Maximising the business value of JD Edwards applications.

JD Edwards is a middle-market Enterprise Resource Planning (ERP) system, primarily designed for small to medium-sized businesses (SMBs) who want a full integration suite linking applications for different processes from order-to-cash to procure-to-pay to financial supply chain management.

Organisations rely on JD Edwards applications to support day-to-day operations and manage the business processes that drive revenue opportunities. However, increased business growth and the accumulation of customer transactions have generated exponential data growth that can degrade application response time, negatively affect customer service and raise operational costs.

This article looks at how businesses can manage continued data growth and maximise the business value of JD Edwards applications.

Effects of Data Growth

The use of ERP systems by businesses leads to an escalation in transaction processing. The resultant data growth can negatively impact on the service and support that companies offer. The effects can slow application performance, strain financial and technical resources and jeopardise the timely completion of business-critical processes.

Most JD Edwards solutions do a effective job of keeping track of the transactions they generate. However, they are not specifically designed to manage the large quantities of data that are created as a result. Typically, they simply retain it within their existing table structure.

As a result, data growth is not properly addressed. In many JD Edwards systems, application degradation is becoming an increasingly important concern. The more a business' databases expand and the more data they store, the more the performance of the applications they support degrades.

Within months of the implementation of solutions, companies are often struggling with performance issues. Database enquiries typically become cumbersome and slow as systems scan entire tables and indexes to find data. The consequent delays are unacceptable, particularly in busy sales environments where swift responses are critical.

In addition, businesses often suffer from increasingly slow batch program scanning. This means that it may take them as many as eight days to complete their month-end closures.

Inefficiently managed data growth also has serious cost implications. Historically, businesses have incurred significant costs either through having to invest in the additional servers and central processing units (CPUs) needed to manage this extra data.

However, implementing upgraded infrastructure does not make it any easier for them to anticipate from where surges in demand are likely to come. As a result, enterprises that traditionally would have bought more storage to solve their data growth problem can no longer budget accurately for additional IT infrastructure and hardware to satisfy their storage needs.

Making The Right Choice

So how can JD Edwards customers address these data management issues more effectively? The traditional approach has been to increase spending on expensive software, servers, databases and storage.

This common response may resolve constraints temporarily, yet even frequent performance tuning and upgrades do not address the underlying problems of an overburdened IT infrastructure. Typically, over the long-term, users will have to invest continuously in storage upgrades in order to keep pace with data growth rates.

A much more effective approach to data growth is to use secure archiving as part of a co-ordinated enterprise data management (EDM) strategy.

Reducing the amount of information in the production database means that less disk space is required for application data, cutting the costs of storage. And as there is less information to sift through, operations run more efficiently and organisations derive more business value from mission-critical applications.

Reducing pressure on the production database enables users to speed their applications and compression allows them to reduce their data footprint. This, in turn, allows businesses to significantly reduce spend on costly nearside storage.

Data within the archive remains visible to the application and can still be accessed by JD Edwards users when required but, because it uses less expensive storage, it is much cheaper to retain than it would be if kept within the production database.

This type of EDM strategy can be applied right across an organisation independent of application, database or infrastructure. For JD Edwards users, it is typically implemented on a modular basis across different functions in the organisation.

Use of EDM techniques has been shown in practice to reduce month-end closures from eight days down to three for many organisations and to improve batch processing rates by up to 80 per cent. At the same time, productivity, supply chain efficiency and customer service levels can be dramatically improved.

There are also significant benefits from a compliance perspective. Data within a live production environment can still be accessed modified and changed. However, once it has been archived, it cannot be altered or modified. In compliance terms, it is audit-ready. A well-executed EDM strategy ensures that all referentially integral information is maintained within a given archive file.

Reducing the Multiplier Effect 

EDM can also help to address the 'multiplier effect'. The rapid growth of application data in production systems is replicated across all "cloned" environments, typically including the development, quality assurance and staging functions. Most users will have between 3-10 copies of the live production database stored in non-production environments.

EDM allows companies to take a proactive approach that addresses the challenges of the multiplier effect, without diverting additional resources from IT business initiatives.

By implementing archiving to segregate current from historical transactions and moving the data to a secure archive, businesses can effectively maintain application databases at a manageable size.

Test Data Management

EDM can also be used to ensure the privacy of data within test environments. Using production data to create realistic test databases can result in a violation of privacy laws if adequate steps are not taken to protect the data.

The effects of this type of violation can be devastating for a company, resulting in negative publicity and erosion of customer confidence, or worse, fines or even imprisonment.

Masking and de-identification techniques ensure efficient and secure use of confidential information in the application testing environment. Data de-identification enables developers and testers to use realistic test data and produce valid test results, while still complying with privacy protection rules. And because it has been masked the data is useless to thieves.

Upgrades and Decommissions

Another area in which EDM solutions can maximise the business value of JD Edwards applications is through the critical process of running system upgrades. Users often find that during the upgrade process their existing database will more than double in size because there will typically be a temporary increase in the data of about 60%. On top of that, the requisite unicode conversion process will typically add a further 60% growth.

As a result, best practice is to archive data before beginning the upgrade process otherwise the process can be extremely time consuming and potentially disruptive to the business. One of our customers recently took 36 hours just to upgrade one table within their general ledger. By archiving prior to the upgrade process, businesses can reduce the amount of data that needs to be upgraded and crucially also the time window required to complete the upgrade itself. The result is the whole process becomes cheaper and more manageable, reducing both the impact on the business and the level of risk involved.

Another important application of EDM in JD Edwards environments is for decommissioning. Many users retain their old systems when they upgrade to the latest version. They keep the old version of the software typically because they are still running reports on it and because it still contains some data that they want to review periodically. By doing so, they waste time and resources and incur significant costs.

EDM enables businesses to take data off the legacy systems, delete older versions of the software but still retain the integrity of and the relationships within the original data model.

Bright Future Ahead

Today, greater numbers of JD Edwards users are appreciating the benefits of enterprise data management. The EDM market is still in its infancy but, once prospective customers view the systems in action, they rapidly see the benefits that EDM can bring right across their organisation and, in particular, the way in which this technology can align business and IT issues in the area of data management.

EDM can be applied successfully across any size of organisation. Including routine archiving as part of scheduled application and database maintenance procedures provides ongoing control for managing data growth, enabling businesses to meet performance targets consistently while ensuring data privacy and providing superior customer service.

Rob Boden, Optim Solutions Consultant JD Edwards--EMEA