It is estimated that organizations spend more than $37 billion annually on enterprise application software licenses alone – not including maintenance, services or other associated costs. So enterprise applications have been and continue to be huge investments for many companies. In fact, many companies have multiple ERP and CRM systems running across various divisions and business units. So you would think enterprises have all the bases covered, right? Not necessarily – a huge piece of these investments get neglected or overlooked, and that is the data that is tied to these systems.
This is the assertion of a new study from Datamonitor, which concludes that while billions upon billions are spent on enterprise application systems, organizations are not investing nearly enough resources or attention in the data that will be moving in and out of these systems.
The Datamonitor report is based on ongoing enterprise application technology market research and monitoring, as well as the results of a survey of 25 senior IT executives in the US, Canada, Western Europe and Asia-Pacific. The full report, written by Datamonitor senior analyst Vuk Trifkovic, can be downloaded here.
How could such a critical piece of enterprise applications be overlooked? Trifkovic says both enterprises and vendors alike tend to concentrate on making the applications operable, which is often a mammoth task within itself. “Given the high cost of implementing enterprise application platforms, the focus is understandably on making the applications operational, which includes change management and enterprise-wide adoption,” he observes. “With the focus on the functionality and user buy-in of new business processes, the data that support those processes are relegated to a secondary concern.”
However, the insufficient attention paid to data in major enterprise deployments may ultimately contribute to the failures of these investments, he warns. That’s because the data supported with these systems may not be reliable, accurate, or up to date. “Inaccurate, inconsistent or simply incomplete data can severely impair enterprises’ ability to understand their internal processes, customers or products,” Trifkovic states. “Without data quality procedures in place, organizations can not grasp even the most fundamental business facts.”
When organizations have attempted to respond to these challenges, it has been through custom-coded or expensive enterprise point-to-point application integration (EAI) projects. The problem is, these approaches usually come to a dead end, due to the extensive maintenance that is constantly required.
What is needed for today’s environments, Trifkovic says, is a common integration platform that can address information requirements on a consistent, enterprise-wide basis. The most immediate solutions to address this challenge – and ensure the integrity and availability of mission-critical data – are customer data integration (CDI) and master data management (MDM), Trifkovic says. “The payoffs are immediate and range from improved customer support to boosted customer loyalty, and the generation of new cross-sell and up-sell opportunities,” he says.
Trifkovic makes the following recommendations:
- Adopt a comprehensive data strategy. While data management gets plenty of attention on application rollout stages, it tends to get moved to a backburner in subsequent phases of the application lifecycle, Trifkovic says. “Enterprises need to formulate comprehensive data management and integration strategies that can deal with the issue of data in the enterprise application roll-out phase, operation phase, consolidation phase, and even in decommissioning phase.”
- Audit current data integration and management capabilities. “The role of auditing is to establish the existing maturity level regarding the flexibility, data-quality and data latency required,” says Trifkovic. “This will provide evidence supporting steps that need to be prioritized and worked out, and clues as to how to make an enterprise application platform successful.”
- “Future-proof” your data integration platform. “Elements to consider range from the current maintenance of custom integration approaches, to gauging the scale of increase in data volumes and estimating the future pace of the business,” Trifkovic advises.
- Take the longer, strategic view on data integration. Typically, the benefits perceived “are primarily tactical, aimed at making immediate improvements to processes,” Trifkovic says. “Enterprises should also take a longer view and consider how data integration platforms can create far-reaching strategic impact through business model innovations, enabled by low-latency delivery of richer data, such as fine-grained market segmentation, personalization of products and services, and better understanding of business environment variables.”
Today’s business environments tend to be highly diverse, with large assortments of enterprise systems supporting different functions and business units. However, to be competitive and effectively compete on analysis, enterprise decision makers need a right-time, enterprise view on what’s happening and what will happen within their businesses. A comprehensive data integration platform should be considered a standard component of any enterprise application architecture to provide the data movement backbone necessary for operational systems such as ERP and CRM. This will ensure that the mission-critical and operational data that businesses depend on is always current, consistent, complete, and reliable.