theCUBE presents Dell Technologies World, brought to you by Dell. Welcome back to Dell Tech World 2022, you're watching theCUBE. My name is Dave Vellante, I'm here with my co-host, John Furrier, live event, I would say 78,000 people, really exceeded our expectations. And we're here with Chuck Whitten, who's the co-chief operating officer and chief dot connector, I sometimes call him at Dell Technologies. Chuck, welcome to theCUBE. I am thrilled to be here. How great is it to be back in Las Vegas, 78,000 people here talking innovation, it's great. It's like Jeff said this morning, I'm really thrilled to be in Vegas maybe, but I'm happy to be back live, so yeah. Friends and customers, great to hear. Awesome, okay, the operative phrase is multi-cloud by default, that's kind of the buzz from your keynote, what do you mean by that? Well look, customers have woken up with multiple clouds, multiple public clouds, on-premise clouds, increasingly as the edge becomes much more a reality for customers, clouds at the edge. And so that's what we mean by multi-cloud by default, it's not yet been designed strategically. I think our argument yesterday was, it can be and it should be, it is a very logical place for architecture to land because ultimately customers want the innovation across all of the hyperscale public clouds, they will see workloads and use cases where they want to maintain an on-premise cloud, on-premise clouds are not going away, I mentioned edge clouds, so it should be strategic, it's just not today, it doesn't work particularly well today. So when we say multi-cloud by default, we mean that's the state of the world today, our goal is to bring multi-cloud by design, as you heard. Yeah, I mean I totally agree with you 100%, we all know multi-cloud exists, it's by default, it's not going away, it's only going to get more complicated. What are you guys seeing in terms of the customer need as this becomes more of the strategy plus operations? I want to operationalize multi-cloud, is it an abstraction layer? How do you guys see the customer requirements? What problems are they trying to solve? Well look, the multi-cloud by default today are isolated clouds, they don't work together, your data is siloed, it's locked up and it is expensive to move and make sense of it, so I think the word you and I were batting around before this is an interconnected tissue, that's what the world needs, they need the clouds to work together as a single platform, that's the problem that we're trying to solve and you saw it in some of our announcements here, that we started, starting to make steps on that journey to make multi-cloud work together much simpler. It's interesting, you mentioned the hyperscalers and all that capex investments, why wouldn't you want to take advantage of a cloud and build on the capex and then ultimately have the solutions, machine learning is one area, you see some specialization with the clouds, but you start to see the rise of super clouds, Dave calls them and that's where you can innovate on the cloud, then go to the multiple clouds, Snowflakes one, we see a lot of examples of super clouds. Project Alpine was another one, I mean it's early, but it's clearly where you're going, the technology is just starting to come around, I mean it's real. Yeah, I mean why wouldn't you want to take advantage of all of the cloud innovation out there? Well the answer would be I don't want to do that if I'm going to feel locked up, if it's going to be too expensive, so again I think Project Alpine's a perfect example of a step on that journey, if you can create a common storage pool, a fabric if you will that allows you to choose where you're going to process your data and store it and more importantly give your teams the same M&O tools, the same skill sets, the ability to operate on-premise or in the public clouds, you know I think ultimately the theme of the last couple of days in multi-cloud for us has been customer choice, we want to give them the choice to operate how they want to so they can take advantage of all those cloud services. Real quick, where does that innovation go from that Alpine project because that's the software defined and I believe that's all your IP, all Dell Technologies IP, so that factors in, so is that going to make the hardware more innovative, is it going to be more application specific, where do you see that going? Well look, putting our file block and object storage into the public clouds just gives them choice on taking advantage of enterprise class storage software, you know you saw in our announcements today, we're not stopping the innovation in our core arrays and hardware and in fact the theme today was software innovation, I think we announced 500 different software updates across PowerFlex, PowerMax and PowerStore, so look, we're going to continue to innovate across the storage portfolio, now we're giving customers the choice, hey you want it in the public cloud, that's what project Alpine will let you do. Michael had a smile on him, I won't say spring in a step because he's sitting in that chair, but he's smiling about the market share numbers on that, so pretty impressive, you guys got a good commanding lean there. The super cloud thing, back to that concept, Snowflake, as we consider super cloud, they took their IP, put it on a hyperscaler, differentiated themselves, have great value and scale, and they're running away with it, it looks like, at this point, I mean you got data bricks, you got redshift in there and all this stuff, but as a concept it's working and now they're on multiple clouds, how do you see that super cloud connecting with Snowflake, because you guys are building a little Snowflake connector, there's one of the big announcements here is Snowflake and Dell, so can you talk about that? It was probably the one that got the most excitement from customers in the last day, and so look, you said it well, Snowflake, one of the most exciting companies in the data space right now, and a vision from that company to say hey, let's make the consumption of data as simple as cloud operating models have made the consumption of infrastructure. Well we share that vision and love that vision, but we're each coming at it from different parts of the stack, right? So we're coming at it from storage up to data, they're coming data management down to data, it's a perfect match of our capability, so the announcements we made in our partnership, we're going to start with two use cases that our customers have been asking for, the first is the ability to bi-directionally copy data from our storage to Snowflake's data cloud, that's exciting, but the more exciting one that created the buzz is, if you don't want to move your data to the public cloud, Snowflake only operates in the public cloud today, we're now giving the opportunity to access their data services on-premise, and that's the excitement from customers that have said, hey look, I want to take advantage of Snowflake's capabilities, but for regulatory or security reasons, I'm not doing that today, this is a ground breaker. Well it's the interesting thing is, because as many people know, Snowflake requires you to put their data in their cloud in Snowflake format, this is the first example of non-native data being accessed into the Snowflake cloud. Exactly right, exactly right, so again, for customers that say, I just can't do it, I cannot move my data, now they have an option, it's the first time Snowflake has collaborated with an on-premise infrastructure player. How'd that deal come about? Well it started as all great deals in our business to Michael to the top, so it was a, you know, and then it's been our teams working together closely, always, you know, alongside our customers, because that customer feedback of, I want to take advantage of Snowflake's capabilities, you know, it's been, we've been incubating it for a few months now, and it was great to bring it out on stage yesterday. I mean it makes a lot of sense, you connect the dots, so to speak, we look at what Michael was saying, these compute hubs, towers for 5G, to small edges, and big edges, and data centers all coming together, really key value parts of how data is going to be moving around, it's not just storage, it's data as code, it's a big part of the transformation. Incredible, yeah. I mean look, that was the start of the theme yesterday, look, the great unsolved problems in infrastructure right now is data is everywhere, it's sprawling, it is less secure than we would like, help, and help me make sense of multi-cloud. I'd love to get your reaction real quick while I got you up here, because data science is a well-known practice. There's been the rise of a hot persona that seems to be, you know, growing in numbers, but it's a scarce skill, that's data engineering, because the data's not just doing visualizations, there's a lot of architectural work being done to solve that strategy problem. What's your reaction to this new data engineering at the scale that we're talking about? Yeah, I mean it's a space I'm just learning about, to be honest with you, data engineering, but look, part of what we observe is, it takes a lot of calories from organizations to get data in a place where you can make sense of it and make decisions, and whether that's data scientists spending too much time cleaning, or the advent, as you said, of data engineering to create the architectures to help make that decision. Look, there's a lot of work that goes into that. It would be great over time to automate that, I think that's also the next great step on the journey. You know, Chuck, when I did the intro, I really didn't set it up that well, because you know, people, oh hey, here's the new guy, but you have a lot of experience with Dell, you've been a consultant to the company for a long, long time. Tell us a little bit about that, I'm interested in what you see as your greatest strengths that you bring to Dell. Yeah, well as you said, look, I am the new guy-ish, I think it's been eight months, I don't know how long I can continue to use that as the excuse, but I had worked with Dell for over a decade as a consultant previously at Bain and Company, so you know, look, my background is, as a strategist, and I did lots of work in sort of M&A and private equity, and so that's my background, I'm your sort of classic MBA, who spent a decade in technology, in a decade alongside Jeff Clark and Michael in the transformation of the company, so I hope I bring the right sort of outsiders, but insiders perspective to the party, if you will, but you know, I've certainly learned a lot in the last eight months as you get alongside and inside the machine at Dell. So irrespective of the financial magic- I think I know what question he's going to ask. Irrespective of the financial magic that Dell did with the VMware spin, as a consultant, one could have gone through a mental exercise of saying, hey, what about spinning it in? You've got this great software asset, everybody wants software with marginal economics. Okay, the decision was made, and now we're on to the future.  