WEBVTT - Youth Unemployment is Solvable 0:00:15.076 --> 0:00:21.116 Bushkin, I may have Higgins and this is solvable. Interviews 0:00:21.116 --> 0:00:24.276 with the world's most innovative thinkers working to solve the 0:00:24.276 --> 0:00:28.836 world's biggest problems. I'm Nikola Gilombic. I'm the founder and 0:00:28.916 --> 0:00:32.836 chairman of the Harambee Youth Employment Accelerating So my solvable 0:00:32.996 --> 0:00:36.996 is to reduce significantly youth unemployment in the South African 0:00:36.996 --> 0:00:43.276 economy and increase young people's access to future work, which 0:00:43.356 --> 0:00:47.836 is going to be globally and locally sustainable. South Africa 0:00:47.876 --> 0:00:51.076 has one of the highest youth unemployment rates in the world. 0:00:51.756 --> 0:00:57.476 Nikola's organization, the Harambee Youth Employment Accelerator, says that about 0:00:57.556 --> 0:01:00.876 forty percent of this generation of eighteen to thirty four 0:01:00.956 --> 0:01:06.116 year olds are expected to never secure stable work. Imagine 0:01:06.116 --> 0:01:09.236 what that does to an individual, and then imagine that 0:01:09.236 --> 0:01:13.356 it's happening to forty percent of young people in your country. 0:01:13.396 --> 0:01:17.596 The impact is enormous, not only on the individual's well 0:01:17.636 --> 0:01:21.636 being in health, but imagine the loss of potential, missing 0:01:21.636 --> 0:01:24.436 out on the skills and energy of these people who 0:01:24.516 --> 0:01:28.796 really should be shaping the country's future. In South Africa. 0:01:29.036 --> 0:01:32.436 That lack of opportunity is still skewed by the legacy 0:01:32.476 --> 0:01:37.636 of apartheid and now alongside rapid globalization, which has left 0:01:37.716 --> 0:01:42.396 many young people geographically removed from job opportunities. You see, 0:01:42.476 --> 0:01:46.516 under apartheid, non whites were forcibly moved to areas far 0:01:46.676 --> 0:01:50.516 from city centers and not inequality endures today in the 0:01:50.636 --> 0:01:54.076 time and money people have to spend traveling even to 0:01:54.116 --> 0:01:58.716 find work. A twenty sixteen study found that young unemployed 0:01:58.756 --> 0:02:02.836 people spend five hundred and sixty rand that's around thirty 0:02:02.836 --> 0:02:06.676 eight dollars per month searching for work, and that's more 0:02:06.716 --> 0:02:10.956 than the average per person income of the households our 0:02:10.956 --> 0:02:14.676 guest Today, Nikola Gilambic is tackling the issue head on. 0:02:15.276 --> 0:02:18.716 She's trying to bridge the gap between the skills unemployed 0:02:18.756 --> 0:02:23.156 young people have and the skills potential employers are looking for. 0:02:24.036 --> 0:02:27.556 Harambi is working on all sides of the problem. They're 0:02:27.596 --> 0:02:31.396 working with the government to create jobs in tourism, conservation 0:02:31.636 --> 0:02:36.476 and in building a green economy. They're also training unemployed people, 0:02:36.916 --> 0:02:40.716 and they're training employers so that the employers can look 0:02:40.756 --> 0:02:45.636 beyond paper qualifications and see real life skills. It's cool 0:02:45.676 --> 0:02:49.436 how they work. Nicola uses face to face methods coupled 0:02:49.436 --> 0:02:53.196 with big data and that work is now spreading beyond 0:02:53.236 --> 0:02:57.356 South Africa. Okay, let's listen to Nicola now in conversation 0:02:57.476 --> 0:03:01.836 with an Applebaum, can you describe to me the problem 0:03:01.916 --> 0:03:04.076 in a nutshell? What is the problem that you're trying 0:03:04.116 --> 0:03:07.156 to solve. South Africa has one of the highest youth 0:03:07.196 --> 0:03:12.276 unemployment rates in the world, and that has multiple dimensions. Firstly, 0:03:12.636 --> 0:03:15.796 our economy is just not producing enough jobs and all 0:03:15.876 --> 0:03:18.556 most likely never produce enough jobs to absorb the young 0:03:18.596 --> 0:03:23.276 people that we have. Secondly, we have an education system 0:03:23.356 --> 0:03:26.476 that is not preparing young people for the world of work. 0:03:27.396 --> 0:03:31.076 And Thirdly, we have massive inequality in South Africa. So 0:03:31.556 --> 0:03:34.796 even the opportunities that do exist in the economy are 0:03:34.836 --> 0:03:39.996 not accessible for young people from poor households who don't 0:03:39.996 --> 0:03:43.756 have the social networks or the means to access those opportunities. 