Brigitte Baumgartner Garcia — Aibidia Digital Transfer Pricing Advisor
Introduction
We have always been surrounded by data. What has changed in the last few years that has made data more relevant now than ever is, however, the ways in which we utilize this data. With social media, online activities, and digitization of our personal data, our information is being used to define how we interact with everything around us. In the corporate world, this use of data relates to artificial intelligence, improved analysis, predictions, and automation of processes. By affecting industries of all kinds, from service providers to healthcare, construction and finance, data is turning into the new oil. Nevertheless, data in and of itself is not a particularly useful thing. Data needs to first be generated, collected, stored, analyzed and finally used for machine learning and model building before some type of added value can be realized.
Structured Data and Transfer Pricing
In transfer pricing we are used to collecting and storing data from different legal entities and different departments. In most cases, this data ends up in disparate files and folders that are used later to generate transfer pricing documentation, incurring a significant manual work burden in the process. If the transfer pricing department is lucky, there is some type of logic behind the gathering, storage and processing of relevant data for transfer pricing purposes. Unfortunately, transfer pricing professionals usually work without a pre-established logic or methodology. Not because they want to perform their job in this way, but because they are more reactive than proactive. In a lot of cases they react to audits and tax administration requests, with each local file requiring days or weeks of work to be ready for an audit. Despite some lingering doubts, company tax departments are already realizing that this way of working is not sustainable. The secret of a sustainable transfer pricing compliance workflow is, therefore, pre-established work methods with structured data. Is such a thing achievable without automation? I personally do not think so.
A well-designed and structured automation tool for your transfer pricing data is the necessary framework for an efficient transfer pricing workflow. Any generation of transfer pricing documentation without structured data can, and likely will, turn into a nightmare or be obsolete in a couple of years.
Structured data helps the transfer pricing professional because it enables the ability to focus on relevant information and not on manual work. It reduces time that would be better used for strategizing, analyzing substance, mutual agreement procedures, advance price agreements and transfer pricing forecasting. Utilizing a structured data approach also minimizes the risk in audits and exchange of information among tax authorities through an appropriate management of for the whole group. Finally, the concept also allows quick validation reviews for transfer pricing adjustments in a proactive way.
Transfer Pricing professionals are being challenged by businesspeople to digitize processes and save costs, but the question for our purposes is: are all automation tools built on a notion of structured data? No, the market offers different approaches how appropriate one or the other is, will depend on the company long and short-term goals and how the specific solutions solves the transfer pricing challenges. What makes a tool powerful for transfer pricing processes is the amount of time that is saved in manual work, the validation possibilities that derives from the logic and structure of the tool, the analytics which help professionals move from tax language to business language and finally the capability of having the documentation in a machine readable format which is already required by some tax administrations and will be the future of transfer pricing compliance.
Conclusion
With respect to compliance processes, there will be always alternatives to get the job done; for transfer pricing purposes there are three typical different paths. The old unstructured manual method that tends also to be more expensive and time consuming than any other alternative. The middle ground solution, which involves establishing internal processes or implementing automation with unstructured data. Or, finally, the generation of documentation based on pre-establish logic and structured workflows that allow structured data to be the basis of transfer pricing success. It is clear, at least to me, that the third option is the best way to future proof your transfer pricing activities.
