A Gartner study poses that, “By 2019, IT service desks utilising machine learning enhanced technologies will free up to 30% of support capacity.”

In addition, the features that machine learning introduce will also add a tier of intelligent automation to traditional IT service desks. This will aid decision-making, enhancing staff productivity and opening up a level of smarter self-service for the end user.

The faster networks become, the more data is consumed and generated. In today’s digital world, with its fast networks and constantly evolving technology, information is being accumulated at a rapid pace. This poses challenges for IT Service Management (ITSM) teams, who are inundated with enormous data streams, often too large to process manually. However, the application of Machine Learning to sift, sort, analyse and manage Big Data could help to simplify the tasks of ITSM.

The three V’s

Traditional ITSM departments are under constant pressure, dealing with the three “Vs” of Big Data, Volume, Variety and Velocity.

Volumes: ITSM receives massive volumes of data, compounded by the surge of data from the Internet of Things (IoT) daily, making effective sorting virtually impossible.

Variety: of data grows ever more complex, as so much data is generated from so many devices and in so many ways.

Velocity: of data means that it arrives so fast, it must be processed immediately or it is lost.

For ITSM teams, there is valuable information to be had from Big Data; information that once tapped into, improves operations and service delivery.

The other two V’s?

There are two other “V’s” of Big Data, lesser known although no less important, are:

Veracity: the accuracy and integrity of data. Where the true value and meaning lies – but also the biggest challenge. Being able to extract the meaningful data from the unprocessed bulk of it is increasingly difficult to achieve. This is where Machine Learning proves itself as invaluable.

Validity: gives relevance to the data and works together with Veracity. The importance lies in the applicability of the data to reach the desired outcome.

Though accuracy is imperative, organisations should still consider the ‘age’ of the data being used, as Machine Learning depends on the latest information provided.


Imagine if an agent had immediate, real-time access to a customer’s information and solutions and was able to, at the click of a button, effectively addressing the demand or need of the customer.

That is the power of data combined with machine learning capability; the ability to assist customers in real-time.

Machine Learning is an effective tool, enabling support IT staff to understand ‘patterns’ from the past and make predictions for the future from the large amounts of accumulated data. Traditionally, ITSM already makes use of intelligent computing, which collects an abundance of data. Machine Learning, when properly applied, automates the process of sorting through the data, identifying patterns and applying them to provide possible solutions to common issues.

In an age where customer experience is a critical component of a business, the ability to answer requests with more accuracy, speed and precision becomes a differentiator.

Machine Learning also enables a ‘self-service’ functionality that customers are able to leverage to resolve common issues. The automated process should relieve some of the pressure that ITSM departments feel – freeing up their time to focus on the more complex requirements.

The real-time predictive analytics and automation offered by Machine Learning further adds to the basket of potential, by helping to support ITSM staff in their engagements with customers.

Machine Learning marries knowledge management with an organisation’s capacity to provide the right knowledge, at the right time, to the right people – enabling ITSM to operate quickly, smoothly and accurately, while providing customers with an enjoyable experience.

Unfortunately, even though machine learning allows for many opportunities within the business, most organisations believe that it is costly.

When it comes to the numbers, the cost implications of Machine Learning when weighed against the benefits, are easily negated. Faster service provision with fewer errors means fewer returns to fix the same problems, and the ability to simultaneously handle multiple queries with more accuracy. In the long run, any investment in Machine Learning to back up your ITSM will quickly be made up in gained time and happy customers.

Ultimately, ITSM is all about the quality of service provision that enables customers – and ITSM teams – to operate faster, better and cheaper. Applying Machine Learning and Big Data principles to ITSM, with the backing of ITIL frameworks, will go a long way to helping companies to achieve this.

Edward Carbutt | Executive Director | Marval Africa | edward@marvalsa.netwww.marvalsa.net/MarvalSA/ |





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