Making future-proof organizations with smart operations analytics

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How can organizations reach operational efficiency on a daily basis?

Having spent many years in the domain of applications, infrastructure, and automation, if there is one thing that’s become crystal clear to me, it’s that IT Operations does not lack tools, metrics, alerts, or events. If anything, it has a deluge of data and has been a sorry victim of “monitoring everything.” So, how can we ensure that organizations can reach operational efficiency on a daily basis? Simply put, by leveraging “smart operations analytics.”

Powered by machine learning algorithms, smart operations analytics can evaluate in milliseconds what may take us days to decipher. This evolution of automation now makes it possible for IT operations to monitor and analyze everything in pretty much real-time.

From correlation to causation

In our daily practices, we often fail to identify the issues going on in production— sometimes because the issues have not surfaced yet or because we just miss information due to the extensive monitoring going on in production. From an ADM perspective, if we take a closer look at IT service management, and analyze a reported incident for it, we often find a lot of commonalities between the incidents. What we do next is identify certain trends between them and that’s exactly what we can achieve with operational analytics: if we feed these trends to Machine Learning (ML) once, we can automatically start detecting anomalies in a faster way and resolve the incidents even before they can take place. More importantly, it is based on all the historical data that our customers already have exhibited.

So, what does smart operations analytics give you?

  • More insights in your daily operations
  • More information about the correlation between issues
  • Detection of the root causes for individual issues and track the incidents that may happen
  • Identification of a possibly bigger root cause that lies underneath

Connecting the dots with Machine Learning

Gartner predicts that by 2022, 40 percent of all large enterprises will use machine learning to support monitoring, service desk, and automation processes. In Capgemini, we are already using a lot of these techniques, for instance, in the Public sector in the Netherlands. But what’s more interesting is the fact that we have a smart analytics solutions for every single market segment right now. The development, operational, and business teams can benefit from it at length; whether it is to achieve better technical excellence by resolving issues faster and keeping the systems more stable, or business that can achieve cost-optimization, leaving room and budget for further innovative optimizations to become future-ready.

The beauty of machine learning lies in the fact that it caters to all users; everybody can use it to optimize their own operational and business efficiency because they have access to their own data through one central access point, irrespective of whether the focus is SAP or custom software development. And, it is really easy to start with it: we get all the raw data and transform them into more structured information so that we get valuable and actionable insights to improve the development and operational teams and help the business in achieving their KPI’s.

Smart operations analytics to achieve smarter business impact

IT operations is a natural home for machine learning and data science. Automated analysis of the data created by IT systems is critical for detecting the clues as to why applications and systems misbehave. If you look at ADMnext, we have a lot of tools in there, and one of them is the Auto FMA (Automatic Failure Mode Analysis) tool which helps in structuring ticketing data and optimizing delivery. For example, if there are 200 tickets for password resetting, by clearly pinpointing the associated root causes of issues and correlating them to a specific error, operations managers can better maintain peak operational efficiency for their IT infrastructures, reduce the mean-time-to-resolution within support organizations, and provide end users with a near error-free experience.

In a nutshell, smart operations analytics and machine learning help ensuring:

  • Less unforeseen disrupted services
  • Guaranteed higher up times
  • Reduction in cost per ticket
  • Identification of the type of tickets on which the most amount of time is spent.

Discovering endless possibilities with ADMnext

Aligned to our mantra, at ADMnext, we make infinite possibilities happen. To provide a seamless experience to your customers, we offer applications that are compatible with new technologies and can drive meaningful digital transformation, bolstering our position as a strong strategic player in the market when it comes to innovation. By offering smart operations analytics, we help our clients in being more proactive in solving incidents than being reactive, reducing total cost of ownership, and making it easier for them. So, ADMnext is about optimizing your interaction with the end user and utilizing your applications more efficiently in order to transform your landscape and make it future-proof.

Are you ready to excel in the fundamentals of ADM? Do you want to expand your capabilities to be fully digitally ready and innovate like never before? On that note, you might also want to take a look at our latest PoV, ADMnext Power of Zero: an actionable framework for achieving business excellence through hyper-efficient core IT.

If you’d like to discuss more, please drop me a note, and I’ll be happy to help!

Author

Jaap van Arragon

Continuous Improvement Manager, Automation Lead, Capgemini Netherlands

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