Data is transforming tax and finance functions, helping teams switch focus from routine compliance work to become strategic, data-powered generators of insight, capable of guiding the wider organization. This transformation is particularly important considering the speed and scale of regulatory change and the need to share ever-greater volumes of granular data electronically with tax and finance authorities.
Accessing and operationalizing high-quality data at speed, however, continues to be a challenge for most organizations. The latest EY Tax and Finance Operations Survey reveals the extent of this challenge, with tax personnel currently spending three-quarters of their time (75%) on routine compliance work, which includes data collection and cleansing, tax return compliance and related reconciliations. Meanwhile, tax practitioners spend just 28% of their time on higher-value work such as data analysis, tax planning, managing tax controversy, general strategy, communications and risk management.
The key to unleashing the full transformative power of data lies in enabling tax teams to access the high-quality information they need. This is no simple task. Nearly half (48%) of organizations cite the lack of a sustainable plan for data and technology as the biggest barrier to achieving their vision for a modern tax and finance function.
Forward-thinking organizations are now using a range of strategies to overcome this data challenge, including centralizing and improving data creation at source and using artificial intelligence (AI) to pinpoint low-confidence data, so it can be escalated for people review.
Creating a single view of tax truth
Terri Beigh, EY Partner, Tax Technology and Transformation, Ernst & Young US LLP, is currently collaborating with Microsoft and one of the world’s largest manufacturing companies to help overcome this data challenge and transform the organization’s tax and finance function. She says the solution is to achieve a single view of “tax truth” which can then be used with confidence across multiple teams and processes.
Beigh explains that standard practice typically involves individual tax and finance teams retrieving the information they require to satisfy their compliance requirements.
This means that multiple teams requiring a trial balance, for example, often run completely different T-codes, resulting in different figures. Tax and finance teams must then engage in a potentially protracted retrospective reconciliation process. As a result, the process of data operationalization can become somewhat adversarial, according to Beigh.
“When locally generated data is shared, each team usually thinks their trial balance is the most accurate, while every other team’s data is wrong,” Beigh says. “Each team has their own tried-and-tested way of doing things. Teams can still achieve their compliance requirements, but this process lacks accuracy and it’s inefficient.”
This local generation of data also exposes differences in layout and language across jurisdictions. For example, every time a finance director wants to generate a trial balance, they must provide it in multiple formats and layouts, drawing out a complicated process even further.
Standardizing and centralizing tax and finance data
The solution for Beigh’s team, Microsoft and client-side collaborators, is to eradicate duplication by centralizing the data generation process and tracking core data points back to their original source.
“We embarked on a journey of data standardization and centralization,” Beigh says. “This involved establishing how many teams needed a trial balance, agreeing a standard format with the same parameters and the same periods of use.
“Instead of five versions of a trial balance, every team starts with the same one, pulled centrally at the same time and given to the teams at the same time.”
The result is a single data pipeline stretching all the way back to the general ledger entries for all detailed financial transactions, with Application Programming Interfaces (API) connectors automatically retrieving data from SAP using Microsoft Finance Insights solution.
This new data-generation process has superior controls and is more accurate due to a vast reduction in manual handling. It is also faster and less labor and resource intensive.
Mariusz Beben, Senior Director Microsoft, Industry Solutions Delivery, explains that automated data extraction played a key role.
“We effectively replaced hundreds of monthly manual information requests with scheduled and automated data pulls, backed up with automated quality checks. This gives tax teams more time to query and reconcile any data discrepancies before a tax return is filed, rather than after,” Beben says.
