A Piecemeal Approach to Turning Data into Revenue

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By Ayanda Dlamini, Business Development Manager, LGR Telecommunications

Data monetisation – the art of turning information into actions that generate business revenue – is generating a lot of interest among enterprises around the world. The possibility that information can be collated and analysed, to deliver the silver bullets that improve enterprise bottom lines, is a very attractive one to enterprises and their financial management.

But there are concerns about the size of the investment and the high end skills needed for enterprises to maximise the value of their data. In some respects, it is a valid concern. An all-encompassing approach to harnessing all internal and external, structured and unstructured data and running real-time analysis of it all would indeed require a significant investment in technologies and skills. The good news, however, is that monetisation of data can also be approached in a piecemeal fashion. Most enterprises can take immediate steps to improve the business value of their data, using their existing technology resources.

Enterprises can begin by taking a fresh look at their internal data sources, where they typically have extensive data on customers they already have. By applying new analytics models and innovative approaches to the use of their existing data, enterprises are likely to identify customer behaviour patterns useful for sales planning, opportunities for upselling and cross-selling, and areas where operational improvements can reduce spend – which is in itself a revenue opportunity.

If we consider that bottom line depends on both income and expenditure, it makes good sense to turn to existing data for insights that help drive down costs. Better data analysis may help enterprises to reduce fraud and risk by identifying possible risk factors in particular regions or customer segments, or by highlighting patterns of behaviour that may indicate fraud. Enterprises might also apply reporting tools to discover more efficient routes to deliver goods or better mechanisms for service delivery to particular customer segments.

Enterprises may then go a step further, and tap into readily available data that may not require a significant upfront investment. There are many opportunities for enterprises to understand customers’ consumption patterns, sentiments, and even their location, based on readily-available information. This may come from social media, in the case of telcos it may include interconnect data, or it may even include data shared or traded across industry verticals. The sharing or trading of data raises some compliance questions, but in reality all indications are that data trading already takes place.  In South Africa, we are not yet seeing an integrated partner approach to data monetisation where efficient platforms are put in place to maximised the value of content.

It should be noted that the use of aggregated data should be approached with caution in our regulatory environment. Enterprises may make use of certain aggregated data in which the personal element is removed, but it is not always clear whether enterprises have the processes in place to ensure that all the data is being stored, managed and used in a compliant way. Enterprises will need to put processes in place to ensure the data in use complies with law and that they have the necessary tools around master data management at entry points, to process the data in such a way that they remove the personal information. This also drives a need for IT and data management professionals to work closely with compliance and risk management professionals.

Sharing data across an intelligent platform in a regulatory compliant way would offer enterprise partners numerous opportunities to optimise the use of that data, gaining newer and deeper insights into their customers’ behaviour and preferences. Done well, this could also result in customers receiving less broad-based marketing and more targeted offers they may actually be interested in.

With CEOs focusing increasingly on extracting full value from customers and growing revenue, while still controlling costs, better use of data presents unlimited potential for business. Unlocking the value of data simply requires the right tools and more innovative thinking.