Tag Archives: Good ITSM

AI, ESM, ITSM

Will AI break ITSM out of its IT operations cage?

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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.

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ITSM

Why your ITSM house of cards is a bad deal for your business

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Is your ITSM implementation like a house of cards, prone to fail with the slightest disturbance?  Here’s some examples:

  • A request for change that isn’t appropriately vetted yet is implemented within the live environment. Subsequently, that implemented change results in an extended outage of a critical business system.
  • Service interruptions are characterized by frantic efforts to restore service, cause analysis exercises that produce more theater than substance, and lost opportunities for improvement.
  • A seemingly simple service request that requires extraordinary effort and time to fulfill.
  • An IT organization that is surprised when the failure of a third party’s product or service cripples the business.

ITSM, done well, delivers effective and efficient services and practices based on the use of technology.  Done well, ITSM connects IT efforts and technology investments to business results and strategy.

Instead, what many ITSM implementations produce (or reinforce) is siloed behavior, disjointed delivery efforts, lack of transparency, and poor end-user satisfaction. Further exasperating the situation is that in many cases, IT doesn’t even understand how what it does enables business results and value realization.

Why does bad ITSM happen within good IT organizations?

Every IT organization has talented people who are knowledgeable, smart, and have outstanding technical skills. These people are motivated to be the absolute best that they can be and are driven to  succeed. Good ITSM should augment the efforts of these talented people and enhance the overall performance of the IT organization. ITSM should help the IT organization become a valued, respected, and competitive differentiator for a business.

Sadly, this is not the case with many IT organizations. Many implementations have fallen short of achieving the benefits of good ITSM and wasted the talents and efforts of people within IT because the foundational elements needed for success are missing. What are some attributes of a “house of cards”  ITSM implementation?

  • Taking only a “technology-first” approach – While having the appropriate tools are important, good ITSM doesn’t result only from the implementation of technology. With a technology-first approach, ITSM thinking becomes limited to the capabilities of the technology, and not how ITSM should meet the needs of the business.
  • No alignment to organizational strategy – ITSM implementation is about IT, not about how IT efforts and provided technologies enable the achievement of business goals and objectives. Other than justifying the organization’s investment in the selected technology, there is no business case that was developed to help executives recognize the value of the investments in ITSM.
  • No shared and agreed understanding of ITSM benefits – Some organizations believe that ITSM is just something “that the service desk does” for processing a user request or managing an incident. Making a bad situation worse is that many within IT think that ITSM has nothing to do with the work that they are doing.

How did this happen?

There are several reasons why ITSM is no more than a house of cards for many organizations.

Many ITSM implementations suffer from short-term thinking, prioritizing technology implementation over business value and employee experience, or even worse, prioritizing internal IT concerns over business results.

A house of cards ITSM implementation is often the result of inconsistent processes and a lack of governance, exasperated by poorly designed, implemented, and unenforced policies.  As a result, different parts of the IT organization manage its work differently, making transparency into IT difficult.

In most fragile implementations, ITSM was treated as an IT initiative, not a business initiative.  Had business stakeholders been involved from the beginning, ITSM would be business-oriented, with reports and measures that matter. Instead, ITSM became a layer of bureaucracy for interacting with IT.

Regardless of how it happened, there’s been no reason for senior business management to care about ITSM – until now.

Why business executives need to care

Historically, many senior business executives have paid little attention to service management – and understandably so. Reports contained data that had no meaning to executives. Performance metrics produced by IT said one thing, but end-users told a vastly different story regarding their experiences with technology and processes. ITSM was viewed simply as something being done at the service desk. With so many foundational elements missing, many ITSM implementations gave executives little reason to care.

But times are changing – and changing fast.

Businesses are rapidly and increasingly relying on technology to drive the business –  and the customer experience – to new horizons.  With ever increasing frequency, customers are interacting with technology, such as intelligent automation, chatbots, natural language processing, and generative AI, and not with humans.

But without good ITSM, how can an organization ensure that technology is delivering the desired value and outcomes needed by both the business and its customers? There are many known cases (including the UK’s NHS IT program[i], Canada’s Phoenix Pay System[ii], and Knight Capital Group software deployment[iii]) where businesses that ignored good service management practices and have experienced significant and embarrassing failures.

The fact is that today’s digitally driven businesses require good ITSM for business success. The question that was usually never answered remains – how will your ITSM implementation support your business’ strategy?

Today is a good day to prepare for the ITSM of tomorrow

Good ITSM is more relevant today than ever for modern, digital businesses. Here are three steps for moving ITSM from a house of cards to a reliable and solid business capability.

  • Develop a business capability map. A business capabilities map is a visual tool used to depict what a business does, not how it does it. A business capability describes the capacity, materials, and expertise an organization has or needs to complete its work.[iv] One of the things that makes a business capability so interesting from an ITSM perspective is that capabilities have outcomes.
  • Conduct an ITSM capability assessment. Not to be confused with a maturity assessment, a capability assessment evaluates the organization’s service management abilities, capacity, and skills. Do not limit this assessment to IT operations – look at ITSM capabilities holistically, from strategy through design, development, transition, and continual improvement.
  • Do a gap analysis between the business capability map and the ITSM capability assessment. What areas of business capability are well-supported by good ITSM practices? Where are the gaps between business capabilities and ITSM capabilities? What are the impacts of those gaps? What needs to be done differently from an ITSM perspective to meet the demands and requirements of those business capabilities?

Stop relying on an ITSM approach that is built as a house of cards. Completing the above steps will start your ITSM implementation on an incredible transformation to strategic capability, both for the organization and for IT.

[i] Asgarkhani, M. (2022). Failed tech deployment initiatives: Is poor IT governance to blame? European Conference on Management Leadership and Governance, 18(1), 524–528. https://doi.org/10.34190/ecmlg.18.1.728

[ii] Ibid.

[iii] https://dougseven.com/2014/04/17/knightmare-a-devops-cautionary-tale/

[iv] https://www.lucidchart.com/blog/a-quick-guide-to-business-capability-maps , Retrieved February 2024.

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ITSM

Are your improvement efforts starving for continuous feedback?

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In my blog, “Four ways that organizations have dehumanized IT – and how to fix it”, I suggested  that organizations should “ditch those satisfaction surveys”.  Instead of satisfaction surveys, I recommended that organizations should conduct face-to-face focus group meetings. Focus group meetings drive a human-to-human discussion which typically uncovers insights into improvement opportunities.

When I later posted the blog on LinkedIn, Sami Kallio, my friend and CEO of Happy Signals commented, “…don’t you feel that that you should do both [distribute and collect satisfaction surveys and conduct focus group meetings]?”

Well, yes. Sami is correct. Organizations should do both – distribute and collect satisfaction surveys and conduct focus group meetings.

But in my experience, many organizations just don’t do a good job with their customer satisfaction surveys. One of the challenges with these surveys is that the return rate is usually anemic at best.

But Sami’s comments made me think. Why aren’t customer satisfaction surveys effective? Is it more than just the poor quality of questions that are being asked?

Maybe it’s that organizations can’t handle the truth (sorry, couldn’t resist the movie reference), so they don’t seek it out.

Or maybe – and much more likely – organizations are not prepared for continuous feedback.

Three reasons why organizations fail with continuous feedback

Getting continuous feedback regarding an organization’s products, services, and processes is a good thing. Continuous feedback provides timely insights and uncovers opportunities for development and improvement. Continuous feedback also enhances employee engagement[i], improves communication[ii], and can lead to better decision making[iii].

So why do organizations fail with continuous feedback?

  • No formally defined approach to continual improvement. Without a formally defined approach to continual improvement, continuous feedback goes nowhere. In many organizations, continual improvement activities are ad-hoc. Even when these ad-hoc activities are performed, they are rarely tracked – and even more rarely reviewed for effectiveness.
  • No management support. Do you see the phrase “continual improvement” as an objective within a company’s mission/vision/goals (MVG) statement? If not, resources for continual improvement will be difficult to obtain. Organizations will invest in the objectives identified within MVG, which are typically focused on innovation and growth. Senior managers are incentivized to achieve the goals and objectives found within the MVG. Continual improvement, on the other hand, is usually not perceived as being innovative, and as a result, isn’t adequately funded. Paradoxically, some innovations within organizations result in an increase in technical debt, which only exacerbates the need for continual improvement.
  • Having a culture that does not value continuous feedback[iv]. In today’s rapid paced, “always on” business environment, it’s easy to overlook or put off opportunities to reinforce the value of continuous feedback. When was the last time that your department celebrated a big win? Are one-on-one meetings frequently delayed, or even worse, cancelled? Are people’s calendars double (and triple) booked? Do employees understand how their work contributes to business success? Without feedback, there can be no improvement. Leaders must instill a culture of continuous feedback – an environment that values and contributes to feedback at the personal, departmental, and organizational level.

The idea is good. The execution…not so much.

The concept of continual improvement driven by continuous feedback is a good idea. Continual improvement is simply good common sense. I believe that organizations that do not continually improve aren’t just sitting still – they are moving backwards. Why? Organizations exist in a constant state of change – business environments change, marketplaces change, regulations change, consumer needs change, technology changes, skill sets change. A formal approach to continual improvement isn’t a “nice to have”; it’s a fundamental competency for every organization to master to successfully navigate the constancy of change.

Continuous feedback provides a great way to monitor the resulting impact of these ever-evolving changes on the people and processes. Some of that impact may be readily visible to an  organization, through measures like increased contact volumes at the service desk or an increased number of incidents. But it’s more that IT measures. Quantifiable measures such as reduced profitability and revenues are also ways to gauge the business impact of the ever-evolving change.

But what about the impacts that may not be as visible? Issues like longer lead times, loss of reputation or credibility, having the wrong mix of products and service offerings, or people that haven’t received adequate training to do their jobs? Continuous feedback provides a means for capturing these issues as well.

Are you dropping the ball between feedback and improvement?

If continuous feedback is not delivering the benefits your organization needs, here are three suggestions to try.

  • Define goals for continuous feedback. When it comes to continuous feedback, are you just “checking off the box”? Or are your surveys asking meaningful questions regarding the impact of change or any friction being encountered in the respondents’ daily work? To get the answers that you need starts with defining goals for continuous feedback.
  • Ask the right questions. While rating a product, service, or support action on a numerical scale makes for some easy math, it really doesn’t render useful or insightful feedback. Think about it – when you see a restaurant review that contains written comments from the reviewer, you are better enabled to make an evaluation of that restaurant. The same idea goes for continual feedback. Asking specific open-ended questions encourages specific and more detailed feedback – feedback that can better evaluated to identify improvement opportunities.
  • Start keeping score. Review the feedback that is currently being collected to identify potential improvement opportunities. Then, for any identified improvement, define what success looks like before taking any further action. What will the impact of the improvement action be to the organization, to the consumer, and to the employee? What will be different? How should improvement be measured – in terms that makes sense to each stakeholder of the improvement.  Make the improvement even more meaningful by capturing financial, efficiency, and effectiveness measures. Providing meaningful measures and reporting for improvements help justify the next improvement – and reinforce the value of continuous feedback.

Done well, continuous feedback makes for better interactions, better processes, better products, better communications and collaboration, and better services. Defining clear objectives for  continuous feedback, asking the right questions, and tracking achievements will help overcome barriers to success with continuous feedback.

 

[i] https://www.talentquest.com/blog/how-continuous-feedback-improves-employee-engagement , Retrieved March 2025.

[ii] https://prezentium.com/effective-communication-in-the-workplace , Retrieved March 2025.

[iii] https://www.linkedin.com/advice/3/heres-how-you-can-harness-benefits-team-input-before-ty13f , Retrieved March 2025.

[iv] https://www.linkedin.com/pulse/6-reasons-why-your-continuous-feedback-program-failing-rnm1e , Retrieved March 2025.

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ITSM

Is your ITSM approach looking through the windshield…or at the rear-view mirror?

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“In the business world, the rear-view mirror is always clearer than the windshield.”

Sadly, this 1991 Warren Buffet quote applies to many ITSM implementations. Why?

Because the focus of those ITSM implementations is on what has happened, instead of what is happening.

Think about it. Our respective businesses are focused on the view through the metaphorical windshield. The view through the “windshield” represents both what is happening now and the journey ahead. And while the future is unknown, businesses try to create the future by establishing goals and objectives. From a business perspective, the possibilities and opportunities for success are typically found when the organization is looking through the windshield.

Continuing the metaphor, the focus of so many ITSM implementations is the rear-view mirror – a view of what has happened. Make no mistake – trending and performance reports, monitoring tools that deliver event alerts, and recently-written knowledge articles are important contributors to good ITSM. But those reports, tools, and articles are typically inwardly focused, discussing items and topics that are relevant and meaningful only to the IT organization. In other words, those ITSM implementations are more focused on yesterday and less on the future.

The impact of always looking in the rear-view mirror

Why is the “rear-view” perspective an obstacle for ITSM implementations? I would argue that the perspective of continually looking back is not aligned with business goals and objectives. This is one of the factors between ITSM being perceived as a business enabler versus ITSM viewed as a costly expense.

It comes down to this question – what does your business perceive as “value”? Candidly, business value is rarely – if ever – found by looking in the rear-view mirror. In my experience, businesses perceive value when actions taken within the organization result in achieving business  mission, vision, goals, and objectives (MVGO). Businesses perceive value when the data captured, used, and maintained within the organization produces information that enables timely, fact-based decision-making. Businesses perceive value as innovation, responsiveness to the market, increased revenues and profitability, delivering a differentiated experience, and standing out from competitors.

Shifting the ITSM view to the windshield

Does your ITSM implementation enable your business? How does your ITSM implementation help the organization to achieve its MVGO? For many organizations, ITSM is more about IT and less about their businesses. Few organizations (in my experience) develop and maintain a service portfolio, much less a service catalog. I rarely find ITSM implementations reporting measures that relate to the business objectives; rather, most measures and reports align to internally defined IT performance targets.

I’m not suggesting that IT departments stop supporting and delivering the operational aspects of ITSM. I am suggesting, however, that ITSM implementations expand their scope to include the “windshield”. The mindset must shift from seeing ITSM as a means of control or just implementing some tool. The mindset must shift to viewing ITSM as a business enabler.

This means that ITSM implementations must become more strategic from a business perspective. Strategy is about aligning resources and efforts to achieve organizational goals – in other words, looking through the windshield, not just the rear-view mirror.

Shifting the ITSM view to the windshield

Here are some tips for shifting ITSM from just a “rear-view” mirror perspective to also include the windshield.

  • Learn the business of your business. By understanding the business, IT professionals can make informed decisions, improve their communications with non-IT colleagues and become more proactive in developing technology-based proposals for growing and improving business activities.
  • Understand how people, processes, and technology (PPT) enable business outcomes. How does (or can) people, process, and technology enable the organization to achieve its MVGO? What are the vital business functions of the organization? How does PPT enable those business functions?
  • Think and act in terms of business outcomes. How can (or does) ITSM enable or deliver the business results that impact MVGO? Having answers to this question will help shift the perspective and perception of ITSM to a more strategic and business-aligned capability.
  • Measure and report things that are relevant and meaningful to your business. Frankly, no one outside of IT cares how quickly the service desk responds to requests or how many incidents are closed. Identify, measure, and report on metrics that have an impact on the business of the business.
  • Shift SLAs from an IT operational focus to a business focus. In my experience, what many ITSM implementations call a “Service Level Agreement” (SLA) are neither agreed with anyone outside of IT, or discuss the business impacts of IT services. Unfortunately, this is an approach that is deeply engrained within many ITSM implementations. Begin the shift by working with non-IT colleagues to map a frequently followed value stream. Doing this will result in a mutual understanding of the value stream, the business drivers, and success criteria. Use this information to then document and agree a business-focused SLA for that value stream.

In many organizations, ITSM has not achieved its potential. Part of the reason for that is that those ITSM implementations are too focused on the past and only on the IT organization. What could be possible if those ITSM implementations also look ahead rather than just looking behind?

Need some help shifting your ITSM perspective from just the rear-view mirror to what is happening now and ahead?  Let Tedder Consulting and our proven and impactful approach change your ITSM environment to a business enabler.  Contact us today!

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AI, ITSM

Five critical steps for making a good AI/ITSM decision

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There is no question that AI-enabled technologies have the potential for significant positive impact for organizations overall, and for ITSM specifically.  This recent TechTarget article highlights a number of positive business impacts resulting from the adoption of AI-enabled technologies, such as new capabilities and business model expansion, better quality, more innovation, and personalized customer services and experiences.

New and existing ITSM-related vendors are rushing into the space with solutions like AI-powered automation, conversational AI, intelligent chatbots, predictive analytics, and agentic AI (A web search on these terms will return numerous examples!).

And we’re only scratching the surface.  New AI-enabled capabilities are on the horizon, such as:

  • AI agents capable of executing discrete tasks independently based on personal preferences or providing customer service without requiring specific prompts.[i]
  • AI-powered cybersecurity in the form of automated, near-constant backup procedures and AI tools for managing sensitive data to enhance data protection and resilience.[ii]
  • Small Language Models (SLM) that aim to optimize models for existing use cases. SLMs can be trained on smaller, highly curated data sets to solve specific problems, rather than act on general queries (like Large Language Models).[iii]

But just because these rapidly-evolving technologies represent the “latest shiny new thing that really helps” (a tip of the cap to Paul Wilkinson) doesn’t mean that you should succumb to the fear of missing out by just “doing something”. In my experience, a new technology alone rarely (if ever) solves a business challenge.  When it comes to technology investments, it’s better to make a good, informed decision, based upon the unique needs and challenges faced by your organization.

Yet, AI-related technologies can have and are having a significant positive impact on ITSM environments. Many organizations are already benefitting from the use of AI-enabled chatbots, automated ticket management, and service request automation.

The pressure to introduce AI-enabled capabilities to ITSM implementations is real. But which tools?  What capabilities?  How can one decide?

Five critical steps

Here are my five critical steps to making a good AI/ITSM decision.

  • Define overarching goals for using AI within ITSM. It’s easy to become captivated by the latest products and features, especially in today’s AI/ITSM market frenzy. But chasing new products and features usually results in a short-sighted approach to technology adoption that will likely not meet longer term goals and needs. AI within ITSM should not be approached as a point solution; rather, AI should be considered within the broader perspective of ITSM. How will adding AI capabilities address current challenges?  How will adding AI enable the organization to realize future ITSM objectives? Defining overarching goals for AI in ITSM – in business terms – ensures that broader perspective .  Defining overarching goals also establishes the foundation for measuring AI/ITSM success.
  • Conduct a SWOT analysis of the ITSM environment. Conducting a SWOT analysis identifies a company’s internal strengths and weaknesses, as well as external threats and opportunities. Understanding an organization’s ITSM SWOT identifies the critical factors that must be considered before developing an AI strategy. A SWOT is a good way to understand an organization’s readiness and ability to take on an AI initiative.  Having the right stakeholders participate is critical to the success of a SWOT. Include stakeholders (especially non-IT colleagues) that have an interest in both ITSM and in AI capabilities and use.  Include stakeholders that will freely share thoughts and ideas and have a pragmatic understanding of organizational issues and challenges.
  • Develop the AI strategy. What is the approach for bringing in AI into your service management implementation? An effective AI strategy is not about finding places to “plug-in” an AI solution. It’s about understanding the organizational change, data, skills, budget, and infrastructure that will be needed for successfully utilizing AI technologies within the ITSM environment to help achieve the organization’s mission, vision, and goals.  Use the results of the ITSM SWOT as an input to this strategy.
  • Define evaluation criteria. The next step is to define the criteria by which potential AI solutions will be assessed. Defining this criteria up-front helps prevent falling victim to ‘shiny object syndrome’ and identify the solution that is best for your organization. As part of that criteria, consider the solutions alignment with the AI/ITSM strategy, costs (initial, ongoing, and cost effectiveness), the effectiveness of the solution to leverage issues identified in the SWOT, and how the solution enables the pursuit of potential future opportunities.
  • Develop and present the business case. Gaining and maintaining the commitment of senior management is critical for success.  When a potential solution is found, develop and present the business case for that solution. Discuss the technical and cultural challenges that come with AI adoption. Discuss the opportunities that AI with ITSM will provide.  Discuss how a solution will address SWOT and align with the AI strategy.  Discuss the benefits of implementing the solution , how risks will be optimized, and how success will be measured.  Discuss the consequences of doing nothing. Most importantly, ask for management commitment.

