Tag Archives: Service Management

AI, ESM, ITSM

Will AI break ITSM out of its IT operations cage?

Leave a comment
Share twitterlinkedinmail

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.

Share twitterlinkedinmail
ITSM

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

Leave a comment
Share twitterlinkedinmail

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.

Share twitterlinkedinmail
ITSM

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

Leave a comment
Share twitterlinkedinmail

“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!

Share twitterlinkedinmail
AI, ITSM

Five critical steps for making a good AI/ITSM decision

Leave a comment
Share twitterlinkedinmail

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.

 

 

 

 

 

 

 

Share twitterlinkedinmail
ITSM, Leadership, Organizational Change

Nothing will change. Unless you change.

Leave a comment
Share twitterlinkedinmail

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.

 

Share twitterlinkedinmail
AI, ITSM

Three AI truths with IT Service Management

Leave a comment
Share twitterlinkedinmail

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.

Share twitterlinkedinmail
Human-Centered Design, ITSM

Can Human-centered Design rescue your ITSM investment?

Leave a comment
Share twitterlinkedinmail

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.

 

Share twitterlinkedinmail
AI, ITSM

The 3 Pillars of Success for AI-enabled Service Management

Leave a comment
Share twitterlinkedinmail

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.

Share twitterlinkedinmail
Digital Transformation

You Can’t Automate What You Don’t Understand

Leave a comment
Share twitterlinkedinmail

The case for automating workflows is a strong one. There are plenty of reasons why organizations are looking for the right automation tools, including but not limited to:

  • Frees staff from performing tedious, high-volume, low-value tasks
  • Creates cheaper and faster process execution
  • Improves customer experience
  • Makes it easier to scale

I’m not here to argue the case of automation. When done correctly, it can achieve all those benefits above. And many organizations see success when they automate simple, one-step tasks, like password resets.

However, automation can start to feel like a catch-22, especially for those organizations who realize initial success with their simple automated tasks. That’s because they start the automation initiative by looking for the right tools. Many automation conversations in organizations are about the various tool vendors and weighing the features of each tool. And for simple automations, perhaps that’s not a bad way to make decisions.

But if you want to automate multi-step, complex workflows, the tool is the last thing you need to identify. Let’s explore how to make sure you get these multi-step automations correct.

Principles of Good Automation

1. Automation often means orchestration
The term “automation” is often used to describe things that are actually service orchestration. Automation is the act of automating a single task, like password resets. Orchestration refers to automating multi-step processes to create streamlined, end-to-end (and often inter-departmental) workflows. When determining your automation needs, be clear on whether your goal is only to automate or orchestrate.

2.Don’t automate or orchestrate “just because you can”
Every organization has plenty of workflows and tasks from which to choose to automate. But just because you can automate something doesn’t mean that you should, especially in the first stage of your automation initiatives. You want to focus your initial efforts on the tasks that:

    • Are performed on a high-frequency basis, are tedious for people to perform, but are well-defined and produce predictable results.
    • Consume a disproportionate amount of a team’s time. This may indicate that the process is not well-defined to begin with! In this case, be prepared to first invest time into process design.
    • Drive the most ROI for your business. It doesn’t make sense to spend hours and hours defining and automating a task that is only performed on an infrequent basis.

3. Everyone involved must be ready for orchestration for it to work
Creating multi-step, complex workflows almost always involve more than one team or person. You have to have everyone involved in the entire process involved and that requires a level of transparency from everyone in the organization.

Too many organizations begin automation initiatives despite having little insight into the actual steps involved in a workflow—and therein lies the problem. Those organizations are trying to automate work that they don’t understand.

Gaining Transparency is key

The solution for avoiding automation and orchestration missteps is to start by gaining transparency into the work currently being performed – before you start to automate. Here’s how:

  • Get the whole team involved. Automation and service orchestration has to be a collaborative project, or it will never work. People are often resistant to automation initiatives because they do not understand the objectives of the initiative or were not provided with an opportunity to provide feedback. To help overcome this resistance, illustrate how orchestration and automation will not only improve productivity, quality, and efficiency, but will also improve the employee experience by removing toil from daily work.
  • Identify needed business outcomes. Business outcomes are king to all else. You’re going to burn precious resources spending so much time automating tasks and orchestrating procedures that don’t result in measurable and valuable business outcomes. Before automating, first evaluate how a particular workflow achieves business outcomes
  • Understand end-to-end workflows. Does everyone on the team have a shared understanding of each step in a workflow? Is there a clear understanding of how each team contributes to that workflow? Many organizations don’t have this type of insight and it causes massive breakdowns during the execution of a process. Getting insight into the steps involved enables automation. Otherwise, attempts to automate will only result in frustration.