So I guess as a consultant, you turn that into opportunity. So where is that opportunity? How do you feel about, how do you think about that really hardware, heavy hardware exposure, and where you want to go in the future? Well look, I think that's what we've been talking about the last couple of days. So the VMware spinoff was a moment in which the world looked at us, and I think asked the question you did. What are you, right? Are you a legacy hardware company, or where you're going? But the reality of the world is, it's a multi-cloud world. So it was a signal also to the world that we're not a VMware stack competing against other cloud stacks. We are first and best with VMware. They are still our most strategic partner. But we work with all the hyperscalers, and it's a big world that is becoming multi-cloud. So strategically speaking, as that becomes the reality of infrastructure, and importantly, as data explodes at the edge, we're perfectly positioned as a company. That's the strategy. We like to say these trends are coming our way. It's never been a better time, honestly, to be the leader in infrastructure from the leader in client devices all the way to the core data center in the cloud. How do you think about, you have quite an observation space as a long-time vein consultant, how do you think about the skill sets required to make that transition? Yeah, absolutely. Well, look, we think a lot about it, right? Because certainly we have a lot of the native skills we need to win in the data era as the leader in storage, and the leader in infrastructure. We secure more mission-critical workloads than anybody. We know a lot about data. But what we're talking about now is not just persisting data. It's about protecting data. It's about moving data, right? And those are different skill sets that we're sort of acquiring and always looking at our teams to think about it. Look, we can do a lot of that organically. We are also always contemplating the right strategic M&A at the right time to sort of add to that talent and technology. You got the balance sheet for it now, so. We do indeed, we do indeed. We get the M&A question in there. But my question to you is, as you look at these systems, because we've always said in theCUBE many times, distributed computing's back. It's never went away. Cloud is just a version of that with on-premise and edge. It's an operating system. It's got all the IO, it's got the control plane. It's the internet, right? And so as you look at that, there's a system and with the scale of cloud, ecosystems are emerging and they're super important because if you're plugging in playing solutions, you got glue layers, you got automations coming, AI, machine learning, the partners aren't just totally dependent on each other. The interdependencies go away. So as you see partners that could be Lego blocks and be composed into these large-scale solutions that you guys are rolling out, what is the role of the ecosystem? What does the future ecosystem look like? How do you tell if it's healthy and take us through that new formula? Because we see it changing. Well look, we've been very explicit in our strategy that partnerships have to be a part of our strategy. We can't solve all the problems of the data in multi-cloud world alone and that when you see announcements like Snowflake or you see us announce continued collaborations with each of the hyperscalers or even how we continue to invest in and double down on our VMware relationship, it's an acknowledgement that look, to solve the problems that our customers are telling us, this super cloud you're describing, this integrated multi-cloud journey, we're going to solve a lot of it ourselves but a lot of it we're going to have to partner with. It's just got to be part and parcel of any good strategy. Luckily we're a natural ecosystem partner. As I said, we are not another cloud stack looking to build a walled garden, right? We know our spot in this game and it is to make multi-cloud simpler across the infrastructure layer. Somebody asked me, is Snowflake part of Dell's ecosystem or is Dell part of Snowflake's ecosystem? I said yes. Yes. Because that's a perfect example. I think that's exactly right. These only work and we've learned this with VMware when it's mutually beneficial to both sides. So you look at the use cases we're talking about with Snowflake, right? Bio-directionally copy data from our storage to their data cloud that's beneficial to Snowflake and our customers and of course, bringing data cloud on-premise beneficial to us. So look, there's more win-wins when you stare at these partnerships than there are zero-sum moments. I think that's a key point from even a decade ago. The platform wars were well identified. If you were a platform, they competed against each other. You got now platforms with platforms because of the synergies of the integration. This is a new dynamic. It's the great world of tech. It's cooperation and there's certainly places where we compete sometimes, but other places that we cooperate. And so yeah, we're excited about our position in this multi-cloud ecosystem. We think we've positioned the company perfectly. How do you spend your time? As a COO? You just had Dell. I mean, give us sort of break down. Yeah, well look, I think what makes it fun is no two days are alike, but together, Jeff Clark and I share responsibility for setting strategy with Michael and then aligning the leadership team on our strategic priorities. And in the world we live in, there's days you wake up and today is supply chain day because something has happened in the world, but often it's with customers or investors. So it's a true COO general manager job and I would tell you no two days are the same. Strategy, solving problems, keep it things moving, talk to the customers. Leading the team, setting a vision and listening to customers, right? I mean, at the end of the day, we talk a lot about our durable competitive advantages as a company. I think our single greatest competitive advantage is our go-to-market reach and the fact that we touch more customers and partners than anyone in technology. And that gives us an inside track on what they're worried about, what they're thinking about and how we can help. It's interesting, you mentioned earlier how things come back around on cycles and we're seeing hardware matter more than everything. In fact, we're doing an editorial thing on why hardware matters. Look at the advances in silicon and a smaller footprint of powerful devices compute about towers and edges and so the role of hardware and then you've got the software-defined software and the role of open source and all this. It's almost a perfect storm to kind of reset this none of the trajectory of growth where hardware innovation's working with the new software. Can you quickly react to that? No, I think it's spot on. I think the future of architectural innovation is really exciting when you look at what CPUs and GPUs and DPs and all that's able to do in the future of infrastructure and eventually the ability to compose your infrastructure to the workload versus have it be rigid and silent. I mean, there's as much innovation inside the infrastructure as there is in the ecosystem and that's exciting for our customers, right? It's going to make them more efficient. It's going to make them able to make decisions with data better than they are today. It's great to be in our space for sure. It's great to have you on.  All right, well, I've watched from afar and admired and it was really painless, so thank you. Thank you so much for coming to CUBE. No, thanks for having me. It's great to have you. We'll keep it right there, everybody. Dave Vellante and John Furrier will be back right after this short break. You're watching theCUBE at Dell TechWorld 2022.


Okay so it's 10.35 so we are on 9.35 sorry I think we need to start now so welcome to this what is time diary analysis of work my name is Pierre Walterie and I will take you through this hopefully interesting journey so we have a lot to talk about and I'm going to take you through basically six things today so I will say a few words about who we are as the UK data service then I will talk a little bit about what we mean by work in the context of this type of time diary based analysis short history of time use so that we understand a little bit what this type of approach is about and then so the main meals so to speak of the main course of this presentation I will talk about time diary instruments to measure work estimates that are derived from them and a couple of research based examples so about the UK data service who are we so we are for those who don't know us the main repository for UK secondary social science data we also provide support training and guidance to users and all of this is freely accessible funded by the Economic and Social Research Council our main users historically are academic researchers and students but increasingly also now government analyst charities in the voluntary sector business consultants as well as independent research research center and all think tanks we curate various types of data our core business historically were large-scale cross-sectional UK government surveys such as for example the lead before survey but also we curate major UK longitudinal surveys where individuals are followed over time large multinational database for example from the OECD as well as international survey data as well we provide guideways and access to census data both current and history records business and some business and administrative data as well as data one of surveys or qualitative multimedia data that ESRC funded researchers have a duty to live with us and last but not least we also provide support and training to users via our help desk so any one of you using our data can ask this question on our head desk via webinars and online workshop which are either data sets based methods based or software focused we have an increasing collection of online learning materials such as our data skills modules and forthcoming data skills pathways and also we help users not only with traditional survey data but also with new forms of data social media data for example via our computational social science team okay so that was about us but now let's start with the topic of today's proper so what is work it may seem like a pedantic question but I think it's important that we actually know or make explicit what we are talking about work is a potentially huge topic work can be described as joy effort meaning conflict resources usage or via the earnings and wealth production its deep rise but obviously as you can imagine this is not we are what we're going to look at we are not looking at work from the point of view of a total social fact to use sociological jargon but we are looking at work rather and maybe more humbly through those aspects that can be measured and that can be measured in a specific way that is as the time we dedicate to it together with some contextual information now moving to the way work is formally defined I will present maybe two common definitions here so the first one is the one that is brought forward by the international labour organisation and why does it matter because it's behind the conventions that are used for most social and economic statistics used by national statistics surface so work is defined in terms of whose it is for so for own use or used by others and also divided in terms of whether it leads to producing services or goods so which leads to the these various categories you can see here on the plot our news production work employment for pay or profit unpaid training work etc etc and volunteer work another definition that is also interesting and you will see while later instead of going through this complex typology we can simply define work as anything that you may was someone else third party to you to do sorry on your behalf without losing the direct utility that you rise from it so from that perspective cooking a meal or looking at the children is work but watching a film is not because obviously the utility you derive from watching a film cannot be transferred and importantly this is work irrespective of whether someone the third party is actually paid for it okay so now how has work or how have time use been developing over time so why I'm mentioning this because basically time use research to some extent is indiscretinguishable