How do you deal with scattered data?

TaxReco Shorts

Finance professionals deal with large volumes of tax & transaction data. They need to deal with this data for periodic compliances, management reporting, dealing with customers/vendors and audits & assessments. This data is complex, difficult to interpret at times and needs to be simplified for reporting & compliance purposes in desired templates.

But do you know where do they spend majority of their time?

Majority of their time is spent on data extraction and converting it into meaningful formats. This happens despite using the best of ERP systems.

Let’s look at the two main reasons behind these. These reasons are assimilated based on the interactions we have had with companies in the last three months.

TDS Accounting – Most of the companies have been doing TDS accounting by passing Journal Vouchers (JVs) in their books. These JVs are passed cumulatively for multiple transactions for one customer (which is still ok) and across multiple customers (imagine the sheer volume involved in the extraction of the data in this case).

Data available in multiple tables in ERP systems – Data required by finance team is often not available in single report. There are multiple reports which are downloaded from ERP systems and these reports have to be joined manually to interpret the data and make it presentable. This is the most common problem faced while interacting with companies. The most common answer is “We want to automate but data availability is an issue since  it is present in multiple files”

While the responsibility of the finance team is defined in the first paragraph, what they end up doing at the end of every period is actually struggle with data.

If these problems are solved for finance professionals especially the one listed second, finance professionals can use their spare time available in analyzing the data rather than preparing the data.

How do you solve data availability issues in your organization?

Hint: Finance professionals know finance and they are not expected to be data scientists 😊

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