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4 Questions to Help Decide if You Need Predictive Analytics

Sridhar Iyengar

The rise in digitization has contributed to the growth and complexity of unstructured data (text, audio, video and more). Users now access data more than ever before, making downtime more impactful to business. So IT teams need to be on guard and nip downtime issues in the bud before they culminate into a much bigger problem.

One efficient way to minimize downtime is to adopt IT operational analytics (ITOA) practices in your enterprise. By deploying ITOA, teams can constantly monitor IT systems to analyze and interpret data from various IT operational sources. This enables them to predict potential service downtime and reduce the mean time to repair (MTTR).

Predictive analytics is a popular ITOA technology that you can leverage to improve your business by leaps and bounds. Predictive analytics analyzes relationships among various data points to predict behavioral trends, growth opportunities and risks, which can add critical value to your business.

Here are a few questions to help you decide if predictive analytics is right for your business.

1. Do you need a better way to tackle application downtime?

By leveraging their data, predictive analytics allows businesses to prevent downtime. Predictive analytics uses adaptive algorithms to analyze existing historical data to observe past and current behavior from applications and networks. The goal of this analysis is to discover any potential problems before they develop.

If there is any deviation between the measured value and standard value, a notification is immediately sent to the IT admin, warning of a potential issue. This enables enterprises to take stock of those issues before they impact customers.

2. Are your customers really happy?

Enterprises often make the mistake of assuming their customers are satisfied. Reality, however, might tell a different story. Applying predictive techniques in your business processes will accurately assess if a customer is happy or disappointed with you and your services.

For instance, by analyzing emails, predictive analytics can illuminate areas related to customer satisfaction and suggest ways to engage customers better. Predictive analytics gives enterprises a competitive edge so they can choose better techniques to promote products and services that will win them more customers.

3. Is your data secure?

With security attacks rampant in the digital world (the WannaCry ransomware attack is a recent example), enterprises should take measures to safeguard their data from any breach. Due to the wide distribution of security attacks, it is rather challenging to estimate the volume and dollar value of the data loss. Leveraging predictive analytics will enable enterprises to identify possible vulnerabilities in their system to determine the probability of such attacks.

4. Are you managing your IT resources efficiently?

Predictive analytics can be used to monitor resource capacity and determine if it needs to be restocked. This will enable teams to make informed investments at the right time and avoid the dangers of running out of IT resources. This is critical as it allows enterprises to scale their infrastructure in accordance with their user growth.

Any enterprise that wishes to take better control of its IT operations — and predict the occurrence of unprecedented downtime — should consider investing in predictive analytics. Predictive analytics aligns an enterprise's technological goals with its business strategy and is in high demand. As predictive analytics takes off, the rising competition will prompt ITOA vendors to differentiate themselves by offering simpler and more affordable solutions, making predictive analytics available to everyone.

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4 Questions to Help Decide if You Need Predictive Analytics

Sridhar Iyengar

The rise in digitization has contributed to the growth and complexity of unstructured data (text, audio, video and more). Users now access data more than ever before, making downtime more impactful to business. So IT teams need to be on guard and nip downtime issues in the bud before they culminate into a much bigger problem.

One efficient way to minimize downtime is to adopt IT operational analytics (ITOA) practices in your enterprise. By deploying ITOA, teams can constantly monitor IT systems to analyze and interpret data from various IT operational sources. This enables them to predict potential service downtime and reduce the mean time to repair (MTTR).

Predictive analytics is a popular ITOA technology that you can leverage to improve your business by leaps and bounds. Predictive analytics analyzes relationships among various data points to predict behavioral trends, growth opportunities and risks, which can add critical value to your business.

Here are a few questions to help you decide if predictive analytics is right for your business.

1. Do you need a better way to tackle application downtime?

By leveraging their data, predictive analytics allows businesses to prevent downtime. Predictive analytics uses adaptive algorithms to analyze existing historical data to observe past and current behavior from applications and networks. The goal of this analysis is to discover any potential problems before they develop.

If there is any deviation between the measured value and standard value, a notification is immediately sent to the IT admin, warning of a potential issue. This enables enterprises to take stock of those issues before they impact customers.

2. Are your customers really happy?

Enterprises often make the mistake of assuming their customers are satisfied. Reality, however, might tell a different story. Applying predictive techniques in your business processes will accurately assess if a customer is happy or disappointed with you and your services.

For instance, by analyzing emails, predictive analytics can illuminate areas related to customer satisfaction and suggest ways to engage customers better. Predictive analytics gives enterprises a competitive edge so they can choose better techniques to promote products and services that will win them more customers.

3. Is your data secure?

With security attacks rampant in the digital world (the WannaCry ransomware attack is a recent example), enterprises should take measures to safeguard their data from any breach. Due to the wide distribution of security attacks, it is rather challenging to estimate the volume and dollar value of the data loss. Leveraging predictive analytics will enable enterprises to identify possible vulnerabilities in their system to determine the probability of such attacks.

4. Are you managing your IT resources efficiently?

Predictive analytics can be used to monitor resource capacity and determine if it needs to be restocked. This will enable teams to make informed investments at the right time and avoid the dangers of running out of IT resources. This is critical as it allows enterprises to scale their infrastructure in accordance with their user growth.

Any enterprise that wishes to take better control of its IT operations — and predict the occurrence of unprecedented downtime — should consider investing in predictive analytics. Predictive analytics aligns an enterprise's technological goals with its business strategy and is in high demand. As predictive analytics takes off, the rising competition will prompt ITOA vendors to differentiate themselves by offering simpler and more affordable solutions, making predictive analytics available to everyone.

APM

Hot Topics

The Latest

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...

Almost half (48%) of employees admit they resent their jobs but stay anyway, according to research from Ivanti ... This has obvious consequences across the business, but we're overlooking the massive impact of resenteeism and presenteeism on IT. For IT professionals tasked with managing the backbone of modern business operations, these numbers spell big trouble ...

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...