from a willingness to understand better household or workers productivity so the prehistory of time use research or if we look at the prehistory of time use research we will see that it starts in the early 20th century where various authorities or intellectuals were interested in understanding a little bit how a peasant household in the case of russia women in poor household in the case of the fabians in london were either working or producing goods this there's been a more example with soviet economists looking at time budget how russian workers were spending that time obviously frederick taylor's scientific organization of work in the narrow sense of line assembly workers u.s. departments for agriculture studies on the time use of farm and town workers the uk mass observations all of these studies were trying to understand how through how people spend their time but also how household were producing goods and services closer to our interest here are batches studies that were sorry that started being promoted after the second world war so the founding father of modern time use studies is a hungarian sociologist who's called sander alexander salai and who in the 1960s set out to create a comparative study of urban household and all the time use of urban household in 12 countries so it was quite a feat as you can imagine in the middle of the cold war gathering research team on both sides of the iron curtain and um yes collecting survey data from the so and it's it is to be credited for the first use of time diary as it's still currently being used so time diary defined as uh uh an instrument which gathers who does what where with whom uh over 24 hour periods a second uh panel year of uh time use research is uh Jonathan Gershune at the center for time use research here in the uk set up the multinational time use study and which is still one of the main source of harmonized time use uh data after uh and slightly later uh international nomenclature of time diary data uh were uh created so the icatus uh at the united nation or the harmonized european time use study uh at the eu via euro stat so that's really a brief uh history of the field of time use research but now how do time use research uh or how do time use time there is instrument uh measure uh things and measure work so time there is basically our survey data in overwhelmingly survey data so these are surveys in which on the one hand uh as any other survey you would have uh individual questions such as the whole while you what is your job etc etc but in addition to this normal person uh level survey uh you have a time diary so a time diary is a special type of questionnaire in which people are asked to tell or to write down at various intervals but the most common one is 10 minutes time slots uh what they were doing i'll come back to this in a second so it's usually collected on two days per person basis one week day and what day at the weekend and so in the perspective of time diary the unit of observation is not the person anymore but the day so we have a sample of days so to give an example the 2015 uk time use survey collected us more than 16 000 such diary days uh from 10 000 respondents in a 4 000 household and collected data uh time diaries for all uh people aged eight at the both in uh these households so now the instrument of time diary per se uh the most common time diary instruments record activities over 24 hours uh and uh the is made of a core set of four variables so the first one is what are people what am i if i'm the rest of them doing uh or was i doing if i feel it uh after the fact uh mainly uh what was i also doing because most people often do some form of multitasking where was i like when i was doing these things and uh who else if any uh was also present when i was carrying these activities so these are the four sets of uh variables that are collected in time diary data in addition and more recently uh time diaries data have been recording some measure of uh immediate well-being enjoyment or uh the extent to which it devices were also used while carrying out activities so that's what uh a pen and paper traditional uh diary could look like so this is the instructions that were uh shared with users participants of the uk uh time diary uh study of 2015 and so you can see uh each line sorry each row of the table represents a time slot a 10 minutes time slot and then people uh filling the way uh the days the activity of their days in each one of the columns main secondary activity uh with a device was used where where they were uh and uh whether other people were present okay let's go back to work so to speak in addition to this standard time diary in which all sorts of activity but of course including work are uh recorded there's a paid work specific uh instrument that's called the work schedule and that has been collected in uh a number unfortunately not all uh main uh time use surveys so it's it's uh interesting because it collects paid work uh for a full week so it's not just two days per week uh it has a slightly closer resolution of 15 minutes uh instead of 10 but it's basically a very convenient way of mapping uh someone's paid working life through uh out of the week so that's what it looks like uh it looks like basically a series of flying that uh people rows on which people can draw a line that represents the amount of time that is spent uh on paid work so a full week could work like this and we have data uh for the UK in 2015 for example that's a really convenient uh instrument especially for researchers who are interested in looking at uh work rhythm uh atypical work schedule at etc okay so we've talked about sample we've talked about time diaries but there's also the issue or we need also to be aware of what people feel in their time diaries or how what people feel in their time diaries is actually uh coded uh and historically this has been done via standardized nomenclatures of activity uh there are several of them so uh the oldest one is probably the multinational time you study uh one so created by uh Gershuni I mentioned earlier but it gave rise or to other nomenclatures such as the HITUS one for the EU or ICATUS for the UN so these nomenclatures are basically standardized list of activities and among which uh paid work for those of you who are interested in uh different ways of conceptualizing paid work and then provide an example in a moment uh it's interesting to look also at maybe large scale or uh studies time you study national studies such as the Indian time you study which has its own nomenclature or the American time you study so this is uh a snapshot uh and of course you can imagine I can't provide a full description of nomenclature on slides but it's just a couple of snapshots from these uh nomenclatures so this particular one comes from the Indian time you survey and the Indian time you survey is interesting the activities are classified according to which uh part of the economy they contribute so your paid work will be classified according to whether it's for agriculture and what kind of contribution it makes to agriculture and you can see that given the the current importance of agriculture for Indian household there's still a level of detail that you wouldn't find anywhere else so at the other end uh that's uh the recommendation and the detailed description of work according to the harmonized European time user studies so the guideline your EU based guidelines you can see its work is defined uh not as much uh as through its contribution to the economy but as employment so it's basically work as we call it in European time you study is the time you spend uh on doing the activities as an employee and as main and secondary job the multinational time you study uh also provides uh its own uh categorization of paid work created activities so it doesn't go as far in detail as uh heaters but the logic remains the same so uh are considered paid work um oh i considered uh work primarily uh so paid work is main job at home second job or what the whole or not at home um travel is part of work breaks or other time at workplace um and of course these are these are not uh the only form of work that are recorded i'm just focusing on this here for convenience but of course other type of unpaid work are recorded such as housekeeping you can see cleaning or caring for other people i can see that some questions are being asked in the q and a but i will answer these when uh at the end of the presentation okay so maybe one last thing before we move on to uh some estimates of time diary data uh the data structure so i'm not going to go too much into detail but typically what do time diary uh files or data set look like the answer is unfortunately there's not one common or universal way of uh coding uh time uh diaries but a very common one is uh files in long format so each line of search data set records uh an episode which is a unique combination of activity location uh and co-presence and uh so these episodes embedded within uh persons uh within persons and days uh it may sound a little bit abstract so that's what it looks like uh in practice so you can see this is um some uh time diary uh of uh from a Spanish survey so the first um 19 uh lines uh in the table represent a day uh as recorded by one person and from line uh number 20 onwards we have the second uh so a second day from another person within the same household um and you can see we have um so typical typical survey identifications a household number person number uh and but here the time uh diary specific elements so we have episode number so ranging from 1 to 19 all of the different episodes recorded by the person their duration and what they were about so we are on a Sunday so there's not much uh paid work here there's some unpaid work um but so that's just to provide a an idea of what it looks like okay but now it's time to move on to uh maybe uh paid work uh estimates with time diaries so i am going to uh take you through how typically a researcher or researcher would estimate uh basic quantities of uh work uh with time diary data and maybe the most common of such quantities is duration since we have uh all these episodes and the duration uh it's relatively straightforward to compute how much people uh how much time people spend doing stuff and uh in our case stuff is paid work uh per day so in terms of how to do it uh you people usually do it by flagging uh in the diary data set relevant uh episodes or work data set defined by the coding here so i'm using data from the multinational time use study so coding from the multinational time use study and i am not including commute uh as uh part of work so once these have been uh coded and here i provide some example uh with the our software package uh the next uh thing is to uh make sure that these work episodes actually record the duration of uh the episodes and if we were to uh have summary statistics for these uh episode we would see it's extremely low uh six minutes per on average as a mean and why is it low simply because we are not looking at what we should we are looking at the mean overall mean uh uh duration of work episode instead of the total uh amount of uh work uh duration of work per day in order to be able to account for the duration of work per day we need to sum uh so to do some of uh episodes work rated episode per day and it's this sum uh whose mean that we can uh then uh look at uh and uh compare across country if that's the sort of analysis we are interested in so we can see here uh our first daily estimate of uh time use uh work rated time uh duration it's still quite low it's about 126 minutes for spain and 151 minutes for the us it's really low so uh what's going on here why why is it so low um is it because we