Data in transfer pricing
In digital transfer pricing, data is essential. Data is different types of information that usually is formatted in a particular manner. For example, data can be in the form of words, numbers, images and so forth. And generally, there are two types of data: unstructured and structured data.
Unstructured data is where the information is available in a wide range of formats, and a computer cannot quickly process it. It may need to be processed and stored by humans, who can analyze the information. Here are examples of unstructured data from a transfer pricing world:
Example 1: Extract from the OECD Guidelines 2022, p.333
Why is it unstructured data? Because it is raw text. To make things worse, it's not even a text, but a picture of the text. It has certain logic and facts embedded, but it is not machine-readable - you can't give a computer task to list allocation keys based on it (at least without using advanced AI technologies).
Example 2: Description of the transfer pricing case
Same as above, this is raw text with a certain logic, but only experienced humans can read and make sense of it.
Structured data, on the other hand, is where data is usually structured in a particular format which makes it easier to analyze or process. It is available in a specific format like a spreadsheet or database, which computer programs can easily read or extract information from. Let's modify one of the previous examples to make it structured:
Now, the transfer pricing scenario from Example 2 is presented in a structured way - the information has specific characteristics (dimensions) and is formatted in the table. Each separate cell in the "data" column is a data point (BOLD). And since it is structured, we call it a structured data point.
Why do you need structured transfer pricing data points?
Traditionally, unstructured data is used in transfer pricing, which makes the entire process manual and error-prone. But the critical issue is that even if the information is available in the tables, it is not structured so that computer programs can easily analyze and make sense of it.
The answer lies in using structured data as part of a digital approach to transfer pricing. If a company collects structured information and stores it in a computer system, transfer pricing or financial specialists can easily analyze it and use it for transfer pricing policy and compliance purposes. Here are a few benefits of having structured data in transfer pricing: