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Operational resilience starts with making the right decisions at the right time.

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For businesses today, decisions often need to be made in seconds—but the consequences can last for years. Picture a major retailer’s e-commerce site buckling under Black Friday traffic or a cybersecurity team racing to contain an active breach. In both cases, success—or failure—hinges both on having the right data available to make good decisions, but also on how quickly and confidently the right decisions can be made with it.

Businesses are swimming in data. Logs, metrics, events, telemetry—it’s everywhere. But as any security or IT leader will tell you, more data doesn’t automatically mean better decisions. In fact, too much noise often leads to paralysis. That’s why the organizations that thrive are those who’ve cracked the code on transforming raw data into clear, contextual, and actionable intelligence.

And increasingly, vendors are shifting to meet that need.

The Data Paradox

IT ecosystems are complex, and they can be ticking time bombs if not properly monitored and managed. When something goes wrong—whether it’s a service degradation or a cyber intrusion—the clock is unforgiving. You need to know what’s happening, why it’s happening and what to do next, ideally all within minutes.

The paradox is that while organizations now have unprecedented visibility into their environments, they’re still failing to act quickly and effectively. Why? Because the data is fragmented. Observability lives in one dashboard. Security alerts come from another. Service tickets are buried in a separate ITSM queue. The result is a scattered picture of what’s actually going on.

To put it plainly: visibility without actionability is useless.

SolarWinds Doubles Down on Operational Resilience

That’s the reality driving the latest announcement from SolarWinds. The company unveiled a sweeping set of enhancements designed to unify observability, incident response, service management and AI-powered automation into a single operational fabric. The goal: empower IT and security teams to navigate hybrid environments, resolve issues faster and maintain business continuity in the face of mounting complexity.

“One of the biggest concerns we hear from customers is how to stay resilient amid rapid technological advancements and economic pressures,” said Cullen Childress, chief product officer at SolarWinds in a press release. “Every new wave of change—from digital transformation to generative AI—feels like a storm threatening their business.”

I spoke with SolarWinds CEO Sudhakar Ramakrishna about the challenges organizations face and how this announcement will help customers tackle them. He explained that the company’s strategy is rooted in delivering best time to value. “It’s no longer enough to simply collect and display data. Organizations need a connected system that delivers meaningful insights and enables action in real time,” he explained. “That’s the foundation of operational resilience—and, increasingly, cyber resilience as well.”

Cybersecurity Is a Business Decision Engine

At the core of this update is the integration of Squadcast, which brings AI-powered alert isolation, on-call management, runbook automation and real-time collaboration through tools like Microsoft Teams and Slack. Ramakrishna noted how this supports a proactive, structured approach to incident response—minimizing downtime and speeding up recovery.

Cybersecurity is often framed in technical terms, but it’s fundamentally a business decision engine. A delayed response to a breach isn’t just a security issue—it’s a risk to revenue, customer trust and brand equity.

The latest SolarWinds enhancements aim to shorten that response window by turning telemetry into decisions. “We’re focused on giving teams back the most valuable resource of all: time,” said Ramakrishna. “Whether it’s keeping services online during a surge or mitigating a threat, the ability to act with clarity and speed changes the game.”

Secure by Design, Resilient by Default

These innovations build on the company’s Secure by Design initiative, which was implemented in response to the now infamous 2020 supply chain attack and now includes practices like ephemeral development environments, triple-build code verification and software bill of materials transparency.

“We are now known for what we have become much more so than what has happened to us,” shared Ramakrishna, who took the reins of the company in the wake of that incident. “There is a constant security consciousness that exists across the organization—and expediency never takes precedence over security.”

Lessons for Security and IT Leaders

According to Ramakrishna, the move toward integrated, AI-driven platforms sends a clear message: speed, not size, is the new metric for resilience.

A few takeaways for IT and security leaders:

• Interrogate your telemetry: Are you just collecting data, or turning it into outcomes?
• Tear down the silos: Security, operations and support teams must speak the same language.
• Invest in AI, not hype: Use AI to reduce noise, not add more dashboards.
• Think beyond automation: Use AI to drive smarter, faster human decision-making.

Clarity at the Speed of Threat

Eevery second counts in business. Cyber threats evolve by the minute—or sometimes even second—and organizations cannot afford to operate in fragmented, reactive silos. The winners will be those who unify their data, automate intelligently and empower their teams to act—not just see.

