Data Unit Costing

There's a bottleneck at the heart of modern commerce

Data is the fuel of modern commerce. It drives everything around us: our smartphones and bank accounts and industrial infrastructure. But there's a problem. Data has terrible quality. It is dirty stuff–hard and costly to clean and 95% is waste.

It is hard to clean...because it is hard to measure...because it is an Intangible Asset. None of us can financially measure the value of our own raw data. It can be mined but not cash-measured to assess the daily cash value owned by each creator, generator, maker, and consumer.

The need for rapid data monetisation

We need business metrics to use statistical improvement methods, such as the 80/20 Rule (Pareto analysis) to improve the quality. But this means that we must have cash value, to create "x" and "y" variables.

This is not possible because Intangible Assets have $0.00 daily value. Data monetization can take weeks and months of work by teams of financial specialists and analysts. Teams use traditional methods; workarounds that were created to get around the inability to rapidly monetize data (see: "Solution/Part C", "Problem Deep Dive" page).

Example of Pareto Analysis Chart

We've solved the rapid data monetization problem. We deliver Cash Valuations, Variables and Dataset Book Value results in days instead of the traditional weeks or months. Customers use our SaaS solution to get continuously better metadata to:

Improve data and dataset quality
Improve productivity at every step of the workflow
Improve the profitability of data operations, products & services
Identify the bookable value of raw data assets

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Data Unit Costing

The need for rapid data monetisation

Example of Pareto Analysis Chart

Further Reading