Cautions

Before moving forward with introducing AI within an ITSM environment, here are some cautions of which to be aware.

  • Good AI will not fix bad ITSM. The adoption of AI technologies can enable and enhance ITSM capabilities. However,  AI is not a “magic wand” that solves issues like poor process design, inadequate service management governance, and ineffective measurement and reporting.
  • Don’t overlook data quality and governance. Many organizations have data quality and data governance challenges. AI needs data – lots of it – and that data must be accurate, reliable, and trustworthy. Data quality and governance is not just a challenge for ITSM, it is an organizational problem.
  • Is there an ITSM strategy? Many organizations are not achieving the full potential of ITSM adoption. Rather than applying ITSM holistically, many implementations have only focused ITSM implementation on IT operational issues, and not on how ITSM enables business outcomes. Without an overarching ITSM strategy, AI investments risk becoming short-sighted and expensive point solutions that do not address business needs.

Augmenting the ITSM environment with the right AI capabilities can be a huge benefit for the organization, ITSM, and the employees of an organization.  But introducing AI within ITSM is not a decision to be taken lightly. Taking a systemic approach to identifying, justifying, and selecting solutions sets the right expectations with stakeholders and helps ensure successful introduction of ITSM with AI.

[i] https://www.uc.edu/news/articles/2025/01/innovation-experts-predict-top-tech-trends-for-2025.html , Retrieved January 2024.

[ii] Ibid.

[iii] https://www2.deloitte.com/content/dam/insights/articles/us187540_tech-trends-2025/DI_Tech-trends-2025.pdf , Retrieved January 2024.

 

 

 

 

 

 

 

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ITSM, Leadership, Organizational Change

Nothing will change. Unless you change.

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A few years ago, I was invited to conduct an ITSM assessment for an organization. While the request itself wasn’t unusual, it was unusual in that I had conducted an ITSM assessment for that same organization a few years prior. The  IT leadership of the organization had not changed over that time, apart from a different person leading their ITSM adoption efforts. But I was intrigued by the prospect of revisiting a past client engagement to learn whether my previous recommendations had had the positive impact that I had determined was possible.

After conducting interviews, examining their ITSM policies and procedures,  reviewing their IT strategy, and evaluating their ITSM performance reports, I was disappointed to find that there had been no substantial change in their ITSM journey from when I first visited.

I confronted the CIO with my findings. During our conversation, he acknowledged that there had not been much progress in their ITSM journey. He went on to ask if I would simply just tell them exactly what they needed to do, based on my “deep” knowledge of his organization.

I was taken aback. It had been a few years since that first assessment. Over the course of the two engagements,  I had spent about a total of 30 days interacting with the organization – hardly what I would consider a qualification for having a “deep knowledge” of the organization.

So, I took a deep breath, looked the CIO in the eye, and told him that – that I felt that 30 days of engagement over a few years doesn’t constitute a “deep” knowledge of the organization. Further, it was not an issue of not knowing what needed to be done – what needed to be done was clearly outlined in both assessment reports. The issue was that no one – including the CIO – wanted to change.

And then I said it.

“Nothing will change unless there is change.”

And with that, our meeting ended. I packed up my laptop,  left the building, drove away….and  subsequently was not invited back.

Everybody wants change. No one wants *to* change.

I see it all the time. People within an organization get enthusiastic about making a change, improving what is currently being done, expanding and enhancing their capabilities, thinking in terms of possibilities. Excitement fills the discussions within the conference rooms. People leave meetings eager to get started.

And then the time comes for the work that needs to be done to make the change….and sadly, things often go kaput.

What happened?

The 3 U’s of failed change

I’m no psychologist, but from everything that I have read, experienced, and observed about failed change, it seems to come down to the basic human instinct of fear of change. In my experience, that fear of change presents itself in one or more of the following symptoms that I call the “three U’s of failed change”.

  • Unknown – Change pulls people out of their personal comfort zones, where they feel safe. According to this article, this uncertainty feels like failure to our brains, and our brains automatically work to prevent us from failing.
  • Unprepared – Many people resist change because they feel unprepared. Provided training doesn’t really prepare people for the change, and as a result, there is a feeling of loss of mastery. Communications aren’t two-way, so there is no opportunity for feedback or to get answers to questions.
  • Unwilling – Even though people know that processes and systems aren’t working as well as they could, people have become comfortable in their interactions with those processes and systems. They “know” where the issues are, and how to make things work despite those issues. Changes to those processes and systems are perceived as a threat to the personal value of the people doing that work.

These are powerful reasons why change fails, but they are not insurmountable.

How can anything change…unless *you* change?

Is change working through your organization? Are you personally going through change? The answer to these questions is likely “yes”. Organizations are continually changing and evolving. As individuals, we are continually evolving as well. Think about it – what is different about your organization today when compared to two years ago? Compared to two months ago? What events or learnings over that time – both from a professional perspective and a personal perspective – have had an influence on you?

Change is constant – in our lives and in our careers. Here are some tips that I have found useful when experiencing change.

  • Educate yourself. Much of the angst around change is the fear of the unknown. To combat that fear, learn all that you can about what is changing. This will help restore any feelings of loss of mastery.
  • Ask questions. Fill in gaps in your understanding about what is changing. Listen for the “why” – the compelling reason change is necessary, and what success will look like after the change. This will help with any feelings of being unprepared.
  • Try it on. While it takes courage to push through the unknown, leaning into the change and exploring possibilities provides a sense of control. Being a pioneer within the change helps overcome feelings of loss of value. Trying on the change also provides you with valuable insights that you can use to make data-driven decisions about your next steps.

Change is a constant – in our organizations, in our jobs, and in our personal lives. Don’t let change paralyze you – take control. Educating yourself, asking questions, and trying on the change gives the you power and control you need to successfully push through the unknowns associated with change.

 

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AI, ITSM

Three AI truths with IT Service Management

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There’s no question that introducing AI capabilities can have a dramatic impact on IT Service Management (ITSM). Done well, AI adoption will free up ITSM professionals to do the work for which humans are uniquely qualified, like critical thinking, contextual understanding, and creative problem-solving. Furthermore, AI will enable organizations to realize many of the theoretical benefits of ITSM. For example, the use of AI and machine learning can leverage comprehensive in-depth data, not just a small recent sampling, for cause analysis, problem detection, and impact determination of problems. Another example is the use of AI can increase the data of the IT environment and automate the remediation of incidents.

