Monday, 31 January 2011 17:00

Data Management Best Practices That Don't Cost Bank

By Data Flux
- Sponsored Editorial -
Coming off a rough few years for businesses all over the world, it's no surprise that we're all concerned about maximizing our financial recovery as quickly as possible. With that in mind, companies might be tempted to avoid investing in what they perceive to be 'luxury' IT solutions for fear that they won't see immediate ROI.

For some reason or the other, data quality and management is considered by some as a 'nice-to-have,' not a 'need-to-have,' and the result is that businesses are losing money and making decisions based on faulty, error-ridden information. This has a broad effect on more than just storage or ERP - bad data jeopardizes customer relationships, ruins marketing campaigns, gets companies audited for compliance violations and sabotages their competitive advantage, and that's just the beginning.
Companies looking for ways to invest in data management solutions don't need to worry about spending unreasonable quantities of money for over-the-top stacks of applications, half of which aren't even necessary. One way of thinking about data management in the near-term is to borrow a phrase from green initiatives - reduce, reuse and recycle. 
Essentially, IT and business groups should try to do some version of these to maintain the integrity of their operations and relationships.
Reduce refers to a reduction in the number of enterprise applications that an organization has to manage.  This is critical as companies attempt to modernize operations on more cutting-edge platforms, but it has a couple of side-benefits that may be more important than a system-wide upgrade.  For IT staff, a streamlined application footprint helps drive down the costs of supporting business systems.  For the business side, fewer applications mean less data spread throughout the organization.  This has the benefit of cutting down on confusion while also empowering line employees to make smarter day-to-day decisions.
Reuse evokes a strategy of taking existing data management initiatives and pulling them forward to the future.  For example, many companies have already started data management initiatives - a manufacturer undoubtedly has started to untangle data issues in the supply chain, while a telecommunications company should be hard at work on customer data issues.  A smart strategy is to reuse the gains from these initial efforts in the future.  The rules, processes and procedures for collecting, managing and archiving data can be created once and used repeatedly.  This has the effect of making data management an instrumental part of daily business - and can increase the consistency, accuracy and reliability of data throughout the enterprise.
Recycling indicates that the entire data management program can be thought of as recycled ideas from past efforts in other areas.  This is not groundbreaking business advice.  A company spends money to maintain and manage corporate assets like fleet, buildings and production equipment.  Data is the one asset that every company has - but not every company takes full advantage of their data.  Ideas like Six Sigma and Total Quality Management have been popular ways for introducing quality into any business discussion.  Why not recycle those ideas and extend them to the information that drives business?  In this sense, recycling keeps you from creating data garbage.  And that's one less thing you have to throw out.


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