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SmartData Collective > Uncategorized > Guiding Call Center Workers to Data Quality
Uncategorized

Guiding Call Center Workers to Data Quality

SteveSarsfield
Last updated: 2009/05/21 at 7:10 PM
SteveSarsfield
5 Min Read
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Data Governance and data quality are often the domain of data quality vendors, but any technology that can help your quest to achieve better data is worth exploring. Rather than fixing up data after it has been corrupted, it’s a good idea to use preventative technologies to stop poor data quality in the first place.

I recently met with some folks from Panviva Software to talk about how his company’s technologies do just that. Panviva is considered the leader in Business Process Guidance, an emerging set of technologies that could help your company improve data quality and lower training costs on your call centers.

The technology is powerful, particularly in situations were the call center environment is complex – multiple environments mixed together. IT departments in the banking, insurance, telecommunication and high-tech industries have particularly been rattled by many mergers and acquisitions. Call center workers at those companies must be trained where to navigate and which application to use to get a customer service process accomplished. On top of that, processes may change often due to change in regulation, change in corporate policy, or the next corporate merger…


Data Governance and data quality are often the domain of data quality vendors, but any technology that can help your quest to achieve better data is worth exploring. Rather than fixing up data after it has been corrupted, it’s a good idea to use preventative technologies to stop poor data quality in the first place.

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Challenges Data Analytics Can Solve in the Call Center Industry

I recently met with some folks from Panviva Software to talk about how his company’s technologies do just that. Panviva is considered the leader in Business Process Guidance, an emerging set of technologies that could help your company improve data quality and lower training costs on your call centers.

The technology is powerful, particularly in situations were the call center environment is complex – multiple environments mixed together. IT departments in the banking, insurance, telecommunication and high-tech industries have particularly been rattled by many mergers and acquisitions. Call center workers at those companies must be trained where to navigate and which application to use to get a customer service process accomplished. On top of that, processes may change often due to change in regulation, change in corporate policy, or the next corporate merger.

To use a metaphor, business process guidance is a GPS for your complicated call center apps.

If you think about it, the way we drive our cars has really improved over the years because of the GPS. We no longer need buy a current road map at Texaco and follow the map as far as it’ll take us. Instead, GPS technology knows where we are, what potential construction and traffic issues we may face – we simply need to tell it where we want to go. Business Process Guidance provides that same paradigm improvement for enterprise applications. Rather than forcing training on your Customer Service Representatives (CSRs) with all of its unabridged training manuals, business process guidance provides a GPS-like function that sits on top of those systems, providing context-sensitive information on where you need to go. When a customer calls into the call center, the technology combines the context of the CSR’s screens with knowledge of the company’s business processes to guide the CSR to much faster call times and lower error rates.

A case study at BT leverages Panviva technology to reduce the error rate in BT’s order entry system from 30% down to 6%, an amazing 80% reduction. That’s powerful technology on the front-end of your data stream.

Covering the world of data integration, data governance, and data quality from the perspective of an industry insider.

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TAGGED: call centers, csr, data quality
SteveSarsfield May 21, 2009
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