But AI is not a “magic wand” for ITSM.

Before introducing AI capabilities into ITSM, organizations must first consider these three AI truths.

Truth #1 – AI needs good data

For the use of AI to be effective, it needs data. Lots of data. But, if that data is inaccurate, lacks integrity, or is not trustworthy, then the use of AI will only produce inaccurate or poor results.

Data quality is an issue that many organizations will have to tackle before realizing the complete benefits of introducing AI to their ITSM implementations. These means that organizations will have to step up their technology and data governance posture. According to this recent Privacera article, a fundamental principle of data governance is having a high-quality, trusted data source.  Having trusted data sources enables capabilities like ITSM to make accurate and reliable decisions regarding service management issues. But if the data sources used by ITSM tools contain data that is unregulated, the ability to automate responses is significantly hindered.

Truth #2 – AI doesn’t mean process design goes away

The need for effective ITSM processes and procedures doesn’t go away with AI adoption. Machine learning can be used to detect data patterns to understand what was done to resolve an issue. But what machine learning doesn’t do is determine if what is being done is the best approach. Machine learning doesn’t consider organizational goals and objectives with the adoption of ITSM. Machine learning cannot determine what processes are missing or need improvement to gain needed effectiveness and efficiency with ITSM.

Truth #3 – AI doesn’t replace knowledge

“Reducing cost”, often in the form of headcount reductions,  is frequently used as the justification for AI investment, as the use of AI will enable ITSM activities to be automated. And it’s true – many of the ITSM activities currently performed by humans can and should be replaced with AI-enabled capabilities, such as the automated fulfilment of service requests, automated response to incidents, and problem data analysis. But one of the hidden costs of using AI to justify headcount reductions is the form of knowledge loss – the knowledge inside people’s heads walks out the door when their positions are eliminated. And this is the knowledge that is critical for training the chatbots, developing the LLMs needed, and to the continual improvement of AI and ITSM.

While AI can provide the “how” for “what” needs to be done, it cannot answer the “why” it needs to be done.

Good Governance facilitates AI-enabled ITSM

Without governance,  AI can do some serious damage, not just with ITSM, but to the organization. As the role of IT organizations shifts from being data owners (often by default) to being data custodians, having well defined and enforced policies regarding data governance is critical. This means that the frequently found approach to governance consisting of an IT track and a corporate track is becoming untenable. As organizational processes and workflows become increasingly automated, enabled by AI capabilities, governance must become cross-functional[i] , with sales, marketing, HR, IT, and other organizational functions all involved. Organizations must consider and address data-related issues such as compliance with data privacy laws, ethical data use,  data security,  data management, and more.

An effective approach to governance enables organizations to define their digital strategy[ii] to maximize the business benefits of data assets and technology-focused initiatives. A digital strategy produces a blueprint for building the next version of the business, creating a bigger, broader picture of available options and down-line benefits.[iii] Creating a successful digital strategy requires an organization to carefully evaluate its systems and processes, including ITSM processes. And as ITSM processes are re-imagined for use across the enterprise in support of organizational value streams, effective governance becomes essential.

Getting ready for AI-enabled ITSM

What are some of the first steps organizations should take to get ready for AI-enabled ITSM?

  • Formalize continual improvement. One of the most important practices of an effective ITSM implementation is continual improvement. As organizations are continually evolving and changing, continual improvement ensures that ITSM practices evolve right alongside those business changes. And just like service management, AI adoption is not an “implement and forget”; in fact, AI will absolutely fail without formal continual improvement.
  • Answer the “why”. To say that there is so much hype around the use of AI within ITSM would be an understatement. Before jumping into AI, first develop and gain approval of the business case for using AI within ITSM. How will success be determined and measured? What opportunities for innovation will emerge by relieving people from performing those tedious and monotonous tasks associated with the current ITSM environment? What returns will the organization realize from the use of AI within ITSM? What new business or IT opportunities may be available because of the use of AI within ITSM? A good business case establishes good expectations for the organization regarding AI and ITSM.
  • Begin thinking about how AI can be leveraged by ITSM process designs. As discussed in this recent HBR.org article, AI will bring new capabilities to business (and ITSM) processes. With these new capabilities, organizations will need to rethink what tasks are needed, who will do those tasks, and the frequency that those tasks will be performed. The use of AI will enable organizations to rethink their ITSM processes from an end-to-end perspective, considering what tasks should be performed by people and what tasks should be performed by machines.

The concept of augmenting ITSM with AI is a “no-brainer”.  However, success with AI in an ITSM environment requires a lot of up-front thought, good process design, solid business justification, and considering these three AI truths.

[i] https://2021.ai/ai-governance-impact-on-business-functions

[ii] https://www.techtarget.com/searchcio/definition/digital-strategy

[iii] Ibid.

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Human-Centered Design, ITSM

Can Human-centered Design rescue your ITSM investment?

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Is your organization struggling to realize a return on investment with ITSM?

If you answered “yes”, you’re not alone. Many organizations are not getting the expected return on investment that was expected by adoption ITSM practices. Organizations are facing several challenges to realizing a ROI with ITSM.

  • “IT Operations only” approach. Many ITSM implementations have only focused on ITOM (IT Operations Management) aspects, such as managing user support requests, resolving incidents, or implementing changes. Services are not defined in terms of business outcomes or business value, making it difficult to determine the holistic benefit of ITSM practices.
  • Poorly defined workflows. This survey revealed that 43% of organizations cited excessive manual processing or insufficient automation as their top ITSM challenge. This points toward having poorly defined or undefined workflows that are obstacles for automation and AI-enabled capabilities.
  • Ineffective ITSM practices. According to this survey , 56% of businesses reported a significant impact on revenue due to technology downtime. Does this indicate ineffective incident management, problem management, change management, and continual improvement practices?
  • Total cost of ownership associated with ITSM tools. The cost of implementing ITSM doesn’t stop with the implementation of the tool. Ongoing maintenance costs, both in terms of licensing, support, and daily management of the platform contribute to the cost of ownership. Post-implementation costs, such as user training, organizational change management, and ongoing process improvements also add to the cost of ownership. Many IT organizations also struggle with what they see as conflicting demand between business priorities and operational activities.
  • Lack of specific ITSM success goals and metrics. Many organizations have not defined specific success measures for ITSM adoption. Further compounding the challenge is that organizations have not defined metrics that indicate how ITSM contributes to the organization achieving its mission, vision, and goals.

These are big challenges for many ITSM implementations determining an ROI. But in my opinion, there are two reasons why ITSM isn’t delivering the expected ROI.

