One of the most immediate and practical issues that that MNEs are facing is how to deal with the large volumes of information that they are expected to collect and present to tax authorities. Visual dashboards – which can now be developed easily using readily available software – are an effective tool for quickly examining the large amount of financial data that are being prepared to comply with new documentation requirements (such as the CbC form that many MNEs will have to prepare starting in 2016) and/or to evaluate transfer pricing risks. The key concept behind a video dashboard is that you can use a combination of pictures, slicers or filters, and tables to get quick insights into the data. This is better seen than described, and so the video below provides a quick introduction into how such dashboards work, using sample data for FakeCo – a company with 297 legal entities and three supply chains.

At this point, you have the option of either going directly to a 4 minute video that illustrates the use of such a dashboard – just click here or on the map to the right – or of continuing to read about the uses of visual dashboards.

 

Dealing with the large amounts of information that are now being routinely collected and processed as part of the transfer pricing process requires the ability to process available information quickly and effectively, as well as an ability to update such analyses as new information comes available. PowerPoint presentations and written reports have significant limitations in this regard, in that they are generally presenting a static, pre-defined look into the data. The visual dashboards that have become readily available over the last several years represent a useful alternative, in that they can not only summarize significant amounts of information in a way that is easy to understand, but they also allow for the quick exploration of different subsets of the information and can be readily refreshed to incorporate new information. The dashboard below provides an example of one such visual dashboard for a hypothetical MNE (FakeCo) with three supply chains and 297 different legal entities.

The dashboard shown above has three components:

One, an interesting graphic, which is on the upper left of the dashboard shown above.  This graphic is a map where the circles indicate total profits in each country, with large circles showing countries where there are high total profits while small circles show countries with more limited total sales. The green bubbles indicate countries with tax rates of greater than 10%; the dark bubbles countries with tax rates of less than 10%.  (Other graphics can also be used.)

Two, several “slicers” (in the upper right) allow the user to look at different subsets of the data. Thus, while the bubbles on the map show profits for all three supply chains in aggregate, checking the box for supply chain one will generate the map on the far left below, checking the box of supply chain 2 will generate the map in the middle, and checking the box for supply chain 3 will generate the map on the far right. As can be seen below, the three supply chains have quite different attributes, with profits in supply chain 2 concentrated in two principal companies (one in Bermuda and the other in Switzerland)., while the other two supply chains supply chains have very different attributes.

Supply Chain 1

Supply Chain 2

Supply Chain 3

 

Three, a data table (at the bottom). The data shown in the data table change as the user of the dashboard selects different subsets of the overall company, and allows the user to focus on those data that are match these different subsets. I have found that this is a very effective way of looking for anomalies in the data (for example in draft CbC tables) that are likely to warrant further attention, either because they may be errors or because they may draw attention to specific risk factors.

Of course, looking at static pictures such as those shown above is not what visual dashboards are about – they are about the ability to look at data dynamically and see how “slicing” the data is different ways can provide insights into the data. If you have not already watched the embedded video, click here go to a video showing how a simple dashboard can be used to examine the attributes of selected financial data for a hypothetical MNE with 297 different legal entities spread across three different supply chains.

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