Tag Archives: CIO

What CISOs Already Learned: Service Management’s Language Problem

November 3, 2026 Doug Tedder Leave a comment

Most boards don’t discuss incidents, changes, requests, SLAs, MTTR, or knowledge articles. Yet many service management leaders continue to present those metrics as though they are inherently meaningful to executives.

Twenty years ago, many security leaders approached executive communication in much the same way. Conversations centered on vulnerabilities, patch compliance, security controls, and other technical topics. Today, successful CISOs are far more likely to discuss business disruption, operational resilience, regulatory exposure, and organizational risk. In fact, Deloitte specifically advises CISOs that “technical metrics don’t resonate in the boardroom” and recommends focusing discussions on business impact and organizational value instead.

Service management is facing a similar challenge.

Service Management’s Language Problem

Contrary to what some might believe, service management doesn’t have a language problem because practitioners are poor communicators. Service management has a language problem because many organizations have confined it to an operational role.

For years, service management has been associated with incidents, requests, changes, service desk operations, and SLA reporting. The result is predictable: service management leaders naturally talk about the things they’ve been asked to manage.

The irony is that service management frameworks have never described service management that narrowly. At its core, service management exists to help customers achieve desired outcomes while creating value through the effective use of services. Services are intended to support business objectives.

Yet many organizations have reduced service management to the efficient execution of IT processes.

When Service Management Doesn’t Discuss Value

Somewhere along the way, many organizations stopped managing services and started managing tickets. We claim to practice service management, but much of what we actually manage is operational workflow.

The result is a credibility gap. We tell executives that service management is about value, outcomes, and business objectives. Then we present dashboards filled with ticket counts, SLA attainment, backlog volumes, and MTTR. We should not be surprised when executives struggle to connect service management to business value.

This challenge is not new. Chris Barrett has written extensively about bridging ITSM concepts to boardroom value. One of his observations is that IT often arrives at executive and board discussions in a reactive or defensive posture, reporting incidents, outages, project status, and risks rather than discussing value creation. As he put it, for many organizations IT arrives at the board table like an unwelcome house guest.

If service management leaders want executive attention, we should stop asking executives to care about incidents, requests, and SLAs. Instead, we should demonstrate how service management reduces friction, improves productivity, enables organizational agility, strengthens resilience, and helps achieve strategic objectives.

The problem becomes particularly visible when we look at one of service management’s most common measures: the SLA.

The SLA Test

Consider the ubiquitous SLA.

Organizations proudly report SLA attainment percentages as evidence of service quality and value delivery. Yet many of these so-called SLAs are nothing more than configuration settings within an ITSM platform: response targets, resolution timers, escalation thresholds, and workflow triggers.

They measure whether the tool performed as configured. They do not necessarily measure whether the business achieved a meaningful outcome.

A true service level agreement should reflect a business need. It should describe how a service supports patient care, enables transaction processing, facilitates customer on-boarding, or supports critical manufacturing operations.

Instead, many organizations report:

95% of Priority 2 incidents resolved within eight hours
98% first-response compliance
99% SLA attainment

An executive’s reasonable response might be, “That’s interesting, but what does that mean for the business?”

And too often, IT struggles to answer.

As I’ve argued previously, many organizations don’t actually have service level agreements. They have ticket processing targets masquerading as service level agreements. In many cases, what is called an SLA is really just an ITSM platform configuration setting.

An SLA that cannot be connected to a business outcome is just a timer.

What CISOs Learned

As cybersecurity matured as a business discipline, successful CISOs recognized a fundamental truth: executives and boards were never going to become interested in cybersecurity simply because security professionals thought it was important. To gain executive attention, security leaders had to demonstrate how cybersecurity affected the organization’s ability to achieve its objectives.

That shift changed the conversation. Discussions that once centered on vulnerabilities, patches, and security controls increasingly focused on business risk, resilience, regulatory exposure, and operational continuity. The lesson from successful CISOs is not that they learned a new vocabulary. The lesson is that they stopped describing technical activities and started describing business consequences.

Lessons for Service Management

Too often, service management conversations begin with incidents, requests, changes, SLAs, ticket volumes, and other operational measures. While those metrics may be important to managing services, they are rarely important to executives in and of themselves. Executives are far more interested in understanding how technology services contribute to employee productivity, customer experience, organizational agility, operational resilience, and strategic success.

Consider how differently the same information can be presented. A report showing that MTTR improved by 15% may be meaningful to IT operations. A discussion explaining that employees regained access to critical business tools more quickly, reducing productivity losses and business disruption, is meaningful to business leaders. The metric hasn’t changed. The context has.

The same principle applies to services themselves. Many IT organizations still define services by the technologies they manage. Business leaders, however, do not invest in technology for technology’s sake. They invest because technology provides the capabilities to enable communication, collaboration, revenue generation, customer engagement, and other business outcomes.

Perhaps the most significant shift is how we think about tickets. Service management professionals often view incidents, requests, and complaints as work that must be processed efficiently. Executives tend to see something different. Every ticket represents friction. It is evidence that something is delaying a transaction, interrupting productivity, creating risk, or preventing someone from achieving a desired outcome.

Seen through that lens, tickets become less about workload and more about understanding barriers to organizational performance.

Ultimately, the most effective service management conversations begin not with an activity but with a business objective. The question should never be, “How many incidents did we resolve?” The more important question is, “What business outcome did our efforts help achieve?”

The Conversation Must Change

For years, service management has measured what matters to IT. The challenge now is to communicate what matters to the business.

The lesson from CISOs isn’t that they abandoned technology conversations. It’s that they stopped leading with them. Successful security leaders learned to connect technical activities to business risk, resilience, and organizational objectives. Service management leaders must make the same shift.

If we want executive attention and support, we must stop asking executives to care about incidents, requests, SLAs, MTTR, and ticket volumes. Instead, we need to show how service management increases productivity, enhances resilience, reduces risk, drives growth, enhances employee and customer experience, and contributes to reaching strategic goals.

The organizations that elevate service management from an operational discipline to a strategic capability will be those whose leaders deliberately connect services to business outcomes and organizational value.

The journey to the executive suite or boardroom does not begin with better dashboards. It begins with a better conversation.

Leadership, Service Management

If Service Management is about business value, then why don’t we talk about…Business Value?

October 5, 2026 Doug Tedder

Service management has always been about enabling business outcomes, yet many organizations still practice it as a technology management discipline. The question isn’t whether service management understands business value—the question is why organizational leadership, and IT cultures often fail to frame it that way.

Why we don’t understand

There are several reasons why service management is misunderstood—from both IT and non-IT perspectives.

It’s an identity problem – Frameworks like ITIL^® have emphasized value creation, outcomes, and services for years. Yet in practice, many organizations still experience service management as a collection of operational processes. There’s a gap between the theory and the implementation.
The approach to service management adoption – This may have been one of the unintended consequences of widespread framework adoption. Organizations spent years implementing IT operational practices like incident management, change management, service request management, and maybe a few other practices…and stopped. Service management success was measured in terms of IT compliance with these practices and IT-defined performance measures rather than organizational outcomes. The conversation became “Did we follow the process?” instead of “Did the process improve customer outcomes?”

And when that happens, the organization naturally associated service management with bureaucracy instead of value creation.

Leadership delegated – or ignored – service management instead of owning it – Many executives view service management as something to delegate to IT rather than as a management discipline that spans the enterprise. Consider how CEOs typically discuss strategic priorities in terms of customer experience, digital transformation, innovation, growth, and operational resilience. Rarely do CEOs discuss service management as a strategic differentiator. Ironically, these strategic priorities depend on the outcomes from good service management to realize strategic success.
IT made service management about itself – IT initiated an implementation project without inviting non-IT colleagues to be part of the strategy or design of service management. As a result, many service management implementations are focused only on the work of (some parts of) the IT organization and not on the business of the business.
IT reinforces the misconception – Many IT organizations continue to define themselves by technology rather than by the services and business outcomes they enable. Ask an infrastructure team what they do, and you’ll likely hear about managing servers, networks, cloud platforms, and endpoints.

Ask non-IT colleagues what they need, and you’ll hear things like closing sales, shipping products, collaborating with employees, and processing customer orders. Those are entirely different conversations. Technology should be discussed as an enabler, not the objective.

Why this matters now

I think the rise of AI makes this conversation even more important.

AI can make individual tasks dramatically faster. It can summarize incidents, route requests, answer questions, generate code, and automate workflows. But as I’ve said before, AI cannot compensate for a poorly designed service operating model. If the underlying service is fragmented, the data is inconsistent, ownership is unclear, or processes optimize local efficiency instead of customer outcomes, AI simply accelerates those shortcomings.

Organizations that will benefit most from AI won’t necessarily have the best AI. But they will have the clearest understanding of:

the services they provide
the outcomes those services are meant to achieve
the governance to continually improve them

That’s the domain of mature service management—not as an IT function, but as a business capability.

Imagine a sales organization whose “service” is enabling representatives to close deals. If requests for pricing, CRM access, and contract approvals bounce across siloed teams and misaligned tools, AI chatbots and copilots will only help sales reps get faster (but poor) answers to a broken process. When service management focuses on the end-to-end sales outcome instead, AI can amplify a well-designed service rather than accelerate dysfunction.

It’s about the business

Here’s the deeper issue.

Many organizations still see service management as running services. I think the future of service management is managing the enterprise through services.

That’s a subtle but profound distinction. “Running services” is concerned with system availability, meeting SLAs, and resolving incidents. “Managing the enterprise through services” asks (and provides answers to) the following questions:

Are customers accomplishing what they came here to do?
Are employees able to deliver value without unnecessary friction?
Are our services adapting as customer needs change?
Are we creating outcomes that strengthen the business?

The first perspective is operational.

The second is strategic.

The opportunity is there…if we only take it

For me, that’s the opportunity for the profession. Service management doesn’t need to reinvent itself; it needs to reclaim its original purpose; it needs to reframe the conversation. Instead of being known for process governance or just as a service desk, it should be recognized as the discipline that enables organizations to consistently deliver value, improve experiences, and adapt with confidence.

In that framing, here are examples of some of the clearest indicators that service management is succeeding:

Employee Experience – Employees spend more time creating value and less time dealing with technology challenges.
Customer experience – Customer interactions are easier, which helps drive improved satisfaction.
Revenue protection – Effective service management protects existing revenue by minimizing or eliminating the impact of disruptions to customer-facing systems.
Time-to-market – New products and services reach customers faster.
Strategic Execution – Good service management ensures that technology investments support, deliver, and sustain strategic goals and objectives.

When executives talk about digital transformation, operational resilience, and customer experience, they are already talking about the outcomes of service management—even if they don’t use that language.

It’s time for service management professionals to help leadership reframe the conversation from “IT processes” to “services that deliver strategic business outcomes.”

Customer Experience, Service Management

Why Are Companies Missing the Critical Link Between Service Management and Customer Experience?

September 3, 2026 Doug Tedder 1 Comment

Few CEOs will disagree that customer experience (CX) matters. Leading CEOs increasingly treat customer experience as a strategic differentiator, not just another service function. Research from BCG identifies CX as the highest-priority investment area, while IDC’s global CEO survey highlights customer experience as a core executive priority for growth and innovation.

Yet unlike CX, service management rarely appears as a CEO-level strategic priority.

But here’s the disconnect. Most CEOs don’t recognize good service management as one of the principal mechanisms for delivering good CX. The more effectively service management becomes at improving the customer experience, the more strategically relevant it becomes.

What’s Missing?

There are two critical factors why companies are missing the link between service management and CX.

Service management has an image problem – For decades, service management has been associated only with IT service desks, tickets, approvals, and IT process compliance. When executives hear “service management”, they think about service desk metrics, change approvals and change advisory boards (CAB), and system outages. They don’t think about customer loyalty, revenue growth, or competitive differentiation – even though those outcomes depend on how well services are managed end-to-end.

IT doesn’t help itself either, as many service management environments are limited to IT operations and infrastructure. Measures and reports from IT only reflect operational outputs, not business outcomes. As a result, service management is viewed as operational overhead rather than a strategic capability.

CX is diluted – In many organizations, CX is owned by different parts of the business. Most organizations place CX under Marketing, Sales, Customer Success, or other departments. Each of these departments focuses on and optimizes different metrics. Marketing measures brand perception. Sales measures revenue growth. Customer Success measures customer retention.

Meanwhile, service management lives in IT, operations, or a shared services function. IT measures SLA compliance. Operations measures cost. Shared Services measure cost per employee.

