Looking Under the Covers to Drive Big Data Analytics

Executive Insights3 minutes readFeb 5th, 2014
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As data sources that an enterprise needs to collect, comprehend and act upon continue to grow, it is not surprising that CIO Magazine predicts that 47% of CIOs expect to complete a Business Intelligence project in the next year. If you can’t collect the right data and understand it, you won’t be able to act upon it for the benefit of your business or consumers. Although Big Data has been a key challenge for many years, the increase in mobility and the inherent requirements to access and send data from these devices has caused big data solutions to increase in priority.

Many companies possess the skills and resources internally to attack the Big Data challenge, others will look to augment their in-house tools by purchasing additional software solutions and services expertise. A good first step is to inventory and map the various data sources that need to be analyzed, the collection tools currently being used and what is being done with the data today. Companies that are already utilizing outsourcing partners for portions of their business should also leverage their expertise and additional information they can provide through the data they are gathering about their environment.

“In today’s world, productivity is the chief currency, and by applying Big Data analytics, we can enable our clients to be more productive and make better choices,” said Paul Gleeson, vice president Global Operations and Strategic Sales Support for Unisys Global Managed Services. “As an organization, we collect an enormous amount of valuable data. Using this insight, we can tell our clients which software or hardware is problematic and which is robust. We can also use Big Data to drive problem resolution down to the SKU level and hardware manufacturer.”

According to Gleeson, outsourcing providers can add real value to clients by using data in a whole new way.

“For one client, analytics showed us that contractors were 1.6 times more likely to contact the call center than employees. After digging deeper, we discovered that the cause was actually training. Onboarded employees had two weeks of training, whereas contractors had none,” Gleeson said. “By adding a process for contractor training, the company not only saved money in help desk support but also improved productivity.”

So Big Data projects don’t always require big budgets if you take advantage of resources and tools you already have in conjunction with the advancement in hardware technology that is making storage cheaper every day.

Just like many projects, continue to track and review results, make adjustments to support changing requirements and new data sources.

For more insight on this topic, read the Outsourcing Center 2014 Forecast article on On the Edge – Disruption in Big Data Outsourcing Analysis and Business Models.

Tags-   Analytics Big data Data Mining