5 questions around transfer pricing data analytics 5 questions around transfer pricing data analytics

TP data analytics is easier than you think, especially once you have a clear picture of your data-related processes. Automation and standardization are key for quality, time saving and recurring tasks. Let your data tell a story and reveal unknown insights to make meaningful business decision.

Everyone is talking about transfer pricing (TP) data analytics. With the amount of information available, the question quickly arises: where should I begin?

There are many points of contact between transfer pricing and data analytics. Before trying to figure out where to start, we suggest asking important questions first, such as: what is most relevant for your business? What can be standardized best while increasing data and documentation quality? What will save the most time?

From our experience, the following topics have emerged that various groups across all sectors are grappling with:

• Automated and standardized intercompany transactional data preparation, incl. quality checks
• Data purity, data consistency, and data complexity as well as traceability
• Actual margins deviating from target margins, or inconsistent with entity profiles
• Very time-consuming preparation of additional information, e.g. for local compliance returns
• Reconciliation of transfer pricing data with data of related tax topics, e.g. VAT, Customs, etc.

To be able to answer the previous questions, a good understanding of current processes (including ongoing management and updates) is key: 

• What data is available?
• Where does the data originate?
• How is it currently being processed?
• What mappings are being made?
• What controls are in place?

Once you are clear on current processes, you will have a good overview of what is going well and where there is room for improvement. 

To guarantee increased data and process quality, it is helpful to develop a group-wide framework. This should provide information on the individual steps to be taken in data collection, processing, management, storage and maintenance.

Your data can tell a story and unfold insights you have not seen before, if you:

• prepare your data by cleaning, sorting and organizing it to ensure a consistent quality level
• join your data with intelligent mappings, incl. quality tests like e.g. naming of transactions or consistent entity names across all datasets to avoid sources of error
• transform your data to gain (multi-dimensional) insights

Since data is often available in the same way (especially raw data), systematic and structured data processing makes sense. The ideal aim is to generate the same structured output at the push of a button every year.

Once the data has been prepared, joined and transformed, data visualizations help make the facts and circumstances more tangible and tell a story. You will also likely gain new insights into how your processes can be enhanced.

Business can be affected in different ways.

With the help of small decisions, a rebalancing of time investment can be made possible. Actions may include standardizing and automating time-consuming low-value-add tasks to deploy resources to where they deliver best value. 

Increased visibility and control on TP metrics can help manage the TP lifecycle better, for example:

• In operational transfer pricing (OTP), business actions can be derived, for example, through an actual vs. budget margin analysis. Such an analysis can reveal whether applied transfer prices were as planned.
• Increased visibility on transactional data enables more informed decisions and implementation around transfer pricing policy and adjustments.
• Data analytics is also particularly helpful in the preparation for and during tax audits (tax authorities also use analytics). 

TP data analytics and data processes in general also provide opportunities to relate data to other business and tax areas, e.g. business restructurings, indirect tax. A better, consistent view and evaluation can lead to fruitful business decisions and enhanced communication with various stakeholders, including tax authorities.

Various solutions can help automate, standardize, increase quality and save time on repetitive tasks, such as:

• automated and standardized preparation of intercompany transaction data, incl. quality checks and data traceability
• automated data preparation for TP returns where applicable
• Entity margin monitoring and financial cockpits to ensure profits are in line with policy

You might also want to leverage the possibility to combine such solutions directly with an automated and standardized preparation of TP documentation, e.g. local files, into which the processed data can be fed automatically.