In 2019, all of the top five most valuable US businesses were tech companies. But what’s more transformative is that in this decade and the future, every company will be a tech company — irrespective of what you sell.
Take the case of Walmart, which is the largest brick-and-mortar retail company in the world. In the last few years, in order to compete with the e-commerce disruption, it has made some significant acquisitions in the space. Not just in the US, where it bought Jet.com — which was the biggest deal at the time — but also across the globe, with the acquisition of Flipkart.com in India, for instance. Fast forward to now, it is the second largest online retailer, even if by a distance.
As more and more companies undergo digital transformation, putting tech at the core of their businesses, their ability to succeed will come to depend on their IT backbone. So, IT Ops — the monitoring and management of organizational technology (typically other than software engineering) — will come under immense pressure.
IT Ops, as we know it today, will become insufficient, for various reasons.
Digital transformation initiatives has enabled unprecedented scale in technologies across the board — compute, storage, network, security etc. Along with scale, also came variety, of infrastructure and processes, creating complexity that outpaces traditional IT Ops.
As a result, traditional IT Ops can no longer:
Breaking a scaling business into smaller manageable business units is a logical move enterprises regularly make. While it is good for local optimization and closer oversight, it misses out on leveraging organizational knowledge and size.
As a result, IT Ops in a siloed organization will suffer from:
With fast-paced nature of IT projects and with new development paradigms like agile, IT Ops teams are constantly spinning many plates at once. Managing complexities, addressing various different departmental goals/metrices, putting out fires, meeting compliance standards, IT Ops will not be able to demonstrate ROI for the organization as a whole.
As a result, IT Ops will suffer. It will:
To overcome these challenges, IT Ops teams in many enterprises adopt automation. It works, in most cases. It makes them react faster to incidents; centralised dashboards in real-time for faster decision-making. But, in the long-run, localised automation for organizational issues is like treating a chronic illness with band-aid.
For true innovation at scale, IT Ops needs to break down siloes, measure outcomes effectively, and align themselves with business goals — IT Ops needs to become predictive and pre-emptive.
AIOps is the application of machine learning and data science to IT operations to make them more efficient. Gartner predicts that AIOps in large enterprises to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023.
An AIOps platform is a data layer for your IT Operations.
Firstly, it can intelligently automate monitoring at scale. An AIOps platform can separate the noise from the signals — filter out the real incidents that demand your attention.
It can integrate your siloes, even if not break them down. In that, you can continue to have your departments and verticals run as smaller units, yet be connected seamlessly through the centralized AIOps platform for efficiency and global optimization.
This improves governance, allowing you to have an organization-wide view of your IT. As a corollary, AIOps can improve measurability of key metrics and link back to business ROI. It can eliminate tool sprawl and optimize not just your applications, but also data usage.
In our opinion, the biggest advantage of adopting AIOps is that it changes the face of your IT operations from machine centric to customer centric. Instead of being an asset management function, AIOps can enable your IT to focus on your customers — be it internal like employees and vendors or external like your end-consumers.
With AIOps, your IT teams will build deeper relationships with your customers, pre-empt issues, and offer proactive service, having direct impact on your bottom line. Read our whitepaper to know more about how AIOps can impact each of these areas.
In fact, Nia AIOps helped a large European bank automate their L2 support, achieving 90% improvement in MTTR and equivalent reduction in IT operations effort. Click here to read the case study.