Strong CIOs & CTOs Demand Complete Documentation With No Excuses - Or No Production Deployment

March 31, 2024

Incomplete, inaccessible, and inconsistent documentation is not a team discipline problem. It is a leadership permission problem. Teams produce incomplete documentation because their leaders allow them to - through tolerance, through exceptions, and through a persistent willingness to accept the excuses that make incomplete documentation sound reasonable. The impacts of poor documentation are far-reaching and significant, touching every team, every system, and every stakeholder in the enterprise. This article addresses CIOs and CTOs directly, discusses the scope and consequences of the problem, and describes the simple, structural policies that strong technology leaders can put in place to correct it - and explains why enforcement is straightforward: an undocumented application does not go to production, and the consequences for missing that gate are immediate and visible to everyone who matters.

Author: Frank Guerino

The Cost Nobody Attributes Correctly

Every IT organization carries a massive, invisible tax from documentation failures. The costs are real, recurring, and significant - but they are almost never attributed to their root cause. They show up distributed across incidents, projects, headcount, and timelines, attributed to complexity, to turnover, to the difficulty of the systems involved. The root cause - the absence of complete, accessible, current documentation - is rarely named on any report or business case. That invisibility is what allows it to persist.

The specific costs are worth naming, because naming them is the first step toward building a business case for eliminating them:

Onboarding new resources. When a new engineer, architect, operations specialist, or analyst joins a team and the systems they are responsible for are poorly documented, their productive ramp time is measured in months rather than weeks. They spend their first weeks and months interrupting senior team members with questions that documentation should have answered, reverse-engineering systems through code and configuration files, and making cautious assumptions about system behavior because they cannot find a definitive description of what the system is supposed to do. The cost is measurable: it is the salary of a capable professional who is not yet contributing at full capacity, multiplied by every month the ramp takes longer than it should. In organizations with high documentation quality, new team members reach full productivity significantly faster. The delta is a direct, quantifiable cost of the documentation gap.

Training without adequate documentation. Training programs that attempt to transfer knowledge about systems that are incompletely or inconsistently documented are expensive to develop and ineffective to deliver. Trainers cannot produce accurate, consistent training materials from systems they do not fully understand themselves. Training participants cannot learn reliably from materials that are incomplete, inconsistent, or out of date. The organization pays for training development, training delivery, and the follow-on support that becomes necessary when training produces understanding that is partial or incorrect. Well-documented systems produce better training materials faster, at lower cost, and with higher knowledge transfer fidelity. The training cost premium for underdocumented systems is rarely attributed to the documentation gap - it is attributed to the complexity of the material - but the connection is direct.

Debugging and correcting issues. When something goes wrong with a system that is poorly documented, the time required to diagnose the root cause and implement a correct fix is dramatically higher than it would be for a well-documented system. Engineers spend time establishing context that documentation should have provided: understanding the system’s design, mapping its dependencies, identifying the data flows that could be implicated, and reconstructing the intent behind the implementation they are trying to fix. Bugs are misdiagnosed because the engineer fixing them does not have an accurate mental model of the system. Fixes are implemented incorrectly because the engineer does not understand the downstream consequences of the change. The debugging and correction cost for underdocumented systems is consistently higher, consistently slower, and consistently more likely to introduce new issues in the process of fixing the original one.

Incident response delays. Production incidents in systems without current runbooks and triage plans take longer to diagnose, longer to resolve, and produce larger blast radii. The operations engineer responding to a 2am alert on a system they have never touched before cannot move efficiently without operational documentation. Every minute spent establishing context rather than executing a recovery procedure is a minute of downtime, a minute of customer impact, a minute of revenue at risk. Mean time to resolution is directly and measurably affected by the quality and currency of operational documentation. The cost of an extended incident is visible and painful. The root cause - the absence of the runbook that would have cut resolution time by half - is almost never attributed correctly.

Knowledge loss from staff turnover. When an engineer who built or deeply understands a critical system leaves the organization, the knowledge they carry with them is a cost that lands immediately and compounds over time. The system does not break on day one. But the next incident, the next required modification, the next integration project that touches the system will all take longer and carry more risk than they should. The cost is paid in the elevated effort of every subsequent interaction with that system, indefinitely, until the knowledge is reconstructed through investigation. In organizations where systems are well documented, staff turnover is a manageable operational event. In organizations where systems live primarily in the heads of the people who built them, turnover is a recurring institutional crisis.