None of these groups discuss business or customer outcomes. And no one is accountable for connecting these metrics to a coherent view of CX.

Why This Disconnect Hurts CX

Why is this a problem? The biggest issue is that while customers experience services end-to-end, organizations providing services do not. Customers don’t experience departments; customers experience journeys. For example, ordering a product involves several departments within the organization, including Marketing, Sales, Finance, Inventory, Shipping, Customer Support, and IT. To the customer, it’s one experience. Inside the organization, it is eight different organizations, eight leaders, eight budgets, and (likely) eight different sets of priorities. Compounding the situation, service management often stops at the boundaries of the IT department instead of orchestrating the end-to-end service and experience.

Secondly, the relationship between service management and CX is indirect. Unlike a marketing campaign, which is expected to directly drive business outcomes like increased sales, the connection between service management and business results is less obvious. For example, a well-defined and executed problem management practice should result in fewer incidents. Fewer incidents mean more reliable services. More reliable services result in lower customer effort, higher satisfaction, and greater customer retention – factors that are considered as part of CX.

While each link is logical, the effects accumulate over time and across organizational boundaries, so business leaders rarely trace the outcome back to improvements in service management.

The Shift: Service Management As A Strategic CX Enabler

The core issue isn’t that service management exists – it’s how it is defined. Many organizations still treat service management as an IT capability when it is really an organizational capability for consistently delivering value. When service management is reduced to “running the service desk,” its connection to CX looks narrow and tactical. When service management is understood as “the discipline that coordinates people, processes, technology, suppliers, and information to reliably deliver outcomes customers value,” CX becomes one of its most important measures of success.

That suggests the challenge isn’t simply to improve service management—it is to reframe it.

Organizations need to stop viewing it as a collection of IT operational processes and start viewing it as the operating model that enables consistent customer value across the whole enterprise. CX then becomes not a separate initiative, but evidence that the service management system is functioning effectively.

This shift also has implications for how service management professionals communicate. Rather than leading with process maturity or operational metrics, they should begin with customer outcomes and business value, showing how practices like incident management, problem management, knowledge management, and continual improvement reduce customer effort, increase reliability, and strengthen trust. When framed this way, service management becomes a strategic enabler of CX rather than a back-office function that supports it.

Make The Link Real: Your Next Steps

Bridging the gap between CX and service management doesn’t start with new tools; it starts with how you design, measure, and talk about services. The following actions give service management leaders practical ways to connect their work directly to customer journeys, outcomes, and executive priorities, so service management is seen as a driver of CX – not just operational overhead.

Use journey mapping to drive defining the operating model – Journey mapping provides the “outside in” perspective that many service management implementations lack. By using journey mapping, the IT organization can understand the customer experience. Colleagues working in other areas can understand the critical role of technology in delivering that customer experience and why an operating model must be viewed from an end-to-end perspective.
Measure and report customer outcomes and business value – Many IT organizations only measure and report operational metrics, which have no meaning or relevance to anyone working outside of the IT organization. For example, report on customer effort scores, renewal rates, or time-to-value alongside traditional service performance measures.
Drop the “geek speak” with non-IT colleagues – Translate incidents, requests, CMDBs, and changes into the language of customer retention, revenue, and risk so that executives can see the strategic impact of service management.
Define IT services – Defining the services provided by IT in terms of business value and business results is a critical first step in shifting the perception of service management from processes and tickets to business needs and strategy.

If CX Matters, Service Management Must Be Strategic

When organizations recognize service management as a strategic operating model for delivering customer value – not just an IT function – the gap between CX rhetoric and CX reality begins to close. The work is not about more tickets or more tools; it is about aligning journeys, outcomes, and governance so that customers experience services the way leaders say they should.

Leadership, Service Management

Why Enterprise Service Management is the Operating Model Your Organization Needs

June 8, 2026 Doug Tedder

New technologies promise greater speed, increased accuracy, improved productivity, and more efficiency. Many organizations invest in these new technologies to address those challenges and unlock new capabilities.

But in many cases, after significant investments in time, resources, and people, these new technologies don’t deliver those promised results. What happened?

Did internal silos and outdated processes get in the way? Are workflows clumsy, with poor handoffs between departments? Are those workflows even defined? Were the results promised by the new technology internally translated into quantifiable goals, frictionless interactions, and clear accountabilities?

While a technology first approach is often followed for solving business problems, such an approach rarely achieves the intended results. Why? Because the problem is not a technology problem. The problem is often in the organization’s operating model. What if enterprise service management (ESM) is the new operating model?

The challenges of operating models

McKinsey defines an operating model as “a strategic blueprint that defines how a company organizes its people, processes, technology, and governance to deliver value to customers and achieve long-term goals. It acts as the functional bridge, translating a high-level business model (the “what”) into daily actions (the “how”), ensuring efficiency, scalability, and alignment across the organization.”

The fact is that every organization has an operating model. Work is being done somehow, whether it is by design. And design and adoption of the operating model is the problem that ESM adoption could resolve.

But organizations resist changing, much less defining, their operating models – even though organizational leaders agree that they should. Many executives say that their operating model must be rethought, yet over 30% of those executives point at internal resistance as a barrier to redesign.

So, if defining and implementing operating models result in better ways of working within organizations, why do executives get resistance?

Fear of the unknown – People fear the unknown and worry about how new roles, workflows, or decision rights will affect them.
Internal politics – Concerns over losing control, influence, or decision right results in pushback against defining operating models.
Siloed operations have become deeply embedded – In the absence of an operating model, internal teams and departments have locally optimized the work that they are doing without considering the impact on the overall organization.

Introducing technology in the absence of a defined and agreed operating model only exacerbates these issues.

Why ESM is your operating model is ESM

Good ESM helps organizations understand their existing (even if undocumented) operating model. But ESM is not just ITSM extended across the organization. ESM is an organizational capability for holistically delivering business value and outcomes, based upon shared processes, appropriate technology, increased collaboration, and better communication across the organization.

To me, the purpose of an operating model and the purpose of ESM sound the same. Should ESM be your operating model? Should your operating model be ESM?

When organizations commit to defining, implementing, and following an operating model, the result is clarity regarding roles, responsibilities, and decision rights. Functions align better with business strategy and customer outcomes.