  • ITSM has been and continues to be about IT, not about the business. Most ITSM implementations are focused on how to manage the work of IT, not on delivering business results.
  • ITSM practices were not designed with business outcomes and value in mind but instead based upon the requirements of the ITSM tool being implemented.

And even if one of the drivers for ITSM implementation was to manage interactions with end users – an operational aspect of IT management – the end user typically had no voice or input into the design of ITSM practices. And the lack of user involvement with ITSM design shows up in the experience with IT. As an example, the 2023 Global IT Experience Benchmark report from Happy Signals indicates that 49% of survey respondents identified “IT Support Services” as a negative factor regarding their experiences with IT.

Haven’t people always been a core focus of ITSM?

In theory, a core focus of ITSM is the people that interact with technology. “Customers” are the people that have defined the requirements and need for a service. It is the customer that determines the value of the service that IT provides. Customers are also users of those IT services. “Users” are people that rely upon and interact with IT services to get their work done. The use of the technology associated with these IT services is intended to improve productivity and efficiency of users in getting this work done.

But in practice, ITSM adoption has been more about how IT manages its work, and less about how the experience or success people have with technology. In fact, users are rarely – if ever – part of process design or technology implementations associated with ITSM.

Think about it. In practice, most incident management practices are built around routing and closing tickets as quickly as possible. Service desks and their agents are evaluated by how quickly an issue is closed (with “closed” usually being an IT judgement, and not confirmed with the end user), and not in terms of the user experience.

In practice, Service Level Agreements (SLAs) do not discuss business performance measures, but describe how IT measures its work. And many SLAs are defined by IT with no input from the end user or customer – yet the end user is expected to act within the terms of the SLA. In practice, “customer” satisfaction surveys are not engaging the customer, but rather the user. Compounding the situation is that the return rates of those satisfaction surveys are anemic, and actions are rarely (in practice) taken based on the information captured in the few surveys that are returned.

So how can organizations get the focus of ITSM back on people?

It’s about PPT plus HCD!

In the early 1960s, Harold Leavitt introduced what eventually became known as the “golden triangle” or “three-legged stool” of People, Process, and Technology (PPT) as guidance for managing change within an organization. The model represents if one component shifts, the other two must also shift to maintain an effective balance as change progresses.[i]  The PPT framework is simple but powerful. And while PPT is a mantra often heard as part of ITSM adoptions, the ‘people’ aspect is often ignored, as the focus is typically on the implementation of the technology associated with ITSM.

How can organizations take impactful, people-focused actions based on the PPT framework? This is where human-centered design (HCD) comes in. HCD is a framework for creative problem-solving that focuses on understanding the needs, wants, and limitations of the people who will most directly benefit from the solution.[ii]  It’s about designing with empathy for the people that will be interacting with the solution. HCD is composed of three elements:  desirability – the product or service meets users’ needs; feasibility – the product or service is technically feasible;  and viability – the product or service is viable as a business model.

There are real benefits when organizations shift to an HCD approach.

  • Technology teams build better, more robust products and services when they have a true understanding of individuals, their needs, and their journeys. [iii]
  • Leveraging human-centered design principles also helps technology teams deliver faster and at lower costs — mostly because they’re hitting closer to the mark on their first delivery. [iv]
  • Gartner’s 2021 Hybrid Work Employee Survey, which found that employers with a human-centric philosophy across the business saw reduced workforce fatigue by up to 44%, increased intent to stay by as much as 45%, and improved performance by up to 28%.[v]
  • A McKinsey study found that over 5 years, companies with strong design practices outperformed their industry counterparts in terms of revenue growth and returns to shareholders. [vi]

It’s a compelling argument for introducing HCD into ITSM practices – and bringing the focus of ITSM back to people.

Shifting the focus of ITSM to people

How can HCD be applied to ITSM? It all starts by asking “what do people really want?” from ITSM. Here are some tips for getting started.

  • Start where you are. Don’t throw away what has been done with ITSM, but human-centered design begins with a mindset shift. Commit to making ITSM more about the business and less about IT by shifting from a “technology-first” mindset to a “human-first” mindset.
  • Truly capture and understand the user perspective. Let’s face it – the way that the user perspective is typically captured today (via post interaction surveys sent from the service desk) isn’t that effective. What are better ways for IT organizations to understand the user experience? First, asking better questions (not rating questions) will yield better answers into the true user perspective. Going to where work is being done and observing user interactions with technology is powerful and informative. Hosting regular, periodic small focus group meetings with users provides opportunities for deeper discussions about the user perspective.
  • Include users in continual improvement actions. Including end users as part of continual improvement actions uncovers underlying needs, improves experience, and helps provides solutions that solve the real issue.

Shifting ITSM practices from a technology-first to a people-first approach will have a major positive impact on users, customers, organizations – and ITSM.

Need help with shifting your ITSM practices from a technology-first mindset to a people-first mindset? It starts with understanding the user’s experience. We can help – contact Tedder Consulting for more information.

[i] forbes.com/sites/forbestechcouncil/2024/04/19/20-expert-tips-for-effective-and-secure-enterprise-ai-adoption,  Retrieved April 2024.

[ii] https://www.mural.co/blog/human-centered-design Retrieved April 2024.

[iii] https://www.cio.com/article/413079/cios-find-big-benefits-in-shift-to-human-centered-design Retrieved April 2024

[iv] Ibid.

[v] Ibid.

[vi] https://www.mckinsey.com/capabilities/mckinsey-design/our-insights/the-business-value-of-design, Retrieved April 2024.

 

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AI, GenAI, ITSM

4 things IT can do to improve Business-IT Alignment – and enable AI success

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A few years ago, I thought that we had finally moved beyond the conversation of “business-IT alignment”.  I thought that business processes and technology had finally become integrated; if not integrated, then at least the boundary between business processes and technology was significantly blurred.

Well, I was wrong. Business-IT alignment – or the lack thereof – is still a thing.

We’re still struggling with business-IT alignment

This recent CIO.com article discusses seven hard truths of business-IT alignment.  Here are a few of those hard truths:

  • “The business is not your customer.” I agree. For IT to act like non-IT colleagues are ‘customers’ simply drives a wedge between the IT department and the rest of the organization. This behavior also provides IT with an excuse for not understanding the business of the business.
  • “Like it or not, you are responsible for business outcomes.” That’s true. The real value from the use of technology is for the organization to realize business outcomes and value. But too often, IT sees and measures success in terms of projects getting done, or laptops being delivered, or contacts at the service desk being resolved.
  • “The business really does need to understand what you do.” That’s also true. While the IT department is responsible for the installation and maintenance of digital technology, IT must be more than just a technology caretaker. IT organizations must help the rest of the organization understand how the use of technology supports business strategy.
  • “You’re probably talking about the wrong things.” Couldn’t agree more. Many of the measures and reports that are being produced by IT are only because the tools being used by IT make it easy to produce these measures and reports. Do these measures have any meaning or relevancy to the rest of the organization?

