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Analytics: one size does not fit all

By Tracy Burrows, ITWeb contributor.
Johannesburg, 27 Nov 2012

ITWeb Business Intelligence Summit 2013

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Categorising all business analytics tools under a single umbrella can lead to confusion, says PBT Group CIO Martin Rennhackkamp.

There is confusion in business over what business analytics should include, what is needed at each stage of a business' maturity, and what can be done with advanced analytics results once they have been collated, says Rennhackkamp.

"There are many classes of analytics - for example, data exploration (exploring and analysing to discover trends and patterns), conventional analytics (reporting and dashboards), and advanced analytics. Now that vendors are bringing to market advanced analytics products capable of predictive forecasting, segmentation and classification, businesses may find it difficult to interpret these new numbers and act on them."

Rennhackkamp explains that advanced analytics tools generate numbers based on complex formulas. "If they are correctly interpreted and applied, they can be very valuable."

For example, he says, a telco may use these tools to predict customer churn before a customer has indicated he or she intends to move to the opposition. How? Rennhackkamp explains that in some countries, there is a clear pattern for a customer to move to the service provider his or her friends are using.

"Which service provider friends are using can be determined by what numbers a user calls most. In one country, for example, we've determined that if there is an increase in the number of calls a user makes to numbers of another service provider, there is a high probability the user will change to that service provider within a month. By monitoring these trends, interpreting them correctly and acting on them - say by offering a new deal to that customer - the service provider can reduce churn."

However, he notes, patterns and trends are different by demographic, region and country. "What some vendors try sell is black box analytics, but effective advanced analytics needs to be tailored to the type of data you work with."

Rennhackkamp says there has been significant uptake in the use of advanced analytics. However, the skills needed to correctly interpret and act on the information these tools generate depends on skilled data scientists and close collaboration between them, IT and business.

To capitalise on the benefits of advanced analytics, companies need to be willing to adapt their business strategies, he says. "They should have in place business strategies for how the company will act on any results that emerge, in order to act quickly on findings. They might even get surprising results they didn't plan for, and may have to change their plans on the fly."

While advanced analytics may deliver a wealth of information, it is not necessarily the right solution for every company, Rennhackkamp says. "Whether you need data exploration, conventional analytics or advanced analytics depends on the business' level of maturity, strategic goals and requirements.

"Business needs to cut through the vendor hype and identify where its growth path is and what specific features it needs now," he says.

Rennhackkamp will discuss the types of analytics tools and their uses at the upcoming ITWeb BI Summit. For more information about this event, click here.

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