As organizations strive to turn complexity into clarity, one truth is becoming inescapable: the future of resilience belongs to those who can turn insight into action before the damage is done.

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Are AI Product Managers The Role Of The Future?

Key Areas Of Proficiency Are Required For The AI Product Manager

AI product managers will need to demonstrate an understanding of AI and machine learning technologies and how AI models are trained, tested, and implemented. They will also need to have data science skills, understand AI model performance, and have knowledge of regulatory, ethics, and bias understanding.

Key Areas Of Proficiency:

• AI-specific technical competence
• Data science skills
• AI model performance
• Regulatory, ethics, and bias understanding
• Education, evangelization, and influence management

Every Product Manager Will Be An AI Product Manager, So Start Learning Today

Just as the "internet product manager" evolved to become a component of today’s standard product management practice, Forrester predicts that AI will also become part of the standard product manager’s role in the future. Generalist PMs will need a baseline understanding of AI so they can thoughtfully integrate AI capabilities into existing products and continually improve those capabilities based on technology changes and customer feedback.

Product Leaders Must Support Their Teams’ AI/ML Learning

Product management leaders must take a strategic approach to upskilling their teams about AI and ML by fostering a culture of learning and providing hands-on experiences. A good start is providing AI literacy courses, hands-on learning opportunities, and online interactive options.

Conclusion

As AI becomes a crucial part of the standard product manager’s role, it is essential for product leaders to support their teams’ AI/ML learning. By fostering a culture of learning and providing hands-on experiences, product leaders can ensure their teams are equipped to handle the challenges of AI product management.

FAQs

• What skills do AI product managers need?
  • AI-specific technical competence, data science skills, AI model performance, regulatory, ethics, and bias understanding, and education, evangelization, and influence management.
• Why will every product manager be an AI product manager?
  • AI will become part of the standard product manager’s role in the future, and generalist PMs will need a baseline understanding of AI to thoughtfully integrate AI capabilities into existing products.
• How can product leaders support their teams’ AI/ML learning?
  • By providing AI literacy courses, hands-on learning opportunities, and online interactive options, and by fostering a culture of learning and providing hands-on experiences.

Are you looking to unlock the full potential of your business? In today’s fast-paced digital landscape, data and analytics are no longer optional, but a crucial part of any digital transformation strategy. With the right tools and expertise, you can gain valuable insights, make data-driven decisions, and stay ahead of the competition.

The Importance of Data and Analytics in Digital Transformation

Data and analytics are no longer just about crunching numbers and generating reports. They are now a key driver of business success, helping organizations to optimize operations, improve decision-making, and stay competitive in a rapidly changing world.

Why Data and Analytics Matter

Data and analytics help organizations to:

• Gain insights into customer behavior and preferences

• Identify areas for improvement and optimize operations

• Make data-driven decisions, rather than relying on intuition or anecdotal evidence

• Stay ahead of the competition by being more agile and responsive to changing market conditions

The Challenges of Data and Analytics

While the benefits of data and analytics are clear, many organizations struggle to implement effective solutions. This can be due to a range of factors, including:

• Limited resources, including budget and personnel

• Complexity and technical difficulties in implementing and maintaining data analytics solutions

• Lack of expertise and knowledge in data analysis and interpretation

• Resistance to change and cultural barriers to adopting new technologies and processes

Overcoming the Challenges of Data and Analytics

While the challenges of data and analytics are real, there are many ways to overcome them. This can include:

• Seeking expert guidance and support to help implement and maintain data analytics solutions

• Investing in employee training and development to build in-house expertise

• Starting small and gradually building up capabilities and expertise

• Building a strong business case and demonstrating the value of data and analytics to stakeholders

Conclusion

Data and analytics are no longer optional, but a crucial part of any digital transformation strategy. By gaining insights into customer behavior, identifying areas for improvement, and making data-driven decisions, organizations can stay ahead of the competition and achieve their goals.

FAQs

Q: What is the difference between data and analytics?

A: Data refers to the raw information, while analytics refer to the process of analyzing and interpreting that data to gain insights and make informed decisions.

Q: Why is data and analytics important for businesses?

A: Data and analytics are important for businesses because they help organizations to gain insights into customer behavior, identify areas for improvement, and make data-driven decisions.

Q: What are some common challenges that businesses face when implementing data and analytics solutions?

A: Some common challenges that businesses face when implementing data and analytics solutions include limited resources, complexity and technical difficulties, lack of expertise and knowledge, and resistance to change and cultural barriers.