ESM succeeds by empowering people, clarifying responsibilities, and supporting cross functional collaboration to deliver business outcomes.

When organizations commit to good ESM, the result is standardized processes and enhanced visibility regarding how value flows through the organization. This makes it easier to identify problem areas, simplify workflows, and clarify expectations and roles.

When organizations commit to defining and implementing an operating model, that operating model becomes the blueprint for service delivery. Processes facilitate the actions that bring the blueprint to life.

The introduction of new technology changes the enterprise operating model by reshaping how the whole business creates, delivers, and captures value across structure, processes, people, and governance—not just how IT runs.

Good ESM illustrates how technology enables or supports processes and people in delivering business outcomes and value.

Governance is a core enabler of good ESM, by providing the structures needed to effectively govern emergent technologies and distributed processes at an operational level.

An operating model defines how governance happens on a day-to-day basis.

5 Steps toward adopting ESM – and defining your operating model

How can business executives accomplish both defining the operating model and adopting ESM? Here are five steps to getting started:

Stop thinking of ESM as “ITSM everywhere”. It’s not. ESM applies service management concepts across the organization to enable a clear understanding of how work and value flows from start to finish – across departments. Many ITSM adoptions are (incorrectly) focused internally on IT.
Clarify the technology strategy. When business strategy and technology strategy are developed independently, the result is poor technology decisions and missed business opportunities. For success in the digital economy, the business and technology strategy must be integrated.
Understand the current state. Identifying and mapping the current ways that value flows through the organization not only brings transparency and clarity into how work is being done, it also identifies improvement opportunities. It will also highlight the need for operating models and ESM.
Think, talk, and act in terms of “PPTG”. The key to success with both ESM and operating models is thinking through PPTG – People, Process, Technology, and Governance. What skills and competencies are needed for organizational success? How should work flow across the organization? What systems and technology are needed? How will decisions be made? Thinking, talking, and acting in terms of PPTG establishes the foundation for success for operating models and ESM.
Start with what’s most important – Identify and begin with the critical few end-to-end processes within the organization. This will get the right parts of the organization involved. It also enables a bigger impact on the organization, validates the value of operating models and the use of ESM, builds momentum for continued improvements, and shifts the mindset of business executives from just buying-in (“nice idea”) to commitment (action).

When organizations embrace ESM as their operating model, technology starts working for them – not the other way round – unlocking clarity, alignment, and measurable value.

AI and Modernization, Governance, Service Management

AI isn’t Failing – Your ITSM Foundation is Shaky

April 2, 2026 Doug Tedder

Many organizations are frustrated that investments in AI have not delivered anticipated results, especially regarding IT Service Management (ITSM).

Introducing AI into an ITSM environment offers huge potential—but most organizations encounter similar obstacles. Here are some of the common challenges that organizations encounter:

Data and process maturity problems – AI amplifies immaturity—it doesn’t fix it.
Organizational and cultural resistance -Fear and misunderstanding slow adoption.
Lack of structured governance and continuous improvement – AI needs ongoing oversight and continual tuning; it is not a one-time deployment.
Unrealistic Expectations – Senior management often expects AI to immediately reduce headcount, solve all categorization and routing issues, replace Tier 1 support and deliver human-level accuracy…. All on day one. AI is a tool; it is not magic.

But despite these well-publicized challenges, many organizations jump in headfirst and invest in AI tools that promise dramatic improvement of their ITSM capabilities. But the excitement of implementing that AI-enabled chatbot or copilot quickly fades when the organization starts to realize that their ITSM environment just isn’t ready.

Just like you can’t build a house on a shaky foundation, implementing an effective and impactful approach to AI adoption within ITSM must start with a strong foundation. Good ITSM is part of that strong foundation.

What is “Good AI”?

Let’s first discuss “Good AI”. Good AI is:

Aligned with human goals and values – Good AI supports human intentions, helping people make better decisions, work more efficiently, or access information. Good AI does not mislead, manipulate, or undermine autonomy.
Safe, predictable, and reliable – Good AI behaves consistently and avoids unexpected or harmful outcomes. It should be transparent regarding its limitations.
Fair and unbiased – Minimizes bias and treats groups and individuals equitably.
Respects privacy – protects user data, uses the minimum data necessary and allows users control over how data is collected and used.
Transparent and explainable – People should be able to understand how AI reached a conclusion, what data it used to reach that conclusion, and how confident it is in its result.
Human-centered – Designed for real human needs, intuitive/easy to interact with, and supportive (not replacing humans where judgement and empathy are vital.

But “Good AI” cannot fix “Bad ITSM”.

What is “Good ITSM”?

As I’ve said before, “good ITSM” is a business enabler, not just an IT function. Good ITSM:

Standardizes how work gets done across the organization, improving both productivity and throughput.
Provides clarity and transparency into how value flows through the organization, enabling better visibility of end‑to‑end value streams.
Identifies and defines services and processes that underpin organizational value streams, helping connect IT work directly to business outcomes.
Brings repeatability, reliability, and measurability to all aspects of the organization—not just IT operations.
Follows a human-centric approach emphasizing outcomes, experience, and putting people at the center of service delivery.

Good ITSM is foundational for realizing the benefits of good AI. Unfortunately, many organizations wanting to implement AI follow the same mistaken approach to technology adoption…by starting with the technology, and “working backwards” to process and people. These organizations are trying to build their AI houses on shaky ground – a recipe for unnecessary cost, frustration, and missed expectations and opportunities.

“But we already bought the AI tool”

Perhaps your organization is on this same path to AI adoption – starting with the technology. And likely, your organization is encountering the same challenges that many other organizations face when introducing AI to their ITSM environments. It may seem like you’re facing a “mission impossible”. What steps can be taken to turn this difficult circumstance into a positive outcome?

