SOFTWARE PRODUCT ENGINEERING
Commit with confidence. Prove what it returned.
Planview is the platform for software delivery execution and outcomes. It sits above your delivery toolchain, bringing strategy, capacity, flow, and outcomes into one connected model. So technology leaders can commit to what engineering can hit, surface risk before it cascades, and connect what engineering ships to the outcomes it was meant to drive.
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Software product engineering has a translation problem
Engineering delivers. Sprints close, releases ship, deployments land. What those deliveries moved for the business is the part that stays invisible, rarely translating into terms the board can see. As AI and agent investment accelerates, that gap only widens.
The Planview Platform was built to fix this. It sits above the toolchain where the work happens, surfacing the capacity constraints and cross-team dependencies where delivery breaks down. It connects every engineering investment to the outcome it was funded to produce.
Commit with confidence. Surface risk early. Prove the value, not just the output.
Erfolgsgeschichten
How three engineering leaders connected delivery to outcomes
32% revenue growth
Huntington National Bank shifted from a project-based model to a product and value stream-centric approach powered by Planview, reducing idea-to-delivery cycles from two years to monthly releases.
„Wir mussten neue Funktionen schneller und effizienter bereitstellen, um uns auf dem Markt besser behaupten zu können. Dank Planview waren wir dazu in der Lage.“
SVP, IT Transformation & Delivery Director, Huntington National Bank
Read Customer Story
Six signs you have a translation problem
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1
The CFO asks what engineering’s work returned this quarter, and the answer is hard to assemble.
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2
AI and agent investment is growing, but its contribution to business outcomes is hard to demonstrate.
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3
Jira, ADO, and GitHub each hold a piece of the delivery picture, but the pieces don’t reconcile into one view leaders can rely on.
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4
Teams commit to dates with full confidence. The dependencies that will break those dates surface too late to fix without multiplying the cost.
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5
The investment case for the next engineering cycle is harder to defend because the ROI from the previous one was left unclosed.
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6
The roadmap review takes longer than the market shifts it is meant to respond to.
The gap between what engineering ships and what the business can see it returned is a visibility problem, not an execution problem. Watch an on-demand demo and see what closing that gap looks like.
Anerkennung durch Analyseunternehmen
The analysts who cover software delivery and portfolio management name us a Leader, year after year.
über 3.000
Kunden auf der ganzen Welt
3.1M
Benutzer auf der Planview Plattform
45%
des Fortune 100 Konzerns Planview
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
Peer Reviews
ON-DEMAND-DEMO
Watch how delivery is connected to the outcomes it funded
See how Planview sits above Jira, ADO, and GitHub to surface cross-team risk, measure end-to-end flow, and connect every engineering investment to the business outcome it was funded to produce.
Demo ansehen
How Planview helps
Your Challenge
- Investment without proof
- Roadmaps that lag the market
- Commits that don’t ship
- AI investment without governance
- Fragmented delivery data
Problem
The engineering budget grows. The CFO asks what it returned. The answer is hard to assemble and comes back as activity, not outcome. Run costs absorb more of the budget each cycle, and the governance conversation stays stuck at cost.
What it costs you
- The CFO benchmarks IT cost and the conversation starts and stops there.
- The investment ask for the next cycle gets harder to defend because this cycle was left unclosed.
- AI and agent investment accumulates without a line to the outcomes it produced.
Planview delivers
- Investment-to-outcome tracking: Connect every technology spend line, including AI and agent investments, to the business outcomes it was funded to produce.
- Planned-versus-realized benefits tracking: Close the loop between what was committed at funding and what was delivered, over time.
- Executive-ready outcome views: Replace assembled reports with traceable, real-time data built for CFO and board review.