0:03:44.556 --> 0:03:48.276 Why is this such an important problem to solve? So 0:03:48.476 --> 0:03:56.316 if we talk about global inequality and sustainability, households around 0:03:56.356 --> 0:03:59.916 the world have to feel that young people can transision 0:03:59.956 --> 0:04:03.876 into an economy and provide for families. Otherwise we just 0:04:04.036 --> 0:04:09.756 do not have a stable social core. So it's really 0:04:09.876 --> 0:04:13.716 vital that young people feel that they can progress. Young 0:04:13.716 --> 0:04:17.076 people feel they have opportunity. Young people feel they have 0:04:17.156 --> 0:04:21.396 mobility in society, both in order to sustain social cohesion 0:04:21.916 --> 0:04:25.876 as well as to actually grow productive economies into the future. 0:04:26.436 --> 0:04:30.516 And in South Africa today, as I think is becoming 0:04:30.556 --> 0:04:34.076 the fact in many economies around the world, young people 0:04:34.316 --> 0:04:37.876 who should be an asset as the working age population, 0:04:38.196 --> 0:04:41.276 are actually trapped outside of the economy. When one looks 0:04:41.316 --> 0:04:45.356 at a problem like youth unemployment, which in South Africa 0:04:45.476 --> 0:04:47.676 is much higher than it is in many other parts 0:04:47.676 --> 0:04:50.716 of the world, how does someone like you begin to 0:04:50.716 --> 0:04:52.836 tackle it? How do you break the problem down in 0:04:52.876 --> 0:04:56.156 your head? So we've decided to be really pragmatic actually 0:04:56.156 --> 0:05:00.836 insolving the problem. The first starting point was to understand where, 0:05:00.876 --> 0:05:04.276 in fact are opportunities in the economy and where are 0:05:04.276 --> 0:05:06.516 they today and where are they likely to be in future. 0:05:07.316 --> 0:05:09.756 And then to understand who are the young people that 0:05:09.956 --> 0:05:15.396 we have, what is their actual educational and readiness for work, 0:05:15.836 --> 0:05:18.236 and what are they capable of? What are their assets, 0:05:18.276 --> 0:05:21.476 what are their attributes? And how might we match the 0:05:21.556 --> 0:05:24.076 young people we have and the opportunities we have in 0:05:24.116 --> 0:05:27.276 a better way, And where we find gaps, what is 0:05:27.276 --> 0:05:30.916 the shortest, quickest and most efficient way to close those gaps, 0:05:31.396 --> 0:05:34.836 not falling back on the traditional models of needing to 0:05:34.876 --> 0:05:39.276 send people to university for multiple years or needing to 0:05:39.476 --> 0:05:43.476 create entirely new jobs. Is Can we work with young 0:05:43.596 --> 0:05:46.996 people to close gaps in a much more agile way, 0:05:47.036 --> 0:05:49.916 to judge their potential in new ways, to be able 0:05:49.916 --> 0:05:52.396 to see attributes that they have that might be suitable 0:05:52.436 --> 0:05:55.836 for existing jobs. Can we also work with employers to 0:05:55.956 --> 0:05:58.676 change the way they're higher Can we change the way 0:05:58.676 --> 0:06:01.596 employers judge the potential of young people? Could you give 0:06:01.636 --> 0:06:05.356 some examples of what you found when, for example, when 0:06:05.356 --> 0:06:08.636 you looked at young people, what were they lacking and 0:06:08.676 --> 0:06:11.396 what was that you can give them that wasn't already 0:06:11.396 --> 0:06:15.076 available through the educational system. So, when we worked with 0:06:15.116 --> 0:06:18.716 employers in some growing areas of the economy, like global 0:06:18.756 --> 0:06:24.116 business services, back office processing, and banking, employers still today, 0:06:24.356 --> 0:06:29.196 despite tech, we're hiring people into those jobs and we're 0:06:29.236 --> 0:06:32.916 tending to seek graduates for those jobs. And we were like, well, 0:06:33.156 --> 0:06:36.236 do those jobs rarely require graduates? They were also running 0:06:36.676 --> 0:06:40.556 mathematics tests for a number of those jobs as screeners, 0:06:40.636 --> 0:06:44.556 and we're screening people out in South Africa, most young 0:06:44.596 --> 0:06:46.756 people and especially those from poor families will not have 0:06:46.796 --> 0:06:49.476 studied mathematics at school and will not have performed well 0:06:49.476 --> 0:06:53.956 in mathematics. When you actually looked at the jobs, they 0:06:53.956 --> 0:06:57.916 didn't require mathematics and they certainly didn't require university degrees. 