You can’t get fired for buying ServiceNow
-Ancient IT proverb
You’ve probably heard this or even felt it yourself. And it has been true to a large extent. The breadth of possible use cases that ServiceNow offers is truly amazing.
If you have the budget and the time and the resources and access to certified consultants, you might as well stop reading, go over to servicenow.com and sign up.
That said, not every organization can afford to shell out millions of dollars for one platform that they know they won’t fully leverage. If you can, your choice is simple. ServiceNow has been the market leader for decades and provides a gamut of capabilities.
But if you want to put in the research work and explore other options, this guide is meant to help you understand and evaluate them.
The introduction covers the ServiceNow monopoly in ITSM. If budget and access to development resources are not major concerns for you, quite frankly ServiceNow is your safest choice.
Since it looks like you’re up for a nuanced exploration of the larger ITSM marketplace, let’s start by looking at how this space has evolved over the last decade or so.
Most ITSM software vendors have incrementally improved their offerings, but for a technology space, there haven’t been any radical innovations. Completely new enhancements have also been few and far between.
There have been a few broad trends:
About ten years ago, ITSM vendors started opening up to the idea of “consumerization of IT”. The rationale was that employees of a company – or IT end users – were consumers in their day-to-day lives. They were used to a certain level of ease while using consumer products.
These products became even more efficient in the digital era. Digital-first apps, like Uber, DoorDash, etc. were highly intuitive. In their personal lives, users could book a cab, or order food, or get products delivered to their doorsteps, with the click of a button.
When these users came into the workspace, the enterprise tech they needed to use made them feel like going back in time.
New ITSM tools that emerged during this time were optimized for ease of use and used that as a selling point. We moved from clunky interfaces to smoother UI that both end users and support agents loved.
The other thing that changed, was that these vendors started talking about enterprise service management, or ESM.
ESM, in a nutshell, refers to the practice of extending ITSM principles beyond the realm of IT – to areas like HR, Finance, Legal, Facilities etc. We would argue that that was a natural next step and wasn’t disruptive from a product perspective, since what these departments got, was a scaled-down version of the IT product.
ITSM vendors, almost unanimously, built the ability for multiple teams to co-exist and manage their support and services within a walled space. HR agents, for instance, had access to just HR tickets and could set up HR-related automation workflows without being overwhelmed by an org-wide view of these features.
Truth be told, the world of ITSM hadn’t seen any radical changes despite these broad themes and smaller trends. That is until the AI revolution.
To be fair, AI has existed for a while but was limited to a few large or innovative companies and some early adopters. Then OpenAI launched ChatGPT and everything changed.
GenAI – and, by association, AI – gained mass popularity. AI adoption among IT end users skyrocketed* thanks to its practical value. This was perhaps the first major technological trend where the business caught on first and IT needed to play catch-up. But there was just no putting the genie back in the bottle.
In our opinion, we’re at a technology inflection point and AI has the potential for unforeseen innovation. Thoughtful application of AI will not just incrementally improve IT processes, but will push us to reimagine what they could (and should) look like.
Despite all this, the IT world seems to be divided into two separate camps when it comes to AI adoption. We’ll break them down in the next chapter.
There are folks in the IT space who think that the hype around AI is just that – hype. Some of them are even worried about their employability or are too wary of taking the leap.
Camp two wants to adopt AI because it seems to be the flavor of the year. Or because their C-suite or board is breathing down their necks to adopt AI.
While it’s important not to give in to the hype around AI, or any trend for that matter, you need to be pragmatic about it.
You also need to realize that your competition might be exploring AI and its applications to improve operational efficiency, user/customer experience, productivity etc. The longer you wait, the harder it will be to catch up, especially because of all the learnings that they would have amassed. Suffice it to say that we’re in the third pragmatic camp when it comes to AI in ITSM.
Since you’re reading this guide, you’re probably past the decision of building vs buying AI, at least for ITSM. So we won’t go into how incredibly expensive it is to build AI capabilities in house.
That brings us to the next question – should I go for a traditional ITSM tool that recently added AI capabilities as an afterthought or a new-age one built from the ground up with AI capabilities?
In other words, “Should I and my team go for a tool with bolt-on AI capabilities or one with built-in AI?”
To truly understand the difference, imagine buying a phone just before the first iPhone was launched. Now imagine that you also bought a PDA (Personal Digital Assistant), a GPS navigation device, a digital camera, and an iPod a few weeks before they became obsolete.
Enterprise software saw a shift from on-premises to the cloud or SaaS. In 2024, SaaS products in general, and ITSM software vendors in particular, are at a similar crossroads. Apple, under Steve Jobs, was bold enough to cannibalize the iPod, among other products.
But most ITSM vendors will think long and hard before completely rewiring their product for a new way of doing things. This is especially true for modules that are currently being used by their customers and entrenched within hundreds of IT organizations.
Aside from the bolt-on vs built-in approach to AI, traditional ITSM tools are different from modern ones in a few different ways:
You’re likely using some product or service to manage your IT operations. Hopefully, you have a crystal clear understanding of:
If you don’t, before you make a list of potential ITSM tools and dive into their websites to understand their features and capabilities, start by getting a thorough understanding of the current state of things. This would include your processes, use cases, and other connected platforms in your tech stack.
Let’s unpack these:
What IT processes or practices do you currently use your ITSM solution for? How does information flow? What does the end-user experience look like? What happens after the ticket is raised?
Are there documented processes that work like clockwork or does it vary based on the user or IT professional in question? Are there workflows to automate ticket routing, approvals, assigning priority, etc?
