Data Analytics: The Emerging Cataclysmic Force in the Communications Industry



thank you hello how's everybody doing so I'm in the expectations management business and I've come up with a title the emerging cataclysmic force for the communications industry data analytics okay great expectations appropriately set too high I actually would like to change the title I would just like to turn it into a question it's a question we're working on and it's a question I'll opposed to all of you you know advisors and practitioners you know our data analytics a cataclysmic force for us yet in the communications industry I do feel strongly they will become that in pockets of our work growing pockets and many of the work here the academic shins and and the practitioners it is but this is absolutely just use that metaphor i think this entire topic is a bicycle that is being built as we ride it so hopefully in the context of all the great scholarly work that we've been given this is something of a update from the front lines of what's happening in terms of what i really want to try to achieve here in the next 34 minutes I want to look and we're just talking about this actually analytics yes understand important out there a buzzword a piece of jargon and something important to our lives but actually I think about it in two ways this is a discussion about data data defined the most broadly we're going to talk about that more and then it's really about insights okay like what are we going to do with that data it's the same question we've had for four decades what are we going to do with the data that we have the methods that we have to process that data to come up with insights that really matter for the enterprise analytics if you think about data and insights as sort of two train cars I think analytics is really kind of like the coupler right that's connecting the car it's using technology and right don't get me wrong if you're on the Metroliner you know you want a really good coupler on that train but that's kind of the way I think about it the other thing that I hope that we can do is in going through some of the work we're doing some of the theory and observations we've had select a little bit on ourselves as practitioners whether we are outside advisers or trusted internal advisors I'll throw out a couple of things I've got on my mind as a practitioner you know have we as a set been late in upscaling ourselves in this area real broadly right I mean data and analytics I'm the sort of marketing side of the house there's been a lot of work and a lot of insight and tools and technologies and commercial applications are we a little bit slow to the game here I asked with all due respect the other thing is is that do we and this is true of everybody again do we get sort of fixated on the datasets you know and and sort of oh my gosh let's let's cleanse that data and things like that and do we really ask ourselves and so what's the insight that we can find what are we looking for doing do we do we start is the starting point the data set or is the starting point some of the hypotheses that we have that are going to be relevant to our business and then let's go figure out what data can help us get insights that help us with those hypotheses you know we think that probably where things are going is you know from this idea of just harnessing big data to really blending little and big data blending a lot of different data sets that's going to be important really important you know so for example you know an ft article that's a piece of data at Ft headline you know a tweet is a piece of data they're both important they could have important city to the organization but they are not equally important and so as you blend data just like in a recipe you're going to want to do proper measurement and proper waiting and the way that's going to happen is to bring research methods and social science rigor to what we're doing so we've got to have that kind of data science expertise and and capability but we've got to combine it with research science so that's that's one thing we see places going the other thing is is you know again we see you know right now there's a there's a cat phony of critical factors emerging across the organization we think that that can get in the way of and what we need to stay focused on is finding you know singular root cause analysis I mean again think about your own organizations you know and think about the pockets of data that exists and the silos and even the turf and dare I say the political agendas and things like that and so what you have is you have a bunch of different places where data is being developed managed and then it's being synthesized for insights but is it being sort of brought together in a holistic way again thinking about it from the c-suite perspective for for the CEO for the organization in the enterprise to make you know to make decisions you know for example if you're a large multinational corporation you know consumer package of incorporation and you got a problem in China you know you got a problem with customer complaints you know do you have a product development problem do you have a China marketing team problem you know do you have a global customer service problem you know it sort of like the old joke if you pose that quote that single question what's my problem in China you're going to get three data supported answers if you're kind of like you know relying on a bottom-up perspective of this and so again we have to figure out how to elevate that how to have the c-suite able to to gather data so that's that's kind of our feeling about data some initial thoughts about what it means for the CEO going to talk to you in a minute about what we think this means for the organization and some things that we are doing actually for actual clients that they are actually paying us for and and hopefully we can glean some thinking about that however you know the the key part of this and we talked about this ourselves a lot we think that there is a great need for data science excellent real subject matter expertise you know around our clients and their industry and and and and the and the operating environments there in but in order to take all of that and to have unbelievably bulletproof insights that you can stand in front of a CEO into a board meeting with the design of how we really research this and and and come out with these insights requires real research methodologies unbelievable social science rigor

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