From project to product:

The path to new value creation

The shift from project-based to product-based delivery is not just structural; it is philosophical. Projects end; products evolve. Enterprises that once defined success in milestones now measure it in customer outcomes and business impact. Scaling that shift requires more than reorganizing teams; it demands a new operating rhythm and a unified way of defining, funding and measuring value.

To maximize the value of product-oriented delivery, organizations should adopt a model built on eight key elements. These elements serve as foundational pillars, each engaging different parts of the organization to drive a broad and sustainable transformation.

1. Value streams

2. Fit-for-purpose operating model

3. Clear objectives and key results (OKRs)

4. Integrated shared services
5. Delivery key performance indicators (KPIs)
6. Championing transformation

7. Streamlined tools

8. Exponential engineering

Each element is leveraged at different points within the transformation journey. An organization will start with value stream mapping to create a playbook that will define the transformation based on the organization’s nuances. Learn about each of the elements below.

Eight pillars for product operating model transformation

1. Define value streams

At the beginning of this journey it’s important to outline value streams, a process that defines distinct customer segments and maps their journeys to where and how the organization creates value. Value streams are a central part of the transformation from a siloed organization to one built around customer journeys or value streams.

Organizations could face a lack of true alignment with their customers, particularly in understanding who they are and what they value. Defining value streams around customer journeys does more than just improve business alignment; it forces architectural alignment across the organization.

Instead of building and operating in fragmented, siloed systems, teams begin to organize around end-to-end flows of value. This shift promotes integrated platforms, more reusable services and clearer ownership, making it easier to deliver cohesive, cross-functional solutions that meet customer needs.

2. Develop a fit-for-purpose operating model

Before you start executing the new way of working, it is important to build a foundational understanding of the operating model and the robust governance structure that enables it to scale across a product-driven organization. Packaging this up in a formal playbook helps describe the new way of working with details about the roles and responsibilities, team archetypes, work-item taxonomy, and any other topic that enables working within this transformation.

In this playbook, the organization can document the demand-intake funnel process and align strategic initiatives to showcase portfolio management and resource capacity management. This approach enables leadership to focus on initiatives that deliver the greatest value, fostering a disciplined environment where decision rights and ownership are clearly defined. It also allows the continued oversight, management and integration of waterfall-based projects or transformation programs that inevitably continue long after product delivery.

This can lead to a consistent value-based roadmap that guides IT resource allocation and business outcomes. Many organizations may already do this, but what they often miss is establishing a delivery rhythm—a consistent cadence that aligns with the identified increment and allows time to build toward maturity, predictability and team accountability.

3. Establish clear objectives and key results

The product strategy must be directly connected to the company’s vision, growth objectives and market positioning. This goal-setting methodology serves as a framework for defining the objectives and tracking them based on their key results to translate their outcomes into the intended value realized.

One of the powerful aspects of OKRs in scaling product operating models is their ability to cascade effectively through an organization. With business leaders, strategic objectives are defined with high-level key results that reflect business-critical, portfolio-based outcomes. These key results then serve as the foundation for the next layer—typically business units, product areas or domains—transforming into their specific objectives.

This cascading continues down to product pods, where key results from the layer above become the team’s objectives, contextualized with measurable outcomes relevant to their scope. In effect, the key results at one level become the objectives at the next, creating a clear line of sight between day-to-day team activities and overarching business goals.

This structure is a strategic enabler: It aligns the organization around common goals, drives sharper go-to-market execution, and strengthens customer satisfaction with timely, relevant solutions. Equally, it can boost financial performance by scaling successful products rapidly and cutting low-value initiatives before they consume resources.

4. Integrate shared services

Within an organization, shared services and platform enablers refer to centrally managed capabilities—such as security, infrastructure and data services—that provide foundational support to product teams. Though specialized and domain-specific, these services are critical in allowing teams to focus on delivering customer value without duplicating effort.

The shared services function acts as an enabler to coordinate with product teams and align on delivery needs. This is further highlighted through kanban-style workflows for the continued ability to pull work in to meet existing shared services priorities and support product pod requirements and dependencies based on roadmap needs.

Integrating shared services into the new way of working requires coordination among pods and a voice of leadership. By embedding shared services and platform enablers into the operating model, organizations realize faster speed to market, lower operational costs, and significantly improved experiences for product teams and pods.