0:06:58.476 --> 0:07:01.636 Employers were just using those as screening proxies. So what 0:07:01.676 --> 0:07:04.596 we were able to do is then look at the 0:07:04.636 --> 0:07:07.516 young people and say, well, what do I need to 0:07:07.556 --> 0:07:10.596 be a really great call center agent or what do 0:07:10.636 --> 0:07:15.116 I need to be a really good customer service facing individual? 0:07:15.316 --> 0:07:18.356 And of course what they're needed was great conversational competence. 0:07:18.996 --> 0:07:21.516 What they needed was to be well versed in English. 0:07:21.596 --> 0:07:24.196 What they needed was to be able to multitask on 0:07:24.196 --> 0:07:28.436 a computer. And all three of those actually maybe things well. 0:07:28.516 --> 0:07:30.876 So in the case of conversational competence, that may be 0:07:30.956 --> 0:07:34.276 an attribute they already have. In the case of learning 0:07:34.316 --> 0:07:36.876 to multitask on a computer, it may be a case 0:07:36.876 --> 0:07:38.756 of I've never seen a computer, but I've got a 0:07:38.796 --> 0:07:40.836 high learning potential and if you give me one, I'll 0:07:40.916 --> 0:07:44.276 learn really quickly. And in the case of practicing English, 0:07:44.316 --> 0:07:46.916 that's an opportunity to speak to somebody who speaks English 0:07:47.276 --> 0:07:50.676 rather than going back to school. So you know what 0:07:50.716 --> 0:07:52.996 we were able to do is then partner with the 0:07:53.076 --> 0:07:58.596 government to try and redirect some of the training spending 0:07:58.876 --> 0:08:01.636 that's happening in government, some of the skills money that 0:08:01.836 --> 0:08:04.676 is being in fact, vast amounts that are being spent 0:08:04.716 --> 0:08:08.476 by both government and the private sector on training young 0:08:08.556 --> 0:08:12.636 people that isn't relevant to the work that's available, and 0:08:12.836 --> 0:08:15.516 that just frustrates them further because they spend their own 0:08:15.556 --> 0:08:18.276 money and their own time and the government's money being 0:08:18.316 --> 0:08:21.476 trained and still don't actually have the basic competencies they 0:08:21.556 --> 0:08:23.596 need for the jobs that are available. So what we've 0:08:23.636 --> 0:08:28.076 been trying to do is find these short solutions, quick solutions, 0:08:28.156 --> 0:08:32.356 much more efficient solutions that give young people just the 0:08:32.436 --> 0:08:35.116 leg up they need to get into their first opportunities 0:08:35.516 --> 0:08:37.876 and make their way to get a foothold in the economy. 0:08:38.196 --> 0:08:41.116 Can you give me a specific example of a kind 0:08:41.116 --> 0:08:44.716 of short term program or solution, maybe an individual that 0:08:44.756 --> 0:08:47.676 you've met, and what kind of training do you mean 0:08:48.596 --> 0:08:51.556 in the short term? So, for example, some of the 0:08:51.596 --> 0:08:56.476 programs are a few days long to prepare somebody for 0:08:57.356 --> 0:09:01.676 customer service roles where they haven't been customers themselves. They 0:09:01.756 --> 0:09:04.956 come from a poor family and they haven't had the 0:09:04.996 --> 0:09:08.436 opportunity to just kind of engage with strangers and communicate 0:09:08.436 --> 0:09:10.556 in English with rangers, and a lot of that is 0:09:10.596 --> 0:09:14.716 just about the confidence to find one's voice and engage, 0:09:15.116 --> 0:09:17.916 particularly in English. Many of them have been sitting at 0:09:17.916 --> 0:09:20.476 home unemployed and just getting used to the fact that 0:09:20.516 --> 0:09:22.636 they have to stand on their feet all day. Comes 0:09:22.636 --> 0:09:24.996 a really important part of the training. It's a simulation 0:09:25.036 --> 0:09:28.236 of the work that prepares people to