Once you’ve gained transparency into the current work, now you’re ready to evaluate tools. While this may require more time at the outset, doing this foundational work is key to long term success with automation.

Good automation and good service management go together

To be clear, good automation will not fix bad service management. When you try to use automation to address poor service management issues, all that happens is that you screw up faster – and automatically. And your end-users and customers immediately feel the impact of bad service management.

But when good automation is combined with good service management, watch out. Good service management helps you do more with your resources, helps you get everyone on the same page – both from the technology and the business outcomes perspectives, and helps you deliver that differentiated experience. Good service management ensures that you’re taking a holistic approach to delivering IT products and services. And when you start automation efforts by understanding how value is delivered through IT products and services – you’ll automate the things that both make sense and deliver the most value for both the organization and the user.

Tedder’s Takeaway: Why it matters

Tools alone will not make automation work. Automation is only successful when there is a shared and agreed understanding of the resulting business outcomes, combined with having transparency into how work is being done. Augmenting good service management with good automation delivers the differentiated experience for both the organization and the end-user.

Are your automation efforts stuck? Are you not realizing the benefits of service orchestration? Let Tedder Consulting help! From value stream mapping to process design and improvement, Tedder Consulting can enable automation that is both impactful and delivers a great customer experience. To learn more, schedule a free, 30-minute meeting with Tedder Consulting today!

Share twitterlinkedinmail
ITSM

What’s The ROI of Service Management?

Leave a comment
Share twitterlinkedinmail

IT service management has typically been seen as yet another cost inside of what is perceived to be a cost center known as “IT”. Why? Because many IT organizations still view service management as operating overhead…and nothing else. The potential business value of good ITSM is ignored.

Many IT organizations could start becoming a strategic organizational partner if they understood the ROI of their work. ROI, or Return on Investment, is an important financial metric that most value centers use to measure success. Unfortunately,  90% of all technical support organizations fail to measure ROI. 

But, a simple shift in thinking about service management and ROI will create major opportunities for IT.

Why is ROI important to IT?

Why should IT leaders care about ROI? Simply put, ROI is the language of the business. Everyone in the C-Suite understands ROI and how important it is in making business decisions. When IT leaders start discussing ROI with peers, they are taking the “techno-speak” out of the discussion.  As a result, ROI makes IT more relatable and understandable to the rest of the business.

Relating IT in terms of ROI within the organization can lead to bigger budgets, better staffing, and improved service relationships. Data shows that top performing IT support organizations produce a ROI of 500% or greater on an annual basis!

Understanding the ROI of Service Management

Measuring the ROI of service management starts with quantifying work. But not in the ways that many typically think, like counting closed tickets or tracking time to resolution. Rather, quantify service management in terms that truly demonstrate business value—measures like savings (or “costs avoided” as an early CFO of mine schooled me about) through better processes, improved productivity, or investments in innovation.  These are the kinds of topics business colleagues care about – not IT operational measures. 

Here are three examples where you can illustrate a business-relevant ROI of good service management. 

ROI Area #1 — Time is Money

According to estimates, the global impact of unplanned downtime is 14.3 billion and employees lose an entire day of productivity due to unplanned downtime. 

Many ITSM leaders measure IT productivity in terms of number of incidents resolved and time to incident resolution. This is a flawed approach.  An incident is not a “value-add”. While there is (limited) value in resolving an incident, the real business value is not having incidents at all. 

So how might good service management practices produce an ROI?  Let’s take an example. Company XYZ implemented service management improvements during quarter two. These changes included improving change enablement practices and developing and publishing self-help knowledge articles regarding the most-frequently encountered issues. 