Duplicate work and reinvention. When the design decisions, architectural patterns, and lessons learned from one system are not documented, the teams building the next system start from scratch. The same problems are solved again. The same mistakes are made again. The same alternatives are evaluated and rejected for the same reasons, without the benefit of the prior analysis. The cost of this reinvention is not just the engineering time spent on the redundant work - it is the organizational learning that is lost between projects, the institutional knowledge that should be compounding but is not because it was never captured.

Security and compliance exposure. Regulatory audits, security assessments, and compliance examinations require documentation. When it does not exist or is incomplete, the organization either cannot respond to audit requests - producing findings and remediation obligations - or scrambles to assemble partial evidence under examination pressure, producing a response that is both expensive and less credible than well-maintained documentation would have been. The cost of a regulatory finding is direct and quantifiable: remediation programs, management distraction, potential fines, and in some industries, heightened scrutiny on every subsequent examination.

Poor change management and unintended consequences. Change management processes that cannot draw on accurate dependency documentation produce impact assessments that miss critical relationships. Changes that should have been staged, coordinated, or rejected proceed without adequate preparation. The resulting incidents - the downstream system that broke because nobody knew it depended on the component that was changed - are attributed to operational failure rather than to the documentation gap that made the impact assessment incomplete.

Vendor and contractor inefficiency. External vendors, contractors, and system integrators who work on underdocumented systems spend a disproportionate portion of their engagement time on discovery work that should have been covered by documentation. Every hour a contractor charges for understanding a system that should have been documented is an hour that was paid for by the organization but delivered no new value. The cost is compounded when the same discovery work is repeated across multiple engagements because the documentation that would have captured it was never produced.

None of these costs appear on any report as “cost of inadequate documentation.” They appear as engineering hours, as extended incidents, as audit findings, as contractor overruns, as slow projects. Because they are misattributed, nobody builds a business case to eliminate them. They are accepted as the cost of complexity, of scale, of operating in a fast-moving environment. They are not. They are the cost of a leadership choice, and they stop the day the choice changes.

The Excuses Leaders Accept - and Why They Should Not

The excuses for incomplete documentation are consistent across organizations, industries, and technology generations. They have been heard at Merrill Lynch, at major life sciences and pharmaceutical companies, at financial services firms, at healthcare organizations, and at technology companies of every size. The specific wording varies. The substance does not. And none of them survive scrutiny.

“We didn’t have time.” This is the most common excuse and the least defensible. Documentation was not deprioritized by accident - it was deprioritized by a decision, usually a series of small decisions made under schedule pressure, each of which felt reasonable in isolation and collectively produced a system that went to production undocumented. The time that was “saved” by skipping documentation is repaid many times over in support costs, incident response time, and onboarding friction over the life of the system. The real statement is not “we didn’t have time” but “we chose to spend our time on other things,” and the person who made that choice did so because they did not believe there would be a consequence for it.

“The team knows how it works.” This is a single-point-of-failure risk wearing the costume of a reasonable answer. The team that knows how the system works is a team. Teams change. People leave, get promoted, get reassigned, take parental leave, or simply forget the details of a system they built two years ago and have not touched since. The moment the knowledge is concentrated in individuals rather than encoded in documentation, the organization has made a bet that those individuals will always be available when that knowledge is needed. That bet loses, consistently, at the worst possible times. “The team knows how it works” is not an answer to the documentation question. It is a description of exactly the problem documentation is supposed to solve.

“The code is the documentation.” Code describes what a system does, imperfectly and at a level of detail that is inaccessible to the majority of stakeholders who need to understand the system - operations teams, data teams, security teams, auditors, business analysts, and the architects who need to understand how this system fits into the broader enterprise. Code does not describe why decisions were made, what alternatives were considered, what the operational procedures are, how incidents should be triaged, what the data integration landscape looks like, or what the system’s dependencies are. Code is evidence of implementation. Documentation is the explanation of intent, design, operation, and context. They are not substitutes for each other.

“We’ll document it after the release.” After the release, the team is already working on the next release. The documentation that was deferred to after this release will be deferred again to after the next one. Post-release documentation is a promise that almost never gets kept, because the urgency that would motivate it dissolves the moment the release is complete and the next priority takes its place. The only documentation that reliably gets produced is documentation that is required before a gate. Everything else is optional, and optional documentation does not happen.

