Data quality is a big problem for businesses. A recent Gartner survey found that organizations estimate the average cost of poor data quality at $12.8 million per year. That’s a lot of money spent on lost customers and revenue opportunities all because of bad data. There is something you can do, though. In this topic, we’ll be discussing why it’s not enough to employ the SYSPRO ERP system in your business; you must also safeguard the integrity of the system’s data to protect your business’s future growth and success.
A Team’s Approach to Data Integrity
Maintaining data integrity is a continuous process that supports system health and empowers organizations to make better, more informed business decisions with their data. Value comes from the accuracy and consistency of an organization’s data, and, without that, the data is worthless. You can’t make strategic data-driven business decisions that meet your goals and objectives if they’re based on dirty data. You’ll end up making major decisions based on “intuitions” and “best guesses”, putting your company in a precarious position. According to an Experian report, this is the sad reality for most businesses because 95% of organizations see negative impacts from poor data quality, resulting in wasted resources and additional costs.
Managing a successful data update with your SYSPRO ERP system is more than a one-person job. You’ll need to set up a migration team and involve your Quality Assurance staff in the process. They can make sure all the quality standards are met throughout the process. This may sound intimidating, but if the migration team follows pre-defined checklists and procedures, it’ll help ensure no critical steps are missed and the project is a success. Involving staff will also help create a data-driven culture, mostly because they’ll be better able to understand the connection between better business decisions and accurate data.
The Whats, Whys, and Hows
When planning for a data update initiative, you should first understand what your SYSPRO’s data architecture is. SYSPRO 8 is entirely SQL-based, whereas SYSPRO 7 and earlier versions can be a hybrid of a SQL and CISAM database or strictly a CISAM database. In general, SYSPRO’s data tables are tightly integrated and have many dependencies. A fulsome inspection and analysis of your data architecture and all its intricacies is definitely a requirement before any data updates are done.
The user needs to be very careful when importing data. They must know why it’s important that all data relationships are considered and then follow through on that understanding by carefully mapping each of these relationships out. Otherwise, you run the catastrophic risk of destroying valuable data you can’t recover, or, at the very least, creating an even more time-consuming and complicated data mess. Data sources should be verified, and data validated before any imports are done. Before the update, double check to make sure no critical data is missing by discussing and triple-checking that all the necessary data is accounted for in the transfer.
Finally, how to ensure a successful data update is by thoroughly investigating and examining the data migration requirements. Complete a full review of the migration details and create a data migration strategy so that a shoddy experience doesn’t create more problems. A review of your existing data will discover inconsistencies and help you weed out obsolete and redundant data. Be selective in what historical data you want to keep. Not all old data needs to be readily accessible or is beneficial to your business moving forward.
Cleaning Your Data
Any ERP is only as good as the data it contains. If you have flawed business data, you can’t make educated business decisions no matter what best-in-class ERP system your business has. Fixing typos and the likes is a $4.5 billion market and are just one crucial part of managing your data to guarantee accuracy. Develop and maintain consistent and defined structures and formats for data sets. For example, only allow entries of ‘Street’ and restrict entries of ‘St’ or ‘St.’, or don’t allow null values, or only allow a specific number range of between 50-65. Once you have data collection best practices in place, maintain it going forward to avoid having to go through the process of cleaning up faulty data sets again. Cleaning dirty data takes time and resources but it’s worth it so you’re not making major business decisions on erroneous and unfounded data.
There are tools out there to help you achieve proper data validation so you can have quality and clarity in your business data. Quantum Architecture is an export/import tool that should be used to ensure valid data. We don’t recommend importing directly into the SQL, as no data validation occurs this way. Many companies use Excel or Report Writer to extract data as well. Whatever tool you choose for your data validation, make sure it’s the right choice and you understand how it works.
There are a lot of things to consider before jumping head first into a data update initiative. Talk to a BT Partners’ specialist to help you get started on creating a successful data migration strategy for your business.
