• Digital Transformation

Knocking Down the Barriers to AIOps Success

By: Renée Lahti |
Chief Information Officer

Businesses are going through an unprecedented digital transformation driven by the arrival and maturation of a slew of new technologies. Take cloud as an example. Once hesitant to expand beyond their four walls, companies are now shifting to hybrid and multiple cloud environments, and deploying new native cloud technologies at an unprecedented clip—according to Cloud Native Computing Foundation, the use of cloud native technologies in production has grown by over 200 percent since December 2017.

You heard me right, more than 200 percent growth in less than one year. One of the byproducts of this is explosive growth in new connected devices, which are generating 2.5 quintillion bytes of data every day.

That’s a lot to digest so I’ll give you a moment.

Now close your eyes and imagine the new levels of complexity that businesses face. You can just see the data coming from all directions. Now imagine trying to glean valuable, actionable insights from each piece as it passes by.

One solution is Artificial Intelligence Operations, better known as AIOps. Hitachi Vantara’s Chief Solutions and Services Officer Bobby Soni recently wrote an article titled “AIOps: Make Peace, Not War Rooms.” If you haven’t read it, I encourage you to do so.

The more I get into AIOps, the more excited I get about the possibilities. The hardest part is knowing where to begin and then fighting the urge to plug AI into the entire organization. My advice is to stop right there! While AIOps can have a business-wide impact, it cannot be rolled out company-wide right out of the gate. It’s at this point that businesses should pause and consider the opportunity.

First, there is no standard AI business model that we can all follow when it comes to these solutions. Second, you need to get the organization to buy into AI and then, once you do, you need to prove its value.

So where do you start?

Come up with a plan, which begins by taking a deep look at your infrastructure and the data that’s being generated. This is where your team is critical. No one in your organization knows this data better than your employees who see it and touch it every day. Your data scientists, programmers and other technologists can identify critical patterns and pinpoint where AI can have the biggest impact. For one business it could be customer service, another the sales organization, etc.

Next, figure out areas where it could have the quickest impact and come up with a strategy around development of these solutions. As you move ahead, don’t be afraid of trial and error. This is an agile process and unforeseen things will occur. The key is that your sprints continues, you declare failures (and learn) and ultimately your efforts end with a win.

I recently went through this process right here at Hitachi Vantara. Part of my job is focused on modernizing our core IT infrastructure and supporting Hitachi Vantara’s digital transformation. We recognized an opportunity to deliver innovation at AskIT, our IT Service Desk, and free up employees to focus more of their time and energies on other complex challenges that meet the needs of our customers. Our answer was a new chatbot named, Anah.

Anah stands for Autonomous aNd Astute Helper and she’s the newest member or our IT organization. Anah provides automated and intelligent written responses to the most commonly asked questions received by AskIT. She does this by using Pentaho for feedback collection and data analysis to improve her skills over time, minute-by-minute. The more employees interact with Anah, the smarter she gets.

Now, thanks to Anah, our service desk technicians can focus on tackling more complex queries and problems, saving both time and cost while improving AskIT’s service quality and, as I mentioned above, keeping their focus on our customers.

This new chatbot demonstrates how new innovations such as AI can turn data into actionable insights. We see immediate impact and continuous improvement on the business by increasing the efficiency of the service desk. At the same time, we’re enhancing the customer experience by being more proactive, predictive and responsive to their issues and questions.

It is also a great example of how these new innovations need to be introduced to a business. By identifying a pain point, bringing teams together, and implementing an agile quick-win approach, we came up with Anah that is now paving the way for other projects to come.

2 thoughts on “Knocking Down the Barriers to AIOps Success”

  1. Good progress with Anah! I would imagine that Anah will be able to create service tickets automatically, reset passwords, setup new accounts with work flow, and support shift left with incident resolution. The goal will be to eliminate waste which equates to service desk tickets in the first place. Very exciting times. Thx

  2. Renée , I agree with specifics documented in this blog. Today the AI craze has gotten most companies to plug AI into the entire organization without getting adoption and buy in or defining the projected value before implementation. These unplanned blanket implementations without the required evaluation of critical patterns is what aids to barriers against AI success. As your blog called out, a continuous focus on the customer and the introduction of new innovations that solve for existing pain points, we help us continue on the Hitachi Vantara winning journey.

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