“The system is too complex to document fully.” A system too complex to document is a system too complex to support, too complex to hand off, too complex to modify safely, and too complex to audit reliably. Complexity is not an excuse for the absence of documentation - it is the strongest possible argument for its presence. The more complex a system, the more dependent the organization is on comprehensive documentation to manage it effectively over its operational lifetime. If a system is genuinely too complex to document, that is a design problem that should have been addressed before the system was built, not an operational reality to be accepted after it is in production.

Strong CIOs and CTOs have heard all of these excuses. They do not accept them, not because they are unsympathetic to the pressures that produce them, but because they understand what accepting them costs the organization over time. The standard is not perfection on the first release. The standard is that no system enters production without its documentation, and that standard has no exceptions.

And in the current era, not one of these excuses is even credible on its face. We live in a time when artificial intelligence can generate documentation quickly, accurately, and at a level of completeness that would have required days of engineering effort a few years ago. AI can read a codebase and produce architecture summaries, data flow descriptions, API specifications, and dependency maps. It can reverse-engineer source code into structured documentation that covers the concepts a runbook or integration specification requires. It can draft operational procedures from configuration files and deployment scripts. The “we didn’t have time” excuse, always weak, is now essentially indefensible. The tools to produce documentation quickly and well exist and are accessible. What remains missing, in the organizations where documentation is consistently incomplete, is not the time or the tooling. It is the leadership standard that makes documentation non-negotiable.

What Complete Documentation Actually Means

Before demanding complete documentation, define it. One of the most common reasons documentation requirements fail in practice is that “complete” is never specified precisely enough to be auditable. If completeness is defined as a feeling rather than a checklist, every team will have a different definition and every gate review will produce a different standard. Completeness must be defined as a specific set of artifacts, each with a defined scope, that together provide the coverage required for a system to be operated, supported, modified, and audited by people who did not build it.

The artifact set will vary by organization and by system type, but the core categories that apply to virtually every production system include:

Architecture and design documentation - the purpose of the system, its design decisions, the alternatives that were considered and rejected, its key components and their interactions, and its place in the broader enterprise landscape
Data integration specifications - every integration that moves data into or out of the system, including source, target, payload, format, transport mechanism, frequency, and the data entities involved
Build and configuration documentation - how the system is built, configured, and deployed, including environment-specific configuration parameters, infrastructure requirements, and deployment procedures
Operational runbooks - step-by-step procedures for every routine operational task: starting, stopping, scaling, backing up, restoring, and validating the system
Incident triage plans - documented procedures for diagnosing and responding to the failure modes most likely to affect the system, including escalation paths, diagnostic steps, and recovery procedures
Data dictionaries and data model documentation - what data the system manages, what each data entity means, what its quality standards are, and what its regulatory classification is
API and service specifications - the interfaces the system exposes and consumes, in sufficient detail for consuming teams to integrate without needing to contact the owning team
Security and access control documentation - the security model, the access control design, the authentication and authorization mechanisms, and the regulatory obligations the system carries
Dependency maps - the upstream and downstream dependencies that would be affected by changes to or failures of this system

Enterprise Architecture is the natural owner of the artifact templates that define what completeness means for each category. EA produces reusable, standardized documentation frameworks that every team works from, ensuring that coverage is consistent across all systems and that completeness is auditable rather than subjective. A runbook template defines what a runbook must contain. An integration specification template defines what an integration must document. Every team fills in the same structure, which means every artifact can be reviewed against the same standard. The absence of a required section is visible. The presence of a section that covers only surface detail is auditable. Consistency is the precondition for accountability, and Enterprise Architecture is the function that makes consistency achievable at scale.

Policy 1: No Production Without Documentation

This is the most important policy a CIO or CTO can establish, and it is structurally simple. No system or application enters the production environment until its documentation is complete and has been reviewed and signed off by the appropriate gating organizations. The gate is not a suggestion. It is a hard stop. A system without complete, reviewed documentation does not go to production. This policy has no exceptions, because every exception communicates that the policy is negotiable, and a negotiable policy is not a policy. Beyond the operational costs, allowing undocumented systems into production is a liability — one that surfaces in audits, in incidents, in regulatory examinations, and in every situation where the organization must demonstrate that it understands and controls what it has deployed.