How about using AI adoption as a catalyst for shoring up the shaky ground of bad ITSM? Here’s a suggested approach:

Establish a goal – Define and agree on two to three business-oriented goals for AI adoption within ITSM. AI within ITSM should not be approached as a point solution; rather, AI should be considered within the broader perspective of ITSM. Defining overarching goals for AI in ITSM – in business terms – ensures that broader perspective.
Define how those goals will be measured – Measures should be more than just from an IT operations perspective. Measures should also reflect things like reduction of friction, accuracy of the AI-provided solution, user satisfaction, and usability.
Pick a value stream – Start with one high-impact, highly visible value stream that would benefit both the IT consumer and the IT organization, like “onboard a new employee”, or “provide access”. Identify and review the procedures that support the steps identified in the value stream. Are those procedures documented and in use? Are there steps that are missing procedures?
Involve the right people – As with most value streams, success depends on the engagement and contributions of people both within and outside of the IT team.
Conduct experiments – It is impractical to think that you’ll be able to accomplish the goals and objectives of AI adoption within ITSM in a single go. Use small Plan-Do-Check-Act (PDCA) loops to experiment and learn, not only about the AI tool’s capabilities, but also how best to leverage those capabilities within your ITSM environment. PDCA loops will also help identify where ITSM practices just aren’t ready: poor data capture or quality, dead-end workflows, inconsistencies in categorization and escalation, and other “bad ITSM” behaviors.
Share the learning – Sharing the learning improves collaboration, strengthens understanding of both ITSM and AI, and helps build momentum for further adoption and use.

Ready to turn AI frustration into AI advantage?

AI won’t rescue bad ITSM—it will expose it. The organizations that succeed with AI aren’t the ones chasing shiny technology; they’re the ones with strong processes, clear value streams, and a culture ready for change. When ITSM is solid, AI becomes a multiplier. When it’s not, AI becomes a mirror.

Use this moment. Let AI adoption be the spark that fixes shaky workflows, strengthens data quality, and aligns teams around meaningful outcomes. Start small, learn fast, and build momentum.

Ready to turn AI frustration into AI advantage? Start by strengthening your ITSM foundation—because that’s where real transformation begins.

AI and Modernization, Human Centered Design, Leadership

Technology is Easy. Experience is Hard. Here’s How to Get it Right.

March 3, 2026 Doug Tedder

There is a tendency within many organizations to take a “technology first” approach to solve every business challenge. In more cases than not, this approach simply creates more challenges and friction within organizations; it is a very short-sighted view.

Organizations do need technology – without it, organizations cannot compete in the digital economy.

But there is a lot of FOMO in today’s business technology environment, valuing speed over strategy.

The often-ignored aspects of rapid technology implementation

When an organization prioritizes speed of implementing technology, it usually results in some significant issues being ignored. Issues such as:

Changes to the organizational operating model. Technology changes the enterprise operating model by reshaping how the whole business creates, delivers, and captures value across structure, processes, people, and governance—not just how IT runs.
Impact of change on people. Organizations often underestimate, if not ignore, the impact of technology implementation on the people the technology was intended to help.
The weight of technical debt. Unless governance keeps pace with technology introduction, rapid introductions of technology can introduce new technical debt in system architectures, data, and model lifecycle. At the same time, many organizations ignore the impact of existing technical debt from legacy systems, customizations, and integrations.

Experience enablement ensures successful technology implementations

Think about it – in the digital economy, all companies have some level of technology enablement. But this ever-increasing rush to implement technology out of the fear of being left behind will have negative consequences – unless the fundamental challenges noted above are addressed.

But I believe that success with technology implementation depends on a single critical factor – the people that use that technology. This highlights the need for a good human experience, both between organizations and their external stakeholders as well as the stakeholders within those organizations.

I am convinced that the experience – the total end‑to‑end journey and feelings of a person interacting with a company or product – is the differentiating factor for organizations in the digital economy. But if technology implementations do not enable that differentiating experience, those organizations will not realize their full potential in the digital economy.

Can an organization achieve its strategy, the demand for speed and agility in the marketspace, and address the need for a good experience for those that interact with technology? The answer is yes – but organizations first must slow down to go fast.

Four Steps to Slow Down and Accelerate Success

How can an organization meet the demands for speed and agility in the market space, yet ensure that technology implementations enable the right experience? It can be done – if organizations first slow down to go fast. Here are the four steps organizations must take to slow down to accelerate success.

Digital business strategy – A well-defined digital business strategy is a critical first step for organizations wanting to leverage technology to deliver business outcomes and value. A digital business strategy ensures that the appropriate technologies are identified for achieving those business results.
Mapping value streams – A value stream map shows how value flows through an organization – and the systems and technology that enables the flow of value. When organizations understand their value streams, they can identify and address any areas of friction resulting from the use of technology.
Define proto personas – Proto personas help organizations understand the goals, needs, and behaviors of the consumers that will be using their products and services.
Journey mapping – Whether it’s a customer or an employee, it’s critical to understand the experience of people’s interactions with an organization. Use those proto personas to produce journey maps. Journey maps depict the touchpoints and experiences – and the impact of technology (good or bad) – humans have while interacting with an organization.

Technology without delivering the right experience is a recipe for failure

As I’ve written before, if technology implementations do not enable that differentiating experience, those organizations will be left behind in the digital economy. But admittedly, organizations taking a “tools first” approach to business challenges is nothing new.

But, delivering that right experience should not be left to chance. A “tools first” approach may address one area of concern but typically will miss other areas of concerns. Different consumers have different expectations of the experience they have with organizations. Implementation of technology without a well thought and integrated business strategy results in wasted time, money, and resources. Such an approach usually results in needless complexity. The different value streams within an organization have different requirements for velocity. Technology solutions must accommodate those requirements.

These are leadership issues, not technology issues. And it takes courage to stand in the face of well-intentioned but misguided demands for rapid technology implementations.

The best way to ensure success in the digital future is to plan for that future. Defining the digital business strategy, mapping value streams, understanding who will be interacting with your organization using proto personas, and journey mapping provides a clear path to success in the digital age.

AI and Modernization, Leadership, Service Management

From IT Support to Enterprise Nerve Center: ESM Is the CIO’s AI-Era Edge

February 2, 2026 Doug Tedder

In this recent CIO.com article, Mike Blandina, the CIO at Snowflake, made some predictions regarding the CIO role. As one would expect, AI adoption is a significant part of Blandina’s predictions, but there are a few details within his predictions that I found interesting:

The need for governance frameworks – As organizations adopt AI-enabled capabilities, they must also adopt responsible AI practices. CIOs will be held accountable to implement governance frameworks that span the entire AI lifecycle, with clear ownership, regular audits, and documented risk assessments.
Enterprise-wide innovation – The CIO role will shift from ‘IT’ to ‘ET’ – enterprise technology The traditional IT metrics will still matter, but CIOs will increasingly focus on business outcomes. The IT function becomes less about infrastructure and more about delivering intelligence.
Technology must move from only support to business-critical – Blandina concludes his article by stating that “successful CIOs will be those who elevate technology from a support function to the central nervous system of the business.”

