The latest release of Ayehu NG has some critical and advanced new features, most notably a new and improved self-service capability, that allows end users to fulfill service requests and even remediate incidents themselves.
Self-service is becoming a huge imperative for IT. Why is that?
According to Gartner, it’s very simple.
“Business consumers are comparing their enterprise IT self-service experience with their consumer experience, driven by companies like Google, Facebook, Yahoo, Amazon, Apple, eBay and UPS. I&O leaders should do the same.” (emphasis mine)
Source: Gartner ID G00340706 | Published October 4, 2017 | Refreshed September 24, 2020
In other words, the bar is being set by other companies that everyone, including your organization’s users, are interacting with every day. They’re seeing how well self-service works OUTSIDE your enterprise, and it’s driving their expectations of how well self-service should work INSIDE your enterprise.
When most people think about self-service in an enterprise environment, they increasingly think about chatbots as the delivery channel. I’m talking of course about chatbots like Teams, which as everyone knows is published by Microsoft, or Slack which is increasingly being more tightly integrated with Google.
Just to be clear though, Microsoft OWNS Teams, but Google DOES NOT own Slack. At least not yet, anyways.
So these two have emerged as the primary interfaces for a lot of enterprise self-service apps over the last few years.
The reason why Teams and Slack dominate this market is pretty obviuos – daily active users. Teams has 75 million and Slack has 12 million.
These are the most recent official numbers, but they’re from earlier this year. The current number of daily active users is almost certainly much higher.
Interestingly though, despite Teams having more than 6 times as many users as Slack, Slack actually has 28% more subscribing organizations than Teams – 640 thousand compared to 500 thousand.
Again, these are the most recent official numbers, and everyone is eagerly awaiting updates from both Microsoft and Slack to get a better idea of how they’re currently splitting market share.
Despite these huge usage numbers though, it turns out that chatbots as a self-service delivery channel are not for everybody. They’re definitely not a “one size fits all” solution.
There are a few specific reasons why.
One big reason is simply that user expectations aren’t being met. The chatbot may not have the conversational sophistication users are looking for, or it’s not providing the answer a user was hoping to get.
The reason for that might be a lack of training data. Many chatbots are driven by AI and machine learning, which require lots and lots of training data in order to begin displaying some intelligence. Depending on the use case being addressed, the chatbot may not have enough training data available for it to satisfy the machine learning requirements.
Of course, a lack of training data is really just part of the broader category of a lack of resources. Chatbots are not a one-and-done type of initiative. They need to be updated, fine-tuned, and generally maintained throughout their lifespan. However, a lot of organizations don’t have the resources for that, so a chatbot may not be for them.
Finally, there’s the ever-present issue of cost. Chatbots are not necessarily cheap to deploy, especially if you want to do it right with AI and automation, and that may put it out of budget range for many organizations, especially SMB’s.
If you’re an enterprise IT decision maker, what do you do?
You know you want self-service because it reduces costs. Also, many of your users are eager for a way to avoid submitting tickets to the help desk and then wait until they’re fulfilled. This is especially true if they’re part of a younger demographic, and already expect to be able to fulfill their own requests or even remediate their own incidents.
Yet at the same time, you feel chatbots are not right for your organization.
Ayehu NG can help, by providing a chatbot alternative through its automation platform.
We do that in this newest release, v1.8, by simply adding a little more functionality to enable creation of self-service forms that end users can interface with to fulfill their own requests or remediate their own incidents. The self-service form is actually a natural extension of what we already do, automate routine IT tasks, and it will allow you to deflect a large amount of ticket volume from your help desk.
In fact, when deployed, we’ve seen self-service significantly increase first contact resolution rates by as much as 65%!
What are some use cases you can apply this dynamic self-service capability to? There are too many to list, and in addition to the universal ones, there are probably quite a few use cases unique to your organization that would make great candidates for self-service.
However, thanks to Gartner, we can categorize just about all self-service use cases into one of 5 buckets:
- How-to: These are simply inquiries about how to accomplish, access, or operate IT resources.
- Password reset: There are estimates that this task alone can account for as much as 40% of a help desk’s ticket volume.
- Break/fix: If a user can’t access or operate an IT resource, give them the ability to fix it themselves.
- Service request: These can include things like asking for a new laptop or provisioning a VM.
- Requests for status updates: Responding to user requests for status updates on any of the above is probably one of the bigger annoyances for help desks. With self-service, a user can look that up themselves, and the help desk won’t need to be bothered.
One last thought.
Once you create a self-service channel for your end users, you often need to incentivize them to use it so it can fulfill all the lofty ROI projections that were used to justify deploying it.
The good news is, that’s relatively easy to do by simply ensuring that better outcomes are available to them via self-service as opposed to calling the help desk.
For example, let’s say a user wants to provision a VM.
Just institute a policy that if they provision it by requesting the help desk to do it, they’re only eligible to be allocated 8Gb RAM for their VM.
However, if they provision the VM via self-service, they can allocate themselves as much as 12Gb of RAM.
This is a simple, straightforward way of accelerating user adoption of self-service at your enterprise.
If you’re interested in test driving Ayehu NG and seeing for yourself how much value self-service can add to your environment, please visit our website and click here to download your very own free 30-day trial version today.