AIOps tools and solutions are rapidly being adopted by enterprises across the world.

Here are 9 KPIs that can help you measure the effectiveness and impact of AIOps solutions in your company

Manage the organization’s IT infrastructure with artificial intelligence.

It increases visibility, maximizes agent productivity, enhances IT performance, and much more.

Supply chain management is a complex medley of processes in which even a slight lack of visibility or synchronization can lead to enormous losses and overheads.

But with the recent developments in AI & machine learning, we can now harness historic and real-time supply chain data to discover patterns that help us understand what factors influence the different aspects of the supply chain network.These insights help companies in getting a competitive edge, streamline processes, cutting down on costs and increasing profits, and leveraging recommendations to enhance the customer experience.

According to Gartner, at least 50% of global companies would be using AI-related transformational technologies such as Machine Learning in supply chain operations by 2023.5 Ways In Which ML Acts As A Game Changer In Supply Chain Management 1.

With big data analytics, manufacturers can analyze different types of data including past sales demand, chanel performance, product returns, POS data, promotions data etc.

Unexpected and extended downtimes can result in out of stock situations and lost revenue.In order to avoid these situations, companies are replacing the reactive and inefficient break-fix service model with proactive maintenance approaches – predictive and preventive maintenance.This involves using machine learning to analyze data from smart parts and sensors and predicting when a machine/part will fail and determining the right time for repairs and  replacements.This allows companies to reduce excess inventory, mitigate the costs and disruption caused due to unscheduled downtime and ultimately improve customer satisfaction and brand loyalty.In addition, machine learning can also help understand how to extend the life of the existing assets, determine common reasons for failure and take necessary proactive steps.3.

Logistics Last mile logistics in supply chain management is prone to operational inefficiencies and costs upto 28 percent of the total cost of the delivery.Some common challenges in this area include:Not able to find a parking spot for large delivery trucks near the customer’s destination and having to carry the package to its destination by walkCustomers not being at home to sign the receipt of items and thus causing a delay in deliveryDamages to the package during this last leg of deliveryIn most cases, it’s very difficult for companies to identify exactly what’s going on during this last mile.

In today’s dynamic and highly componentized IT landscape, predictive analytics offers the much-needed ability to proactively predict future outages and automate fixes before they bring down the entire infrastructure.Owing to the rapid digitization of business operations, IT teams need to constantly monitor and analyze large volumes of data, resulting in extended delays in identifying and solving issues.

On top of that, a single IT issue can trigger thousands of alerts, logs, and events, and with the ITOps team working in disconnected silos, it becomes extremely difficult to diagnose the root cause and solve issues.Predictive analytics, powered by big data, artificial intelligence (AI), and machine learning, overcomes these obstacles to improve application performance, network uptime, and IT infrastructure resiliency by predicting and mitigating outages, and reducing maintenance and operations expenditure in the process.Gartner predicts that the number of large enterprises that use artificial intelligence in IT operations to combine big data and machine learning functionality to enhance or optimize IT operations and automate processes and tasks to grow by 40% by 2023.Let’s understand how predictive analytics is transforming ITOps.Predictive Analytics: An Evolution In IT Today’s IT operations monitoring and management systems leverage predictive analytics for collecting and integrating data, normalizing it, and analyzing it in real-time.Machine learning algorithms analyze past incident data to predict and resolve potential incidents in the future.Here are some ways in which predictive analytics is transforming IT operations.1.

Dynamic Thresholding And Anomaly Detection An anomaly detection algorithm uses unsupervised machine learning to get familiar with the IT environment, recognize expected behavior, and set dynamic thresholds against vital performance metrics.Consequently, event patterns are analyzed in real-time and compared against expected behavior, and the IT team is alerted when a series of events showcase anomalous activity.Moreover, fuelled by artificial intelligence, the system also accounts for false alert suppression and seasonality, i.e.

For example, a 90% system utilization is normal during peak business hours, but indicates an issue when the same metric is hit on a Sunday morning.Anomalous group of events are helpful in –Alerting the team regarding an unplanned activity, for example a cyber attackMaking IT operations more agile by improving planning for significant events, for example, Amazon increasing capacity to ensure infrastructure and applications perform well during the ‘Big Billion Sale’.2.

Predictive Maintenance Of Application Health In Real-Time Performing application health monitoring in real-time allows ITOps teams to respond to a degradation in application health before operations come to a standstill.Available data generated by the application, including configuration data, network logs, application logs, performance logs, and error logs, is compiled.

Multivariate machine learning techniques analyze this data, across different dimensions, to learn the application’s normal behavior.As new data enters the application, the model identifies unusual patterns and sends it to the IT personnel to follow up before a business-critical outage takes place.3.

Hence, CIOs must invest strategically in IT to survive the tough times and build a resilient, future-proof workplace for the times to come.CIOs need to approach cost-cutting in a manner that has a minimum adverse impact on the business’ medium-term and long-term health.

While introducing cost reduction measures within the organization, CIOs must focus on three aspects –Understanding the full range of potential options for reducing costsTaking cognizance of the built-in flexibility in IT spendingFocusing on the present while preparing for a new normal in the post-COVID worldSuch measures can ensure business continuity and help CIOs redirect funds into investments to accommodate new business priorities.Here are the three ways we are helping CIOs reduce IT operations costs by 30% in 2021.How Can CIOs Reduce IT Operations Cost By 30% In 2021?

Azure Cost Optimization Cloud cost optimization has become a top-rated priority for CIOs, particularly in the COVID-19 pandemic.

As more organizations move their resources to the cloud to reap benefits such as increased flexibility and unparalleled scalability, CIOs mustn’t lose sight of the associated costs.

CIOs must ensure costs do not spiral beyond the budget to maximize ROI, reduce the total cost of ownership (TCO), and leverage cloud services in the best possible manner.As a Microsoft Gold Partner, we at Acuvate offer an AI-driven Azure Cost Optimization (ACO) solution designed to help CIOs better optimize their Azure spending, increase predictability, monitor usage, and detect anomalies related to costs.

The best ways to optimize these costs include – (i) identifying unused resources, (ii) finding the right resource size, (iii) consolidating idle resources, and a host of other measures.ACO delivers the most actionable optimization recommendations, with key features that include –AI-enabled cost anomaly detectionProactive cost optimizationData insights on forecast and budgetService analysis and provisioningRobot to take action on recommendationsGovernance, admin control, security, and complianceOur ACO solution includes interactive dashboards that help CIOs gain faster insight into key metrics, including anomalies, potential cost savings, idle resources, etc.2.