Admittedly, these are all topics that have been long discussed. What is different now?

At the risk of stating the obvious, the difference now is the business demand to adopt AI-enabled capabilities. This demand represents a significant opportunity for CIOs to transform the role and reputation of IT. Now is the time to act.

Are you ready for the new (renewed?) expectations of the CIO role? Can your IT organization elevate its thinking from just developing and implementing technology solutions to delivering business outcomes?

If not, enterprise service management (ESM) may be the solution.

Why ESM is the solution

ESM is a way to meet the new expectations that organizations will have of CIOs. While ESM leverages the principles of IT Service Management (ITSM), true ESM is not just extending IT workflows into other departments within an organization. ESM is an organizational capability for holistically delivering business value and outcomes, based upon shared processes, appropriate technology, increased organizational collaboration, and better communication across the organization.

As I’ve said before, when done well, ESM drives greater operational efficiency, fosters cross-department collaboration, reduces costs, enhances customer satisfaction, and increases an organization’s ability to adapt quickly to changing business needs. It also strengthens governance and compliance, while the improved service delivery resulting from effective ESM enables a truly differentiated customer experience.

Don’t fall for “imposter ESM”

Unfortunately, many organizations have adopted what I would call “imposter ESM”. For example, many organizations have fallen into the trap of trying to extend IT-oriented workflows into other parts of the organization. Other organizations have used the guise of an ESM initiative to spread the costs of an expensive ITSM tool across the organization. Still others take a technology-first approach and install department-specific modules intended to manage workflows within those departments.

None of these approaches deliver the benefits of real ESM adoption. The CIO can avoid imposter ESM by following these tips:

ESM is best considered as a business strategy designed to deliver value and improve both the employee and customer experience across the enterprise.
ESM requires that organizations break down silos and focus on end-to-end value streams, which involves collaboration across departments.
ESM establishes the foundation for compliance to governance policies to ensure consistent and measurable business outcomes and value.

Good ESM positions organizations to take advantage of AI-enabled capabilities. But it’s more than that – good ESM positions the CIO to establish IT as a business-critical capability, driving appropriately-governed technology to deliver business outcomes.

Elevate Enterprise Value through Strategic ESM Foundations

These critical success factors for ESM also provide a great foundation for effective ESM.

Understanding how value is perceived within the organization – Talk to other business leaders to understand how they perceive value – and how to measure and report on that value.
Understanding and mapping organizational value streams – Value stream mapping provides visualization of how value flows through the organization. A value stream map also depicts where collaboration is required for the customer to realize value.
Understanding the journeys of customers and employees – Journey mapping provides insights into the experience of individuals as they interact with the organization. Journey mapping provides the foundation for delivering differentiated human experiences, both within and external to the organization.
Committing to continual improvement – Formally build continual improvement capabilities to ensure that the organization can react to changes in the business environment in a timely fashion to ensure on-going value to its stakeholders.

AI adoption can be transformational with an organization. But, as with any transformational and impactful solution, there is no “magic wand.” Technology – like AI – only amplifies the current state of workflows and behaviors – right or wrong. Outcomes come from the interactions of people, systems, and tools – not just tools alone. Good business results come from an effective strategy for achieving objectives – not from chasing technology without clear business goals and defined success measures.

Good ESM is no different. But the benefits of good ESM are more than establishing a holistic and collaborative approach for delivering business value and results. Good ESM provides the foundation for governance, fuels innovation by understanding how work gets done, and shifts the role of IT from technology support to business enabler.

Governance, Leadership, Service Management

CEOs want tech results, not tech talk – Here’s how to deliver

January 12, 2026 Doug Tedder

While many CEOs know that the use of technology is crucial for business success, what they don’t know or understand how technology use contributes to that success.

According to this CIO.com article, CIOs reported that less than 2% of their CEO bosses understood the totality of the technology stack.

And in today’s $24 trillion global digital economy, that is a problem.

The right technology solutions can enable competitive differentiation for any organization. But organizations need to have the right skills and mindset in place to enable, support, and deliver that differentiation.

Investments in technology is expensive – a wrong decision can cost an organization significantly. Those poor decisions can often be traced to the lack of an integrated business and technology strategy. In some cases, the IT strategy is developed separately from business strategy . IT doesn’t help itself either – how can CEOs decide where to make investments in technology when IT proposals discuss technology benefits, such as uptime or features, rather than business results like growth, margin, or customer experience?

According to this McKinsey article , many CEOs struggle to understand exactly how IT initiatives and investments drive revenue, customer experience, and efficiency. As a result, IT looks like a cost center. But more than that, projects and investments in technology often become fragmented and underused, resulting in missed opportunities for new products, services, or operating models. One need look no further than the well-documented technology “misses” of companies like Kodak, Blockbuster, and Nokia.

Good service management is the solution

Good service management can solve the technology understanding gap between CEOs and CIOs. But many CIOs often think “we’ve tried that and it didn’t solve this problem.”

But did those organizations really implement good service management? Good service management is not just standing up a service desk and installing a ticketing and workflow tools. Good service management is not just utilizing service management practices to manage IT. Good service management facilitates value realization and business results.

Think about it. Without alignment and integration with the rest of the organization, the IT organization cannot deliver the value and results expected from investments in technology. And this is exactly what good service management does. Good service management is much more than just implementing some tool and standing up a service desk. Good service management requires a holistic view of how technology enables value realization and business results.

Good service management starts with (I’ve said it before) alignment of IT with business goals. Adopting practices like portfolio management, business analysis, relationship management, and strategy management prevents implementation of “technology for technology’s sake” (like rushing to adopt AI-enabled capabilities for example), helps prioritize technology investments and IT efforts based on business impact. Doing this will give CEOs insights into how technology enables return on investment and delivers business results.

But adoption of these practices only establishes the needed scaffolding for enabling and delivering the business value and results expected by the CEO from investments in technology.

McKinsey suggests two actions that every CIO must take with CEOs to close the understanding gap. Coincidentally, these two actions are foundational for good service management.