are looking at every day in in this in an indistinguished way so what would happen if and yes sorry i forgot there's uh this data can be uh easily uh plotted obviously uh but uh maybe it's because we are not looking at uh oh we are not differentiating uh week days and weekend so if i introduce an extra distinction between weekend and week days uh in the empty west weekends and week days are uh follow the u.s convention so the week start on sunday so that's the line of code i'm using here we can see indeed that uh people report clearly uh more time on paid work uh on week days but it still remained though it's still under 200 minutes per day so it's not uh doesn't sound like the the the typical time we would spend on um uh paid work in our normal day so this uh leads us to consider maybe a choice uh most time use uh researcher have to uh take on board which is are we uh interested in uh looking at an overall mean so also looking at uh in our computation at people who did not report work on um uh the data every day or are we only looking at people who reported paid work uh well this is also known as uh participants so on the one hand if we are interested in mapping the whole day of uh server respondent we may want to indeed take everyone on board and uh take participants and non-participants alike but on the other hand if we are only focusing on paid work uh for that matter and we want to reflect or to have a sense of a typical amount of time spent on paid work then we can uh restrict the sample we compute our estimate from to those participants and what happens if we do it then uh we get this type of result so I have retained here the distinction between weekdays and weekend and we can see that now the duration uh the daily duration on average for paid work are becoming more realistic they in most cases they uh stand between 400 and 500 minutes per day which is uh it's about seven hours is uh in correspond to what they expect and from that point on what you can of course uh the conductor or look at national differences okay so that's a first instrument a second instrument um which kind of uh derives from the first one so if we're able to compute duration and select people who were participant or not then we can also compute the probability of participation the probability of reporting paid work uh on a day so which is you know the word probability that our tag tagging variable will be greater than zero and again uh in a way that's more straightforward to compute than uh duration and we can see that on a typical day people in the US for example were more likely to report paid work on weekday at least than say people in Spain or even the UK and that remains true also for weekends a third type of a common instrument that is used by time use researcher exploratory fashion or maybe for general discussion of how people spend their time is time programs time programs are basically plots or maps uh in which the probability of or the probabilities of participation uh in activities are represented at each time point uh that uh that is uh recorded in a time diary so 10 minutes time slots is the the most common one and what do they look like they look like something like this so the x axis here represent the time of the day so by convention time use surveys start collecting diaries at four in the morning and that's uh three 59 the next day and this is weekday in the UK so what we can see here is the proportion of people reporting paid work here in full-time education which is in brownish green color and its rises start rising after 7 a.m peaks at around 11 there's a short slump here for people who have a traditional lunch break and are not eating in front of their computer and then goes back up in the afternoon and go back down again afterwards from 4 30 p.m and really start declining later in the evening and concomitantly sorry other type of activities so reproductive work and shopping is being carried out by people who are not doing a proportion of people who are not doing paid work there so that's a an interesting map of activities and including paid and unpaid work and also uh what is interesting is comparing such maps between people or groups of people or even countries so this uh graph now is the same kind of data but for a sample of french people and of course you can immediately see that in France or people take a lunch break more seriously here and here there's still a better sense of clearer this section between work and non-work for clearer than it is in the UK okay so so far I've presented really basic estimates of work or paid work using time use data now I'm going to look at things that are probably closer to real work research and yes that reflects maybe the type of analysis we would do as researcher either by looking at differences in time use by groups or gender day of the week for example or when we look at contextual aspect of work or when we build really our own research in for theory informed indicators of time use so in first example is something I worked on personally a couple of years ago and it's about looking at unsocial working hours so those of you in the field are familiar with the idea of all the question is to whether having unsocial or untypical work schedule can affect your well-being on your mental health and the nice thing about time diary data is that it's relatively straightforward to build typologies of typologies of paid work based on the time of the day at which work is reported so for example using the work schedule I've talked about before we can identify paid work that happens between say 8 a.m. until 6 p.m. and those that don't those that happen at night in the evening or at the weekend and then that helps us build an indicator of how of the amount of time people spend working on such hours and the proportion of such hours so just in practice it's amounts to flagging in a data set such episodes that are good lab label as social and unsocial some the amount of time they represent and compute means by group and gender if that's what you're interested in and you can also try and this is what I did here build indicators where the proportion of such hours relative to the total amount of paid work is analyzed so that's what it looks like so this is simply differentiated by gender the mean proportion of unsocial hours by sector of activity so we have sectors sorry I'm saying silly things it's not sector it's occupation so ranging from elementary occupation to all the way down or up to professional and managers and what is interesting is that both men and women here tend to have a larger proportion of their working time that is taking place on social hours if they are working in lower skilled occupations so that maybe contradicts a little bit the idea of overworked managers who are available for work at any time of their day anyway so that's an example of mapping unsocial hours according to gender and sector of activity another type of thing you can look at and I apologize for those interested in unpaid work given the limited amount of time for this presentation most of the examples I'm providing are about paid work time diary data also enables us to look at the context of work so we can look at whether people work in isolation people working with children in the room or location work from home but also commuting so commuting and more generally traveling is something that is coded in time diary usually is part of the location variable and we can similarly compute type of commuting by gender and in this case I chose to focus on regions of the UK so these are not percentages these are mean daily minutes spent commuting and Londoners won't be surprised to discover that they are those who spent probably the longest amount of time on their daily commute at the other end people in Yorkshire or the West Midlands having shorter commutes Northern Ireland this way and in another interesting difference and which may not surprise you if you already familiar with the literature in that area is that a man's commute in time tends to be longer than women and this has to do with the division of paid and unpaid work okay so I hope this provides a little bit of initial overview of what sort of analysis can be carried out with time diary data in the context of paid work I wanted to say a quick word about advanced visualization we have more and more fancy nice instruments now that can be used to visualize data so what I've used is really basic bar plots area graph etc but there are people who are developing more advanced tools so just to give a snapshot I won't be able unfortunately to go into the detail here you can see on the top left here it's a time program that I've similar to what I've shown but you can also map transitions so what do people do for example right after right before engaging in paid work and that allows you to map transitions and such a flower type of plot can show you how to do that there's a live animation here showing a little bit like a film of these transitions of yours so this is an animated graph even if I can't show you or maps geographical maps etc so I will share the slides later and those interested in accessing these resources will be able to find them and finally if you're interested in gaining more information about time diary data time diary research I would definitely advise you to look at the center of time use research at UCL and for data either the MTUS data set or series of data sets curated by CTUR or of course the UK data service for the UK based time diary data and I provide also link to ICATUS and HITUS if you want to look at these international nomenclature so I think we are running out of time thank you very much for your interest in the topic


The Equitable Life Assurance Society presents This Is Your FBI! This Is Your FBI! The official broadcast from the files of the Federal Bureau of Investigation presented transcribed as a public service by the Equitable Life Assurance Society of the United States and the Equitable Society's representative in your community. The Equitable Life Assurance Society has nearly 8,000 trained representatives from coast to coast serving over 4 million members. Tonight, an Equitable Society representative has a brief but important message on Social Security. Undoubtedly you've heard about the new Social Security law. Millions of self-employed businessmen, salesmen and others are now included for the first time and those already covered have had their benefits greatly increased. To whichever group you belong, can you think of a better time to look into your family's changed financial position and see just where you stand? To make this a simple job, the Equitable Society has revised its famous fact-finding chart for fathers and mothers. Mr. Keating will tell you all about it in just 14 minutes. Don't miss this important message from the Equitable Life Assurance Society. Tonight, FBI file number 292. It's subject, extortion. It's title, The Backstage Shakedown. With the possible exception of the wanton killer, no criminal is more ruthless than the extortioner. In his arsenal lie many weapons, but perhaps the most potent is fear. Fear on the part of the victim that non-payment will mean exposure, may even mean the destruction of a lifetime's work. Despite that, no criminal is more vulnerable for his defeat is assured when the victim, instead of crumbling, fights back. Different crimes are fought in different ways, but there is only one way to fight the extortioner. Upon the first approach, notify your local police. They form your first line of defense against crime. Give them the chance to do their job, and they will see it done. Tonight's file opens at an FBI field office located in a large Midwestern city. Special Agent Jim Taylor returns to his desk to find Police Sergeant Ken Brown waiting. Oh, hello, Ken. Hi, Jim. Hey, where'd you get that sunburn? It's just a plain old-fashioned windburn. I've been up in the woods the last three days on a surveillance. Well, you're not getting much rest between cases. Oh? I was just in to see your agent in charge. He said to work with you. Oh, and what? You ever hear of the Roswell Construction Company? Oh, I've seen their trucks around town. Why? Mr. Roswell came to headquarters this morning, wanted us to locate his wife. Seems she disappeared yesterday. Is this a kidnapping? I don't think so, but there's extortion mixed up in it. Huh? Roswell found this bundle of letters here in his wife's desk. Oh, thanks. They refer to the fact that five years ago she was in show business doing a strip tease act. Apparently, her husband never knew this. The letter is threatened to expose her. Oh, I see. And the husband thinks that this threat of exposure made her run away. How long have you been married? Three years. You done any checking on her? Just locally, so far. How about her family? She has none. Do these letters ask for any sum of money, Ken? Yeah, $5,000. To be paid when? Well, they didn't say that. You got a full description on Mrs. Roswell? Yeah, right here. Oh, thank you. I'll get an envelope, send these letters onto our lab. The letters are composed of words that were clipped from the newspaper. How about the envelopes? Well, they were addressed by hand. Good. Well, the lab can analyze the handwriting and attempt to trace the origin of those clipped words. I'll let you know, Ken, when I hear anything. That afternoon on the stage of a small theater in a nearby city, a comedian, complete with baggy pants and putty nose, is just concluding a sketch.  I've never heard of sauerkraut pie. What's that you got in your hand, Al? This is pumpkin pie. And what's in the outer world? That's custard. But I don't eat those kind of pies. Okay, my friend, then wear them. Come on, take a bow. What for? Just take a bow. Thank you! All right, girls, get on stage. Look, start the line moving and smile. Will you smile? Can I talk to you a minute? What about? Look, I don't want to sound like I'm beefing or anything, but you're kind of crowding those laughs on me, kid. Laughs? You've been getting laughs? I've been getting the ones you ain't stepped on. For instance? Well, for instance, a pie. Space them. Don't hit me with a second. Wonder the laugh gets a chance to build. Now, wait a minute. No third banana's going to tell me how to lay out a joke. Oh, are you two Ruben again? Yeah, and we don't need any striptease. It'll straighten it out. Is that why you've been cutting out my billing? What do you mean? I was just in your dressing room. There were programs on your shelf. All of them with my name cut out. I don't know what you're talking about. Okay, okay. This ain't Madison Square Garden. Fight on your own time. Well, what's he pulling at? Look, get ready, Helen. You're on next. And you two, get dressed for the finale. Oh, send him right in. Yes, sir. This is about my wife. That's right. Same to us with your complaint. Have you found anything? Well, your wife bought a ticket on the nine o'clock plane last night to Hillsborough. A ticket clerk out at the airport made positive identification, and the Hillsborough police are trying to locate her for us now. I see. Tell me, does she have any close friends there? I've never heard of mention any. The police said that you would look for her address book if you located it yet? Yes, yes. I've gone all through it. And anyone with addresses in it in the three cities where the extortion notes are postmarked? No. Well, we may still get some news today, sir. Well, how, Mr. Till? We're checking every western union office to see if any clerks remember your wife sending a wire to Hillsborough. But she doesn't know anybody there. Well, in a case like this, Mr. Roswell, we've got to investigate every possible angle, sir. Yes. Are you still have the notes? Yes, they're being examined by our laboratory.  All right, girls. Girls. Well, you tomatoes, listen to me. Now stand by for the opening number. I'm ringing in the overture. Opening number? After two months on the road, you ask me that. Honey, by the fifth show every day, I get a little confused. Okay, you're in the opening. And you're supposed to be wearing the red sequins. Well, it's too late to change. Oh, fine. Al? Al, I want to see a minute, please. Is this a beef? I just want to give you my two-week notice. Here, put it in writing. Oh, quitting, huh? That's right. I'll leave the play after we play Brook City.  I will, dear. And remind me not to come to it. Al, see the management gets that notice, please.  Girls, will you lift up them plumes? We just had them plucked and cleaned last week. I also hate dames. Hey, Helen. Al, what do you think? What? What do you think just happened? We already know. Paul's quit. Oh, I know about that, but this is even better news. Remember when we played Dallas? There was an all-night saloon near the hotel? Yeah, I remember the joint. Well, I went in there one night and I walked up to the bar. A 10-gallon hat stacked over and said, you're not from Texas. I said, no, but I can see in the eyes of Texas, they're upon you.  Well, you know how I say. Yeah, like a knife being sharpened. Honey, you'd kill this guy. When I finished the first number, I segwayed into Mexicala Rose and finished off with two courses of deep in the heart of. By now, there ain't a dry eye in the house. Or a good ear. Well, when I finished the 10-gallon hat, wiped his tears away, throws his arms around my shoulder and tells me I got a piece of the next oil well he hits. And? I just got a phone call. It was him. He said a well came in and he'd meet me. All I do is sign some papers and start collecting. You're getting a cut in on an oil well? That's right. Oh, Randy, honey, that's great. I also hate comedians. Where's the guy meeting you? In Brook City. By the way, Al, I'm handed in my notice, too, with that kind of loot who asked to tell jokes. Look, as far as I'm concerned, the whole company can give their notice. Right now, that overtures them and we got a show to do. All right, come on. Places, everybody. Stand by. The thing from the police at Hillsborough? No, not yet, Ken, but I've got a lead. The lab reported on the extortion notes this morning. You know, they clipped out words, the ones that were pasted on the letter paper? Yeah. Well, they checked on it. Found it was better than newsprint and not quite as good as magazine stock. They finally determined that it was from a theater program. In all three notes? Yeah, that's right. And they're from the same program, apparently, because the words strip T's queen were clipped out on one chunk. Then the extortioner could be someone who worked in a show with Mrs. Roswell. Yeah, and I think we've identified the show that person's with now. How? Well, the notes having been mailed from three different cities, our resident agent in each place, checked theaters there. One particular show played in all three towns. Could you learn where they are now? Yeah, they open here tomorrow afternoon. Well, that's a break. Yeah, but not the big one, Ken. There are 28 people in that show. Any one of them could have sent that note. Look, will you contact the company when they get in? I may not be back in time. Yeah, where are you going? See if I can locate Mrs. Roswell in Hillsborough. Brown speaking. Ken, Jim Taylor. I've located Mrs. Roswell. In Hillsborough? Yeah, that's right. How'd you find her? Well, we knew she hadn't made any calls from her home or sent any wire, so when I got out to the airport, I decided to check with the telephone counter there. I showed the operators a picture, and one of them remembered her putting in a call to Hillsborough. Well, did she give you the number? Yeah, and when I got here, I checked with the local phone company. I found the address it was listed under. And Mrs. Roswell is there? Yeah. Ken, call her husband, will you? Have him meet me here in Hillsborough. We will return in just a minute to tonight's exciting case from the official files of your FBI. Now, the Equitable Life Assurance Society is an important announcement about its famous fact-finding chart for fathers and mothers. A new and completely revised edition of this Equitable Society chart has just come off the press. The recent sweeping change in the social security law was the reason Equitable undertook this revision. If you're one of the 10 million Americans who has just been added to the social security roles, you'll certainly want this fact-finding chart for fathers and mothers. And the chart is equally useful to those who have had social security and are due to receive increased benefits. When you get this chart, you assume that the breadwinner of your family has died before his time. The family's regular monthly income is cut off. But the children still need shoes, a roof over their heads, nourishing food. And how much is all that going to cost? What monthly income would your family need to keep going without you? The fact-finding chart for fathers and mothers will give you a reliable and accurate answer. With their new social security benefits, how many additional dollars will they need every week to be well-fed, well-housed, well-clothed until the youngest child finishes high school? In five minutes, the fact-finding chart for fathers and mothers gives you an answer you can trust, guides you every step of the way with simple, easy-to-understand pictures. Think what a relief not to have to worry and wonder any longer. Once you have the facts before you, you can plan intelligently. Chances are that with your present life insurance and your new social security benefits, only a small amount of additional life insurance will do that job of giving your family complete security. Your equitable representative will be glad to work out a sound and economical program for you. In any event, the first step is to ask him for a copy of the revised fact-finding chart for fathers and mothers. There is no change, of course, and no obligation. So get in touch with your equitable representative soon or right care of this station to the Equitable Life Assurance Society. That's E-Q-U-I-T-A-B-L-E. The Equitable Life Assurance Society of the United States. And now back to the FBI file, The Backstage Shakedown. There is a basic reason behind each crime, and the one chosen by the Federal Bureau of Investigation for dramatization tonight is no exception. This extortion could not have progressed as it did without Mrs. Roswell's lack of faith in her husband and in her community and without her mistake of running away. An even more common mistake among extortion victims is paying and hoping in that way to settle the matter. It rarely does, for almost never is an extortioner satisfied with one payment. More often, he returns from time to time. Always for what he promises will be the last installment. Whatever the basis of the extortion might be, paying is not the way out. Your FBI has had years of experience with extortion schemes. Take their advice. Expose the extortioner and save yourself. The night's file continues later the same day in an apartment house in Hillsborough. This is the apartment here, Mr. Roswell. Have you seen my wife? I've seen her about 20 minutes ago. She know I'm coming? No, sir, I haven't talked to her. Yes? Hello, Betty. Eric. I've come to take you home. Oh, darling. No, you see. I'm so glad you're here. No, no. How did you ever find me? Well, Mr. Taylor here found you. Oh, I'm sorry. He's with the FBI. This is my wife, Mr. Taylor. How do you do? Mr. Roswell, I'll wait for you down the hall. Oh, all right. Betty, when you disappeared, I went to the FBI for