Over the last decade, companies have invested heavily in experimentation programs. They’ve hired specialists, purchased costly tools, and run countless tests. Yet despite this significant investment, many leadership teams remain underwhelmed and skeptical of the strategic impact of these programs.

The root cause?

Experimentation has been mispositioned as a cost center rather than a strategic capability—more akin to maintenance than innovation. This fundamental misalignment prevents organizations from realizing the full potential of their testing programs and creates a persistent gap between promising results and business outcomes.

The Experimentation Paradox

The current state of experimentation presents a paradox: organizations run more tests than ever before, yet the strategic influence of these programs often remains minimal. Consider these common scenarios:

• A company runs hundreds of A/B tests annually, yet less than 20% directly influence strategic business decisions
• Successful experiments frequently fail to scale beyond their initial implementation
• Experimentation teams struggle to demonstrate clear ROI to executive leadership
• Knowledge gained from experiments remains siloed within specialist teams
• Test velocity is prioritized over strategic impact and business alignment

These challenges stem from a fundamental misconception about experimentation’s role. When positioned as merely a cost center or tactical activity, experimentation becomes isolated from the strategic decisions that drive organizational success.

How Cost Center Classification Destroys Value

When experimentation is treated as a cost center, organizations naturally gravitate toward metrics that justify the expense through measurable output rather than strategic value. This creates several destructive patterns that CFOs need to recognize:

The Activity Metric Trap

Cost centers must demonstrate they’re “working hard” to justify their budget allocation, leading to metrics like:

• Number of tests run per quarter
• Experiment velocity and turnaround time
• Ideas submitted to the testing pipeline
• Team productivity measures

These metrics optimize for busy work rather than strategic insight, creating teams that run more tests but generate less valuable learning.

The Immediate ROI Obsession

Cost center pressure forces focus on short-term financial justification:

• Conversion rate improvements from individual tests
• Revenue attribution to specific experiments
• Cost per conversion improvement
• Immediate sales lift calculations

This creates systematic bias toward incremental optimizations that show quick wins while avoiding the strategic experiments that could uncover transformational opportunities.

These metrics miss the point entirely—experimentation’s value lies in the quality of learning and strategic insight, not the volume of activity produced per dollar spent.

CFOs regularly classify various business activities as R&D based on their systematic approach to generating new knowledge and competitive advantage. Experimentation demonstrates these same characteristics and deserves similar treatment.

Why Experimentation Qualifies for R&D Treatment

Experimentation meets the core criteria for R&D classification:

1. Systematic Investigation: Experiments follow scientific methodology to investigate business questions
2. Knowledge Generation: Each test creates intellectual property in the form of validated learning
3. Uncertainty Resolution: Experiments specifically address unknown outcomes and market responses
4. Innovation Development: Successful experiments lead to improved products, services, or processes
5. Competitive Advantage: Learning compounds over time to create sustainable differentiation

The QA Analogy: Reframing Experimentation’s Value

The best way to understand why cost center treatment fails is to consider how we think about Quality Assurance (QA) in software development. QA doesn’t justify itself through “bugs found per dollar spent” or “testing velocity.” Instead, QA is valued for:

Risk Mitigation Value

Just as QA prevents costly production failures, experimentation prevents costly strategic mistakes. The value isn’t in the testing activity itself but in the disasters avoided.

Quality Assurance for Decisions

QA ensures code quality before release; experimentation ensures decision quality before implementation. Both are insurance policies against expensive failures.

Systematic Investigation Capability

QA provides systematic methods for investigating potential issues; experimentation provides systematic methods for investigating market opportunities and customer behavior.

Continuous Improvement Infrastructure

QA builds capability for ongoing quality improvement; experimentation builds capability for ongoing strategic learning and adaptation.

The Case for Experimentation as R&D

Innovative organizations are revolutionizing their approach by repositioning experimentation as part of their strategic R&D function. This shift transforms experimentation from a tactical optimization activity to a strategic learning capability that directly influences business direction.

What This Transformation Looks Like

1. From test tracking to decision governance Instead of merely documenting experiments, leading organizations implement governance frameworks that connect testing activities to strategic decision-making. This ensures experiments don’t just produce results but actually inform critical business choices.
   
2. From practitioner tools to leadership capabilities While practitioners need technical tools, leadership needs strategic visibility. Mature experimentation programs provide executive dashboards that demonstrate how experimentation drives business impact, not just conversion improvements.
   
3. From activity metrics to strategic influence The focus shifts from “how many tests did we run?” to “what decisions did our experiments influence?” This fundamental change in measurement transforms how the program’s value is perceived and realized.
   
4. From project management to knowledge systems Rather than treating each experiment as an isolated project, forward-thinking organizations build systems that preserve insights and facilitate organizational learning across teams and time periods.

Closing the Trust Gap

This repositioning addresses what we call “The Trust Gap”—the critical disconnect between promising test results and leadership confidence in those results. When experiments are run in isolation from strategic concerns, leadership naturally questions their relevance and reliability.

By positioning experimentation as a strategic R&D function, organizations create the complete learning loop necessary for experiments to reliably influence business outcomes:

1. Strategic Direction: Aligning experiments with business objectives
2. Governance & Structure: Building effective frameworks that elevate rather than constrain
3. Knowledge Creation: Generating reliable insights through proper methodology
4. Implementation & Action: Translating insights into business actions
5. Organizational Learning: Building institutional knowledge and memory

How to Reposition Your Experimentation Program

Transforming experimentation from a cost center to a strategic capability requires deliberate action:

1. Implement Proper Governance

Put frameworks in place that ensure quality, strategic alignment, and reliable decision-making. This isn’t about bureaucracy but about connecting experimentation directly to business value.

2. Create Executive Visibility

Develop dashboards and metrics that matter to leadership, demonstrating how experiments drive strategic outcomes and business results.

3. Build Knowledge Management Systems

Establish processes and tools that preserve insights and make them accessible across the organization, preventing the “reinventing the wheel” syndrome.

4. Connect to Strategic Initiatives

Directly tie experiments to key strategic initiatives, ensuring that testing activities advance the organization’s most important goals.

5. Focus on Decision Quality

Shift measurement from test quantity to decision quality, evaluating success based on how experiments influence business decisions.

Conclusion: The Future of Strategic Experimentation

The organizations that thrive in the next decade won’t be those that run the most experiments, but those that most effectively translate experimental insights into strategic business decisions.

By repositioning experimentation from a cost center to a strategic R&D function, companies can close the trust gap between test results and business outcomes. This transformation ensures that experimentation fulfills its promise: becoming the engine of evidence-based innovation that drives organizational learning and competitive advantage.

The question isn’t whether you’re experimenting—it’s whether those experiments are systematically influencing your most important business decisions.