Meet with the CEO to clarify business outcomes, not technology. Identify and agree on 3-5 business outcomes where technology much help (such as growth, risk, customer experience) and capture these outcomes as plain, non-technical language statements.
Map IT to these outcomes by creating simple, one-page views that link business goal to technology capabilities to 2-3 simple measures that the CEO can track.

These two actions will have the following impact on service management and IT:

Identifies the right success measures for IT. Many IT organizations measure success in terms of technology (uptime, time to resolve, volume of tickets); measures that are meaningless outside of the IT organization. IT success should be measured and reported to the CEO in terms of business results – reduced waste, customer experience, and business growth.
Shifts the perception of IT as being a “cost center” to a “value enabler” by providing the CEO with regular visibility into how IT is enabling business outcomes.

Three things you can do now to help the CEO

Build better business relationships. Often the only interactions between IT and other business colleagues is limited to project meetings or interactions with a service desk professional. If you are an IT professional, when is the last time you met a colleague outside of IT for coffee to talk about how technology helps – or gets in the way of – doing work and delivering business results? These meetings will provide huge insights into how technology is perceived within the organization.
Define services in terms of business processes and outcomes. Stop putting off or ignoring this task. Services facilitate the realization of business results. The more the IT organization defines services in terms of business processes and outcomes, the less the IT organization will be perceived as a “cost center” and barrier to getting work done.
Start reporting the right things in the right way. Stop reporting metrics outside of IT that have no meaning to anyone outside of IT. Start reporting metrics like reliability and cost avoidance that are related to business objectives.

Technology doesn’t drive success – understanding how it enables success does. CEOs and CIOs who close that gap through strong service management transform IT from a misunderstood cost center into a true value enabler.

AI and Modernization, Leadership

Suffering from AI fever? Here’s why the big picture still matters

August 3, 2025 Doug Tedder

Is your organization exhibiting “AI fever”? “Symptoms” include people asking questions like:

“How can our organization take advantage of AI-enabled capabilities?”
“Where can we leverage AI to automate our workflows?”
“How can we use AI to improve efficiency and reduce costs?”
“What happens if our competitors beat us to the market with an AI-based solution?”

These are legitimate questions. Effective adoption of AI-capabilities is changing the way that companies work, by driving workflow efficiencies and automation, providing data analysis and insights that weren’t before possible, improving work quality, personalizing experiences, and more.[i] The market is crowded with solutions, all of which make it seem so simple to fully take advantage of AI capabilities. It’s easy for organizations to get lured in.

But the potential results from AI adoption don’t excuse organizations from doing the needed critical thinking before making solution decisions. Before jumping on the AI bandwagon, organizations must answer questions like:

What problem will AI solve for the organization?
Do customers want an AI-based solution, and if so, how should it help them?
Is the necessary foundation in place within the organization to benefit from AI adoption?
How will AI fit into the “big picture” of the organization?

The big picture must come first

Understanding the big picture must come first before considering any AI solution. Why is having a holistic (or big picture) approach so important, especially with AI adoption?

First, AI adoption can have a significant impact on the entire organization. Many organizations only think of AI as something that will only impact IT or technology, but the impact can be much more than that. AI impacts multiple areas of an organization, and having a holistic approach and strategy ensures that AI initiatives are aligned across all parts of the organization.[ii]

Without taking a holistic approach to AI adoption, organizations risk implementing a point solution within a workstream that is neither sustainable nor enhances organizational efficiency. While there may be local benefits, the actual outcome is that the overall workstream becomes less efficient. Implementing a solution in this way would be like speeding up only the middle of a conveyor belt. While widgets may move along faster on the conveyor belt, the constraints at the beginning and end of the conveyor belt become highlighted and problematic.

Data and ethics are two of the more significant considerations for the effective use of AI. AI needs data – lots of it – and that data must be of high quality and integrity if results are to be trusted and reliable. The use of data also presents ethical considerations, with issues like data privacy, bias, and appropriate use. These factors mean that data quality and data governance are also part of the AI big picture.[iii]

To fully use the capabilities engineered into AI solutions, these solutions typically require training to function effectively. People within an organization must develop skills and competencies to use the solutions. But here’s perhaps an unexpected twist – not only do the people using the solutions require training, but the solution itself requires training as well. These solutions must be trained using the datasets provided by the organization and tailored for organizational-specific tasks and use cases. Having people with the skills and knowledge for data preparation, tuning algorithms, data visualization, and problem-solving are needed for training the AI.

AI adoption challenges

While AI can bring a lot of capabilities to enhance an organization’s performance, it is far from a “magic wand.” Here are a few challenges organizations are facing with AI adoption.

People. Will people feel threatened by AI adoption? Or will they feel enabled? The best AI capabilities are worthless unless they enhance the ability of people to do their work. Effective and comprehensive organizational change management as part of AI adoption is critical.[iv]
Good AI will not fix broken processes. Having well-defined processes is the foundational structure for AI adoption. It’s straightforward: bad processes result in poor AI adoption and poor outcomes. Without clearly defined workflows, how can an organization identify valuable use cases or strategically expand AI-enabled capabilities, such as automation, or agentic AI.
Missing the skills needed for success. This article from ARM highlights the impact of the lack of in-house AI talent is having on AI adoption. Nearly one-half of leaders feel that the lack of skilled talent is a primary barrier to successful AI implementation.

How to treat AI fever

Do you have that big picture view of your organization? Is your organization prepared to take advantage of the right AI capabilities that elevate organizational performance, efficiency, and capability? Now is the time to get ready. Here are four tips for ensuring a holistic approach to AI adoption.

Map your value streams. One of the most significant challenges to adopting and exploiting AI capabilities is that organizations don’t understand their value streams, much less have mapped those value streams. Value stream maps depict the big picture of how work and value flow through an organization. It also identifies where constraints may be within the organization. With this holistic understanding of its value streams, organizations can better figure out if AI solutions will enhance performance…or enhance constraints.
Focus on ongoing learning and development. “Training as an event” cannot keep pace with the rapid changes in AI capabilities. The rapid pace of AI enhancements demands a continual learning approach to training and development. Adaptive learning is an educational approach that tailors educational experiences to meet an individual’s unique needs, skills, and learning pace, facilitating a continual learning experience.[v]
Invest in your current staff. The best source of knowledge about how work is currently done is the people that are doing the work. This is the exact knowledge that is needed to train AI. Invest in reskilling or upskilling current employees in AI concepts and technologies, enabling them to take on new career opportunities that will emerge with AI adoption.
Answer the “why.” Building a business case not only answers how and why AI adoption will address a business challenge, but it also drives the needed commitment from senior management for making it happen.