Enterprise Architecture owns the control gate. EA defines the documentation standard, maintains the artifact templates, and is accountable for the consistency and quality of the gate across all systems. EA is positioned to own this responsibility because it already maintains the Enterprise Model and the documentation frameworks that define what complete looks like. Owning the production documentation gate is a natural extension of that work, not an additional organizational burden.

The review process is federated across the gating organizations that have domain-specific accountability:

Data teams review data integration documentation - verifying that every integration moving data into or out of the system is documented to the required standard, with source, target, payload, format, and transport specified
Operations teams review operational documentation - verifying that runbooks, incident triage plans, deployment procedures, and configuration documentation are in place and sufficient for a team with no prior knowledge of the system to operate and support it
Architecture teams ensure and review design documentation and dependency maps - verifying that the system is documented in the context of the broader enterprise landscape and that its architectural decisions and dependencies are captured. Architecture teams also ensure all other documentation is in place and part of the deployment bundle.
Security teams review security and access control documentation - verifying that the security model, authentication and authorization design, and regulatory obligations are documented
Etc.

Each gating organization does not need to read every word of every document. They need to verify that the required artifacts exist, that they are populated, and that they meet the coverage standard for their domain. The gate review is a completeness check, not a deep technical review. It can be conducted efficiently by people who know what they are looking for, and it produces a sign-off record that documents who reviewed what and when. In fact, collecting actual signatures from gatekeepers makes them visibly accountable and ensures they will work harder to ensure documentation is in place.

The enforcement mechanism is the simplest possible: an undocumented system does not go to production. There is no complex disciplinary process, no performance management sequence, no escalation matrix to navigate. The gate is closed. If a team wants to go to production on schedule, they produce the documentation. If they choose not to produce the documentation, they explain to their stakeholders why their deliverables are late. They explain to the CIO and CTO why they chose not to meet the standard. Both conversations are unpleasant, and both are entirely avoidable by meeting the standard. In practice, teams that believe the gate is real and will be consistently enforced document their systems. The perceived organizational complexity of enforcement dissolves when the consequence is clear, immediate, and unavoidable.

It is worth being honest about where the difficulty actually lies. Creating complete documentation for the first time - for a system that has never been documented to the required standard - is the hardest part of this work. It requires the most time, the most effort, and the most knowledge gathering. For systems that are already in production and underdocumented, there will be a one-time catch-up investment that is real and should not be minimized. But maintaining documentation from that baseline forward, with each subsequent release and change, is a fundamentally different and far easier discipline. When the structure exists and the templates are in place, updating documentation to reflect a new integration, a changed configuration, or a revised operational procedure is a fraction of the effort that creating it from scratch required. Teams that have gone through the initial documentation effort consistently report that subsequent releases are significantly less burdensome because they are updating a living artifact rather than producing one from nothing. The front-loaded cost is real. The ongoing cost, once the foundation is established, is manageable - and it is dwarfed by the support, onboarding, and incident costs it eliminates.

Policy 2: Standardized, Reusable Documentation Artifacts

Ad hoc documentation - each team inventing its own structure, covering whatever concepts the author thought were important, using whatever terminology felt natural - is nearly as damaging as no documentation. It cannot be audited systematically because there is no consistent standard to audit against. It cannot be searched effectively because the same concept is described differently in every system’s documentation. It cannot be compared across systems because the coverage is inconsistent. It does not transfer knowledge efficiently because the reader must first learn the author’s organizational style before they can find the information they need.

Enterprise Architecture should define and maintain a library of standardized documentation templates, one per artifact type, that every team uses for every system. A single runbook template. A single integration specification template. A single architecture and design document template. A single incident triage plan template. The templates define the sections that must be present, the level of detail required in each section, and the format and terminology standards that make documents consistent and comparable across systems.

The benefits of standardization compound over time. When every system’s architecture documentation follows the same structure, an operations engineer who has read one knows how to navigate all of them. When every integration specification covers the same fields in the same order, a data team auditing integration documentation can move efficiently across hundreds of systems rather than reorienting to a new format with each one. When every runbook covers the same categories of operational procedures, a support engineer responding to an incident at 2am can find the relevant section without searching. The investment in creating and maintaining the templates is made once by Enterprise Architecture. The return on that investment is realized by every team, on every system, for the operational lifetime of the documentation.

