Product data is more important now than ever before. Of course it's always been
important. It's been the basis of all types of sales, inventory and manufacturing
systems since the beginning of IT. But now, with the advent of SOA and a wide
range of ever-broader business requirements, having the right product data in
the right form at the right time is more important than ever before. In addition,
it can't be just any product data - it has to be consistent, reliable and accurate.
For most organizations, that's no easy task.
Let's take a closer look at the issue of product data reliability and business
needs.
At the same time that organizations have been expanding their use of SOA, the
business needs for accurate and reliable product data have expanded. Changes
in online commerce, multi-channel commerce, globalization, in-store systems
and even business intelligence and more sophisticated merchandising systems
have all driven the need for greater accuracy and reliability from the data
flowing through, and created in, an organization.
An organization's ability to use data, such as product data, effectively can
have a big impact on everything from the cost of operations to an organization's
ability to react quickly to market changes. Incomplete or unstructured data
can prevent effective communication and reduce the effectiveness of SOA strategies.
Most organizations have product information flowing in from a wide variety
of outside sources, including: supplier portals, manufacturer feeds, merchandizing
information, legacy systems and much more. Frequently the data sources include
hundreds and even thousands of different manufacturer feeds in different formats,
describing different types of products, with a huge range of variation. "Standards"
for product data depend on what type of product you're talking about. For example,
resistors have a different "normalized" schema than motors or handbags-different
attributes, different validations, different vocabulary, different abbreviations,
etc. In order to manage product data effectively, and organizations needs to
be able to address and react to all those different requirements. You also need
to be able to integrate and consolidate that data in way that makes sense.
As a result, product data integration requirements are almost everywhere. Integration
(and consolidation) of product data is also required for a wide variety of increasingly
critical front-end and back-end functions. For example, in retail, integrated
and rationalized product data is required for guided search and navigation capabilities,
product data enhancement, multi-channel consistency, customer catalogs and other
requirements. In distribution systems it's required for inventory consolidation,
quote matching and more.
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