Amdocs predicts the future and may change Smart Data's perception
Big Data has negative connotations attributed to it – particularly in regards to privacy. The term widely-used for it is often related to the mass collection and monetisation of data which was certainly not helped by the controversy surrounding the NSA's mass surveillance program. Companies fear sharing data seemingly as a result of how it can affect their image rather than how it can improve their services – whilst consumers worry about how their data is being used.
Smart Data, as many writers have started to call it instead, has huge potential but this general opinion is preventing advancements which today we can only dream of. This opinion will change if companies and consumers realise the benefits they could be getting in exchange for their data – but this information needs to be transparent in order to cultivate the necessary culture change.
In a Big Data debate hosted by Amdocs yesterday evening we heard from highly-knowledgeable minds in their field from academia, press, and marketers about the issues preventing widespread adoption and how we can change this sad reality. We also heard about Amdocs’ innovative expanded analytics solution for Smart Data and how it can help bring about this change in perception through clear benefits.
With enough data collected we can predict the future with some amount of reliability. This is a fact confirmed by Professor David Crawford from Essex University who is a specialist in data science. Amdocs’ portfolio of products announced yesterday builds upon the company’s TeraScale, Proactive Care, and industry-focused BI and Data Warehousing Services in order to better understand and make use of the data collected to improve customer service and business efficiency.
Proactive Care (video) automates these future predictions through the analysis of data in an attempt to root-out problems before they occur so steps can be taken to prevent customer frustration. It makes the end-customer happier, and reduces the cost of providing support. Of course this also extends to sales, if you know a customer isn’t likely to be happy with their current service then it may not be the best time to try and sell them a new product. On the other hand, if you want to provide an offer for Netflix to your customer then through data you can ensure you only target the TV fans who will appreciate it rather than spamming those who don’t at more cost to your own business.
If the predictions aren’t spot-on, however, you could end up with some amount of frustration. Imagine if not enough data was available about you to predict you may like the Netflix offer when actually you would be interested? Imagine then hearing your friend on the same package as you has been given the offer?
Matt Roberts, Big Data Analytics and Strategic Innovations at Amdocs, ensures me that through a “machine learning” process these situations are quickly ironed out. Amdocs’ uses micro-segmentation as part of their SmartNet solution to achieve this. He says: “There’s the base which is going to take the offer. It then looks at the variables and applies it back into the model, so it goes 'This guy who didn’t originally take the offer wanted it, and now has a high-usage, so let’s apply this to the rest of the base.' It’s a self-learning machine.”
Professor Crawford added: “This is really where the academia element comes in to make the learning fast – because you want to minimise that. In some industries we have addressed it, but in others we’re only just starting to realise the Big Data opportunities.”
The opportunities for the majority of industries are huge. For the automotive industry it can be used to communicate with the dealership to highlight faults before you're even aware yourself – especially now we're moving to an age of self-driving vehicles. In medicine, we can detect risk areas for diseases and use it to counter-act before breakouts. In law enforcement, crime may even be one day predicted before it happens.
“A successful big data analytics implementation helps service providers meet the challenges of today’s competitive markets. Applying deeper and timelier insights not only drives out inefficiencies and costs, but also improves customer experiences to reduce churn,” said Justin van der Lande, head of Analytics Software Strategies at Analysys Mason.
Big Data is going to cause big change, and it's the natural fear of that we need to overcome.
How do you think we can change the fear of Big Data into being seen as an exciting opportunity? Let us know in the comments.