behave in a 0:09:28.276 --> 0:09:31.796 different way. Getting ready to actually and make a plan 0:09:31.836 --> 0:09:35.396 at home to get places on time is actually something, 0:09:35.436 --> 0:09:38.716 you know, punctuality something employers really really value to think 0:09:38.756 --> 0:09:41.476 it's most likely to get a young person fired in 0:09:41.476 --> 0:09:45.036 South Africa is not arriving on time, but actually navigating 0:09:45.076 --> 0:09:48.236 transport systems in big cities when you're poor is a 0:09:48.276 --> 0:09:51.436 difficult process, especially if you've got childcare concerns as well. 0:09:51.716 --> 0:09:55.356 So a lot of our training is not really training. 0:09:55.516 --> 0:09:58.476 A lot of it is behavioral simulation. A lot of 0:09:58.516 --> 0:10:03.236 it is preparing young people to be ready to take 0:10:03.316 --> 0:10:05.876 on the challenges that that world of work will present 0:10:05.956 --> 0:10:08.436 for them. So that's like a simple example in retail, 0:10:08.516 --> 0:10:11.396 But other one you know would be you know, when 0:10:11.436 --> 0:10:15.116 I say a short program, perhaps an eight week program 0:10:15.116 --> 0:10:20.636 where I am practicing and improving my written English communication, 0:10:20.756 --> 0:10:24.796 or I am practicing my spoken English communication, I am 0:10:24.836 --> 0:10:28.436 demonstrating problem solving capabilities that would be relevant in the 0:10:28.476 --> 0:10:31.676 financial services job that I'm going to go into. And 0:10:31.956 --> 0:10:35.516 a third example would be perhaps a six month program 0:10:35.796 --> 0:10:39.236 where I'm actually, despite the fact that I didn't do 0:10:39.516 --> 0:10:42.836 or succeed in mathematics at school, I'm actually born to code, 0:10:43.356 --> 0:10:46.476 and somebody has found that out about me and they're 0:10:46.516 --> 0:10:48.076 now are going to put me through a coding boot 0:10:48.116 --> 0:10:51.276 camp which is not just going to accelerate me into 0:10:51.316 --> 0:10:55.356 coding despite my absence of good schooling, but also going 0:10:55.396 --> 0:10:59.116 to give me the kind of behavioral readiness to work 0:10:59.116 --> 0:11:02.996 in teams, to collaborate, to problem solve in the way 0:11:02.996 --> 0:11:05.036 that I'm going to need to do when I land 0:11:05.476 --> 0:11:08.876 in a junior programming role. How do you work with employers? 0:11:09.236 --> 0:11:12.556 How do you change their prejudices about young people and 0:11:12.636 --> 0:11:14.716 who would be a good person to hire and who 0:11:15.116 --> 0:11:17.076 is that a kind of a training course they have 0:11:17.156 --> 0:11:19.316 to go through as well? You know, the change management 0:11:19.396 --> 0:11:22.236 journey with employers is probably the hardest part of this journey, 0:11:22.956 --> 0:11:25.636 and some of the tactics that we've employed over the 0:11:26.036 --> 0:11:29.156 last seven years that have really paid off is understanding 0:11:29.196 --> 0:11:33.476 that employers are most influenced by other employers, and so 0:11:33.796 --> 0:11:38.756 Harumby started with some early adopter employers who agreed to 0:11:38.796 --> 0:11:41.956 create the proofpoint and then also to be advocates with 0:11:41.996 --> 0:11:45.036 other employers about the fact that this cohort of young 0:11:45.116 --> 0:11:49.396 people could demonstrate the potential to do these jobs, could 0:11:49.396 --> 0:11:52.316 perform in these jobs. What we were able to do 0:11:52.436 --> 0:11:55.156 also was right from the outset, gather a lot of 0:11:55.276 --> 0:11:58.156 data and create the evidence space that we needed to 0:11:58.196 --> 0:12:02.796 be able to demonstrate this evidence of this that the 0:12:02.876 --> 0:12:05.956 young people could meet certain benchmarks in terms of their 0:12:06.076 --> 0:12:12.236 psychometric and competence potential. So a combination of a lot 0:12:12.276 --> 0:12:16.636 of relationship based change management work with employers as well 0:12:16.676 --> 0:12:21.036 as data and evidence to back this up, I think 0:12:21.116 --> 0:12:25.476 has allowed us to go from having five employers as 0:12:25.556 --> 0:12:29.156 partners at the outset to now having over five hundred 0:12:29.156 --> 0:12:33.636 employers who on a routine basis are accessing young people 0:12:34.236 --> 0:12:38.196 from this pool. Can you give me some idea of 0:12:38.236 --> 0:12:40.836 the effectiveness of the program? How do you know that 0:12:40.836 --> 0:12:42.836 this is working? So I think the first thing is 0:12:42.836 --> 0:12:46.276 that Harrambian now is starting to operate as system scale. 0:12:46.676 --> 0:12:48.756 So we have half a million young people in the 0:12:48.796 --> 0:12:52.276 Harrambian network and are going to have one and a 0:12:52.316 --> 0:12:56.356 half million young people in the network by twenty twenty two. Also, 0:12:56.436 --> 0:12:59.156 by that time, it will mean that for every cohort 0:12:59.196 --> 0:13:02.316 of young people exiting the schooling system or the education 0:13:02.396 --> 0:13:06.316 system every year, that the large percentage of those that 0:13:06.356 --> 0:13:10.636 would normally fall out into not being in education, training 0:13:10.716 --> 0:13:12.956 or employment by the end of the first year will 0:13:12.996 --> 0:13:15.116 now be on a pathway. They will be in a 0:13:15.156 --> 0:13:18.716 positive network, they will be improving their employability, and they 0:13:18.716 --> 0:13:21.756 will be getting access to information about opportunities. So that 0:13:21.916 --> 0:13:25.836 is a system scale solution for the country. Harambee is 0:13:25.876 --> 0:13:29.956 in partnership with the Greatest City region of Johannesburg around 0:13:30.236 --> 0:13:34.276 being a clearinghouse for unemployed people across the city, and 0:13:34.356 --> 0:13:37.356 I think that that model is a replicable one and 0:13:37.636 --> 0:13:41.236 is also being adopted nationally by the national government to 0:13:41.356 --> 0:13:45.076 work in tandem with the Department of Labor to manage 0:13:45.436 --> 0:13:50.196 the pathways of young people from learning to earning. And 0:13:50.596 --> 0:13:54.716 I think that as the Harambee platform becomes a scalable 0:13:54.996 --> 0:13:57.996 to the system, we're also seeing the dramatic impact that 0:13:58.036 --> 0:14:01.756 it can have. It doesn't just translate into more young 0:14:01.836 --> 0:14:07.116 people from poorer household accessing available opportunities. We're also able 0:14:07.156 --> 0:14:11.996 to start working with growth sectors, different industries that are growing, 0:14:12.436 --> 0:14:15.476 new job families that are growing, and to be able 0:14:15.516 --> 0:14:18.956 to almost plan ahead how we can prepare colds of 0:14:19.076 --> 0:14:22.156 young people for the jobs of the future, and to 0:14:22.196 --> 0:14:25.516 be able to match them to areas or parts of 0:14:25.516 --> 0:14:28.956 the country on a place based basis where we can say, 0:14:29.436 --> 0:14:31.596 you know, we're going to grow these industries here, how 0:14:31.636 --> 0:14:34.036 do we get the young people here ready for those jobs? 0:14:34.036 --> 0:14:36.836 And so that allows us to, in a very kind 0:14:36.876 --> 0:14:41.116 of agile way as a country, start to at least 0:14:41.276 --> 0:14:43.396 the growth that we do have, make it work for 0:14:43.436 --> 0:14:46.676 our young people and particularly our poor young people. So 0:14:46.876 --> 0:14:50.556 imagine there's a young person in South Africa who's finished school, 0:14:50.636 --> 0:14:54.996 who's unemployed, who wants to be employed. What exactly are 0:14:54.996 --> 0:14:58.116 the steps that he has to go through in order 0:14:58.156 --> 0:15:00.476 to get a job and how does he find out 0:15:00.476 --> 0:15:03.396 about you? How does he what does he access a website? 