Philips Healthcare Contivo Case Study - Liaison Technologies

In its Healthcare division alone more than 60,000 business messages are generated every ... invoice the customer, the project management team to ensure the MRI ... and unsupported TIBCO software forced Philips Healthcare to take action.
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CASE STUDY

Liaison Technologies Helps Philips Healthcare Effortlessly Map and Migrate Data Across the Organization

In today’s global marketplace the ability to seamlessly share vast quantities of data across the various departments in different continents is critical to maintaining competitive advantage. When a leading healthcare organization also needed to migrate to a new middleware platform such as SAP PI, the process of moving existing data transformations to this platform had to be as invisible to the users as possible. This dual-scenario proved true for Philips, one of the world’s most recognized manufacturers of healthcare, lighting and consumer lifestyle products. At Philips, making data generated by its 116,000 employees in more than 60 countries readily accessible, easily useable and quickly actionable by the rest of the organization has been a strategic intent for many years. It’s no surprise that the company’s motto, which rang true when the company was founded over 120 years ago as it still does today, is to provide ‘sense and simplicity’ to its users.

Quick Facts Company Philips Healthcare www.healthcare.philips.com

Industry Healthcare and Patient Care Technology Products

Every Cog is Vital

Liaison Solutions

Being such a large company Philips creates and manages data on a massive scale, moving it between numerous divisions and across multiple departments and applications.

Liaison Contivo®

In its Healthcare division alone more than 60,000 business messages are generated every day in different parts of the organization. For example, when a new MRI system is sold and an order created, it sets off a chain of messages that impacts many departments. This could include the sales team specifying the order, the manufacturing team tasked to build the system, the buying team required to source the components, the finance team to issue and invoice the customer, the project management team to ensure the MRI system is delivered and installed at the customer’s site, and so on. It takes just one cog in the data-mapping machine to slip for problems to surface, problems that ultimately impact overall process efficiency and operating profit. As a result, ensuring that data is accurately mapped between all departments at Philips is a big priority.

Data Mapping Challenges Philips Healthcare had initially been using a TIBCO-based enterprise application infrastructure (EAI) as the backbone for its business. After more than 10 years, new middleware requirements and unsupported TIBCO software forced Philips Healthcare to take action. To address this, Philips upgraded to a newer TIBCO platform, together with a new canonical model to enforce a single XML-based structure for its data. However, with the new TIBCO platform, Philips found challenges in its existing way of developing data-mapping that needed to be resolved. Hans Sloots, EAI Consultant for Philips’ Healthcare division, explains: “After upgrading to an XML environment, we found that our process of mapping, writing a mapping specification in Excel and then coding it, was not good enough. We often found that mapping specifications

Case Study: Philips Healthcare

and mapping coding were not in sync. We needed a new solution that could not only better define our maps, but could remain flexible enough to transfer them to new middleware platforms as and when they are introduced.”

IT Environment

Transforming data with Contivo®

• MobiMedia sales tool

The team’s search quickly led them to Contivo, a data transformation and integration tool from Liaison Technologies. Unlike most other mapping solutions, Liaison applies artificial intelligence to the mapping process which means it can, based on any situation, automatically suggest the best mapping option available. This drastically cuts down on the time previously required to complete error-free mapping manually.

• Tra