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Most Companies Unable to Achieve Project-to-Product Transformation

Many companies are unable to complete transformational work due to immature operating models and management systems, according to the 2023 Project to Product State of the Industry Report from Planview.

The report found that only 8% of organizations have successfully operationalized their project to product transformation. The low success rate contradicts the previously optimistic outlook from a 2018 report claiming that 85% of executives said they had either adopted or had plans to adopt a product-centric model, motivated by a desire to improve speed to market and agility and to support the move to digital business. Five years later, the report's data underscores the complexity of this multi-year process and its required buy-in and commitment across all levels of the organization.

"In boardrooms across the globe, executives are being mandated to prioritize technology investments that ensure their companies transform and emerge from the current downturn stronger. While some enterprise initiatives are managed as projects, a product-based operating model holds the key to increased efficiency, better customer outcomes, and profitable growth for digital portfolios," said Dr. Mik Kersten, CTO, Planview and author of Project to Product: How to Survive and Thrive in the Age of Digital Disruption with the Flow Framework. "The consequences of slow delivery and technical debt can be seen in very public profit losses and system-wide malfunctions. While there are no shortcuts, there is a roadmap of best practices that accelerates the transition, which the report outlines."

The report reveals that five years into the shift from project to product:

■ 92% of businesses do not have the foundation for a product-oriented model, causing their digital transformation efforts to fail.

■ Business leaders believe their IT and software development teams, in charge of transformation efforts, can deliver 10x more than their actual capacity, leading to team burnout.

■ 40% of digital innovation work from IT and engineering teams are wasted due to shifting priorities at the C-level.

■ Only 8% of what's planned by IT and software development teams gets delivered, inefficiency that can no longer be ignored given today's cost and performance pressures.

Given the criticality of this shift for the future success of traditional companies versus early adopters, the report outlines the critical steps needed to accelerate this transition: a partnership between executives and senior product and development leadership to do the following:

1. Benchmark their progress versus their competitors.

2. Understand and implement best practices to shorten the time it takes to capture the ROI of transformation efforts.

3. Identify the organizational attributes that increase the likelihood of operationalizing the product model by learning which efforts to prioritize.

Methodology: The report combines survey data from 326 respondents with systems data from 3,600+ software development value streams in 34 of the world's leading enterprises

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Most Companies Unable to Achieve Project-to-Product Transformation

Many companies are unable to complete transformational work due to immature operating models and management systems, according to the 2023 Project to Product State of the Industry Report from Planview.

The report found that only 8% of organizations have successfully operationalized their project to product transformation. The low success rate contradicts the previously optimistic outlook from a 2018 report claiming that 85% of executives said they had either adopted or had plans to adopt a product-centric model, motivated by a desire to improve speed to market and agility and to support the move to digital business. Five years later, the report's data underscores the complexity of this multi-year process and its required buy-in and commitment across all levels of the organization.

"In boardrooms across the globe, executives are being mandated to prioritize technology investments that ensure their companies transform and emerge from the current downturn stronger. While some enterprise initiatives are managed as projects, a product-based operating model holds the key to increased efficiency, better customer outcomes, and profitable growth for digital portfolios," said Dr. Mik Kersten, CTO, Planview and author of Project to Product: How to Survive and Thrive in the Age of Digital Disruption with the Flow Framework. "The consequences of slow delivery and technical debt can be seen in very public profit losses and system-wide malfunctions. While there are no shortcuts, there is a roadmap of best practices that accelerates the transition, which the report outlines."

The report reveals that five years into the shift from project to product:

■ 92% of businesses do not have the foundation for a product-oriented model, causing their digital transformation efforts to fail.

■ Business leaders believe their IT and software development teams, in charge of transformation efforts, can deliver 10x more than their actual capacity, leading to team burnout.

■ 40% of digital innovation work from IT and engineering teams are wasted due to shifting priorities at the C-level.

■ Only 8% of what's planned by IT and software development teams gets delivered, inefficiency that can no longer be ignored given today's cost and performance pressures.

Given the criticality of this shift for the future success of traditional companies versus early adopters, the report outlines the critical steps needed to accelerate this transition: a partnership between executives and senior product and development leadership to do the following:

1. Benchmark their progress versus their competitors.

2. Understand and implement best practices to shorten the time it takes to capture the ROI of transformation efforts.

3. Identify the organizational attributes that increase the likelihood of operationalizing the product model by learning which efforts to prioritize.

Methodology: The report combines survey data from 326 respondents with systems data from 3,600+ software development value streams in 34 of the world's leading enterprises

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For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...