Why is this a problem?

Business-IT alignment is not just a catch phrase or buzzword. The digital era is amplifying the importance of having strong business-IT alignment. But within many organizations, business-IT alignment is missing. How does the lack of alignment impact IT and the rest of the business?

First, IT is unable to respond to business demands at the speed of business. Consider the challenge that every modern business faces – serving the digital customer. The digital customer is demanding that businesses provide services at anytime from anywhere. In response, businesses want to leverage emerging technologies such as chatbots and GenAI to meet that demand. But because IT hasn’t been involved in those business strategy conversations, it is forced to play “catch up” to meet these demands – demands for which IT is usually unprepared. IT is not prepared because no one has been trained, much less involved in the selection of this technology – but then IT is expected to make it work as well as fit with existing systems and infrastructure. When IT is forced to play catch up, in-flight projects get delayed as IT resources are shifted to meet new demands.

But this behind-the-scenes work is rarely visible to the rest of the business. To the rest of the business, IT is a barrier to responding to the digital customer.

Secondly, the rest of the organization continues to look at IT as just a cost center. What those outside of IT may not realize is that IT must deliver warranty (security, resiliency, continuity, capacity, performance) as part of its services – regardless if that’s been communicated or specifically requested. Delivery of an expected level of warranty costs money – costs that may not be apparent to non-IT colleagues.

Why ITSM hasn’t helped

Wasn’t ITSM adoption supposed to address issues like the above and align the IT organization with the rest of the business? True, business-IT alignment is a goal of ITSM adoption…but for many organizations, it didn’t happen. Why?

  • ITSM was (and continues to be) an IT initiative with little to no involvement from non-IT colleagues. The initial ITSM project focused internally on IT processes and infrastructure management and excluded defining services and business-IT strategy. Making things worse, IT didn’t map how what it does supports business results or delivers business value. There was (and is) no link established between ITSM goals and objectives and organizational goals and objectives.
  • The ITSM initiative only focused on implementing a tool. This is a suboptimal approach for two reasons. A technology-only focus excludes how ITSM impacts people – both within and external to IT, as well as processes, suppliers, and partners. Secondly, the IT organization only took actions that facilitated use of the tool, not necessarily align with business needs.
  • ITSM is only focused on IT operations – or even worse, just the IT service desk. ITSM is viewed only as a way to deal with end-users of IT products and systems, never considering how technology could be used strategically to deliver business value or results. As a result, not only is ITSM not aligned with the business, IT is not internally aligned.

Successful AI adoption requires Business-IT Alignment

Businesses continue to experience the impact of the digital economy. In the digital economy, the “store” is always open, and customers expect that systems are “always on”.  Customers can (and will) do business whenever and from wherever they want – using any internet-accessible device. Customers expect a differentiated, frictionless experience that provides value. Encountering system downtime or a poor experience is simply out of the question.

And organizations are turning to new capabilities enabled by emerging technologies, like chatbots, GenAI, intelligent automation, and more to meet this ever-increasing customer demand. In the digital economy, the technology managed and delivered by IT is the crucial connector between a business and its customers.

What does this mean for IT? IT can no longer play a back-office role within digital organizations. IT has a critical role as a business operates within the digital economy – and strong alignment between business and IT is required.

The successful use of chatbots, GenAI, automation, and other emerging technologies starts with having strong business-IT alignment. So how do organizations seize this opportunity, avoid the mistakes of the past (as with ITSM adoption), and realize true business-IT alignment?

First, ensure that any AI initiative has clearly defined objectives that are aligned with business strategy.

Second, successful adoption of AI requires strong involvement of business leaders[i]. Successful use of AI-enabled capabilities depends on the AI understanding the business of the business. It’s business leaders that have the knowledge that AI needs.

IT organizations must make the investment in building skills and competencies, in both AI technologies and in understanding the business of the business. Technology-only skills are no longer sufficient. IT must become that trusted advisor to help guide business leaders as the organization navigates the challenges of an AI-enhanced digital economy.

Lastly, good ITSM is an enabler for AI adoption. Good ITSM means aligning activities with business goals and objectives, defining services to ensure a shared understanding how technology delivers business value and outcomes, and providing business-relevant metrics and reporting.  As a result, good ITSM enables fact-based decisions regarding AI adoption, such as where intelligent automation would improve a customer or employee experience.

Nothing will change – unless there is change!

Let’s be clear. Business-IT alignment challenges will not just go away, nor will they fix themselves. It’s up to IT to align with the rest of the organization, not the other way around. And it’s not just the CIO alone that can drive business-IT alignment – the entire IT organization must also drive it as well.

It’s time to break the pattern. Here are some suggestions for breaking through those alignment barriers– all of which can be initiated by IT.

  • Establish and nurture the guiding coalition. To demonstrate its commitment to overcoming the challenges of business-IT alignment, IT must form a team to drive change. This early step in Kotter’s 8-step model demonstrates IT’s commitment to driving improvement in business-IT alignment.
  • Map business value streams – plus. Value Stream Mapping is a great way to identify how value flows through an organization. But don’t stop there – identify and map how technology supports each step within each value stream. Review these value streams with all IT personnel to raise awareness of how IT enables business success. Then, take it one step further. Review value stream maps with non-IT stakeholders and decision-makers. Not only will this illustrate the role of IT in business success, but those stakeholders may also even be surprised to see how technology enables value flow through the business!
  • Look at what you’re reporting to whom. If IT is sending reports full of technology metrics to business colleagues, then IT is reporting the wrong things! Identify and define ways to measure and report on metrics that directly reflect the organization’s mission, vision, and goals. By measuring and reporting on metrics that are important to the business, IT demonstrates how its contributions lead to business success.
  • Get serious about continual improvement. IT organizations can positively influence non-IT colleagues by fixing those things that cause constant irritation when interacting with IT products, processes, and services. Establishing a regular and on-going continual improvement practice to remove these irritants – then publicizing those efforts – will begin to change the perception of IT.

Business-IT alignment has long been a critical success factor for the modern, digital-age organization. Success with AI adoption is raising the need for alignment to a new level. Taking these first steps will set you on the path of business-IT alignment – and AI success.

Does your IT organization continue to struggle with alignment to “The Business”? Let Tedder Consulting help you establish the strong foundation you need so that your organization will realize the business results required from its investments in and use of technology.  Contact Tedder Consulting today for a no-obligation discussion about how we help!

[i] https://www.forbes.com/sites/forbestechcouncil/2023/10/06/why-business-leaders-should-understand-ai-alignment, Retrieved April 2024.

