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Organizations worldwide often struggle with a data paradox. They often feel ill-informed about their customers, prospects, inventory, suppliers and products. They are pressed every day to react to changing market conditions, a more mobile customer base and an increasingly dynamic trading network. Some global companies are even unable to determine exactly how many employees they have.
However, even as companies struggle with an incomplete view of business-critical functions, companies are receiving more and more information via every conceivable venue. A 2008 IDC study found that by 2011, there will be 1,800 exabytes of electronic data in the world – about 1.8 zettabytes or 1.8 billion gigabytes.1 Even as this avalanche of data reaches the enterprise, the reality for most of these organizations is simple: “more is less.” More data is arriving at an organization, but they are less prepared to turn it into meaningful information.
Over the past 15-20 years, companies have attempted to manage this deluge of data and create a more efficient culture by implementing enterprise applications to manage different aspects of the business. The two most common – customer relationship management (CRM) and enterprise resource planning (ERP) – are increasingly relied on to manage customer data and supply chain data, respectively.
In a vacuum, these applications will work “as advertised” by helping maintain and control a segment of the businesses. Where CRM, ERP and other enterprise systems fail, however, is that companies do not operate in a pristine, unaffected environment. They install multiple CRM or ERP packages for different business units and divisions.
Organizations acquire new organizations – and all of the legacy data from these new business units. Data entry is sometimes hurried, and there is little, if any, training for employees charged with collecting information. The result is a chaotic, disparate and disjointed view of the enterprise. The answer for most organizations is to consolidate, migrate and modernize, expecting that a more coherent view of the enterprise will emerge if the data is centralized onto few applications. But while moving to a smaller number of applications will have incredible benefits, it also poses incredible risks. Companies who have already done major data migration or consolidation work often struggle with:
All of these issues have the same root cause: inconsistent, unreliable and inaccurate data in the source systems that is capable of polluting the new application. This white paper will examine how data management technology can solve these issues through a three phase process:
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