If you’re leading change right now, you’ve probably heard business transformation and digital transformation used interchangeably, often in the same meeting, and perhaps even in the same sentence.
In practice, they serve different purposes, and that distinction has material consequences. Roughly 70% of transformation initiatives fail to meet their objectives, not because the strategy or technology was insufficient, but because execution breaks down when the connection between how change happens and why it’s happening isn’t fully aligned or supported by the data underneath it all.
Below, we explore how clarity between business and digital transformation influences the return on transformation investments.
Defining the terms
At a high level, digital transformation and business transformation solve different problems. One focuses on execution. The other focuses on outcomes.
Digital transformation: implementing new tech (the how)
Digital transformation is about using technology to improve how work gets done. In the context of business transformation and digital transformation, this is the execution layer. That might mean modernizing your CRM, automating manual processes, integrating systems, or introducing AI to reduce friction and scale operations.
When you invest in digital transformation, you’re asking questions like:
- How can we work faster?
- How can we reduce manual effort?
- How can we eliminate data silos and make sure all of our tools and systems talk to each other?
These are important questions. But on their own, they’re incomplete.
When underlying data is siloed, outdated, or unreliable, new tools often amplify the problem rather than resolve it.
Digital transformation improves how things happen, but it doesn’t automatically change what you deliver or why clients value it.
Business transformation: changing how value is created (the why)
Business transformation addresses why change is needed in the first place. It’s about redefining how your organization creates value for your clients and how that value is delivered consistently over time.
When you look at business transformation and digital transformation together, business transformation sets the direction. It clarifies what needs to change in your operating model, your client engagement approach, or your measures of success.
In most organizations, value isn’t delivered in a single moment. In relationship-driven organizations, that value is shaped by the quality of relationship intelligence: how well the firm understands who its clients engage with, across teams and over time. That makes business transformation less about adding new capabilities and more about rethinking how your teams work together to create a consistent experience for your clients.
This is where organizations tend to focus on more difficult questions:
- How do clients engage with you across teams and touchpoints?
- Where do hand-offs break down between sales, delivery, and account teams?
- How well do you understand the full client relationship, not just isolated interactions?
Business transformation often shows up as new operating models, new ways of managing client relationships, or new measures of success that go beyond short-term revenue. It usually spans multiple functions and regions, which is why it can be difficult to execute.
Technology can support this kind of change, but without clear business goals, digital initiatives often become costly, time-consuming efforts that fall short of their promised return.
The missing link: why 70% of transformations fail (the data gap)
In most cases, the problem is hiding in the underlying data.
Research from Gartner shows that around 30 percent of CRM data becomes outdated every year. That means by the time a transformation initiative is fully underway, a significant portion of the information meant to support it is already stale.
The issue isn’t just decay over time. Accenture found that only one third of executives trust their data sufficiently to derive value from it. When leaders don’t trust the data in front of them, decision-making slows, confidence erodes, and transformation efforts lose momentum.
You can see the impact quickly. For example, teams spend time hunting for details they’re not confident in. Leaders question reports and dashboards. Frontline staff work around systems instead of relying on them. And despite strong strategy and modern technology, progress slows.
This is where business transformation and digital transformation run into difficulties. Strategy assumes accurate, connected data. Technology depends on it. But when the data foundation is already eroding, both efforts are forced to operate with blind spots.
The result is a growing gap between how the business wants to operate and what its data actually supports and, until that gap is addressed, transformation remains far more difficult than it needs to be.
Case study: how automating CRM data (digital) transformed client experience (business)
LBMC set out to create a trusted, firm-wide view of client relationships so teams could collaborate more effectively and deliver a consistent client experience. With thousands of clients across multiple practices, this required clean, connected, and consistently maintained data.
LBMC introduced Introhive to automate CRM data management and deliver relationship insights directly within email and CRM. By removing the burden of manual data upkeep, CRM adoption increased and professionals could rely on the data to support client-facing work.
Within 90 days, LBMC realized a 567 percent return on investment, driven by time savings and cost reduction. More importantly, trusted relationship data enabled better meeting preparation, stronger account planning, and more consistent client experience management across the firm.
This is what it looks like when transformation initiatives are supported by relationship data that people actually trust and use.
Download the full LBMC case study here.
Strategic takeaway: don’t just digitize bad processes; automate data to enable new business models
Taken together, these points highlight a consistent pattern. Many digital initiatives fail to deliver real change because technology is asked to fix problems it was never designed to solve. Digitizing an existing process doesn’t change the quality of the data the technology depends on.
If business and digital transformation are going to deliver real impact, the focus has to shift from tools to data. Clean, accurate data that’s automatically captured and maintained is what allows new ways of working to emerge. It supports better decisions, more consistent client experiences, and operating models that scale.
This challenge is magnified in relationship-driven organizations. Client and relationship data lives in emails, meetings, and day-to-day interactions, not in forms or systems people want to update. When that information is fragmented or manually maintained, teams rely on personal workarounds. Collaboration suffers, insights are limited, and the organization’s growth depends largely on chance conversations rather than warm introductions based on who knows whom and how well.
Automating data capture and maintenance changes that dynamic. It reduces friction for teams, increases trust in what they see, and creates a foundation for growth that’s built on shared insight instead of individual effort.
Book a demo to see how automating relationship data can improve your organization’s data quality and support more effective transformation initiatives.
BOOK A DEMO