Template maintenance is an ongoing responsibility, not a one-time project. As systems evolve, as new technologies are adopted, as regulatory requirements change, and as operational experience reveals gaps in the existing templates, Enterprise Architecture updates the templates and communicates the changes to the teams that use them. The library of templates is a living artifact, governed by Architecture, that reflects the current state of what complete documentation means for the organization.

Policy 3: Centralized, Organized, and Fully Open

Documentation that exists but cannot be found is nearly as useless as documentation that does not exist. Every IT organization has experienced the situation where documentation for a critical system exists somewhere - on someone’s laptop, in a folder in a shared drive that nobody outside the team knows about, in a wiki that was set up three years ago and has not been updated since, or attached to a ticket in a project management system that the current team does not use. This documentation does not help the operations engineer who needs it during an incident. It does not help the security auditor who is looking for it during an examination. It does not help the new hire who is trying to understand a system they have been asked to support. Documentation that cannot be found is documentation that does not exist for all practical purposes.

All system and application documentation should live in a single, consistently organized, enterprise-wide location that is accessible to every stakeholder - engineers, architects, operations teams, security teams, data teams, auditors, and business leadership. The organizational structure should be consistent: every system has a documentation home in the same place, organized the same way, so that finding the documentation for any system is a matter of knowing the system name, not knowing who owns the folder.

Open access is not optional and it is not a security risk. It is a multiplier. An operations engineer who can read the architecture documentation for a system they have never touched before an incident responds to that incident more effectively than one who cannot. A new hire who can access comprehensive documentation for every system in the portfolio from their first day onboards faster and contributes sooner. An architect reviewing a proposed change can assess its dependencies without scheduling a meeting with the owning team. A business analyst trying to understand the data that flows through a system can find the answer without filing a ticket. A security auditor who can pull documentation directly does not consume engineering time. Every stakeholder who can self-serve from comprehensive, centralized documentation is a stakeholder who is not blocking another team’s calendar or creating an interrupt that disrupts someone’s focus.

The argument against open documentation - that it exposes sensitive information to too broad an audience - conflates access control with documentation quality. The appropriate response to sensitive content in documentation is to handle that content appropriately: classify it, control access to it where access control is genuinely warranted, and redact it from the broadly accessible version where full exposure is inappropriate. The appropriate response is not to make all documentation inaccessible by default. Organizations that use sensitivity as a blanket justification for restricted documentation are, in most cases, using it as a convenient reason to avoid the discipline of producing documentation that is accurate and complete enough to share. Strong CIOs and CTOs recognize this and do not accept it.

Policy 4: Regular Documentation Audits

Documentation degrades. Systems change. Features are added. Integrations are modified. Infrastructure is upgraded. Teams turn over. The engineers who wrote the original documentation are replaced by engineers who know the current system but were not part of the original documentation effort and do not always update what exists. The gap between what is documented and what is true widens silently, year by year, until the documentation that was complete at the time of the production gate review has become materially inaccurate or incomplete.

The production documentation gate addresses the initial completeness problem. Regular audits address the ongoing currency problem. Enterprise Architecture conducts these audits on behalf of the CIO and CTO - acting as the delegated authority for documentation governance across the portfolio. This is the right assignment: EA owns the documentation standard, maintains the artifact templates, and has the enterprise-wide scope to assess documentation quality consistently across all systems and all product teams. The CIO and CTO set the standard and receive the findings. EA does the work of verifying that the standard is being met.

The audit approach is sampled rather than exhaustive. Auditing every document for every system in the portfolio on a frequent cadence would be impractical and unnecessary. Instead, EA conducts structured sampling: a defined percentage of systems are selected for full documentation review on a rotating basis, ensuring that every system in the portfolio is reviewed on a meaningful cycle, while high-criticality systems are audited more frequently than lower-criticality ones. The sampling methodology is documented and consistent, so that the audit results represent a statistically meaningful view of portfolio-level documentation health rather than a selective picture that flatters the best-documented systems.

On a defined schedule - quarterly for high-criticality systems, annually for others as a minimum - the selected systems are reviewed against the current state to verify that documentation remains accurate, complete, and accessible. The audit does not need to review every word of every document. It identifies material gaps: integrations that were added without documentation updates, runbooks that cover a deployment process that no longer exists, architecture documentation that describes a design that was replaced eighteen months ago. The federated review model mirrors the production gate: Data teams audit integration documentation currency, Operations teams audit runbook and triage plan currency, Architecture audits design documentation and dependency map currency, Security audits security documentation currency.

