model Difference
In my experience, organizations that are truly successful in translating technology into results tend to operate differently. They focus on how the business operates, how people operate and what the true process is.
A modern operating model needs cross-functional governance from a multitude of people across the organization. You want to hit every area where someone is going to be impacted, whether that is finance, accounting, IT, operations, field operations or leadership. Each of those groups should jointly define priorities, investment decisions and the metrics that actually matter.
Transformation needs to be measured against value-based KPIs and KRIs. It should also be measured against outcomes as well as project milestones. Margin expansion, revenue growth, customer base, reduction in DSO, cycle-time improvement and efficiency are tangible outcomes organizations can measure. Data should also be treated as a core asset.
Clear ownership, standardization and governance should be embedded into applications and initiatives. Modern systems rely on data, and data is the blood of those systems.
What Leaders Can Do Next
Now more than ever, organizations need to look at automation, AI and analytics and make sure they are integrated into the process. They need to make sure the business is ready for them. These tools cannot sit off to the side as standalone technology. They need to be fully ingrained to drive value. Transformation is shifting from a series of one-off projects to continuous business improvement.
Start by defining clear ownership so everyone knows who is involved in the transformation, who owns it, what the outcomes are and what the expectations are. Align on the value of the transformation before embarking on a project, and identify specific business metrics that create a North Star to focus on. Assign responsibility for data and domains.
With multiple systems, make sure things are harmonized, succinct and working together. More importantly, don’t forget enablement. Enablement is key. Change management drives the vast majority of success.
The Bottom Line
You cannot buy technology and assume it will create an advantage. Competitive advantage tends to come from who is most effectively using their technology.
The organizations that rethink how they operate and align people, data and technology around measurable outcomes are more likely to be the companies that see real business value from their digital investments.
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