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Avoid an ERP Project Failure by Starting With Clean Data

Enterprise Resource Planning (ERP) systems are crucial for any business to manage operations and improve productivity. ERP software helps organizations streamline processes, increase performance efficiency, and gain a competitive edge.

By SourcePro Infotech Pvt. Ltd.Published about a year ago 5 min read
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Enterprise Resource Planning (ERP) systems are crucial for any business to manage operations and improve productivity. ERP software helps organizations streamline processes, increase performance efficiency, and gain a competitive edge. However, implementing an ERP system can be challenging, and many projects fail due to poor data quality.

Even if you have invested months in developing an ERP project – from selecting the right product to identifying the ideal work processes, you could still run into a major failure if you do not clean your data as a part of the project planning.

It sounds terrifying, but you can surely avoid ERP project failure by starting with clean data!

What is Data Cleaning?

Data cleaning is the process of preparing data for analysis.

It involves identifying and correcting inaccurate or incomplete data, filling in missing values, and transforming data into a standard format. It is also known as data scrubbing or data cleansing.

Why is Data Cleaning needed?

Data cleaning is an essential step in the data analysis process because it ensures that the data being analyzed is accurate and complete.

For organizations with large datasets, data cleaning is crucial. It can help reduce errors, improve the analysis’s accuracy, and ensure that the data available is consistent and easy to interpret.

Data cleaning includes what?

The data cleaning processes typically include data validation, standardization, deduplication, aggregation, and normalization. It also involves the removal of outliers, correcting invalid data, filling in missing data, and dealing with data inconsistencies.

What is GIGO?

Often in the data analytics world, we hear the term “GIGO,” now, what is that?

GIGO is an acronym for “Garbage in, Garbage out.”

Any analysis using your sub-par data will produce flawed and chaotic results. No matter how meticulously you follow every other step of the data analytics process, if your data is a mess, you won’t get anything out of it.

For this reason, data cleaning is vital because you should first clean the garbage to build a solid and long-lasting foundation.

What areas of your ERP system need to be cleaned?

The following are some areas that you should consider when cleaning your data:

• Outdated, inconsistent customer data

Unreliable, outdated, and inconsistent customer data- Remove it! Companies must ensure that customer data is up-to-date and accurate to prevent errors. Organizations risk making decisions based on inaccurate data without proper data cleansing, leading to faulty business strategies.

• Remove outdated product codes

Old product codes can be difficult to track and not give a clear picture. It also creates confusion about stocking up on supplies and leads to poor decisions.

• Unentered data in the legacy system

Unentered data gives an incomplete scenario and thus impacts efficiency. As such, data cleansing should be a priority when dealing with legacy systems.This is crucial to ensure data accuracy and reliability.

• Duplication of data

Duplicate data causes major problems when it comes to analysis and reporting. It gives a wrong status which ultimately results in drawing incorrect conclusions. It is essential to ensure data is clean and free of duplicates before it is used for analysis or reporting.

• Vendor information update

Updated vendor information, customer profiles, financial records, and other data must be accurately entered into the system to save time and effort at a later stage. Also, cleaning the data regularly by removing old information can ensure data integrity, improve efficiency and reduce the risk of errors.

• Update closed purchase orders

It is necessary to update closed purchase orders in your ERP systems. It ensures accuracy while giving real-time insights of the account. Moreover, regular data audits help identify any discrepancies or issues with the data before they become a bigger problem.

• Incomplete data fields

When data fields are incomplete, it hampers the decision-making process. Completing the data fields or removing half-filled information makes identifying issues and developing effective strategies easier. Additionally, it reduces costs and time associated with data analysis.

Once the data is clean, enterprises should ensure that their ERP system is configured correctly by following the stages of a successful ERP implementation. Then, companies can move forward with their ERP project smoothly.

Which are the effective tools for cleaning data?

Data cleaning tools are specifically designed to clean data and make it ready for ERP system implementation. These tools aid in removing any discrepancies or errors in the data to ensure consistency and accuracy.

Microsoft Excel

Microsoft Excel has been a staple of computing since 1985. To this day, it remains a popular data-cleaning tool. Excel has many built-in functions for automating the data cleaning process, such as de-duping and replacing numbers and text, blending rows and columns, and combining data from multiple cells.

Programming languages

Most data cleaning processes are automated using scripts. For large, complex datasets, batch processing often requires writing your own scripts (without end-user interaction). The most common programming languages are Python, Ruby, SQL, and R (for the technically inclined). Also, there are plenty of ready-made data cleaning libraries in Python, such as Pandas and NumPy, that can speed up the process.

Visualizations

Visualizing your dataset can be a great way to spot errors. Using a bar plot can help you visualize unique values and identify a category that has been labeled in multiple ways. Scatter graphs can also be used to identify outliers so that they can be investigated deeper and removed if necessary.

Proprietary software

With proprietary software, many companies are cashing in on the data analytics boom. Software like this is aimed at making data cleaning easier for non-data experts. Since there are tons of applications, including the popular ones OpenRefine and Trifacta.

At SourcePro, we strive to ensure your ERP system runs quickly and efficiently. We are committed to providing the highest quality of service and support. Our team of experts is available to answer any questions you may have and provide assistance throughout the entire process.

Contact us today to learn more about our comprehensive ERP software solutions and get started on the path to success.

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About the Creator

SourcePro Infotech Pvt. Ltd.

SourcePro is a synergised team of highly skilled industry experts with the aim of optimising businesses through advanced ERP software solutions.

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