Bedrock Acquires Procoto to Revolutionize Procurement Processes and Enhance Enterprise Supplier Management Capabilities.

The Importance of Clean Data in Supplier Management

In major industries across sectors, the vitality of up-to-date clean supplier data is crucial. Data that reflects the current reality of an enterprise can be a considerable asset, allowing businesses to make smarter decisions and improve their process. While business intelligence and data are a significant industry, according to Accenture, between 60 and 73% of data collected by an enterprise go unused.

This is because, often, the data collected is out of date, inaccurate, or irrelevant. This leaves enterprises needing to filter through vast collections of useless data to glean valuable information. For procurement and AP teams that are in charge of overseeing a massive chain of suppliers, this can cause a lot of significant problems.

Managing payments, overseeing orders, and ensuring compliance with a massive network of suppliers spanning the globe can be challenging enough; but with insufficient data, it can become near impossible to do without financial leakage. 75% of vendor master lists feature inaccurate or incomplete data that procurement and AP teams need, so the issues around clean data in the industry are significant.

To avoid supplier risk and ensure more efficient supplier management, clean data is foundational to success. In this article, we’ll break down what clean data is and why it is crucial for enterprises working with large networks of suppliers.


What Constitutes Clean Data?

Data cleansing steps

Collecting and utilizing data requires taking in a lot of information and then filtering through that information to try and gather insights. However, while this is one of the crucial aspects of enterprise success, data can frequently become irrelevant or corrupted if enterprises don’t properly clean it.

Cleaning data is when a business goes through the data they’ve collected, which in the supplier management industry, includes records of transactions and vendor master lists. Cleaning a data set involves removing duplicate data sets, inaccurate entries, incomplete data, and more to get a clearer picture of the data an enterprise is using.

The entire purpose of data is to provide actionable information to enterprises, quantifying their performance and enhancing their understanding of core processes. Data is considered clean when inaccurate, false, or duplicate details have been removed, making it much more valuable and effective.

Data cleaning is a crucial early step in the data analysis process, allowing enterprises to draw more accurate conclusions from the data they use. It is something businesses can do manually, by going through data sets and standardizing them by hand; or through automation, where enterprises use data cleaning tools powered by artificial intelligence that sort through data sets to spot errors and duplications.


The Risks of Inaccurate Data

Clean data is essential to effective decision-making, and the downsides to not having clean data are tremendous. According to the Harvard Business Review, insufficient and uncleaned data costs the U.S. economy a staggering $3 trillion yearly. It poses a serious threat to businesses that can lead to financial losses, reputational damage, and a decline in both efficiency and results. For enterprises that rely on a global supplier network, inaccurate data is an existential threat.

Master data that shows insights into an enterprise’s entire supplier network and transaction history should be easy to filter through, or enterprises risk accidentally missing some crucial details. These missed details can manifest in duplicate payments and even fraud. When you don’t have highly accurate and current data, you become much more exposed.

Not only can poor data cause a loss in revenue, but it can also lead to worse decision-making and a less-efficient business. Enterprises use business intelligence to guide decision-making, with companies analyzing data and making decisions based on the numbers. If the numbers are inaccurate, the likelihood of reaching a productive conclusion is significantly impaired.

Ultimately, inaccurate or outdated data is a missed opportunity. The purpose of investing in business intelligence is to gain a better understanding of your enterprise and use numbers to improve efficiency and create better processes. For teams handling supplier management, the risk of unclean data is that it can undo all the benefits that good data provides. That is why clean data is a foundational component of successful supply chain management.


How Clean Data Helps Enterprises

Just like unclean data has serious business consequences for enterprises that require significant supplier management, clean data has established benefits. The more clean and organized your data is, the more enterprises are able to glean from the information they collect. This leads to increased benefits that help companies create a smoother, more cohesive supply chain with improved transparency and decision-making.

The first and arguably most important aspect of clean data that procurement and AP teams appreciate is that it allows teams to spot errors and potential risks. Cleaning data enables teams to identify duplicate payments, erroneous information, and a wide range of other crucial errors that pose hazards to the integrity of a supplier network. This can allow teams to spot financial leakage and potential fraud and help them ensure their suppliers are honest and forthright.

Another important aspect of clean data is that removing outliers, duplicate information, and missing values gives enterprises data that is much more informative and useful. This empowers them with high-value insights into trends and costs that can be analyzed to create smoother, more cost-effective processes. In this way, clean data can directly positively impact an enterprise’s bottom line.

Useful data, and the ability to leverage it, have a major positive impact on a business’s bottom line. According to Forrester, data insight-driven enterprises grow at an average rate of 30% annually. With clean data, enterprises can make better decisions, increase efficiency, and cut costs, contributing to better overall performance.


Why Now is a Pivotal Time to Focus on Data Cleaning

If you haven’t cleaned your data in a while and are relying on outdated or ineffective data, there is no wrong time to take the steps necessary to improve. But right now is a time when many enterprises reliant on significant global supplier networks are taking steps to clean their data and ensure their information is up-to-date. This is because there have been massive disruptions to the supply chain that have created an entirely new environment for enterprises to navigate.

The pandemic dramatically altered the global supply chain, and the subsequent great resignation also caused a lot of turnover. According to data from SHRM, 48 million people quit their jobs in America alone, the highest number on record. For vendor management teams, this means that many of the vendors and suppliers that they partnered with in the past have either dealt with substantial changes or might not even exist anymore.

This is a big reason businesses must clean their data to align with modern realities. The more current data is, the more applicable it will be to the contemporary problems AP and procurement teams face. There is no wrong time to focus on cleaning data, but right now is a critical time to ensure data is as up-to-date, relevant, and useful as possible.


How Bedrock Helps Provide Clean Vendor Data

For enterprises that want to ensure the highest quality data while overseeing supplier management on a centralized platform, Bedrock is a high-impact solution. Bedrock is a cloud-based software with an array of features with customization capabilities that makes it fit various needs for AP and procurement teams.

The Bedrock system has data tools that ensure businesses can access clean, up-to-date data on their vendors and financial situation. The Cornerstone Cleanse tools provided by Bedrock are a centralized hub for data that companies can use to validate and clean their data to ensure they are using accurate data insights to guide their decision-making. The Cleanse software can spot duplicate data, incomplete data, and unverified data; so enterprises are aware of when they may be relying on information that is either erroneous, incomplete, or outdated.

Data that is inaccurate and not current can cause enormous problems for enterprises and eliminate the benefits that business intelligence is supposed to provide. With Bedrock’s Cornerstone features, AP and procurement teams can have a central source of truth where they can have absolute confidence that the information is valid and up-to-date. Clean data is necessary for supplier management, enabling businesses to develop more efficient processes, cut costs, and make informed decisions. With Bedrock, organizations can have clean, verified data that provide up-to-the-minute information in a constantly evolving world of supplier management.