Q1 Q2 Q3 Q4
12,792 12,374 10,556 9,843

Because of these changes, XYZ saw over 4,700 fewer tickets in Q3 & Q4 than they had in Q1 & Q2. 

Now let’s apply money to the scenario.  Let’s say every ticket costs the company $10 in productivity loss (of course, it’s much more than this!).  By implementing these improvements, IT helped the organization avoid nearly $50,000 of lost productivity. That’s where the real value and the ROI of service management begins to show itself. 

ROI Area #2 — Avoid unnecessary cost with self service 

Another ROI-enhancing area for service management is the concept of “shift left.” Shift left means moving support and enablement activities closer to those doing the actual work.  For example, moving incident resolution or request fulfillment from a desktop support team to the service desk or from the service desk to Level 0 (self-help), can help an organization avoid unnecessary escalation-related costs. Unnecessary escalations result in support costs that are not directly reflected in performance measures.  Because these escalations appear to be just ‘business as usual’, the cost associated with those escalations go unnoticed. 

How many tickets are unnecessarily escalated that could have been solved by Level 1 or by self-help? According to TechBeacon, a typical service desk ticket can cost around $22. But escalating a ticket can cost an additional $69, making the total cost of the ticket $91. If you are handling tens of thousands of tickets, these costs add up quickly.

But when self service offerings are provided for those repeatable and predictable support and enablement activities, your organization avoids the costs associated with ticket escalation.   

ROI Area #3 — Spend on innovation, not support

This last area is perhaps the most important but often the most forgotten. It’s where poor IT service management practices drain resources from innovation.

To understand how good service management facilitates innovation, let’s start by understanding the basis of IT budgets. Generally speaking, IT budgets have three categories of costs:

  • Fixed costs, like salaries, support contracts, and other operating expenses. These costs typically do not change dramatically year over year. 
  • Innovation, in the form of new projects and improvement initiatives.  These costs represent outcomes that the organization would like to realize through investments in technology. 
  • Maintenance and support, which includes application and software updates, responding to incidents and requests, security monitoring and patching, and other day-to-day activities needed to maintain reliability and availability. 

Again, let’s use some easy numbers for illustration. If an IT budget is $1000, then typically fixed costs make up $500.  Innovation is budgeted at $300, and maintenance and support is budgeted at $200. The organization is optimistic about realizing new value through innovation.  Support costs are acknowledged and seem reasonable. 

Until the impact of poor IT service management practices become evident. Poor IT service management practices result in poor change implementations.  Lots of fire-fighting.  Too many meetings to discuss and decide what should be simple requests.  Automation that just doesn’t work well. Confusion regarding how technology enables current organizational outcomes.  Duplicative products and services. 

And suddenly, the IT organization is spending more time in maintenance and support, and less time innovating. And what part of the IT budget absorbs that additional cost?  The budget allocated for Innovation. Innovation is sacrificed to cover the (unnecessarily excessive) cost of simply keeping the lights on.

Good service management preserves that innovation budget, by doing the right things well when it comes to maintenance and support. 

What is the simple shift in thinking that enables service management ROI? 

How is it possible to realize ROI with service management, rather than looking at it as cost? 

The answer is simple.

It starts with a shift in thinking.  Rather than viewing service management as a means of control, begin viewing service management as a business enabler.  

While the IT operational aspects of service management are important, it is not why organizations need to practice good service management.  

Good service management enables organizations to achieve business outcomes.  Good service management enables organizations to realize value from its investments in and use of technology.  And one of the key ways to enable this shift in thinking is to talk about service management in terms of ROI.  

Tedder’s Takeaway – Why It Matters

Shifting how the organization views service management is a critical enabler for discussing the ROI of service management.  Moving the conversation from cost to results, then attaching ROI to those results.  Having the ability to discuss ROI with organizational peers not only makes IT more relatable, it also repositions IT as a strategic enabler, with a tangible way to understand the impact of good service management. 

Is it time to shift your thinking about service management?  Are you reporting operational measures instead of business outcomes?  What would be possible for your organization if you could illustrate the ROI of service management? Let Tedder Consulting help!  For more information, contact Tedder Consulting today.

Share twitterlinkedinmail