Bigger and faster isn’t necessarily better when it comes to data analytics

Data analytics and big data remains big business, of that there’s little doubt, writes Kevin Stanfield who warns that communications service providers (CSPs) should avoid being drawn into a data analytics arms race.

Big data analytics in telecoms has a market value in the billions of dollars and continues to grow at a healthy rate. In spite of the investments that many CSPs are making, churn, ARPU and customer satisfaction remain just as much of a challenge today as they have always been. Rarely are CSPs held in high esteem by their customers or seen as paragons of customer service virtue.

The author Kevin Stanfield, is analytics product manager at MDS
The author Kevin
Stanfield, is
analytics product
manager at MDS

Investing in data analytics
In terms of investment and returns from data analytics, there’s a real danger that CSPs and MVNOs will be drawn into an arms race of bigger and faster data analytics. It may be that those organisations with the deepest pockets could have the most impressive arsenals. Yet it’s important to realise that data analytics, like any other IT project, must have real and tangible business cases; just being able to analyse huge amounts of data quickly is not enough.

CSPs and MVNOs will increasingly have to choose their data analytics battlegrounds carefully to ensure that business value is understood, measurable, targeted and monitored. Choosing when, where and how to deploy data analytics is as big, if not a bigger, challenge as developing the capability and platforms to perform analytics. Knowing something about your customers is not the same as being able to take positive actions. This often results in a so what scenario.

It’s a given that the nature and cost of deploying data analytics will result in challenges for smaller CSPs/MVNOs. They have neither the budget nor the inhouse expertise to exploit the opportunities that data analytics could present. Increasingly, they will need to turn to an outsourced model, perhaps utilising BSS vendors who have recognised the need to meet data analytics challenges on behalf of their customers and are responding with their own integrated solutions.

The sum of the data whole
There are some compelling use cases, particularly around network performance and quality. When this data can be combined with customer details such as lifetime value, contract status, profitability and other segmentation information, then the data whole is worth more than the sum of the data parts. Where both OSS and BSS data can be brought together to enrich decision-making, there will be a clear competitive advantage. For those CSPs able to realize one complete view of the customer, far richer and more effective analytics data analytics are possible. However CSPs/MVNOs risk putting the cart before the horse, if adequate consideration isn’t given to the data model that underpins the analytics.

Ultimately, the end game is to turn data analytics into actions and outcomes that can demonstrably add value. It is critical to be able to appreciate the context of the customer at any given point in an analytics lifecycle. This is to avoid wasted effort, inappropriate offers or at worst, alienate the very customers the analytics is aimed at delighting, monetising and building emotional connections with.

Do the basics well
What we mustn’t lose sight of in a world awash with data is that analytics isn’t a substitute for doing the basics well. Any CSP or MVNO worth its salt must have a fullyassured customer journey that eliminates the need for retrospective corrective actions; prevention being better than cure. Ensuring the network is performing, provisioning is precise and billing timely and accurate, eliminates many of the analytics use cases. It also provides a more stable, satisfied customer base upon which to let the analytics perform their magic.

 

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