Digital transformation launches typically culminate in exhausting final pushes. Teams work extended hours, sacrifice weekends, and operate on adrenaline and collective determination to get systems over the finish line. IT departments, contractors, merchandisers, and marketers unite in extraordinary effort. When launch succeeds, relief and celebration follow. Everyone assumes the heroic push was temporary—necessary for this particular deadline but not a permanent operating mode.
Then the next deadline approaches. And the pattern repeats. Teams again work nights and weekends. Manual workarounds compensate for system limitations. Individual expertise substitutes for documented processes. The heroic effort that seemed exceptional becomes routine. What was supposed to be a sustainable transformation turns out to require constant exceptional performance just to maintain operations.
This isn't just unsustainable—it's symptomatic. When organizations consistently need heroic individual effort to deliver acceptable customer experiences, the transformation hasn't actually transformed anything fundamental. It has simply relocated where exceptional effort gets applied.
The Unsustainable Cycle
Customer experiences should be seamless, dynamic, and ideally personalized. Websites and mobile applications should anticipate needs and surface relevant content without friction. Yet many organizations achieve this appearance of seamlessness through manual curation that doesn't scale. Teams work tirelessly creating, posting, and managing content when significant portions of this work could be automated with proper infrastructure.
In other cases, automation delivers less than promised. Organizations invest in platforms expecting efficiency gains but discover that workload and manual intervention actually increase as business volume grows. The automation handles routine cases adequately but creates exceptions and edge cases that require human resolution. As volume expands, these exceptions multiply faster than the organization can handle them.
Meeting aggressive deadlines for new product rollouts or campaign launches requires the team to mobilize again. Red Bull, pizza, and marathon meetings become normal rather than exceptional. Corners get cut with intentions to address issues later during the next upgrade cycle. But technical debt compounds faster than organizations repay it. The "temporary" compromises become permanent infrastructure limitations.
Short-term decisions driven by budget constraints and scope negotiations threaten overall program success disproportionately. Saving modest amounts now often creates costs later that dwarf initial savings. But those future costs aren't visible during budget discussions, so near-term savings win decisions.
Every significant project involves periods of intense pressure and maximum effort. The problem emerges when these intense periods become continuous. Pressure for rapid responses grows as customer expectations rise, competitors advance, and technology ecosystems become increasingly complex. Eventually, the esprit de corps that enables performance under pressure collapses under sustained strain.
The Toll on Stakeholders
All stakeholders experience fatigue. Employees burn out first, but vendors and contractors follow. Accumulated technical debt—the gap between quick improvised solutions and comprehensive proper approaches—builds until routine updates become fraught exercises consuming excessive resources just to maintain current functionality.
The costs aren't merely operational. Organizations lose institutional knowledge when burned-out employees leave. They lose vendor relationships when contractors decline renewal. They lose technical flexibility when technical debt constrains what's possible to implement. Most importantly, they lose the competitive advantage they sought through transformation.
Why Heroics Become Necessary
The need for heroic effort emerges from specific structural problems. Projects with too many moving parts, excessive manual processes, and fragile integrations require constant exceptional attention. Minimal viable products rolled out without adequate core functionality and supporting processes never develop stability.
Mismatched organizational rhythms create additional friction. Marketing operates at high velocity, constantly evolving functionality, offerings, and messaging. Finance operates at steadier pace with predictable cycles. IT attempts to keep pace with rapidly evolving technology ecosystems while responding to constantly shifting business requirements. These different operational tempos cause inefficient handoffs, mismatched development schedules, and architectural conflicts.
Add organizational crises—market disruptions, competitive threats, unexpected departures—and finding time or resources to address accumulated technical debt becomes impossible. The minimal functionality everyone reluctantly accepted as temporary compromise becomes permanent baseline. Limited initial scope means even more limitations downstream because proper foundations were never established.
The Accumulation Problem
Quick compromises and "good enough for now" solutions introduce friction that accumulates imperceptibly. Each individual compromise seems inconsequential. Addressing them individually appears not cost-effective. But collectively, they gum up the digital machinery driving customer experience.
This accumulation pattern is particularly insidious because problems remain invisible until they reach critical mass. Organizations operate with gradually degrading efficiency until something breaks dramatically, revealing how fragile interdependencies have become.
The COVID crisis illustrated this dynamic. Remote work transitions exposed how much organizational effectiveness depended on physical proximity and informal knowledge sharing. Layoffs eliminated experienced workers carrying institutional knowledge. Information that was easily accessible through hallway conversations became difficult to locate in poorly organized intranets and neglected knowledge bases.
The Internal Customer Connection
Organizations obsess about customer needs without recognizing that multiple customer types exist within any enterprise. The CEO considers external purchasers but also focuses on shareholders and stock performance. Board members are customers who can replace leadership if dissatisfied. Employees are customers whose effectiveness determines whether external customers receive good service.
Neglecting internal customers—the employees embodying day-to-day operations—creates cascading problems. When workers cannot locate information needed for their jobs, efficiency declines. Supporting customers, developing merchandising plans, onboarding products, creating sales strategies—all these activities slow down when required information is difficult to find.
