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Earlier today NewVoiceMedia announced my appointment as Chief Science Officer, so I thought this would be an ideal opportunity to comment on the background of the appointment, and particularly on why I joined NewVoiceMedia.

I am extremely excited about this new role, as it allows me to bring together several of my passions (contact center innovations, deep analytics, and patents and intellectual property generally) while joining a truly first-rate team. I have long been familiar with NewVoiceMedia, having almost joined them in 2000 as a founder.

The founder, Richard Pickering, is a close personal friend and we were "partners in crime" at Genesys from 1995 through 1998 (our families even lived next door to each other in California for a year). The timing didn't quite work out back in 2000, but as the saying goes, "good things come to those who wait" -- maybe not always true, but definitely true in this case!

I am pleased to be joining NewVoiceMedia at this particular time, because I have been convinced for some time that there is a real opportunity for meaningful change in the contact center space, and in particular I believe the time for cloud-based contact center solutions is now more than ever.

But my reasoning for why cloud-based contact centers are an essential part of the future are perhaps a bit different than the usual. While the benefits of reliable, inexpensive technology that is evergreen (kept up to date by the vendor instead of IT), and that can be acquired on an as-needed basis (and accounted for as a variable, operating expense instead of a large capital expense) are all real and substantial, there is an even more compelling reason to consider cloud-based contact center technologies as a growth sector of technology.

To make the distinction clear, it is helpful to consider Google as a model, rather than for example a hosted IP telephony provider. While hosted IP telephony seems more closely related to cloud-based contact center technology than search engines, the real opportunity in cloud-based contact center lies much closer to the example of Google, and it is based on the value of handling and studying large quantities of valuable data.

Contact centers are the beating heart of many enterprises, comprising as they do a dominant point of contact with customers. And they always carry out intrinsically complex business processes that are characterized by multiple human actors with often conflicting objectives (contact center managers, line of business executives, contact center agents, and consumers each tend to have different expectations of customer interactions). There are many important technology elements in each contact center (telephony infrastructure, routing engine, CRM platforms, dialers, email servers, agent desktops, workforce management systems, call recording systems, etc.), and each of them tends to generate a lot of information.

This information, suitably abstracted to protect corporate and consumer privacy, can be analyzed to understand and then to optimize the complex process of serving customers, in much the same way as Google analyzes vast quantities of data pertaining to consumers' online activities and then uses the results to finely target advertisements.

Analogously to the way Google uses their services to collect large amounts of data, and then analyzes the data using proprietary means to create value, the value being realized in very advanced advertisement targeting, in contact centers the vast amount of data generated by all of the systems can be studied to understand the complex dynamics of customer care interactions, and the value that can be created as a result is that customers can be provided with great interaction experiences, while enterprises can reduce the cost of delivering those experiences, and while enterprises can derive more revenue from each customer interaction (on average).

Even better, all three modes of value creation can occur simultaneously; if deep analytics are used to understand the process at a level of depth far greater than is common today, it does not need to be a zero-sum game where improvements in one area come at the cost of degradation in the other two.

Here is the part where hosting comes in. It turns out, even for very large enterprises, that it is difficult to build and retain teams of advanced analytics experts with the range of skills needed to extract the maximum value from the deluge of data generated daily by each contact center. Moreover, even if an enterprise was able to hire and retain the required experts, quite commonly they end up being repurposed to other tasks. And, even if an enterprise was able to get, retain, and keep on target a team of deep analysts, the team would only be able to learn from data generated by their own enterprise, which means the range of phenomena to which they will be exposed will be limited to those that occur in their particular contact centers.

By contrast, in a cloud-based contact center technology model, the provider of cloud-based services is ideally placed to collect streams of (sanitized) data from many centers across many enterprises and verticals, and to leverage a team of deep analysts by having the team study the rich data set, applying tricks learned from one client's data to help other clients optimize their results.

This cloudsourcing of expertise is exactly what Google does, and it is in my view the best way for enterprises to get ahead of the problem of optimizing contact center operations (by optimizing I mean finding the optimal balance between efficiency and effectiveness, between improving service quality, driving revenue, and reducing costs, and so forth).

I have been certain that this was a major opportunity for some time, including while I was CTO at Genesys and at Nuance. I believe the opportunity has largely been missed by the hosted contact center vendors in the US (many of whom I know very well). When I recently reconnected with NewVoiceMedia, I discovered that the company Richard had started in 2000 had grown, slowly at first but steadily, and was now the leading European provider of hosted contact center infrastructure. I knew all along that Richard and the founding CTO, Ashley Unitt, had had a clear vision from the beginning of a mid-point call platform using standards including VoiceXML and SIP.

What I didn't realize until I started working with them as a consultant earlier this year was that they had put together a strong new management team led by Jonathan Gale, who had come to much the same set of conclusions based on his experience at MessageLabs (which did the same sort of cloudsourcing play in the email space, in which the expertise they centralized was email security expertise). So when the opportunity to join NewVoiceMedia in a new role, as Chief Science Officer, came up, I jumped at the chance.

As Chief Science Officer, I will be responsible for all intellectual property matters for the company (which satisfies my IP itch),for developing technology strategy, and for leading the new NVM Labs organization, which is responsible for prototyping the next generation of cloud-based contact center technologies and working with definitional customers to introduce the new technologies to the marketplace (these last scratch my inventor's itch!). I will be working closely with Jonathan Gale, the CEO, and Ashley Unitt, the CTO, who is responsible for the larger development organization.

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About Brian Galvin

Brian joined NewVoiceMedia in July 2011 as Chief Science Officer. He has 30 years experience in technology-focused enterprises including AMD, SAIC and Genesys. He heads NVM Labs, the research arm of NewVoiceMedia.

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