Resources for software engineering leaders: research, reports, webinars and guides
Bericht abrufen
State-of-the-Industry-Bericht 2024 „Von Projekten zu Produkten“
E-Book
Schnellere Bereitstellung digitaler Produkte: Durch Transparenz und Abstimmung zum Tech-Leadership-Erfolg
The Economist Impact Report
Bridging the Gap: Turning Strategy into Reality
Personalized assessment
Project to Product Maturity Assessment
E-Book
So etablieren Sie ein ergebnisorientiertes Unternehmen
E-Book
Strategisches Portfoliomanagement: Best Practices für die Abstimmung von Strategie, Finanzierung und Umsetzung
Planview in Aktion
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The right solution for software product and engineering teams
Bereitstellung von Softwareprodukten
Planview for Software Product Delivery connects strategy, capacity, flow, and outcomes in a single model above your delivery toolchain, giving CTOs and CPOs end-to-end flow visibility, early risk detection, and investment-to-outcome traceability for every engineering bet.
Häufige Fragen
Delivery performance measures how efficiently code reaches production: deployment frequency, cycle time, change failure rate, mean time to restore. Business value measures what changed after it did: adoption, revenue, retention, cost reduction. The two are related but not the same. An organization can sustain high delivery performance while the business sees no return on its engineering investment, if the right work is not being built or if the connection between output and outcome is not established.
Closing that gap requires a measurement layer above the delivery toolchain that connects what shipped to what it was funded to move. Without it, engineering investment gets evaluated on effort and activity rather than the outcomes those inputs were purchased to produce. Planview connects every release and feature to the OKRs and outcome metrics it was funded to move — so leaders trace what shipped to what changed, and build the evidence base that makes the next investment ask defensible.
DORA metrics (deployment frequency, lead time for changes, change failure rate, mean time to recover) answer how reliably code reaches production. They do not answer where engineering capacity is going, whether funded work is aligned to the highest-value bets, or what any of it returned to the business.
Technology leaders who govern at scale complement DORA with flow metrics (how work moves end-to-end across value streams and teams), investment metrics (which bets consumed how much capacity and what outcome they produced), and dependency and risk metrics (which cross-team constraints are most likely to break committed dates). Together, these give the CTO and CPO a system-level picture that no individual toolchain provides on its own. Planview surfaces all three above the existing toolchain, without requiring teams to migrate or standardize.
The gap widens each cycle as AI and agent investment adds a new cost category without a corresponding measurement layer.
Planview connects them. Investment-to-outcome tracking ties every technology spend line, including AI and agent investments, to the business outcomes it was funded to produce. Planned-versus-realized benefits tracking closes the loop between what was committed at the funding decision and what was actually delivered. The result is an evidence base that makes the next investment ask defensible before the board meeting opens.
Deploying AI agents across engineering without governance boundaries is the same operational risk as deploying contractors without authority limits, budgets, or reporting lines. The question is not whether to deploy AI agents — it is whether the organization has the infrastructure to do it with accountability.
Governing AI agents means defining what the agent can act on independently, what requires human approval, what budget ceiling it operates under, and how its actions are audited against the outcomes it was deployed to produce. Without that infrastructure, AI spend in engineering accumulates without return visibility, and the AI governance conversation with the board stays stuck at risk rather than moving to return. Planview’s agent resource management gives technology leaders the governance layer to deploy AI agents with authority boundaries, budget ceilings, role definitions, and a full audit trail. Humans keep judgment, stakeholder context, and the prioritization decisions that cannot be automated.
Planview sits above the toolchain and connects strategy, delivery flow, and capacity in a single model. CTOs and CPOs use it to see end-to-end flow, surface risks before they cascade, model trade-offs against real capacity, and trace every investment back to the outcome it was funded to produce. It does not replace team-level tools. It gives leadership the picture those tools cannot provide independently.
For in-house technology organizations, common in financial services, insurance, and enterprise IT, toolchain-neutral integration means the platform works across mixed and legacy stacks without forced migration. That matters where multi-decade systems and post-acquisition tool sprawl are the norm.
Planview operates above existing development tools (ADO, Jira, GitHub, and others), pulling credible execution signals without requiring teams to migrate or standardize on a single tool. ADO-heavy stacks, Jira-dominant environments, and mixed toolchains from mergers and acquisitions: the platform works above all of them without disrupting team-level workflows.
Teams keep their tools. Leaders get a consistent flow view above them, with bottleneck detection, dependency mapping, and outcome traceability that no individual tool provides on its own.