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How to Use the FAIR Business Value Framework

The FAIR Business Value Framework is designed to be used in two complementary ways:

1. Qualitative exploration and alignment
2. Quantitative modeling and financial assessment

Both dimensions are essential. The framework delivers value even without any calculation, and its full impact emerges when qualitative insight and quantitative rigor are combined.

This simple flow captures how the framework supports awareness creation and translations to action.

Explore qualitatively → Identify value → Measure quantitatively → Inform decisions

The framework was designed with a flexible and modular mindset. It can be deployed at the level of a research lab or of an entire organisation. It can be used "top down", starting from the higher level drivers, or "bottom up" by modelling a very specific case from one or more of the deeper level drivers.

There are currently 38 calculation formulas, which are parametrized. The user can use any or all of them. That provides a vast amount of modelling options.

1. Qualitative use: identifying and framing value

At its core, the framework provides a structured narrative of potential value creation.

Each level of the framework, namely Strategic Drivers (Level 0), Business Value Areas (Level 1) and Quantitative Drivers (Level 2) is associated with a descriptive narrative text providing contextual explanations. Level 2 is associated with elements that can be calculated.

1.1 Expanding awareness of value

A primary use of the framework is to identify value drivers that may not have been previously considered and expose hidden or implicit benefits of FAIR data. In practice, users may discover value areas they had not initially anticipated. The framework may also act as a checklist of value creation opportunities.

1.2 Supporting qualitative business case development

Even in the absence of numerical data, the framework enables a structured articulation of why FAIR matters and alignment of FAIR initiatives with business priorities. This is particularly important in early-stage of FAIR Maturity journeys discussions, where data may be incomplete and benefits are not yet measurable. (see: fairmm.pistoiaalliance.org)

1.3 Identifying non-quantifiable value

Not all value can easily be translated into metrics. Examples include: increased employee satisfaction and engagement, improved collaboration across teams, enhanced trust in data and decisions, better organizational learning and knowledge reuse. For example, when a data scientist spends less time cleaning data, the benefit is not only time saved, but also improved focus, motivation, and innovation capacity.

Such effects are difficult to quantify directly yet strategically important for organizational performance

1.4 Enabling structured conversations

The framework supports: thought-provoking discussions, reframing of existing assumptions and alignment across stakeholders.

By exploring a given business driver and the associated parameters needed to measure it teams are encouraged to question current practices , identify gaps in data and processes, and define what "good" looks like .

1.5 Providing a neutral and shared language

The framework establishes: a common vocabulary across roles and organizations as well as a neutral ground for discussing value.

This helps to surface implicit assumptions, align technical and business perspectives, and reduce ambiguity in decision-making.

2. Quantitative use: measuring and modeling value

Building on the qualitative layer, the framework enables quantitative assessment of FAIR impact.

2.1 Selecting drivers

Based on their FAIR transformation project, users can select the relevant Level 2 drivers , identify associated parameters, and focus on areas where data is available or can be estimated.

2.2 Defining baseline and target states

For each selected driver: - define current performance (baseline)
- estimate improvements enabled by FAIR

This step often reveals missing metrics and gaps in measurement capabilities.

2.3 Performing calculations

Using the defined parameters, the framework supports the calculation of: cost savings, productivity gains and value creation. Importantly, aggregation into financial metrics such as ROI, NPV, and payback period is provided.

This is implemented through the FAIR Business Value Calculator.

2.4 Scenario modeling and sensitivity analysis

The framework enables the comparison of different assumptions, exploration of scenarios, and assessment of uncertainty and risk. This supports more robust business cases and more informed decision-making.

3. Combined use: from insight to decision

The full value of the framework emerges when qualitative and quantitative uses are combined.

  • The qualitative layer: expands understanding , identifies value, and aligns stakeholders

  • The quantitative layer: checks assumptions , provides impact metrics, and supports investment decisions

Together, they enable: a comprehensive and transparent approach to articulating the business value of FAIR data

4. A tool for transformation, not only calculation

The FAIR Business Value Framework should not be seen only as a calculation tool. It is: - a thinking framework - a conversation enabler - a decision-support system

It supports organizations in moving from intuition and implicit value to explicit articulation of value. In combination with FAIR maturity matrix, this can support the transition from isolated initiatives to aligned, value-driven transformation