Data wrangling tools can help automate the data extraction process. This involves a system comprising three critical steps: extracting, transforming, and loading (ETL), which is key to setting up a data pool. ETL software helps establish a secure agent that can connect directly to the underlying ERP tables. The tools comprising an ETL solution can help organizations pull and consolidate data, perform reconciliations, and execute quality checks using an automated, repeatable, and well-documented approach that leaves a clear audit trail.

Having an ETL process provides flexibility in connecting to various source systems, including ERP, e-commerce and order management, tax software, and flat files, among others. This flexibility enables users to pull in data regardless of format with agility to meet future requirements.

Adopting an ETL system substantially reduces the need to build reports and manually manipulate data. Indirect taxes in particular require massive volumes of data—in many cases millions of records per month. ETL systems can help process those large data sets in minutes, even seconds. ETL tools enable data consolidation and verification from multiple sources to streamline the reconciliation process. This time-saving feature can help save resources and costs and builds greater efficiencies.

ETL tools also allow for enhanced documentation of processes. Organizations can clearly see what is actually being done with the data, enabling a clear link and audit trail from the data back to the ERP and other reporting systems. Seeing how that data was used may be a particularly valuable asset during audits three to four years after the transaction occurred.

A key part of aligning technology to indirect tax data is using analytics to gain insights and see important elements in real time. Analytics allows organizations to flag issues as anomalies immediately rather than in the future when they likely will be compounded. Additionally, analytics enables organizations to look at data more granularly to better analyze its validity.

ETL and its benefits

Once ETL solutions are in place to help gather and manage an organization’s indirect tax data, cognitive learning tools can turn that clean and formatted data into insights for an organization’s stakeholders that can lead to savings.

For example, cognitive learning solutions can apply indirect tax decisions related to a small population of data to a broader population, allowing tax teams to determine quickly whether vendors correctly charged sales taxes or whether organizations appropriately accrued use taxes. This process enables the tax team to import raw transaction-level detail that may date back years and consolidate and map those details with other supporting information, such as contracts and purchase orders.

This process helps select representative transactions by business unit, jurisdiction, or other differentiator allowing teams to review a small group of transactions from a tax technical perspective. Cognitive learning then applies what the team learned from those transactions to the broader population, providing iterative and predictive insights. In other words, cognitive learning enables the tax team to classify all transactions via machine learning rapidly with targeted validation from specialists. These analytics help team members understand the organization’s tax profile and address common issues. These benefits can be extremely valuable from a stakeholder, reporting, and management perspective.