As we illustrated in our whitepaper, implementing an ERP solution that embodies the functionality of all of the systems it is intended to replace is next to impossible. It takes creative problem-solving and a little bit of luck to emerge successfully from one of these massive projects. An important area of focus when deploying a modern ERP system is legacy data archiving. Solving the problem of what to do with the data locked into the old systems you're trying to get rid of can be more complex than you might think.
Do We Really Need to Consider Legacy Data Archiving?
The short answer is 'yes you do'. In the United States, for example, modern regulatory requirements such as Sarbanes Oxley (SOX), PCI DSS, and state healthcare regulations tied to HIPAA require the secure retention of historical data over much longer time frames than you might expect. For example, patient data in Massachusetts must be retained for 30 years in some cases. Aside from compliance standards, historical data can be a risk mitigation tool. If your company has a product recall or legal action against it, easily accessible legacy data could mean the different between months of research or winning a case in court.
Common Solutions to the Legacy Data Archiving Conundrum
Many companies opt to retain pieces of legacy systems to run alongside their new ERP deployment to meet retention requirements. Unfortunately, this strategy is expensive and comes with a very high total-cost-of-ownership. The most obvious solution- making the archived data accessible via the new ERP system- is incredibly cost prohibitive as well. Administrators see the retention of mainframes for historical data access as a 'lesser of two evils'. Although costly, the effort required to shift the legacy data and applications that support it to the new ERP deployment requires a great deal of effort. Retaining the mainframe requires less up-front effort in comparison, so it is the most chosen route.
A Smarter Alternative
Fortunately, legacy modernisation companies offer automated methods to easily migrate pre-relational data to a relational database. In many cases, the applications that use the archived data can also be transformed to a modern code base to enable the organisation to access it natively without the crippling cost of retaining the original mainframe infrastructure and with less effort than cramming it into the new ERP environment.
By moving the underlying data and supporting apps to a secure, searchable archive and decommissioning the original system, the reliance on expensive legacy IT skills is eliminated and mainframe support and maintenance costs disappear. Archiving can also increase productivity and service levels by providing fast, easy access to data whilst eliminating the need for new users to learn how to extract information from old, unfamiliar systems. Furthermore, compliance obligations are fulfilled because data can be archived in a read-only, tamper-proof format and archive rules can be created to automatically delete data at the end of its life.
Under the Hood: Advanced’s Solution
Database migration and application conversion follows a well-defined process that includes the collection and automated inventory, analysis, and measurement of the software and database components collected from the customer environment. The assessment begins with a requirements gathering session and ends with the presentation findings and a plan regarding the environment and the modernisation effort. Iterations of re-collection and re-assessment are a normal part of this phase, as additional components are identified and brought into the assessment scope through analysis. This assessment process is 100% automated, so it is fast, simple, and comprehensive.
The resulting relational database definitions and supporting applications are deployed in a Advanced test environment prior to delivery to the customer to ensure that the generated code is syntactically correct. Workbenches for date type handling allow the new databases and applications to take advantage of all of the “date and time” data types in the relational database as well. The legacy database definition can be re-collected and refactored anytime throughout the project life cycle, preventing the need for freezes on changes to the legacy database structure.
To learn more about legacy data archiving with Advanced, check out our whitepaper: Archiving Data for ERP Deployments.