AI capabilities are evolving at a dizzying pace. Having a holistic or big picture view of the organization is the best way of ensuring that your organization can take advantage of the right AI solutions at the right time to deliver the right results.

[i] “Artificial Intelligence is changing how companies work”, https://www.deloitte.com/ch/en/Industries/technology/perspectives/artificial-intelligence-Is-changing-how-companies-work.html , retrieved April 2024.

[ii] “Why adopting AI needs a holistic approach”, https://betanews.com/2025/02/03/why-adopting-ai-needs-a-holistic-approach-qa/ , retrieved April 2024.

[iii] Ibid.

[iv] “Adopting AI-driven Change Management: Key strategies for Organizational Growth”, https://voltagecontrol.com/articles/adopting-ai-driven-change-management-key-strategies-for-organizational-growth/ , retrieved April 2024.

[v] “Understanding Adaptive Learning: How AI is revolutionizing personalized education”, https://elearningindustry.com/understanding-adaptive-learning-how-ai-is-revolutionizing-personalized-education , retrieved April 2024.

AI and Modernization, Service Management

Will AI break ITSM out of its IT operations cage?

June 6, 2025 Doug Tedder

AI is about to break ITSM from its IT operations cage.

Many ITSM implementations are less about service management, and more about IT operations, or IT process management, or IT measures and reports. Here are some examples:

To many organizations, ITSM is about a weekly meeting to discuss changes to the computing infrastructure, attended by people that have little qualification or authority to discuss, much less approve such changes.
To many organizations, ITSM is about pulling together a group of individuals, sitting them down in front of computer screens and telephones, calling that group of people a “service desk”, then provide little training and less enablement for responding to all IT-related issues or questions.
To many organizations, ITSM is about establishing a portal through which consumers of technology can register requests for the IT organization to fulfill.
To many organizations, ITSM is about implementing a tool, several out-of-the-box workflows (that may or may not be suitable for the organization) and publishing a few reports that have no meaning to anyone outside of IT.

In other words, for these organizations, ITSM is not about the organization at all. ITSM is not about how people, process, and technology deliver business outcomes and enable business value realization. In these organizations, ITSM is about IT.

AI is about to change all of that.

AI will push ITSM front and center

Frankly, AI can nail (has nailed) down the operational aspects of ITSM. Current AI capabilities are well-suited to take on many of the operational aspects of ITSM, like routing work, resolving simple incidents, gathering, analyzing, and logging information, tracking assets, suggesting knowledge articles to resolve an end-user issue, and more.

And that’s the challenge that introducing AI will have for organizations that adopted ITSM only to manage IT operations. With the use of AI, IT will become increasingly visible to the rest of the organization. As a result, ITSM can no longer be a “back office” activity, but rather “front-and-center” as organizations navigate within a digital world. But are IT and organizations ready?

When IT cannot articulate how its products and services deliver business results and enable value realization (beyond cost savings/avoidance), the answer is “no”.

Why is this a problem?

The fact is that many ITSM implementations have ignored the very practices that would enable the “business value and outcomes” conversation with executives. Practices like portfolio management and service catalog, (real) problem management, and continual improvement, for example.

Because these practices have been ignored, IT organizations cannot discuss topics like service cost models. They can tell you what infrastructure costs, or how much is being paid out on support contracts and licensing costs…but not what makes up the specific costs of designing, delivering, maintaining, and supporting services. They can’t predict how investing in improvements will benefit the larger organization and ultimately the business customer. They can’t correlate business value streams to specific IT products and services that enable business results.

Some implementations have isolated service management activities that should be approached from a holistic perspective. In many organizations, service design activities are typically performed by application development teams that are focused on writing code, but with little or no involvement from those that will be supporting or using the solution post-implementation. Another example is organizations that perform software deployments to production environments outside of the purview of an ITSM change management practice.

It gets worse. According to this Forrester post, organizations that have invested in ITSM are finding that more and more of those investments are going toward paying additional costs from maintaining the tools rather than improving ITSM capabilities and driving business benefit.

AI will force Service Management to be an organizational capability

Service management has typically been considered an IT function, but in an ever-increasing digital world, that just won’t work. Service management must be an organizational capability.

For service management to be truly effective, it must reflect and support entire organizational value streams, not just the IT portions. Technology is no longer department specific. Technology connects entire value streams within all organizations. But it doesn’t stop there; in the digital ecosystem, it’s technology that connects organizations to partner organizations to deliver products and services. If enterprise-wide workflows that support value delivery all the way to the customer are missing or undefined, the result is a bunch of disjointed, siloed activities that result in a poor customer experience, missed business opportunities, and loss of competitive capability.

AI will manage the operational aspects of service management, and push ITSM out of the back office. Businesses must start now to elevate their organizational service management capabilities.

Breaking ITSM from its IT operations cage

What first steps should organizations take to begin to make service management an organizational capability? Here are some suggestions:

Invest in training – One of the challenges with current ITSM implementations is that the people involved in the delivery and support of products and service have not been properly trained in service management concepts. Rather, they blindly follow whatever the ITSM tool does, and do not understand the broader concepts and contexts of “service management.”
Map organizational (not just IT) workflows – Develop value stream maps or customer journey maps to illustrate how work moves through the organization or where customers interact with the organization. Include the touchpoints where people, processes, and technology enable the business results and value desired by the organization. These maps capture information that is foundational for developing a service catalog.
Identify business measures – Using these completed maps, identify the performance measures that reflect business outcomes and value.

The era of AI is not just an upgrade for ITSM – it’s a complete transformation for organizations. As AI takes over the operational heavy lifting, ITSM’s true purpose can no longer be confined to just IT. Instead, service management must evolve into a core organizational capability, seamlessly connecting people, process, and technology across entire value streams to deliver real business outcomes. This shift is not optional; it’s essential for organizations that want to thrive in a digital world where technology is the backbone of value delivery and customer experience.

Now is the time for organizations to break free from legacy mindsets, invest in holistic training, map out end-to-end workflows, and measure what truly matters to the business. By doing so, they can ensure that service management becomes a strategic enabler – one that drives innovation, agility, and competitive advantage in the age of AI.