These inefficiencies multiply and amplify. They become normalized as "business as usual" since people adapt to existing conditions rather than questioning them. Only crisis reveals system fragility.
Customer service inevitably suffers when departments cannot access needed information to answer questions or solve problems promptly. No amount of customer-facing polish compensates for internal dysfunction.
The AI Illusion
Some organizations believe machine learning and AI tools will solve their information problems. This represents fundamental misunderstanding. The information needed to train employees and support their work is the same information needed to train AI-based conversational assistants and cognitive technologies. If information isn't properly organized and accessible for employees, it won't be available for AI systems either.
Certain AI applications—semantic search, helper bots—attempt to compensate for poor historical data management. Organizations pursuing these projects often discover that managing information for AI tools presents the same challenges they face managing information for humans. The technology doesn't eliminate the underlying problem; it simply makes the problem more visible and urgent.
Attending to Supporting Processes
Solutions require paying equal attention to people supporting each customer experience stage and their information needs as given to end customers. The same organizing principles helping customers find products should help customer service representatives locate appropriate support articles. Product terms and categories used by finance for forecasting and reporting should be consistent throughout the enterprise for all departments and functions.
This consistency rarely exists. Different departments develop their own terminology, taxonomies, and organizational schemes. Finance reports use one product categorization. Marketing uses another. Sales uses a third. Customer service operates with its own structure. Each department's internal logic makes sense, but the lack of coordination creates massive inefficiency when work crosses departmental boundaries.
Building Sustainable Foundations
Addressing reliance on heroic measures requires shifting to holistic perspective during planning and execution. Individual program scope needn't expand dramatically, but programs should begin with larger context in mind. Several specific practices enable this shift:
Establishing Enterprise Taxonomies
Taxonomies form knowledge scaffolding of the enterprise—frameworks for everything important to the organization. Working sessions bringing different departments together reveal how their processes impact each other and how they use different terms for identical concepts. Even basic terms like "customer" or "product" carry various interpretations across departments. Simply making people aware of these inconsistencies improves coordination.
These sessions shouldn't be one-time events. Organizations need ongoing governance ensuring taxonomy remains relevant as business evolves. Someone must own the taxonomy, approve changes, communicate updates, and ensure consistent application across systems.
Mapping Supporting Processes
For any given platform—e-commerce, customer service, marketing automation—understanding upstream processes becomes essential. How are products onboarded? How is data updated and corrected? How are taxonomy changes determined and approved? Who needs consultation or notification? How is related support content managed? Are support assets reused or recreated from scratch because they're too difficult to locate?
Answering these questions reveals dependencies and bottlenecks. They show where manual processes could be automated and where automation already exists but isn't being used effectively because people don't know about it or don't trust it.
Analyzing Digital Asset Lifecycles
How are digital assets and content managed through their complete lifecycles? Are external agencies responsible for updates? Does the marketing department have access to image components or only finished compositions? Relying on agencies for asset management proves costly and inefficient compared to internal systems with proper training.
Understanding asset lifecycles also reveals duplication and waste. Organizations frequently discover they're creating similar assets multiple times because existing assets can't be found or don't exist in needed formats.
Funding Data Remediation Properly
Data remediation must receive sufficient funding to fix problems at their source. Addressing data quality issues downstream costs approximately six times more than fixing them at origin, yet downstream fixes remain common because they're easier to justify in immediate budgets.
Digital transformations are fundamentally data transformations. When data is missing, incorrect, or inconsistent, transformation fails regardless of how sophisticated the platforms are. This reality seems obvious in principle but gets forgotten during budget negotiations when data quality initiatives compete with visible feature development.
Instrumenting Metrics and Governance
Metrics and KPIs must be integral to governance and decision-making from inception. Data can drive substantial user experience improvements when proper frameworks exist, but these frameworks must be designed and instrumented from the start rather than retrofitted later.
This includes establishing baselines before transformation begins so improvements can be measured accurately. Without baselines, organizations cannot determine whether changes actually improved anything or simply shifted where problems occur.
The Holistic Perspective Shift
Focusing on how upstream and downstream systems manage and organize data encourages holistic views of enterprise information flows. This perspective reveals impacts that improved flows between tools and platforms have on customers. When data flows smoothly, the need for heroic individual effort declines because each department has required information readily available.
This isn't merely about implementing better technology. It's about recognizing that customer experience quality depends on internal operational excellence. Organizations cannot deliver consistently good external experiences while tolerating consistently poor internal experiences.
The transformation that actually transforms doesn't just change what customers see. It changes how the organization functions at fundamental levels. It eliminates systemic dependencies on heroic individual effort by building reliable systems and sustainable processes.
Organizations still need capable people. Individual excellence remains valuable. But organizational success shouldn't depend on extraordinary individual performance being routine. When it does, you don't have transformation—you have a more expensive version of what you had before.
This article was originally published on CustomerThink and has been revised for Earley.com.