Enterprise resource planning (ERP) systems are often the most expensive IT investment for retail and consumer goods organizations. These applications form the digital backbone of those organization and impact all aspects of business from automating and managing day-to-day activities to integrating core systems with customer-facing processes.
But many companies today still struggle with an inflexible ERP system that is not optimized for their business. ERP systems can provide a huge payoff and benefit when enterprises have the ability to convert complex data streams into actionable information in order to optimize business operations and drive better product innovation. Companies must adopt a data management practice that enables a modern and flexible ERP system that rapidly responds to customer needs and new market opportunities.
Overcoming the Data Roadblock
One of the biggest roadblocks to expanding and updating ERP systems is often the manual process of refreshing the mass amounts of data residing within the ERP system and connected front-end technologies, such as point-of-sale systems and ecommerce apps. Manually refreshing those databases for development and end-to-end transaction testing is so onerous that most enterprises only schedule one or two refreshes a year. Consequently, development teams are then constrained to one or two ERP updates a year, or they test with old or fake data sets to increase the frequency of releases, potentially leading to release quality issues and data-related defects.
That’s where a DataOps platform can help to enable fast access to production-quality data and accelerate the frequency and accuracy of ERP updates. Through the combination of data virtualization, self-service access to personal data environments, and automated masking of sensitive information, a DataOps platform reduces the time to refresh data from months to days and provides on-demand access to production-quality data for development and testing.
Take Clorox, a consumer packaged goods titan, as an example. Clorox teams experienced delays in getting full sets of fresh, secure data, which made it difficult to keep up with SAP enhancements and new features. Testers frequently used stale data, which impacted the QA team’s ability to accurately test transactions across SAP and front-end systems, such as its ecommerce platform. Clorox adopted a data platform that allowed them to virtualize the company’s data infrastructure, reducing the time to get data for testing SAP updates and new features from 45 days to just hours. Clorox was ultimately able to accelerate release cycles, enabling IT to the company to react quicker to customer demands and make swift operational adjustments.
Similarly, German toy retailer myToys wanted to move from quarterly to daily release updates on Oracle EBS, which ran everything from purchasing, finance, and accounting to inventory management, customer service, and logistics. The ERP team was sharing only two data environments to support the 70+ Oracle projects per quarter, constraining the development process and stifling innovation. They turned to DataOps to provision virtual database copies, refresh data in hours instead of days, and generate self-service data environments with the right data and application stack for its development and testing teams. As a result, both teams worked in parallel on their personal data environments to achieve their goal of daily release updates.
Another obstacle to keeping ERP systems current with the latest innovations is the concern for data privacy. Development and testing teams need massive amounts of data to accurately test software updates and new features, but privacy policies oftentimes prohibit sensitive data from residing in dev/test environments. Without an automated way of masking sensitive information, i.e., credit card numbers, IT teams spend a huge amount of time manually obfuscating data, or developers are forced to create fake data sets. Both activities not only delay development and testing but also negatively impact the quality of software releases.
A DataOps platform that includes automated data masking can reduce the time it takes to secure data from weeks to hours. Automated masking ensures that sensitive information is turned into realistic, but fictitious data that can be used for development and testing purposes. Secure data can be provisioned and refreshed much faster, thus reducing wait times for engineering teams, compressing testing cycles, and empowering developers to deliver ERP application releases faster and with far greater predictability.
Accelerating ERP Innovation with Fast and Secure Data
IT and development teams must work together to ensure that data does not become the bottleneck to modernizing the ERP systems. This involves both process and people transformation as well as a technology like a DataOps platform that provides data virtualization, referential masking as well as self-service access to data for dev/test teams.