How to Increase Data Quality for a Competitive Edge in Procurement

April 2, 2025

Procurement departments collect vast amounts of data every day. Good data quality is a core business requirement that is vital for maintaining stable operations and making data-driven decisions. Therefore, one of the key strategies for achieving a competitive edge in procurement is by increasing data quality by automating the processing of transactional documents. With the rise of automation technologies, organisations now have the tools to transform their procurement processes into seamless and efficient workflows. In this article, we’ll explore how to increase data quality in procurement by automating document processing with Intelligent Document solutions.

What Is Data Quality in Document Processing?

Data quality in document processing refers to the accuracy, consistency, completeness, timeliness, and scalability of data extracted, analysed, and utilised from documents. High-quality data is essential for automating processes, streamlining workflows, and supporting data-driven decision-making. Reliable data quality ensures that critical information is captured correctly and consistently, reducing risks and enhancing operational efficiency.

Key characteristics of high data quality in document processing include:

Accuracy: Data is correctly captured and free from errors, ensuring that extracted information reflects the original document.

Consistency: Data is standardised and maintained uniformly across systems, with sustainable practices that prevent short-term fixes.

Completeness: Data is comprehensive and meets operational requirements, with no gaps that could impact decision-making or process execution.

Timeliness: Data is captured and made available promptly, ensuring that processing and decision-making occur without delays.

Scalability: Data quality processes are designed to grow with the business, supporting increasing data volumes and evolving requirements without compromising accuracy or consistency.

By maintaining high data quality in document processing, procurement can increase efficiency, reduce errors, optimise sourcing, supplier relationships and inventory management, and better leverage data for strategic decision-making.

The Importance of Data Quality in Procurement

The procurement function is at the heart of many organisations, handling everything from supplier selection to purchase order management and payment processing. When data quality is poor, procurement processes can suffer from inefficiencies, errors, and missed opportunities, ultimately impacting the bottom line. For procurement to drive maximum value, it needs reliable, accurate, and up-to-date data. Here’s why data quality matters in procurement:

Improved Decision-Making: With high-quality data, procurement teams can make data-driven decisions that enhance supplier selection, cost negotiations, and demand forecasting. Inaccurate or inconsistent data can lead to costly mistakes.
Enhanced Forecasting: Clean and reliable data enables more accurate demand forecasting, helping procurement teams plan purchases more effectively and avoid stockouts or overstocking.
Increased Productivity: Automated systems with high-quality data reduce the time spent on manual data entry, error correction, and analysis, allowing procurement professionals to focus on more strategic activities.
Risk Mitigation: Poor data quality increases the likelihood of errors, disputes, and delays with suppliers and other business partners. By improving data quality, procurement teams can mitigate these risks and ensure smoother supplier relationships.

Common Reasons for Poor Data Quality in Procurement

Despite its importance, many procurement teams struggle with poor data quality. Here are some common causes:

Manual Data Entry: A significant portion of data quality issues stem from manual processes. Entering data by hand is time-consuming, error-prone, and often leads to inconsistencies across systems.
Unstructured Data: Procurement teams often deal with unstructured data from suppliers, such as in purchase order confirmations or contracts. This data is difficult to process, interpret, and integrate into procurement systems.
Lack of Data Governance: Without proper data management practices and governance, organisations may struggle to maintain consistent, accurate data across departments and systems.
Supplier-Related Issues:  In many cases, suppliers identify product data quality as an unnecessary cost factor and afford it a low priority, leading to incomplete or inaccurate data being provided, which can affect procurement’s ability to make informed decisions.

How Automation Helps Increase Data Quality in Procurement

The key to overcoming data quality challenges in procurement lies in automating manual processes and improving data capture methods. Automation not only increases the speed and efficiency of procurement but also ensures higher data accuracy through:

AI-Powered Data Capture: Using AI, procurement teams can automate the extraction of relevant data from structured and unstructured B2B documents like invoices and purchase order confirmations. This eliminates manual entry errors and ensures that the right information is processed quickly.
Real-Time Data Validation: Automation also enables real-time data validation, ensuring that incoming data is accurate, relevant, and conforms to pre-defined standards before it enters the system.
Streamlined Data Integration: With automated data processing, teams can seamlessly integrate data from multiple sources, creating a unified view of the supply chain. This integration reduces inconsistencies and discrepancies, improving the overall quality of procurement data.

The Netfira Platform: A Game-Changer for Increasing Data Quality in Procurement

The stream of data can be made controllable and usable by replacing the laborious and error-prone manual interface at the data creation process with an automated one. The Netfira Platform leverages automation to optimise procurement processes, ensuring data is accurate, structured, and ready for use in decision-making. As an Intelligent Document Processing Solution, the Netfira Platform is designed to significantly increase data quality in procurement. It automates the end-to-end workflow of data extraction, validation, processing and export into any downstream system. After digitally connecting business partners, the document processing workflow for each step along the Procure-to-Pay process can be flexibly defined.

How the Netfira Platform Increases Data Quality

Highest Data Accuracy: Netfira automatically captures unstructured data from suppliers with near-perfect accuracy. It converts data into a structured, usable format, eliminating errors and inconsistencies.

Data Extraction and Validation: Using advanced AI and machine learning technologies, the Netfira Platform accurately extracts data from order confirmations, invoices, advanced shipping notices and other transactional procurement documents regardless of format or complexity. The platform validates this data against predefined rules to ensure accuracy, significantly reducing errors and the need for manual checks.

Data Processing with Customisable Workflows: Once data is extracted and validated, the Netfira Platform processes the documents through customisable workflows tailored to specific business needs and contexts. Examples of this include converting units of measure, mapping reference data, or applying tolerances.

Master Data Cleansing: Netfira’s intelligent automation tool cleans up and standardises master data, improving consistency across procurement systems and reducing the risk of data discrepancies.

The Path to Superior Data Quality in Procurement: Intelligent Automated Document Processing

In an increasingly data-driven business world, procurement teams must prioritise increasing data quality to maintain a competitive edge. Automation of document processing is a key strategy for eliminating manual errors, streamlining workflows, and ensuring that data is structured and accurate. Software solutions like the Netfira Platform can help procurement departments overcome challenges related to unstructured data, master data inconsistencies, and slow, error-prone manual processes. This allows procurement teams to focus on more value-adding tasks like strategic decision-making and supplier management. By focusing on data quality, procurement teams can not only improve operational efficiency but also unlock the full potential of Big Data, leading to smarter decisions, cost savings, and stronger supplier relationships. Investing in data quality and automation is no longer a luxury—it’s a necessity for any procurement team aiming to stay ahead in the digital age.