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Key considerations for SMEs that want to use big data & analytics

Aug 15, 2018
Key considerations for SMEs that want to use big data & analytics

SMEs are starting to appreciate the value of using big data for making informed business decisions and understanding customers’ needs.

While the idea of having data that enables you to make better decisions may sound appealing, not many SMEs are equipped to run systems or an office dedicated to this function, hence the outsourcing of this function is a trend that is on the rise.

Dr Yudhvir Seetharam, Head of Analytics at FNB Business is of the view that while the benefits of using big data and analytics is inherently important for SMEs, however the decision must make sense.

Dr Seetharam shares key questions that SMEs should consider before enlisting data and analytics:

Am I willing to pay big bucks – SMEs that want an in-house resource for this function must understand why they want to do so. If the long-term view is to become a data-driven organisation, the short-term pain of hiring an in-house team will outweigh the future costs.

Leveraging good data - The value of analytics is primarily dependent on the quality of big data, amongst other things. If data is not available or of good quality, this will most certainly impact the quality of the result.

Objectives – SMEs need to clearly match their business objectives with their data strategy.  Even though data and analytics have become buzz words, it’s important for SMEs to be crystal clear prior to adoption this function.

Data ownership – Whether you in-source or outsource the data and analytics function, you need to be clear about the ownership of the data set.

“The benefits and disadvantages of outsourcing need to be carefully weighed against what the business wishes to achieve. We are in the age of information, with various permutations of ‘internets of things’ on the rise, businesses must question when and how to move from the traditional way of doing business to digitalising themselves,” concludes Dr Seetharam.