How to fix your data reliability issue

As a high-transaction company, you’re processing thousands or millions of orders, payments, or subscriptions. Your challenge: finding truth in your financial data. Because when transactions flow through your financial software stack (typically consisting of an e-commerce platform, ticketing system, or subscription billing platform, multiple payment processors, and an ERP, for example), tiny inconsistencies can quickly snowball into a pile of unreliable data.

Without reliable data, reconciliation becomes a tangled mess. But there’s more at risk than reconciliation only: misreported revenues, inaccurate forecasting, compliance violations, operational inefficiencies, poor overall financial health, bad decisions, slowing down growth, and unnecessary costs.

Industry research highlights the scale of this issue. A McKinsey study found that knowledge workers spend approximately 19% of their time searching for and gathering information (source). A 2018 IDC study revealed that data professionals lose about 50% of their weekly time on broken data: 30% searching for, governing, and preparing data, plus 20% duplicating work (source). This inefficiency wastes money, resources and keeps financial teams stuck fixing broken data instead of focusing on valuable analysis.

Besides being inefficient, unreliable data leads to unnecessary costs. Research agency Gartner estimates that poor data quality costs organizations an average of $12.9 million annually worldwide (source).

Automation as the key to data reliability

The good news? You don’t have to waste time manually fixing data issues. Automation keeps transactions consistent, spots errors instantly, and gives finance teams one reliable source of truth. No more chasing missing payments or reconciling reports by hand—automated systems sync orders, payments, and accounting with almost no manual effort.

For large companies, this changes everything. Automation boosts efficiency and cuts financial risk by keeping revenue, payouts, and records in sync. With reliable data, reconciliation isn’t a headache—it’s a smooth process that helps the business grow.

“Where there is data smoke, there is business fire”

Why data reliability is essential for business

Automation in data reliability isn’t just helpful – it’s essential. As transactions multiply and system landscapes become more complex, companies that ignore data reliability will struggle to keep up. Reliable data gives CFOs and finance teams the power to make informed decisions, streamline operations, and scale with confidence.

Take Walmart, for example. With millions of daily transactions, they rely on automated data reliability to ensure accurate sales reporting, stock management, and financial forecasting. This keeps their massive operation running smoothly. (source)

As data expert Thomas Redman puts it: “Where there is data smoke, there is business fire.” Bad data isn’t just an inconvenience—it’s a serious risk that can lead to financial and operational chaos. The takeaway? Reliable data isn’t a luxury. It’s a must-have for any high-volume business that wants to grow without constant setbacks.

Example of a subscription-based company.
We had a global company processing a high volume of subscriptions as our client. As is typically the case, they used multiple payment providers and banks. Without automated data reliability controls, their finance team spent weeks fixing discrepancies. Payments went missing, chargebacks were misrecorded, and payout delays led to revenue errors. After automating data reliability, errors dropped, and manual work was cut by more than half.

𝐀𝐜𝐭𝐮𝐚𝐥𝐬 – 𝐓𝐫𝐮𝐭𝐡 𝐈𝐧𝐬𝐢𝐝𝐞™