help. You see, dear, I found those letters. Oh. Why didn't you tell me about them? Eric, I couldn't. Because of what I'd say or think? Partly that, but mostly what other people would say or think. Betty, listen to me. I love you. You're my wife. I don't care what you did before you knew me. But your reputation. The only reputation I'm interested in is the one we maintain with each other. Come on now. Let's go home. We've still got a job to do. We've got to help the police and the FBI find out who wrote those notes. Oh, hi, Ken. I was just on my way up to your office. Huh? That show trip arrived this morning. Huh? I went down to the station to watch them come in. Interview any of them? No, I thought I'd better wait for you. Most of them are staying at the central hotel. I just left Mrs. Roswell. Her husband brought her home? Yeah. I had a list of names of the members of the company that just arrived. We went over it. Any suspects? Too many, unfortunately. She knows almost every one of them, Ken. Oh, and another letter arrived this morning. Mail from the town where they just played. Any instructions in it? Yeah. She used to go backstage this afternoon at the matinee and pick up a note that would be in the mailbox. Should we go along? No. I think it's best that she goes along, Ken. Now, I'm glad I didn't interview any of that troupe. I might have scared the extortioner off. Yeah, that's right. Oh, by the way, I received another teletype from our lab. They checked the handwriting on the envelopes of the notes. It was not done by any known extortioner. Well, maybe we won't need that kind of item, Jim. We should be closing in soon. Yeah, I think we will be, Ken. Just as soon as Mrs. Roswell picks up the note and follows out the instructions. All right, boys, get the table ready. Lemon bit coming up. Hello, Al. Look, honey, we're trying... Betty. Betty Craig. Betty Roswell, Al. Oh, that's right. You're married. Say, you're sure an ad for it, kid. You look swell. Thanks. What's the action? You got any kids? No. No family yet. Hey, Randy. Randy, look who's here. Well, old one, two, three kids. Hello, Betty. Hello, Randy. You haven't changed a bit. He hasn't changed a joke, either. How's the show going? Well, I'm doing great, but business could be better. That television is rough on the box office. I'm going to tell him. The towns we've been planned, they don't even have radios. Oh, my Betty. Oh, hello, Helen.  What are those things? Ice cubes? Of course. Helen, how'd you ever lose all that weight? Oh, split weeks, five a day, and aspirin sandwiches. All right, let's have that street drop. Lemon bit coming up. Randy. First, Paul. Paul. Take it easy. Take it easy. I'll be there. The girls haven't even... Oh, hello, Betty. Hello, Paul. Now, what you doing here? I'm... I'm living here now. Oh, is that a fact? Then you've come to pick up the note. Is that it? What do you mean? There's a note for you out in the mailbox. I saw it when it came in. Oh, thanks, Paul. I'll get it right now. Roswell, Jim. Yeah, she picked up the note. Oh, what were the instructions? She used to wrap $5,000 in a package, address it to a Mr. Webster, and leave it at the desk at the hotel central. Where's Mrs. Roswell now? At the bank, getting the money.  Oh, she doesn't know it can, but we've got a man keeping her into surveillance now. Oh, and the hotel agreed to allow one of our agents to work on the desk until the package is clean. Good. Come on, let's get over there. Any signal yet? No, Jim. I just called the office. They got a report from the lab. The note Mrs. Roswell picked up today was written by the same person who addressed the extortion envelopes. That means it's worth... Jim, the signal. Yeah. All right, come on. Just a minute there. You mean me? That's right. I'm a special agent of the FBI. This is Detective Sergeant Brown of the police. Come on. You know what's in that package, Mr. Webster? My name's not Webster. It's Randy Randolph. I'm the comic at the show down at the strand. How did you happen to pick up that package? One of the girls in the show sent me a note and asked me to get it for her. Have you got that note, please? No. What's all this about? You're carrying $5,000 of extortion money. Huh? What's the name of this girl you claim sent you the note? Oh, Helen, the stripper with one of our show. There she got a full name. Helen Wilson. Why didn't she pick up the package herself? She stayed in her dressing room between shows. Do you think she'd still be there? I guess so. Ken, go by and see her, will you? Sure, Jim. We'll meet your headquarters. I'll bring you where you can. Right. I told you before I got to get back to the theater, so whatever's going on... Well, this is a nice jackpot you got me into, Helen. I don't know what you're talking about. Miss Wilson, I'll explain why you were brought here. I wish you would. You wrote Mr. Randolph here a note asking him to get a package for you at the hotel's central desk. Who wrote who a note? It was in my dressing room after the finale. And the package he picked up contained extortion money. Wait a minute. You mean he got Nail picking up extortion dough and then tried to pin the rap on me? Is that it? I just told him the truth. Hey, now I get it. That routine you were given out about strike and oil was a phony. What routine was that? He did a verse and two choruses on a guy who called him from Dallas. Said he'd meet him here and give him royalties on an oil well he owned. That story was on the level. Who was this man? Well, his first name was Hank. That's all I remember. Anybody with you when you got this call? No. Naturally. And the topper is the guy hasn't shown. I tell you, it's the truth. Now look, please. I think we're getting off the subject. Miss Wilson, someone with your show wrote three extortion letters to a woman here in town. The letters were composed of words clipped out of a theater program and they were mailed from the three... Hold it. Was that about a theater program? The words in the letter were clipped out of a program from your show. Why didn't you say that before? Randy, remember me beefing about Paul cutting my billing out of the programs? Paul who? Paul Caswell, Randy's straight man. I went in his dressing room one day and saw some programs and my billing was cut out of each one of them. What do you mean, your billing? Yet him. She means the way she's described on the program with a marquee. And how are you described, Miss Wilson? As the world's greatest strip tease queen. You hear that, Jim? Strip tease queen. Did you think I played chess for a living? Miss Wilson, those three words appeared in each letter that the extortionist sent. Then Paul Caswell's your boy. When's your next performance? Forty minutes. Ken, I've got a few phone calls to make. I'll meet you all backstage. Girls, girls, will you gather around a minute? Now look, we've only done two performances here and so far we've had ten beefs from out front about the way you're working on the runway. Now I know this is out of character but you're supposed to be beautiful dames, Paradeon. Mr. Dawson is on a kind of the runway. What do you mean? With his holes in it. Ah, that's to match your heads. Now come on, line up and get ready. Now. Yeah, now. Yeah, Randy. You seen Paul? He just went to his dressing room. Oh, thanks. Now come on, girls. Well, once keep us... Will you take a little higher so they can come and Paul's in his dressing room? You want to talk to him now, Sergeant? Or do you want to wait for your FBI friend to get here? Well, I'd rather wait for Taylor but I don't want this man to get away. We better go to his dressing room. We won't have to. This is Paul coming now. He ain't made up. Just got his street clothes on. Looks like he's leaving. Well, will you help me stall him till Taylor gets here? Okay. Well, I know you're going to hate this but I'm saying goodbye. You mean you're quitting right now? That's right. Who is this? Randy, a new straight man? No, this is a friend of mine. Hey, Randy, you and Paul are on next. Well, it's like I'm doing a single now. Paul's leaving now. He's what? I don't act surprised. They gave you my notice last week. Ken! Ken! Oh, hi, Jim. Well, I found out what I wanted. Good. How are these two men? Well, that's Paul Caswell. The stage manager, Al Dawson. Well, he's the man I want to talk to. Who are you? I'm a special agent of the FBI. Well, what do you want with me? Our hand-running experts examine the hotel's central register. Your signature shows you address three extortion letters to a Mrs. Roswell. Are you kidding? No. You also wrote a note that she picked up here during the matinee requesting her to leave $5,000 at the hotel desk. Look, I didn't call for any dough, did I? No, you framed Mr. Randolph here into calling for it and I assume you intended to relieve him of the package as soon as he got back here. Put the cuffs on him, Ken. Let's get going. Al Dawson was tried and convicted in federal court on a charge of extortion. Upon being found guilty, he received a sentence of five years in a federal penitentiary. Tonight's case is an example of how careful the Federal Bureau of Investigation is to secure all the evidence before making an arrest. The records show that more than 97% of all people arrested by special agents last year were later convicted when tried in a court of law. As in this case, the job of the special agent is frequently to prove the innocence of people cast under suspicion by circumstances. There are no ends to the lengths to which your FBI will go in that regard. In one as yet unsolved case, for example, more than 25,000 potential suspects have been cleared. As it does on all files, work will continue on this one. Will continue so long as there is a living suspect. Will continue so long as there is an FBI. In just a moment, you will hear about next week's exciting case from the files of your FBI. But first, another quick message from our Equitable Society representative on the fact-finding chart for fathers and mothers. This equitable chart can do a lot for you fathers and mothers. And the best part about it is, it's so easy to get. There's no charge or obligation. Simply get in touch with the equitable representative nearest you and ask for the fact-finding chart for fathers and mothers. Revised to meet the new social security benefits. Or send a postcard care of this radio station to the Equitable Life Assurance Society of the United States. Next week, we will dramatize another case from the files of the Federal Bureau of Investigation. File number 293. Its subject. Homicide. Its title. The Prodigal Hoodlum. The incidents used in tonight's Equitable Life Assurance Society's broadcast are adapted from the files of the Federal Bureau of Investigation. However, all names used are fictitious. And any similarity thereof to the names of places or persons living or dead is accidental. Tonight, the music was composed and conducted by Frederick Steiner. The author was Jerry D. Lewis. Your narrator was William Woodson, and special agent Taylor was played by Stacey Harrods. Others in the cast were V. Benaderet, Ralph Dumkey, Georgia Ellis, JC Flippen, Bill Johnstone, Charles Maxwell, and Carlton Young. This is Your FBI is a Jerry Divine production. This is Larry Keating speaking for the Equitable Life Assurance Society of the United States and the Equitable Society's representative in your community. And inviting you to tune in again next week at the same time when the Equitable Life Assurance Society will bring you another thrilling transcribe story from the files of the Federal Bureau of Investigation. The Prodigal Hoodlum on This Is Your FBI. Stay tuned for the adventures of Ozzie and Harriet. There's fun for the whole family when Ozzie and Harriet come your way next.