Audit findings are escalated directly to CIO and CTO leadership - the same way security vulnerability findings are escalated - and they are treated as organizational risk on a remediation timeline. A system whose documentation has fallen materially below the coverage standard is flagged and the owning product team is held accountable for remediation. The finding is visible to leadership. The remediation timeline is tracked. And the product team that owns the system understands that the audit is not a bureaucratic exercise - it is EA acting on behalf of the most senior technology leaders in the organization to ensure that the standard they have set is being upheld. That visibility, combined with the clear consequence of a finding appearing on the CIO’s and CTO’s radar, is what gives the audit function its teeth.

AI makes the audit process itself more tractable. EA can use AI tools to perform preliminary documentation completeness checks - scanning documentation repositories for missing artifacts, flagging sections that are below the required depth, comparing documented integration specifications against actual system behavior extracted from code or configuration, and identifying architecture documentation that describes components or relationships that no longer exist. AI-assisted auditing does not replace human judgment on the findings, but it dramatically reduces the manual effort required to identify where human attention is needed. The audit becomes faster, more consistent, and more comprehensive than any purely manual process could be.

The Compounding Benefits of Getting This Right

When all four policies are in place and consistently enforced, the benefits compound across every function and every team in the organization. They are not marginal improvements. They are qualitative changes in what the organization is capable of.

Faster, more effective incident response. Operations teams responding to incidents can find current runbooks and incident triage plans without tracking down subject matter experts. Mean time to resolution drops because the diagnostic steps, escalation paths, and recovery procedures are documented and accessible. The institutional knowledge that previously lived in the heads of a few senior engineers is encoded in documentation that any qualified engineer can act on.

Contained knowledge loss from staff turnover. When an engineer who built and maintains a critical system leaves the organization, the loss is bounded. Their knowledge of that system is encoded in documentation that remains with the organization after they are gone. The organization does not lose the system when it loses the person. This is one of the most valuable and least appreciated benefits of comprehensive documentation - it decouples organizational capability from individual tenure.

Faster onboarding and knowledge transfer. New team members who join an organization with comprehensive, centralized, accessible documentation onboard in weeks rather than months. They can develop genuine understanding of the systems they are responsible for without consuming months of senior engineer time in knowledge transfer sessions that should not be necessary.

Higher scores on independent audits and regulatory examinations. Auditors and regulators ask for documentation. Organizations with comprehensive, current, centralized documentation can produce it quickly, completely, and confidently. Organizations without it spend weeks scrambling to assemble partial evidence and explaining gaps. The audit outcome is predictably better when the documentation exists, and the management distraction and remediation cost of a poor audit outcome is predictably lower.

More effective cross-team collaboration. Teams that can read each other’s system documentation without scheduling meetings with subject matter experts collaborate more effectively, make better-informed integration and dependency decisions, and are less likely to make changes that have unintended consequences for systems they did not realize were downstream. Knowledge sharing across the enterprise - both domain-specific and general - is a compounding organizational benefit that only accrues when documentation is genuinely open and findable.

Dramatically more powerful AI-assisted analysis. AI tools applied to enterprise knowledge - for query, for impact analysis, for documentation generation, for architecture review - are only as powerful as the documentation they work from. An AI system that can read complete, current, consistently structured documentation for every system in the portfolio can answer questions, surface dependencies, and generate analysis that would otherwise require days of human investigation. An AI system working from incomplete, inconsistent, or inaccessible documentation produces incomplete, inconsistent, and unreliable output. As AI becomes an increasingly central tool in enterprise technology management, the quality of documentation becomes an increasingly direct determinant of the quality of AI-assisted work.

The Leadership Imperative

The four policies described in this article are simple. They are not technically complex, organizationally exotic, or expensive to establish. A production documentation gate, standardized artifact templates owned by Enterprise Architecture, a centralized and openly accessible documentation repository, and a regular sampled audit program - none of these require a multi-year transformation program or a significant capital investment. What they require is a leadership decision to treat documentation as a non-negotiable standard rather than an aspirational practice. That decision is simple to make and straightforward to enforce. And yet, far too often, it is not made.