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AI, ITSM

The 3 Pillars of Success for AI-enabled Service Management

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In her book[i], Dr. Kavita Ganesan suggests that any AI adoption be evaluated using three pillars:

  • Model success – Is the AI model performing at an acceptable level in development and production? (In other words, the model performs at the required levels of accuracy, execution time, and other factors.)
  • Business success – Is AI meeting organizational objectives?
  • User success – Are users satisfied with the AI solution and perceive it to be a valid solution?

Many organizations are rushing to incorporate AI-enabled technologies to improve their service management capabilities. AI technologies, such as AI-assistants, chatbots, intelligent process automation, generative AI, and more, can provide a next-level set of capabilities for service management. But are these organizations’ service management practices positioned to fully take advantage of these new capabilities?

Let’s be clear – AI is not a “magic wand.”  AI is a technology. And like any other technology, there are factors that must be addressed if an organization is to realize the benefits that AI can bring to service management.

First, AI needs data – and lots of it. The effectiveness of AI depends on the quantity, quality, relevancy, and timeliness of the data being used by the AI models and algorithms. Any limitations in the data being used by AI will be reflected in the outputs produced by AI – and the use of those outputs by service management processes. The old axiom remains true – garbage in will result in garbage out.

AI cannot be a solution looking for a problem. Just because AI is a “hot topic” now doesn’t mean that it is the solution for every business challenge – especially service management issues. If issues like ineffective workflows, undefined services, poorly defined measures, lack of continual improvement practices, or the absence of high-quality data already exist within the service management environment, the introduction of AI will only exasperate those issues.

Lastly, the use of  good organizational change management practices is critical. There is a lot of FUD (Fear, Uncertainty, and Doubt) surrounding the introduction of AI[ii] within organizations. Yes, there will be impacts to how humans work and interact with technology, but for whatever reason, there is a heightened fear associated with AI-adoption within service management.

Applying the 3 pillars for AI success to AI-enabled Service Management

Before rushing into incorporating an AI solution with a service management environment, let’s adapt and apply Ganesan’s three pillars for success with AI-enabled service management.

The first pillar is business success. How do current service management capabilities support business outcomes and enable value realization? How will the introduction of AI capabilities further enhance the realization of the outcomes and value delivered by service management? If the answers to the above questions aren’t clear, revisiting some foundational elements of service management is in order. Consider the following:

  • Have IT services been defined, agreed, documented, and measured in terms of business value, business outcomes, and the costs and risks associated with the delivery of services? Many IT organizations have defined what they call “services” in terms of
    • what goods and products (like laptops and smart devices) are provided
    • the service actions (like password resets) a service desk will perform, and
    • procedures for gaining access to digital resources (like a cloud-based resource or a shared drive).

Not only does this approach inhibit a mutual understanding of the vital role of technology in business success, but it also commoditizes what IT does. Secondly, this approach fails to establish business-oriented measures regarding results and value.

  • Are non-IT colleagues named as service owners? Are these non-IT colleagues actively involved in the delivery and support of services? This is a significant issue for many service management implementations. In many organizations, IT personnel, not non-IT colleagues, have taken on the role of service owner – the person that is accountable for a service meeting its objectives and delivering the required business outcomes and value. The service owner is critical to understanding what is needed and importantly, how business outcomes and value are realized and should be measured.
  • How might AI adoption enable organizations to consider service management practices that would enhance their business? For example, better service portfolio management would enable better utilization of and data-driven investments in services and technology.

The next pillar is employee success. Frequently (and counterintuitively!), service management practices have been designed and implemented with IT and not the IT service consumer in mind. As a result, interacting with the service desk or a self-service portal can be an exercise in frustration due to the over-technical nature of those interactions. Consider:

  • How might the introduction of AI result in friction-free interactions with services and the fulfillment of service requests? How might AI personalize end-user interactions with service management practices? Consider how AI could shift the burden of interacting with service management practices from the end-user to a personalized and proactive AI-enabled capability.
  • How might the introduction of the AI model result in friction-free interactions with supporting IT services? If consuming IT services present challenges to end-users, it can also be challenging for those that deliver and support those services. Will AI-capabilities enable service management practices to shift from a reactive to proactive stance by identifying and eliminating causes of incidents before they occur? Will AI-capabilities enable better issue resolution by suggesting potential solutions to IT technicians?
  • How might the introduction of AI enable employees to make better, data-driven decisions based on relevant, timely, and accurate knowledge? Knowledge management is among the most significant challenges of a service management implementation, as knowledge is ever evolving and continually being created, revised, and applied. AI may provide a solution – this blog explores how Generative AI could provide organizations (not just IT) with the capability of harnessing its collective knowledge.

The final pillar is AI / service management model success. Frankly, many service management challenges can be resolved through continual improvement activities. Some issues may be resolved through the application of effective and efficient automation. Questions to consider include:

  • How might AI adoption result in better and proactive detection and resolution of issues before those issues impact the organization? How might AI adoption result in improved change implementations through better testing or confirmation of positive business results?
  • Is there sufficient, good-quality data to enable AI-driven service management actions? If AI models are not supplied with sufficient, good-quality data, the results from the model will be suboptimal at best – or worse, just flat-out wrong.
  • What is the required level of accuracy for the model? A “100% accurate” model may be too costly to achieve and maintain; a “75% accurate” model may be perceived as a failure.

Get ready for AI-enabled service management

The introduction of AI to a service management environment can be a game-changer on many levels. Here are four steps to get ready:

  • Make the business case for introducing AI to service management. Think strategically about AI , service management, and how the combination of AI and service management will help the organization achieve its mission, vision, and goals.
  • Communicate, communicate, communicate. The mention of AI adoption may cause concerns among employees. Start open conversations regarding AI-enhanced service management capabilities, incorporate feedback, and proactively address concerns.
  • Identify and define success measures. The mere implementation of AI capabilities within service management is not an indicator of success. Define how the benefits articulated in the business case will be captured, measured, and reported.
  • Begin data governance now. The success of any AI initiative depends on the availability of good quality data. If service management is to leverage AI capabilities, the data being captured must be of good quality. Define and publicize data quality standards for service management practices and ensure compliance through periodic audits.

The introduction of good AI capabilities will not fix bad service management. Applying the three pillars described above will ensure successful introduction of AI capabilities resulting in next-level service management practices for any organization.

Is your service management approach “AI-ready”? An assessment by Tedder Consulting will identify any foundational gaps so your service management environment is “AI-ready”.  Contact Tedder Consulting today for more information!

[i] Ganesan, Dr. Kavita. “The Business Case for AI: A Leader’s Guide to AI Strategies, Best Practices & Real-World Applications”.  Opinois Analytics Publishing, 2002.

[ii] https://www.forbes.com/sites/jenniferfolsom/2024/03/28/meet-your-newest-co-worker-ai  Retrieved April 2024.

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