The « Data Maturity Model » – Part 3.2 [Quantitative Metrics]

The Data Maturity Model – Quantitative Metrics

Quantitative metrics are calculated from precise information / values. They can give a snapshot of any situation, or they can illustrate the dynamics of the evolution.

Volumetry metrics vs. Earned Business Value (EBV) metrics

This pertains to quantitative metrics, as well as qualitative aspects of an entity that can yield / give rise to quantised values. Certain metrics (primarily ratios) have the possibility to be measured with respect to data volumes as well as the Earned Business Value (EBV) contributed by data.

Metric – Data Volumetry ratio [DV Ratio]

The DV ratio is a quantitative metric. It gives a snapshot of the overall usage of Data in an organisation or project.

On the numerator we count the overall volume of data that is used within the organisation or the project. On the denominator we divide using the overall turnover (of the organisation or business division), or, in the case of a project, with the project budget used at that point of time.

Metric – Data Flow ratio [DF Ratio]

The DF ratio is a quantitative metric. It gives a snapshot of the overall streams of Data that affect or influence an organisation or project.

On the numerator we count the overall exchange of data within the organisation or the project, over a particular period of time [days, weeks, months, years]. On the denominator we divide using the change in turnover (of the organisation or business division), or, in the case of a project, with the project budget used, during the same period of time.

Metric – Data Volumetry Evolution ratio [DVE Ratio]

The DVE ratio is a quantitative metric expressed as an absolute ratio. It shows the dynamics (evolution) of data usage within an organisation or project. This metric is an absolute ratio. In broad terms, it is a measure of how much data usage is made for forecasting and planning in the future. This is expressed as a comparison (ratio) to data usage for past performances [Read-only usage]. In other words, it measures the progression of an entity [organisation, project, business division, subsidiary] from Data-sensitive entity to Data-oriented.

On the numerator we count the overall volume of data that is used within the organisation or the project for calculating future projections and planning. On the denominator we divide using the data volumes used in analysing past performances, problems, etc.

 

Data Scorecards

Economic Ratios

 

Previous Page: « Data Maturity Model » – Part 2 [Comparisons & Differences]

Detailed Pages in this section:

« Data Maturity Model » – Part 3.1 [Categorical Metrics]

« Data Maturity Model » – Part 3.2 [Quantitative Metrics]

Next Section: « Data Maturity Model » – Part 4 [Data Neutrality]

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