B2B organizations are investing aggressively in digital initiatives. Gartner surveyed leaders across all industries and found only 48% of those initiatives meet or exceed their business outcome targets. That’s because most companies lack a shared framework for connecting investment decisions to the outcomes they’re trying to achieve.
Instead, decisions happen in pockets. Different teams optimize for different KPIs, as they should, but there’s often no clear connection between those measures or to the organization’s broader goals. As a result, budgets get misallocated, promising projects lose funding because they can’t show their value, and decisions lag when speed matters most. Even approved initiatives can fall short due to insufficient adoption.
Value management addresses this gap by creating a shared value logic for evaluating investment decisions. Functions keep their own KPIs while understanding how those metrics contribute to broader business outcomes, creating a clearer path from investment to value.
What’s getting in the way of B2B organizations
Three entrenched patterns prevent B2B companies from confidently making investment decisions:
- Overweighting what’s already observable. Many B2B organizations default to historically measured financial metrics to measure value. But when sales cycles stretch for months, this approach misses the critical work happening along the way, such as marketing initiatives driving pipeline growth, platforms improving decision velocity, or capability builds retaining more customers. These forward-looking, intermediate forms of value are critical, but are often discounted because they’re harder to measure and attribute to a specific project.
That causes organizations to reject important new investments while continuing to fund legacy programs that once worked but can’t drive meaningful growth in today’s environment.
- Decision makers have the target without the operational plan. When the financial framework lives in a single department, the leaders making strategic decisions often see only the headline without understanding the underlying mechanics. A model tells you what value might be possible, but if the organization doesn’t understand what must change operationally to create that value, they can’t manage toward the outcome.
- Data access without usability. B2B organizations have a wealth of data. You understand your customers’ behaviors, your deal progression, and your operational metrics. But that data is scattered across systems, in unstructured formats, and not arranged in ways that make it useful for investment conversations.
How value management empowers leaders across the organization
A shared value framework doesn’t mean every function makes decisions the same way. It gives each leader a clearer view of how their decisions contribute to broader business outcomes.
CMO: A forward-looking value framework gives marketing leaders a more defensible way to evaluate and explain investments. You can confidently show the path from campaign to outcome in a way the rest of the organization understands.
CIO: A structured value-based decision-making process brings analytical backing to your technology roadmap. It gives you the infrastructure to prioritize initiatives based on business impact, change those that aren’t working, and sustain momentum as business needs change.
COO: A clear structure shows which investments are driving transformation. You can sequence initiatives smartly, resolve prioritization conflicts, and show the organization a concrete path from investment to value.
CFO: Value management prioritizes investments based on financial logic instead of gut instinct. Trade-offs become visible and defensible for all stakeholders.
How to build the capabilities
At the core of value management is a simple reframing: treat every business case as a hypothesis about the future, not a certainty. When you propose an investment, you’re making a claim: if we make this investment, we expect certain things to change operationally, which should create specific outcomes, which should ultimately produce value.
The role of value management isn’t to pretend that a hypothesis is certain. It’s to make your assumptions explicit, establish baselines from the beginning, and keep testing them as evidence emerges.
Three practices help you more effectively test each hypothesis:
- Trace the full chain of investment value. Instead of jumping straight from an investment to the final financial outcome, identify the intermediate outcomes that ultimately create enterprise value. Improvements in adoption, decision velocity, pipeline progression, retention, productivity, or speed-to-close create value before they become visible in the P&L and must be measured to evaluate an investment’s full impact.
- Build an economic lens across the organization. You can’t just measure outcomes at the enterprise level. Data analysts should understand how their work connects to pipeline. Your operations team needs to see how efficiency gains drive velocity. When teams, functions, and leaders understand how their KPIs fit into the larger financial picture and relate to others’ metrics, behavior changes. That’s when enterprise outcomes happen.
- Turn unstructured data into actionable intelligence. Your customer data, operational data, and historical performance data need to be refined into a form that teams and AI can use to make decisions. This requires ongoing effort to make data accessible and interpretable for value conversations.
How to operationalize value management
The capabilities above only drive impact when you embed value management as a standing discipline instead of an evaluation exercise. The framework shouldn’t disappear once an investment gets approved. It should continue to help the organization prioritize, monitor assumptions, understand whether expected outcomes are materializing, and decide whether to continue, change, accelerate, or stop an investment.
Start with the decisions you’ll actually need to make. Look at the next 12 to 18 months, including prioritization conflicts, investment requests, technology choices, and capability builds. Use those scenarios as test cases for your evaluation framework. You’ll discover what works and where the gaps are, allowing you to refine under real conditions rather than in theory.
Get the data, models, and benchmarks to make these calls with confidence. This can’t happen in isolation. You need perspective from organizations in your industry, frameworks designed for B2B dynamics, and the ability to test your assumptions against real-world patterns. Merkle brings pattern recognition, benchmarks, financial modeling, and the ability to translate strategy into decision tools.
When every function can see how its investment choices contribute to enterprise value, you can fund the right work, move faster, and extract more value.