The difference between organizations with strong documentation cultures and those without almost always traces back to a single variable: the experience and judgment of the CIO or CTO. Inexperienced technology leaders tend to neglect documentation policies - not out of malice, but because they underestimate the compounding cost of the gap and overestimate the difficulty of closing it. They accept the excuses. They grant the exceptions. They treat documentation as something the organization will get to when things slow down, without recognizing that things never slow down and the gap never closes on its own. Experienced technology leaders understand something their less experienced counterparts have not yet learned: having complete, centralized, well-organized, and readily accessible knowledge about every system in the portfolio makes them and their entire organization meaningfully more capable. It makes their teams faster, their incidents shorter, their audits cleaner, their onboarding cheaper, and their strategic decisions more grounded. It is not a cost center. It is a force multiplier. And the leaders who have seen both sides of the gap - the organizations where documentation exists and the organizations where it does not - never go back to tolerating the latter.

Documentation is not a team preference. It is a leadership standard. The teams that do not produce complete documentation are the teams whose leaders have communicated - explicitly or through tolerance - that incomplete documentation is acceptable. Every exception to the production gate. Every schedule pressure that is resolved by deferring documentation. Every retrospective that identifies documentation as a gap and produces no structural change. Each of these is a message to the organization that the standard is negotiable, and negotiable standards are not standards.

This pattern has been observed consistently at Merrill Lynch and across many other organizations. The organizations that have the best documentation are not the organizations with the most talented engineers or the most sophisticated tooling. They are the organizations with leaders who established the standard, funded the Enterprise Architecture function that defines and maintains the artifact templates, and enforced the production gate consistently without exceptions. The culture of documentation in those organizations is not the cause of the good documentation - it is the consequence of the leadership behavior that made incomplete documentation unacceptable.

There is a longer-term benefit that compounds beyond the operational and financial returns: culture. When thorough documentation becomes muscle memory — when teams have internalized the practice deeply enough that it no longer requires enforcement pressure to produce — the organization changes qualitatively. Teams that document consistently begin to experience the benefits firsthand: faster incident response, smoother onboarding, less time spent answering the same questions repeatedly, and the ability to return to their own systems months later without relearning what they built. The motivation shifts from avoiding the consequence of not documenting to wanting the advantages that documentation provides. Simultaneously, social norms reinforce the standard: once documentation is consistently present across the portfolio, shipping without it starts to feel incomplete rather than normal, and teams begin to hold each other accountable without waiting for leadership to prompt them. The gate that was initially an external enforcement mechanism becomes an internalized professional standard. That is what a documentation culture actually is — and it cannot be mandated into existence. It emerges when enough people in the organization have lived on both sides of the gap and concluded, from their own experience, that documentation makes their work better. Leadership creates the conditions. Experience does the rest.

Strong CIOs and CTOs understand that documentation is not overhead. It is infrastructure - the knowledge infrastructure that every operational process and asset depends on. They fund it, govern it through Enterprise Architecture, enforce it through the production gate, and audit it on a regular schedule. They do not accept the excuses. They do not grant exceptions. And they do not treat documentation quality as a cultural aspiration that might improve over time if the right people are hired and the right values are promoted. They treat it as a structural requirement that the organization either meets or does not - and they have made their position on which outcome they will accept abundantly clear.

Closing Thought

There is a version of this article that could be written about what great documentation looks like: the elegant architecture document, the perfectly structured runbook, the data integration specification that anticipates every question a downstream consumer might have. That article would be interesting and largely irrelevant to the problem most organizations actually face.

Most organizations do not have a documentation quality problem. They have a documentation existence problem. The systems that should be documented are not. The runbooks that should exist do not. The integration specifications that every data team would benefit from have never been written. The architecture documents that would make onboarding and incident response and audit preparation dramatically more tractable are absent, or present in a form so incomplete and so inaccessible that their existence makes no practical difference.

The solution to a documentation existence problem is not a documentation quality program. It is a gate. An application that is not documented does not go to production. That standard, established by leadership, owned by Enterprise Architecture, enforced by the gating organizations, and audited on a defined schedule, is the entire intervention. The consequences for failing to meet it are immediate and visible: a missed production date and a conversation with the CIO or CTO about why the standard was not met.

Strong technology leaders like CIOs and CTOs do not wait for documentation culture to improve. They proactively change the enterprise culture - by making the absence of documentation costly and its presence a structural requirement of doing work in their organization, without exception. The rest follows.

Published by Guerino Enterprises, LLC – Copyright Guerino Enterprises & Frank Guerino