0:15:03.916 --> 0:15:06.796 Do you find him? How does it work? So young 0:15:06.836 --> 0:15:11.036 people can access Harambi and mostly word through a mobile 0:15:11.076 --> 0:15:15.276 platform which doesn't require a smartphone or a lot of data. 0:15:15.436 --> 0:15:18.796 It's pretty much free and for them to apply to Harrumbi, 0:15:19.836 --> 0:15:22.996 they will get called back and we find that while 0:15:23.036 --> 0:15:25.236 we gather a lot of data from them on the 0:15:25.276 --> 0:15:28.436 mobile phone, it's really important to have somebody interacting with 0:15:28.476 --> 0:15:33.116 them in person. They really appreciate somebody taking the time 0:15:33.196 --> 0:15:36.316 to understand them better, to understand their circumstance better, and 0:15:36.316 --> 0:15:39.716 to make a connection with them. And having made that connection, 0:15:39.716 --> 0:15:43.396 we're then able to sustain that connection through the mobile 0:15:43.476 --> 0:15:48.476 network and through ongoing interactions with young people who get 0:15:48.476 --> 0:15:52.996 offered things over time depending on where they are, what 0:15:53.036 --> 0:15:56.116 their attributes are. So they will be given a range 0:15:56.156 --> 0:15:59.596 of assessments and those assessments will tell us a lot 0:15:59.636 --> 0:16:03.196 about their eligibility for different kinds of roles in the economy. 0:16:03.996 --> 0:16:07.676 But we're trying to use assessments that are not traditional ones. 0:16:07.716 --> 0:16:11.396 We're trying to use assessment that don't exclude young people 0:16:11.516 --> 0:16:15.676 based on their education qualifications, that don't exclude young people 0:16:15.716 --> 0:16:19.676 based on their poverty and social circumstance, but that rather 0:16:19.836 --> 0:16:22.796 can go through those and see the potential of young 0:16:22.876 --> 0:16:26.596 people their attributes. You know, it may be that what 0:16:26.716 --> 0:16:30.676 employers will say is we're looking for grits and resourcefulness 0:16:30.756 --> 0:16:34.916 and problem solving. Well, a young person who's been struggling 0:16:34.956 --> 0:16:39.036 to stay in school and get themselves through school, responsible 0:16:39.156 --> 0:16:42.956 for many things in a poor household, and dealing with 0:16:43.356 --> 0:16:47.036 financial issues day to day has demonstrated a huge amount 0:16:47.076 --> 0:16:49.836 of grits and resourcefulness, which if we are able to 0:16:50.636 --> 0:16:53.356 capture that and demonstrate that in the profile of that 0:16:53.516 --> 0:16:56.396 young person, may mean that an employer can really see 0:16:56.436 --> 0:16:59.276 their potential and understand that they can be an asset 0:16:59.316 --> 0:17:04.116 in the workplace. So Harrumpies process involves a lot of 0:17:04.396 --> 0:17:07.676 new proxies and new assessments that we're using to judge 0:17:07.716 --> 0:17:10.996 young people's potential. If they stay in the network, they 0:17:10.996 --> 0:17:13.436 can also grow their profile, so they will be nudge 0:17:13.476 --> 0:17:18.996 and encouraged to improve things about themselves or gain elements 0:17:18.996 --> 0:17:21.956 of their profile that would strengthen their likelihood to succeed 0:17:21.956 --> 0:17:26.196 in the economy if they're eligible for and could access 0:17:26.236 --> 0:17:31.036 an opportunity, for example, that required them to have conversational English, 0:17:31.156 --> 0:17:33.756 like a great tourism job or a job in a 0:17:33.836 --> 0:17:36.476 call center, which in a South African context would be 0:17:36.516 --> 0:17:39.356 a high quality job for these young people. You know, 0:17:39.396 --> 0:17:42.436 can we nudge them to an opportunity near where they 0:17:42.516 --> 0:17:45.356 live where they could practice their English. Can we link 0:17:45.396 --> 0:17:50.756 them to an opportunity to retake one module of mathematics 0:17:50.796 --> 0:17:52.916 if they were going into or eligible for a job 0:17:52.956 --> 0:17:57.556 that really did require that. Could we take their theoretical 0:17:57.636 --> 0:18:00.796 qualification as an electrician and give them an opportunity to 0:18:01.796 --> 0:18:05.676 visit an institution where they could actually apply what they've 0:18:05.756 --> 0:18:07.956 learned for the first time, because they won't have had 0:18:07.956 --> 0:18:12.596 that opportunity before. So these are very practical nudges and 0:18:12.716 --> 0:18:15.636 opportunities that we would constantly provide to those young people 0:18:15.996 --> 0:18:19.636 to what we call bring them closer to work, and 0:18:19.676 --> 0:18:24.556 then have them in this very sophisticated data driven network 0:18:25.316 --> 0:18:28.996 that also then has demand side intelligence, knows about all 0:18:29.036 --> 0:18:31.556 the jobs that are available in the economy and in 0:18:31.596 --> 0:18:34.556 the geographies in which these young people live, and are 0:18:34.596 --> 0:18:38.076 able to match them and link them to those opportunities 0:18:38.076 --> 0:18:42.396 on an ongoing basis. So your process is really quite individualized. 