De tekst is veel keerder. De structuur is keerder. In de tweede versie was er nog veel meer over van alle verschillende baten die we hebben op verschillende baten, binnen de commissie en met verschillende baten. De meeste van die hebben gegaan en de documenten zijn veel makkelijker om te leren. Maar natuurlijk heb ik een aantal gemakken om te maken, want ik ga niet meer spelen, dus laten we het maken. Het eerste wat ik al op het geval heb gegeven is de straatste status van de EIF. Het is een communicatie. Het bevindt niemand, niet zelfs de commissie-surfaces. En als niet, dingen hebben enorm veel gegeven, sinds ik de commissie heb gegeven, de commissie-surfaces ontvangen met het gebouw. Maar kan je het dan zeggen, het is geïnteresseerd in het Nationaal interoperatieve werk. Nou, als je een EIF of twee dingen hebt, één, het is een commissie-surfaces. En ik kan het heel goed accepten dat het geïnteresseerd is en dat al deze neefen spelen in dezelfde vocabulaire. Maar de tweede, het is een verhaal van de verhaal van de vocabulaire. En ik bedoel heel veel dat, op het gevoel, wat de verhaal van de vocabulaire in dezelfde vocabulaire is, met een ander verhaal van de verhaal van de vocabulaire op het Nationaal niveau, wat betekent dat? Wat is de periode? Waarom hebben we niet meer ambitie? Waarom hebben we de commissie gehaald voor iets zoals een ministerie of declaratie? Like we have one in Malmö, on a government. We should have been some kind of a joint commitment from member states and the institutions to do something. Why not do something like next week in Amsterdam, the signing of the joint initiative on standardisation? We are all stakeholders in standardisation. The career sovereignty that I will work together to introduce it. This remains for the moment a document on the website. That is my first comment. Is it the most efficient method? Should the commission not, I always, I continue to speak we, if I mean the commission. They still beg my pension. So should the commission not be more ambitious. Second, and something that annoys me a lot of course, is that in this vision of the IF, openness is reduced to transparency. When we speak about open standards. When we speak about open internet. When we speak about open access to research. Is that what we speak about? Is it only transparency? Where is freedom of choice? Where is the competition? Where is the idea that openness leads to flexibility? Where is the idea that openness leads to sustainability? It's all gone. Openness just has become transparency. Where is the idea that openness leads to community building? To collaboration, not only between administrations. But between administrations solution providers, citizens and civil society. I just admit that in the e-government plan, at least the other government to think about openness is transparency. So they have done a little bit better there. But this is very disappointing. Second, there is the subtle balance between sharing, reuse, co-operate. If we all use the same tools, then of course we interoperate. But that was not the purpose of the game. Dus, while, yes, developing building blocks, certainly is a good thing. And while, yes, developing building blocks, implementing standards, mate, I would say, replaces paper standards, barcode, which is also certainly a good thing. I miss the collaboration. I miss big projects of the nature like Linux itself. Where the biggest companies of the earth, together with many individuals, all work together to build the ultimate operating system. Of I miss something, a project like legal office. That, when it was open office, has a limited life and a limited community because it was enshrined in a single company that decided all to do with it. And when it can open and became legal office, now has many more collaboration. I miss something like OpenStack. And when building blocks are developed, are made available as open source, they are not open source projects, they are what I call fake open source. It's something like our fiscal. Yes, it's licensed under an open source license, but it's not a community project. It's something to someone who develops, and if you can use it, you're allowed to use it. But that's it, don't bother anymore. There is no real collaboration. And that, I must admit, was already in my time one of the failures of the program. We couldn't really launch real collaboration between administrations. A next talk that probably will be developed further by Nikki is about the relevance of the European Interoperability framework in a cloud-dominated future. Is the underlying model still valid? How do we ensure application portability and information portability in a cloud-dominated world? Interoperability gets a new meaning there. And finally, one of my orders, DABAS, the definition of open standards. Why does the Commission continues to struggle with that? We have seen in the revision of the EIF text, we see the definition that was there in the first revision, the one which says that front is enough. Auto, it also said it must be incrementable in open source. We have seen in the recent documents about standardisation. Single order. Auto, we have heard Oettinger speak in favour of real open standards in various other speeches. En finally, recently, the Commission has said that while TV is also a form of fraud and that while TV is compatible with open source, something that is discussed by many as not being the case. So there are a few talks on some topics where I think that the EIF should have more ambition and should be used more actively to change things.


We're in Frisco, Colorado at the Girls on the Run event painting out some goody bags to all the girls that just completed their 5k Girls on the Run is this awesome program encourages them to get outside where it instills confidence leadership skills and hang out with one another all about being active and being outside and forming those friendships. It partners in really well with Steadman Clinic because we keep people active. Well, they're so excited. They just had a lot of fun. They're running around the beautiful course that they have right now, so they're really excited to be here. I think it's really awesome that Steadman has us out here. It's really great to be able to build this community and make these connections with people in the long run and know that we're here and we want to help. Everyone here today was wearing the number one, so if you cross the finish line, they are all winners.


Live from Las Vegas, it's theCUBE. Covering Discover 2016 Las Vegas. Brought to you by Hewlett Packard Enterprise. Now, here are your hosts, John Furrier and Dave Vellante. Okay, welcome back everyone. We are here live in Las Vegas for HP Discover 2016. This is our six year covering HP Discover. HPE Discover, we used to be called HPE Discover. This is SiliconANGLE Media's theCUBE, our flagship program where we go out to the events and extract the signal from the noise. I'm John Furrier. My cohost, Dave Vellante. Our next guest is one of our favorite guests, Keeve Lump, Sargillai. Welcome back to theCUBE. Senior Vice President and General Manager of the Communication Solutions Business, aka the Telcos, NFV, whatever you want to call it. Growing more. Great to be here as always. Great to see you. Got to say, happy birthday. Recently, I had to celebrate your 50th birthday.  Going on 30. We killed this guy now. We're live, you can't take it back. In all seriousness, pleasure to have you on because you have a good perspective. You've seen a lot of different things going on within HPE, particular. And now you took over the group around NFV. That was the telco. Back when the telcos kind of realized they had to look down the barrel of digital convergence, digital transformation, digital services. What's the update? I mean, how far have they come? I know your group's grown. Certainly you've got a good head count of staff under you now. What's the update with the telcos and the whole service providers? Yeah, I mean, look, the first thing to understand is this is a huge industry, it's a trillion dollar industry. So when we talk about the telcos and also telcos includes things like the cable providers, it's all converging, right? You got cable guys buying phone companies, phone companies buying cable guys, buying content. They all realize they need to become more digital service providers. The basic stuff that they've done in the past which is connectivity, that sort of baseline, they now have to do more things in order to monetize it. What they've monetized before is getting more and more threatened by some of the other players coming in, like for example, what's up, right? You can use that for text messaging a billion users a day, nobody pays anything, right? So they have these entrants coming in and so they have to transform to be digital service providers. They've been very successful, but they need to transform to leverage some of these new technologies. And so I think in the last few years, that's been sort of called NFV, but really it's more than just NFV, it's really transforming. I think at this point, it's more about the how, like there was a discussion before about the why for a while for a few years, then there was a discussion of what it is, why should we do it, and so no one's asking those questions anymore now. It's like, okay, how do we go about doing it? I don't know, we're in the center of that. So I got to ask you, one of the things that we hear all the time from these big providers is that, yeah, table stakes is connectivity, but they still got to ramp up that too, because the demand with phones and people doing Snapchat, I mean, hell, my bills or family bills going through the roof, my kids, but that's just video, more video, more connected IoT now coming, so they got to ramp up the investment on connectivity and then have over-the-top services on top of it. How do they do that? Do they blend them investments together? Do they have a strategy? What are some of the use cases that you've seen that have been successful around, how to balance that? Yeah, well, you hit it on the head, right? They have to do two different things. I mean, demand is growing, but then you got to monetize it, right? Because they're getting less and less dollars per bit, so they have to keep on adding capacity, but they don't get as much money for it. And parallel to that, they also need to figure out new monetization streams that they can make money off of at their margins. So it's a sort of a dual-pronged thing. First of all, they need to figure out how to improve their cost structure by leveraging some of the new capabilities that have shown up with cloud and IT, right? If you look at what cloud has enabled to happen over the last decade and some of the big web providers, right, it's all about automation, right? It's all about things that usually had 10 or nine hands touching are now automated because that makes it faster and also saves a lot of cost. So they need to sort of transform to that. Well, on the same thing, use that technology also to roll out new services. The good news is it's sort of interrelated, right? If you, we are a view of all this and the industry in general talks about the transformation to the telco cloud, which means you take the traditional telco infrastructure, which is very dependable, been around for the basic architecture and hasn't changed since they moved to TCPIP, but monolithic, siloed, even if it's virtualized, it's still very siloed and move that to leverage a lot of the technologies that the cloud has brought to us in the last decade. And again, it's not like these guys didn't know about it that they were building, busy building their networks. And so that's really what they need to go about doing. That will address two points for them. One, it will enable them to have a more agile platform, therefore enabling them to roll out services and be more in the cadence of the cloud where you move things very quickly. And two, it will improve their cost structure so they can continue increasing their capabilities for lower costs. And you mentioned reliability. It's old, reliable TCPIP. Is there a willingness on the consumer to somewhat sacrifice that reliability, that stability in order to get speed and agility? I mean, it's a mix, again. So the consumer, first of all, if you think about the consumer, we know there's a willingness in the consumer, right? Because we all moved from a landline to mobile. And without due respect, mobile is not a dependable landline, right? But it's mobile. So you're willing to put up with it because you get the benefits of having a mobile phone. So the consumer in general is already there. I think for them, it's more complex because there's a big regulatory environment. They've spent 30 years optimizing for the five, nine situation across silos and they have to do two different things. First of all, in the cloud, as you guys know, there's ways of achieving the same reliability, but it's done by replication, not by monolithic stacks. So it's a different culture. Yeah, and I think you mentioned mobile phone. I would argue that, I'd say mobile computer that makes phone calls. So that's really the trend that we see because it's more robust. And now you see Verizon making a bid for Yahoo for three billion that was newsed this morning. Yahoo once- Well, they want to become a digital provider. I mean, when you're looking at the strategies that people have, there's a technology strategy of moving your stack to what we call the new stack, right? Which is really a telco cloud environment. And again, where it's P because of our heritage both in network and in telco, but our capabilities in cloud, obviously, and as IT, we can go drive them there. And in parallel to that, they need to look at new services, like digital service provider, which is where you see Verizon doing some interesting things. So I got to ask you a question. Back in the old routing days and the networking days, because you know a little bit about that too, is the word differentiated services was a specific network term. You use differentiated network services to provide different costs per routing pass and then it kind of creeped up the stack. Is something like differentiated services where the digital world needs to go, where a telco could provide differentiated security, differentiated connectivity, differentiated movies?  