Sheldon Anthony IO

AIOps is a term that describes how IT operations can leverage machine learning (ML) and data science to solve complex and dynamic problems. AIOps platforms use big data and ML techniques to augment and automate various IT operations functions, such as monitoring availability and performance, analyzing and correlating events, and managing and optimizing IT services. AIOps platforms enable IT to handle the increasing diversity, speed, and scale of data generated by IT systems and present it in a meaningful way. According to the International Data Corporation (IDC), by 2026, 90% of Global 2000 CIOs will use AIOps solutions to drive automated remediation and workload placement decisions that include cost and performance metrics, improving resiliency and agility. ^[1] Today’s digital businesses face numerous challenges, but it is still providing opportunities in the fast-paced and competitive market. Customers expect seamless, personalized, and engaging experiences across multiple channels and devices.  To deliver on these expectations, businesses need to leverage the latest technologies and innovations to create value and differentiation.

IT Ops faces many challenges in keeping up with the demands of the modern business environment. A major challenge is the insufficient integration and coordination of various monitoring tools and methods. This forces IT Ops to switch between various tools and dashboards, which hinders their ability to detect and resolve issues quickly and effectively. Consequently, the time to repair increases, the service quality decreases, and the business suffers. To thrive in the digital era, organizations mustn't continue with unsustainable practices. Today’s companies are facing rapid changes, driven by changing customer expectations and fierce competition that they have never seen before.

Puma manufactures athletic and casual footwear, apparel, and accessories. Having 18071 employees around the world as of December 31, 2022 makes Puma the third-largest sportswear company. Due to PUMA's lack of insight into customer orders, it failed to provide a great online shopping experience and missed sales opportunities. With their previous systems, they were losing tens of thousands of dollars in sales every hour because they were not able to detect customer order problems on their 45 e-commerce sites. By hindering customers from making purchases, PUMA lost $108,000 in sales as a result of a nonresponsive inventory system. As part of each order, the system is queried to ensure stock is available. Revenue and goodwill earned by PUMA were lost when it failed. PUMA turned to Splunk for a solution. Using Splunk Cloud Platform and the AIOPS Monitoring solution from partner AIOPSGROUP, the company reduced the average time to detect issues from hours to minutes, and gained the insights it needed to fix problems and ensure a smooth buying experience for its online customers. They have decreased their average time to detect issues to 15 minutes with AIOPS and Splunk, compared to hours previously, 45 worldwide PUMA.com sites with now now benefit from enhanced monitoring and $10k+ per hour in boosted revenue.^[2] 

One of the main objectives of AIOps is to enable IT teams to deal with performance problems proactively, in real-time, before they affect the whole system. AIOps also gives IT teams the flexibility to identify and resolve issues faster, and eventually provide them with predictive insights to avoid issues from occurring in the first place. AIOps is a promising technology that can transform IT operations and deliver better business outcomes. However, AIOps is not a one-size-fits-all solution. Before utilizing AIOps, IT teams need to carefully evaluate their current challenges, objectives, and capabilities. They also need to ensure that they have the correct data quality, governance, and security measures in place to support AIOps. Furthermore, they need to foster a culture of continuous learning and improvement to leverage the full potential of AIOps in their organization.

Market leaders usually start small and are deploying an AIOps platform across their entire IT operations and replacing existing tools in one go, they identify specific areas of work where they can use the platform to achieve an end-to-end process. This allows their technology department to quickly show results that motivate others to use the platform while minimizing the risks. IT teams need to carefully evaluate their current challenges, goals, and capabilities before adopting AIOps. Disrupting a critical business function. A good starting point for a pilot project is to examine the physical arrangement and connections of a specific business service. Such pilots involve both the IT organization and the business stakeholders, working closely together on the implementation to maintain the trust that the IT organization has earned from the business. To avoid falling behind and meet business needs, IT organizations can benefit from AIOps. However, it's important not to solely focus on technology. Look beyond the IT department and see how you can leverage your existing data and analytics resources to create a more intelligent, proactive, and resilient IT operation. AIOps platforms can be expensive and complex products, but you don’t have to break the bank or your brain to explore AIOps and data science applications and use. Many open-source and low-cost ML software options can help you evaluate the potential and benefits of AIOps. To sum up, AIOps is a game-changer for IT operations and business performance. But it’s not a magic bullet that works overnight. It takes strategic vision, teamwork, and trial and error to find the optimal ways to apply AIOps to your specific challenges and goals.