Organizations with effective data-driven prioritization are 2.5 times more likely to be high performers in their industry, yet companies typically use only 50% of available data when making decisions.
This second post in our five-part series focuses on the foundational element of our prioritization framework: data. Building on our introduction to Garry’s Robots Ltd. and their household cleaning robot challenges, we’ll explore how they can use data to choose high-value priorities and avoid development delays.
In this installment, we’ll cover:
- Key metrics for standardized prioritization
- Effective capacity tracking and management
- Creating a single source of truth for decision-making
When data is used consistently in a standardized process, effective prioritization becomes second nature.
Essential Metrics for Prioritization
To prioritize projects effectively focus on these four categories:
Strategic
Strategic metrics assess whether projects align with business goals. They include:
- Strategic fit score (a number representing the project’s alignment with business goals)
- Market impact (a projection of the project’s impact on market share)
- Portfolio balance (a measure of how the project complements other initiatives)
If Garry’s Robots used strategic metrics, it would be clear that the water-cleaning feature is far more valuable than the voice-activation feature. They should define strategic goals first, and then score projects on how well they support those goals (a topic covered in the next blog post).
Financial
Financial metrics quantify a project’s value and cost. They include:
- Revenue forecast
- Development cost
- Margin contribution
Avoid focusing only on short-term gains alone. A low-margin product might still be worth pursuing if it opens up new markets.
Resource Impact Metrics
Resource impact metrics help leaders evaluate a project’s feasibility. They include:
- Required resources and skill sets
- Employee utilization
- Capacity constraints
Garry’s Robots regularly exceeds capacity, spreading engineers across too many projects. This has delayed their water-cleaning initiative. To prevent this, they need visibility into team assignments, skill bottlenecks, and resource allocation.
A 2023 McKinsey study found 90% of leaders believe capacity planning is important, but only 5% believe their organization does it well.
Project Dependencies
Many projects depend on specialized teams, shared services, or other projects for success. To coordinate teams effectively, keep track of:
- Technical requirements
- Supporting projects
- Integration needs
Garry’s Robots’ water cleaning feature depends on two projects: one focusing on mechanics and another on AI-driven surface recognition. Both projects must be completed before either can realize any ROI. Accordingly, Garry’s Robots must map these dependencies early to prevent bottlenecks and delays later.
To assist them in their efforts, Garry’s Robots might create a chart that summarizes these four categories and their importance.
Where Your Data Comes From
To support prioritization, pull data from five sources:
- Strategy. Each portfolio should have a defined strategic goal, such as innovation, maintenance, or compliance. Goal-related measures like OKRs provide criteria for assessing project alignment. If Garry’s Robots aims to increase market share, projects should be scored accordingly.
- Current Product Catalog. Current product performance reveals patterns that could change priorities. If Garry’s current robots struggle with malfunctions, then quality improvement projects could take priority over new features.
- In-Flight Projects. Real-time visibility into current projects provides necessary context for decisions about new projects. It helps leaders minimize duplicate work, conserve resources, and avoid bottlenecks. If Garry’s Robots has an AI-initiative in progress, new AI projects should combine efforts rather than re-inventing the wheel.
- New Projects Being Evaluated. Leaders across the portfolio should know about incoming ideas and work in order to allocate capacity and share resources effectively. If Garry’s Robots has a deadline coming up (like a product launch for a trade show), leaders should anticipate the extra burden and plan new projects accordingly.
- Project Historical Actuals. Review past estimates vs. outcomes. If Garry’s Robots consistently experiences delays when ordering mechanical parts, this should factor into time estimates.
Data Integration: Creating a Single Source of Truth
At many organizations, data is scattered across separate systems. One product team works in Jira, while another works in Excel, and leadership reviews production updates in cumbersome PowerPoint presentations.
As the number and scale of projects grow, fragmented manual tracking becomes error-prone and slow. Important insights get lost, and decisions take too long.
Data-Driven Prioritization in Action
Abbott’s launch of the FreeStyle Libre 3 glucose monitoring system demonstrates effective metric integration. By prioritizing accessibility and simplicity over premium pricing, Abbott positioned their device as a mass-market solution while competitors remained in niche segments. Their data-driven approach balanced strategic market positioning with the financial, resource, and supply chain requirements for global scale.
Put Data to Work for Your New Products
In this post, we explored how Garry’s Robots could transform their decision-making by incorporating four crucial categories of product development metrics, gathered from five main data sources, all integrated into a single accessible platform.
Successful organizations use integrated planning tools to automate data consolidation. When all product data lives in a single platform, teams access consistent information and respond quickly to market demands.
With this strong data foundation in place, Garry’s Robots is now ready to move to the next phase of the prioritization framework: applying consistent scoring methods to evaluate projects objectively. While data tells you what’s happening, effective scoring structures (which we’ll cover in our next blog) will help you interpret that data to make defensible decisions.
One step you can take today is to conduct a focused “data audit” of your resource metrics. Ask your teams: Do we know our true capacity? Can we accurately track who’s working on what? Where are our skill bottlenecks? Since resource constraints are the most common barrier to execution, starting here often yields the quickest improvements to your prioritization process.
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Watch out for the next blog post in this series, where we will explore how Garry’s Robots creates structured scoring systems to rank projects holistically and maximize their newfound data visibility.