So how do they create a differentiated services model? And is it network driven? How do you see that playing out? Well, I think you raise a good point, which is we keep on talking about all this technology. It's a business, okay? So you got to start with the business. Sometimes I laugh and say, look, you're going to have a monkey behind it doing whatever he's doing, as long as it's fast and agile and cost effective, nobody cares. Now reality is you need technology. You need to make it happen. But you want to watch movies on their phone or device. The differentiated, you know, in the US especially is a bit of a difficult term because of a net neutrality. But in general, they need to be able to provide agility, right? So when you talk about differentiated, it's about flexibility using one platform. So, you know, one of the things, for example, you look at and you say, okay, look at IoT, for example, right? So today there is, I don't know, eight billion subscribers. I think we have about 10%, we control, you know, our subscriber system, HLR is probably responsible for about 10% of the subscribers in the world. But there's about eight billion, right? With IoT, you're probably going to get to 80 billion by 2020, maybe 60 billion, right? So you're going to get less per subscriber dollars because IoT is the lower art pool. But if you can figure out a platform that's flexible enough, that allows you to scale to that at a lower cost point, you can still make a lot of money off of it, right? So it's really about building a platform that's the more cost effective per services. Now, there is differentiation. You can of course do a lot of differentiation. You can also, you know, if you look at what some of these guys are doing, let's look at some of the enterprise use cases, right? So you hear a lot about virtual CPE, right? So traditionally, you know, more and more the telcos are looking at providing value out services to enterprises, right? If you're SMB, why do you need to do all the IT? You can just go to telco, they'll give you the whole thing. But for the telco to be competitive, they have to be able to do that without a truck roll, right? So one of the things that they're doing now, and we did a, you know, we have a win that's public about this in Swisscom, where you know, you put a box in there, it's all virtualized, and you can turn off and on services as you want. You put the box there once, and you can add enterprise services. So they need to figure out how they can do a lot of what they're already doing, but faster, cheaper, right? At the cloud cadence, right? The customer today, right? When you think about your experiences, when you want a service, forget about the friendship as service, right? You don't want to talk to this person. You want to go to the web, press a button, pay as you go and move on, okay? Just having that is a big difference, right? Just moving to that kind of consume model where everything is agile and easy. Now again, it's not like the telcos don't understand this. They understand this perfectly well, but they have an installed base of, you know, billions of dollars. Let me give you another example, right? Let's talk about voice, right? Nobody talks about voice anymore, right? Voice is gone. Voice is a $550 billion business, okay? It's contracting at about 8% a year, but it's $550 billion, okay? If they can figure out how to do some of their voice features in a cheaper way and move some of their voice infrastructure, which is probably based on 15-year-old technology to more converged technology based on an efficient... Well, that's unified communications business is kind of pivoting that whole... Yeah, but if they can figure out how to do that in an agile fashion, that's $550 billion you can make margins on. Sorry, you mentioned regulation, net neutrality. How is public policy affecting, supporting, stalling progress? And how does it differ in Europe versus North America? Yeah, I mean, I think in the... Well, first of all, Europe is a bit different because it's a lot more of a competitive environment, right? There's a lot more players. I mean, there's consolidation happening, right? There's a whole discussion about, so, you know, what's the right number of providers per country, right? If you have five providers, they kill each other on costs and the service goes down. If you have two providers, then it becomes a monopoly. Maybe three is the right number. So Europe is a lot more dynamic. In the U.S., I mean, I think the big players are investing heavily, but, you know, we got to be careful with the regulation. If we over-regulate them, they won't have an incentive to invest because at some point they have to be able to provide to get money for their differentiation while making sure. So I think it's hanging out there in the U.S. Is it, in your opinion, is public policy striking the right balance or are they still trying to figure it out? I think they're still trying to figure it out. I think it is a very fine balance because, again, you got to make sure that, you know, it doesn't get to the point where the network, you know, since it sets a key part of the infrastructure of services today, I mean, you can't consume any digital service without the network, so it's a big control point. On the other hand, you got to create an environment that incents the service providers to add value, if they can't monetize it. Well, it's an investment, right? They haven't... Yeah, they're going to spend dollars if everyone, if someone else is always getting all the money for their investments, they're not going to be incentive to invest. On the other hand, since it sets a control point, you got to regulate it. So it's a balance. I think it's getting there. And whoever owns the pipes wins. And I think that's why, you know, I talked about the differentiation services back in the day, the packet sniffers were really taken to the cleaners when they were going in and the service providers and the MSOs were essentially monitoring and throttling packets that weren't from their network. And then you have different networks and traversal... I think, look, the reality is, though, if you look in general in the digital economy, right, agility is the name of the game, okay? You can, if you roll out fast, there's the fast and the dead, essentially, right? I mean, over time, that's what you end up with, right? I'm going to tweet that. High and off. And that's true across the board. And they, again, they understand that. The question for them is, how do they continue running their existing business which they can't, you know, it's very easy to say, well, why don't you just go do this? Well, you know, I don't know, I'm running like a, you know, 50 billion dollar business or 100 billion dollar business, 150 billion, if you look at AT&T, they can't stop everything. So it's a question of how do you adapt the right culture and put in new infrastructure and put in new mechanisms to gain agility because you're going to have to have that agility, which, and what I mean by agility, I mean things like the ability to roll out services quickly, test them and turn them on and off, right? And charge for them and make money. In the past, right? When you wanted to do a service, and this is really a key understanding of how this works, right?  Today, can you imagine the service being planned for six years? I mean, the technology would be like two generations ahead. And so it's about, you know, quickly figuring out what you want to do, rolling it out on your software, composable infrastructure, seeing what sticks, making modifications in agile fashion and going back. This is not how telcos operate, okay? And it's not because they're bad. It's because historically, they haven't had a technology enable that, so that's not how they've operated. Their business model is pretty slow-moving, too. They only have to go very fast. So they need to get to that. They fully understand it, but it's a question of how do you get to that in a fashion that allows you to continue, you know, using your old business? And that's where, you know, we do a lot of work on. So that's infrastructure? That's a, what, a development culture? Skillsets? Starts with culture, first of all. Number one is culture, right? Because it's, you know, it's a different culture. It's not a siloed in the past. The same as the idea a decade ago, right? You created all these silos in order to ensure that you had stability because no one silo could affect the other silo. There's, you know, there's benefits. These things were not done because people didn't know what they were doing. They knew exactly what they were doing. It was the right thing to do at that time. Now it's all horizontal. So different culture, you know, more horizontal culture as opposed to siloed culture, all software, you know, premium on speed, right? Leveraging cloud-based infrastructures and also very business-focused, okay? Monetization. I need to figure out how to monetize stuff. A lot of the agility, agility across the board in terms of, okay, roll out a service quickly, see if it sticks, try it out, make modifications.  But it takes time. Sorry, thanks so much for sharing that great thought. Leadership, just to give you the final word on the wrap here. What does HP do in to solve that problem? HPE, I still can't shake HP, HP Enterprise. What is HP Enterprise doing to solve that problem to make them fast so that they don't become dead? Yeah, well, I didn't say they will become dead, first of all. They are doing quite, I mean- You imply that they would be dead if they didn't move fast. And what I'm saying is that, you know, again, they're sharp. They've been around for many years. I think it's a question of helping them. But look, the key for them is they would like to work with someone who understands telco because their business is different. You can't just take a bunch of IT stuff and stick it there. But they do know that they need to transform. And so they want to work with, you know, less of their traditional folks who's going to keep them where they are and more with folks who understand the private cloud, open source. Is there one weapon that you have that you go in there and say, this is a big gun, you need to use this? Or is it a combination of technologies? Again, so there's two different things that matter. First of all, they like working with HP because we have been working with the telcos for many years. So again, 10% of the subscribers in the world go through some sort of HP software. And they like working with HP because we are a partnering company that is specialized in private cloud and IT. You know, we have our open stack. We have our orchestration stack, service director. And so I think our key weapon is that, you know, we are a leader in IT and cloud that has a strong telco heritage. And so, you know, we are the ideal partner for moving in this direction because we are sort of where they want to go to as opposed to maybe their historical partners that are themselves trying to figure out how to get there. And that creates a good environment for us. They are usually seeking us out and saying, hey, it's me, I really want you to come and help me here because I know you're going to push the envelope. But you know, they're transforming, but it's a process. Sargalai, SVP general manager, the communication solutions group, the telcos, we all have our phones or our home connectivity goes through these telcos and providers. Again, they're the ones powering the network. And thanks for their thought leadership. And thanks for sharing the insight. Appreciate it. This is theCUBE here live at HP Discover in Las Vegas. I'm John Furrier with Dave Vellante. We'll be right back. You're watching theCUBE.