0:18:42.596 --> 0:18:44.796 You have teams of people who work for you, who 0:18:44.836 --> 0:18:48.476 are accustomed to speaking to young people across a wide 0:18:48.556 --> 0:18:51.076 range of very wide range of languages and cultures in 0:18:51.116 --> 0:18:55.716 South Africa and then personalizing a program for them. Although 0:18:55.716 --> 0:18:57.876 we have half a million young people in the network 0:18:57.956 --> 0:19:00.156 we talk about it's you know, it's five hundred thousand 0:19:00.156 --> 0:19:03.676 cohorts of one, and every individual in the network should 0:19:03.716 --> 0:19:07.036 feel like they're on their own personal journey, that there 0:19:07.036 --> 0:19:10.676 are young people at the other end of a call 0:19:11.036 --> 0:19:13.796 that can speak to them, that understand and have empathy 0:19:13.916 --> 0:19:18.436 with their circumstance, who until fairly recently were in the 0:19:18.476 --> 0:19:20.476 same position as them and have now made it into 0:19:20.516 --> 0:19:24.036 the economy and can guide and advise them. And they 0:19:24.076 --> 0:19:27.596 should feel like the profile that they receive and the 0:19:27.676 --> 0:19:32.956 advice and nudges that they get are highly relevant and 0:19:32.996 --> 0:19:36.156 appropriate to them as an individual and to their personal 0:19:36.196 --> 0:19:39.836 circumstance where they live, the kind of household they're in, 0:19:40.516 --> 0:19:42.716 the kind of financial means that they have, the kind 0:19:42.716 --> 0:19:45.756 of transport systems they can access, and the kind of 0:19:45.796 --> 0:19:48.596 school that they went to, and that what's on offer 0:19:48.596 --> 0:19:52.956 should feel highly personalized for them. But obviously, to do that, 0:19:53.396 --> 0:20:00.516 we've had to build very scalable systems, which include taken 0:20:00.556 --> 0:20:04.756 cloud based systems that enable us to gather a lot 0:20:04.756 --> 0:20:07.516 of intelligence that enables us to provide a really quality 0:20:07.516 --> 0:20:11.156 service to individuals, as as well as a national call 0:20:11.276 --> 0:20:14.476 center which means we can actually have personalized interaction with 0:20:14.556 --> 0:20:18.076 young people over the phone, and then in community services, 0:20:18.116 --> 0:20:21.436 in partnerships with government and community organizations, where we can 0:20:21.476 --> 0:20:27.476 extend services and opportunities to young people that are local 0:20:27.756 --> 0:20:29.836 to where they live. It's fascinating as a kind of 0:20:29.876 --> 0:20:32.636 combination of some very old fashioned thinking, you know, one 0:20:32.756 --> 0:20:36.636 to one speak to the person individually, with very high 0:20:36.636 --> 0:20:39.316 tech collection of data so that you know where the 0:20:39.396 --> 0:20:42.476 jobs are in their area and so on. Exactly. I mean, 0:20:42.476 --> 0:20:47.036 I think we fundamentally believe that people need to interact 0:20:47.076 --> 0:20:49.836 with other people, and in fact, we've built a network 0:20:49.876 --> 0:20:53.516 because they need peer networks. They need people to care 0:20:53.516 --> 0:20:56.476 about them. They need to feel that somebody is seeing them, 0:20:57.036 --> 0:21:00.396 and you can't achieve that just with a tech platform. 0:21:01.196 --> 0:21:04.916 On the other hand, the tech platform enables us to 0:21:04.956 --> 0:21:07.836 do things that simply would not be possible at scale 0:21:08.356 --> 0:21:11.396 if we were just running a kind of high touch, 0:21:11.716 --> 0:21:15.516 personalized service, not just the data that we're able to 0:21:15.556 --> 0:21:18.996 gather both on the demand and the supply side, but 0:21:19.036 --> 0:21:22.076 also to once you've made a connection with somebody's stay 0:21:22.076 --> 0:21:26.196 in communication with them through a tech platform that is 0:21:26.436 --> 0:21:30.516 not just scalable but highly affordable. Is this a system 0:21:30.636 --> 0:21:34.236 that you think could be taken to other countries. Does 0:21:34.276 --> 0:21:36.396 this just work for South Africa or do you envision 0:21:36.436 --> 0:21:39.156 it working in other reports of Africa or in the world. 