Are 80% of the tickets about 20% of the issues? What are these issues? How are support agents – across IT, HR, Finance, etc. – handling these? Are there any tasks that they routinely follow?
Who will be using the new software as an admin/agent? What’s their current level of skill and which tools have they used previously? Is the permission and access to information clearly defined for each user depending on their business function, seniority level, geographical location, and other relevant conditions?
Are you a Microsoft ecosystem that uses Teams or a Google ecosystem that uses Slack? What other tools does your team use?
Look at your entire tech stack and see where your current ITSM platform fits in. Where does data flow in from? Where does the data flow out to? Which is the central system of records? Which is the customer or end-user database that you use? Where does your knowledge base live?
Do you use a different tool for asset discovery and management? Do you have an AI assistant or co-pilot that helps users with common queries?
Do these tools have a native integration with your current ITSM solution? Is the integration hacked together, or worse, requires intensive manual work?
Make another list of tools that are currently not integrated due to technical limitations but should have a seamless integration. Again, which integrations (from both lists) are must-haves and which you can live without?
All this will give you a baseline understanding of your goals and requirements with the new tool and what gaps you’re looking to close.
By the end of this exercise, you should have a list of must-have and nice-to-have capabilities. You would also have a better understanding of the budget that would make sense based on your requirements.
Let’s assume the platforms you’ve shortlisted check all the must-have (and quite a few nice-to-have) boxes for process enablement, use cases, and integration with important tools. Great start!
But your business will likely grow over time and so will the complexity of your IT infrastructure. The new tool you get needs to provide a lot more sophistication, so it can scale as you scale.
Let's look at some of the capabilities and features you need to look for in the ITSM solutions you evaluate, especially in 2024.
A GenAI chatbot or virtual assistant that learns from your knowledge base (across multiple sources) and synthesizes responses to user queries will soon become table stakes.
This seems to be the go-to feature for any ITSM platform that wants to market itself as “AI-powered”. But we would urge you to dig a little deeper and understand how deeply ingrained the assistant is within the platform.
A bolt-on GenAI assistant might provide a broken experience. In case it fails and the user needs to follow the ticket creation process from scratch, their patience (and trust) will start to wear out. After a few such experiences they might start bypassing the assistant and going back to sending emails or calling in when they need to contact IT support.
A couple of key questions to ask:
Your users use a tool for internal communication and collaboration, like Microsoft Teams and Slack. Contacting IT or HR support should be no different. And this is the perfect place for an AI assistant to live and provide L0 support. It also needs to make escalation easy without the need to repeat context.
Workflow automation should be a given for any ITSM platform you pick.
AI can make the system more intuitive. With the help of AI, ITSM software vendors will be able to go beyond manually built workflows that need precise conditions to be set in motion. It will understand natural language and infer from context.
It goes without saying that for workflows that can potentially cause disruption in other services, assets, or other areas of the business, there should always be a human in the loop. This can be included in the workflow as a request for approval or acknowledgement from the right stakeholder before the system executes the tasks.
End users might not necessarily know what services they want exactly and what services they might have access to. The assistant can help there as well.
For instance, let’s say someone wants to request for a laptop. The AI assistant can ask probing questions to help them pick the right one. This conversational experience of service request creation can be leveraged to drive efficiency and improve the user experience. And similar to incidents, it can be assigned to the right person. Whether the assistant lives on Slack or Teams, make sure approval requests are sent over the right platform.
Despite an AI assistant and automation, some tickets will still come through to the service desk. They need to be triaged and routed in a relevant manner.
AI can help here as well based on:
A solution where AI has been built in from the ground up would be able to intelligently assess each query or ticket and recognize whether it's an incident or a service request. If it’s an incident, AI can identify the impacted service, asset, and user context and route it to the right team and assign the right priority.
While the primary goal of incident management is to restore normal service operation as quickly as possible with minimal impact on the business, it sometimes requires you to use a temporary workaround.
Ensure that the platform has a provision for problem management, which aims to identify, document, and ultimately, resolve the root cause of repetitive incidents. AI can recognize whether other incidents have been reported with the same underlying problem and link them to a new/existing problem record.
Changes, of all kinds, need to be carried out in a systematic and orderly fashion. See to it that the platform comes with robust change management capabilities.
There are a few things that you should look for, like documenting the context behind the change (attaching relevant incidents, problems, and assets) and the change plan (including a rollback plan in the event something breaks). Look at how stakeholders and their mutual relationships are managed – assigning and tracking tasks and getting the change plan reviewed and approved by the CAB (Change Advisory Board).
A powerful AI system can assist during change creation. It can alert you of any additional assets that could potentially be impacted by the change or any other changes that this one might clash with, so you can reschedule or reprioritize them.
Whether your current ITSM tool has sophisticated asset management capabilities like asset discovery, tracking, MDM (Mobile Device Management) or integrates with a different platform you use, the new system should support it.
Look for a CMDB (Configuration Management Database) to maintain a centralized repository of all your software and hardware assets and effectively manage the asset lifecycle.
Oftentimes, reporting on IT metrics is a manual process and feels like paper pushing, involving a bunch of spreadsheets, “vlookups”, and SQL queries.
Ironically, the sheer amount of data makes it hard to do anything meaningful with it. Enter.. AI. With a smart system, you can ask a natural language question, like “What was the issue escalation rate last month?” or “Which of the L1 agents need to be trained on Employee Satisfaction?” and get actionable insights.
AI can also predict future issues based on trends that humans might miss. It can help you assess the assistant’s performance with accuracy reports, helping you improve it over time to adapt to your organization’s data, culture, and taxonomy.
Once you’ve made a list of potential platforms that measure up to your feature requirements, here are some additional things that would help you narrow it down.