5. Utilize delivery key performance indicators

Many organizations evaluate in some shape or form, but many miss out in building evaluation tools that are delivery performance-based. Delivery performance KPIs serve as essential tools to evaluate critical aspects of how an organization operates, offering visibility into both performance and organizational health.

Establishing clear product-level metrics that highlight operational efficiency and ROI while giving the transparency needed for data-driven capital allocation helps ensure every dollar advances strategic priorities. Delivery outcomes can be met through predictability by standardizing these metrics across teams and leveraging common tools through which organizations create a common language to assess productivity, plan capacity and align on delivery expectations.

This consistency enables more accurate forecasting, better resource allocation and faster course correction when needed. In the context of a product operating model, KPIs are foundational—not only for tracking progress and success at every level, but also for enhancing predictability, enabling teams to be equipped to meet outcomes, and driving continuous improvement at scale.

6. Champion the transformation

As organizations engage in a product-centric transformation, many stakeholder groups may not see a need to engage or actively champion the change that comes along with it. Many times, organizations leave business leaders out of the early stages and then struggle with securing their engagement and championing of the new way of working.

With a transformation of this scale, it’s essential to assess different stakeholder groups (e.g., business unit leaders, business relationship managers), understand their degree of change in their role and daily responsibilities, and provide a clear pathway to adapt to the change and increase their fluency in leading in this new way of working.

By understanding these factors, targeted resources can be designed to support stakeholders throughout this transition of change with tailored training, workshops and communication strategies specific to the needs and concerns of each stakeholder group. These steps should clearly articulate the drivers and benefits of the change, outline the transformation timeline, detail the anticipated impact on individual roles, and define the expected outcomes. Such a focused approach helps facilitate smoother adoption and maximizes the overall effectiveness of the transformation initiative.

7. Streamline tools

To successfully scale a product operating model, organizations need a centralized, top-down, aligned tool stack that supports and reinforces every layer of the model. As teams, products and portfolios expand, a fragmented tool landscape can lead to misalignment, siloed data and operational inefficiencies.

An integrated tool stack addresses this by creating a unified system of record—connecting priorities, roadmaps and dependencies across teams and enabling consistent workflows across the enterprise. This tool stack plays a foundational role in scaling by standardizing how work is planned, tracked and measured. It enables organization wide OKR alignment, demand intake and capacity planning, ensuring that strategic objectives are translated into executable work at every level.

As the number of pods and products grows, tooling helps ensure repeatability and coherence in how teams operate—driving a common language, shared metrics and traceable outcomes.

8. Embed exponential engineering

As organizations scale their product operating models, they often quickly encounter diminishing returns from traditional engineering delivery. Linear increases in development capacity no longer translate to proportional gains in innovation or speed. The potential result: rising technical debt, bottlenecks across the value chain, and productivity plateaus that erode the economic efficiency of the operating model itself.

To restore leverage, forward-leaning enterprises are embedding exponential engineering practices at the core of their operating models. This shift can reframe engineering from a cost center to a value multiplier—a system in which each additional unit of talent, technology or investment yields disproportionate returns in throughput, quality and adaptability. AI-assisted code generation, automated testing and rapid data analytics all save developers more time for innovation and feature development. The productivity gain from coding alone is estimated to be worth US$12 billion in the United States.¹

By integrating AI-enabled developer tools, digital co-pilots and intelligent automation into product team workflows, organizations create compounding productivity effects across their engineering ecosystems. These tools don’t just help accelerate delivery; they enhance the economics of reducing marginal cost per feature, shrinking cycle times and freeing human capacity for higher-order design and innovation.

This is not a tooling upgrade; it’s an economic rearchitecture. Technology leaders redesign team structures, funding models and platforms to enable automation at scale and eliminate value leakage across the software development life cycle (SDLC). The potential result is a self-reinforcing system where speed generates savings and savings fund innovation, sustaining the growth flywheel of the product operating model.

Bringing success to the forefront

Product models themselves don’t create value—the system that funds, governs and accelerates them does. The next generation of enterprises will likely distinguish themselves not by how agile they are, but by how intelligently and continuously they turn rhythm into return. Explore examples of the pillars in action—along with three key levers for success in our full report. 

Endnotes

1. Kelly Raskovich et al., “IT, amplified: AI elevates the reach (and remit) of the tech function,” Tech Trends 2025, Deloitte Insights, 2024, p. 38.