0:21:39.556 --> 0:21:43.356 I definitely think it has application beyond South Africa. We 0:21:43.476 --> 0:21:47.916 have recently begun the process of applying the model in 0:21:48.316 --> 0:21:52.356 Rwanda in partnership with the government there and MasterCard Foundation 0:21:52.396 --> 0:21:56.436 and others, and we have had a tremendous amount of 0:21:56.516 --> 0:21:58.996 interest from other parts of Africa, but also other parts 0:21:58.996 --> 0:22:02.476 of the world. I think the world has caught up 0:22:02.476 --> 0:22:05.916 with us on this future of work problem and also 0:22:06.076 --> 0:22:08.876 of the problem of young people in particularly poor young 0:22:09.236 --> 0:22:12.276 or being excluded from the economy. I definitely think that 0:22:13.316 --> 0:22:17.516 the solutions that we're building have great relevance globally. The 0:22:17.636 --> 0:22:22.716 way we're assessing potential, the way we're managing demands supply 0:22:22.836 --> 0:22:26.356 matching on a much more real time and agile basis, 0:22:26.516 --> 0:22:28.876 and the way we're breaking through some of the barriers 0:22:28.916 --> 0:22:32.516 of the education system. I think we'll have relevance way 0:22:32.556 --> 0:22:35.836 beyond South Africa, probably globally. So give me an example 0:22:36.036 --> 0:22:39.516 of how your program might change the life of one individual. 0:22:39.716 --> 0:22:41.876 So let me tell you about Cindy and She lives 0:22:41.876 --> 0:22:46.276 in a poor township outside of Cape Town in South Africa, 0:22:46.476 --> 0:22:49.436 member of a fairly large family. No one in the 0:22:49.476 --> 0:22:52.836 family's working, single mom. She has a young child of 0:22:52.876 --> 0:22:57.276 her own and the child is not in daycare. The 0:22:57.356 --> 0:23:01.876 family kind of is scrounding around food on a daily basis, 0:23:02.476 --> 0:23:05.356 accessing some government grants pretty much run out by the 0:23:05.436 --> 0:23:09.436 end of the month, and so in that circumstance, Indie 0:23:09.836 --> 0:23:14.676 manages to hear about the her rumby Youth Employment Accelerator. 0:23:14.796 --> 0:23:19.996 She accesses her RUBY through her mobile phone and came 0:23:20.036 --> 0:23:24.796 in by all our assessments a really high potential individual. 0:23:25.156 --> 0:23:29.236 She just was off the charts in her psychometric profile 0:23:29.556 --> 0:23:32.276 for the world of work and in her learning potential 0:23:32.276 --> 0:23:36.516 and ability to learn quickly. So she was successful in 0:23:36.676 --> 0:23:40.836 accessing a two month bridging program which prepare her for 0:23:40.956 --> 0:23:44.196 a care center job at a premier health insurer in 0:23:44.236 --> 0:23:49.476 South Africa. And one of the days on the training program, 0:23:49.596 --> 0:23:52.116 she was late. And it's a real kind of issue 0:23:52.116 --> 0:23:54.236 on the training program to be late, because punctiality is 0:23:54.236 --> 0:23:56.076 one of the most important and valued issues on the 0:23:56.076 --> 0:23:59.156 training program, and she was like ten minutes late, and 0:23:59.196 --> 0:24:01.596 it turned out that she had been mugged on the 0:24:01.636 --> 0:24:05.716 way to the program, had everything stolen from her. She 0:24:05.836 --> 0:24:09.116 was very anxious about her child, and the whole situation 0:24:09.196 --> 0:24:11.316 been really terrible. She was most concerned that she was 0:24:11.356 --> 0:24:13.996 ten minutes late for the program because she just saw 0:24:14.036 --> 0:24:17.956 this as her ticket and her chance to shift the 0:24:17.996 --> 0:24:20.396 trajectory of her life and that of her child. She 0:24:20.476 --> 0:24:24.356 stayed on the program, and Stall a few years later 0:24:24.756 --> 0:24:27.796 successfully landed and has kept her job at She's now 0:24:27.836 --> 0:24:31.436 actually been promoted in this job at this insurance company. 0:24:32.196 --> 0:24:34.076 One of the things that Cindy talks about, which I 0:24:34.116 --> 0:24:38.956