Statistically Speaking

Statistically Speaking
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Statistically Speaking is the Office for National Statistics' podcast, offering in-depth interviews on the latest hot topics in the world of data, taking a peek behind the scenes of the UK's largest independent producer of official statistics and exploring the stories behind the numbers.

  1. 24 MAR

    Supermarket Sweep: Measuring inflation with over a billion scanner beeps

    Miles and guests unpack how the ONS is collecting the prices from more than a billion supermarket checkout and online sales to measure UK inflation.  Transcript Scanner data podcast transcript Miles:  Hello and welcome to statistically speaking, the official podcast of the UK's Office for National Statistics. I'm Miles Fletcher, and in this episode, we're taking an in depth look at a very big change in how the ONS produces its estimates of inflation, no longer the sole preserve of clipboard wielding prices collectors roaming the supermarket aisles. The digital revolution has now fully arrived. From this month, the UK's inflation indices are now partly based on millions of prices data gathered directly from the tills or scanners, to be precise. How is it all done? What is the role of Taylor Swift in all this? Yes, there is one. And what are the benefits for economists, decision makers and all of us ordinary folk who worry about the cost of living. Here to unpack it all for us is Mike Hardy, who has led the project here at the ONS, and top economist and former member of the Bank of England Monetary Policy Committee, Jonathan Haskel, professor of economics at Imperial College London. Professor to start with you: to understand what's changed, it'd probably be helpful to remind ourselves how consumer prices inflation has until now been calculated. Essentially, it was the ONS and its agents checking the prices of 1000s of items on a monthly basis to see how they changed.   Jonathan: Yeah, that's right, and the ONS has gone to an enormous amount of effort in order to make that collection representative and make it consistent. But of course, in the modern era of scanner, data, computers, e commerce, things like that, there are other ways of doing it. I guess the important point, which Mike can talk about some more, is that one of the things that we know from statistics is that having a big sample isn't necessarily going to be better if you have a representative sample to start with. So I think one of the interesting points about all of this is whilst the scanner data is collecting many more data points, it's a fascinating check on the representativeness or otherwise of the ONS survey and the procedures thus far as to whether the actual average of all of that will turn out to be very different or similar to what's done before. It's a great advantage to have all of this extra data, but one shouldn't overstate either the advantage or use it as a way of rubbishing what the ONS has been doing in the past.   Miles: So to put it this way, perhaps then, what the ONS has traditionally been doing in collecting prices, is to take this big monthly snapshot of retailing and prices, and what people have been paying for items. What it's got now, what it's moving to in the digital age is moving from a still picture, perhaps to a rolling 4k video, and from that, it can find out exactly what has been missed out of the inflation calculations previously.   Jonathan: Well, I'll just put a little bit of a spin on that. One of the things that the price collectors do, and they're very, very careful to do, is to make sure that that snapshot is consistent across the snapshots, if you sort of see what I mean. So there is a bit of a rolling element to those snapshots already, because, for example, if you're going to collect the price of, let us say, Ladies jeans, which is something that I was doing with the price collector recently, you want to be sure you collect the price for the same good over time. And the point about the price collectors is they're extremely conscientious about making sure that, in the case of ladies jeans, they are coloured blue. They've got either a flared leg or not a flared leg. They've got the same number of pockets, they've got the same amount of stitching, they've got different decorations on them. To make sure that those goods remain the same is actually very important, and that's something actually which the hand collection can do. And as I say, I think that means that the snapshot element is maybe not quite the right metaphor, if I may say, miles. It is the relation. It's a consistent element over time, a consistent snapshot if that's using a metaphor   Miles: That said it's more than just blindly following the same list of products every month. But nonetheless, the traditional way of doing things has had significant. What do you think those are?   Jonathan: I guess the limitations are that when one is collecting a sample, any kind of sample at all, one is always doing one's best to try to hope that that's a representative sample, and having more data then is going to help if it turns out that the sample is unrepresentative. So I think that's one part of it. I think the other part of it is, of course, it's becoming increasingly costly to hand collect these numbers, and you know, like any public agency, one wants to be as careful as one possibly can with taxpayers money. That's the sort of second thing. And the third thing is, especially in the era of the Internet and dynamic pricing and so forth, these prices change, you know, at sort of dizzying rates as firms change their prices throughout the product cycle of the good. And therefore the sort of consistent snapshots may miss some of that variation,   Miles: And all that data, of course, is out there to be learned from, isn't it? Essentially, Mike, is that what the scanner data project has been, it's been all about harvesting that data and using it to produce what's being described as a step change in how inflation is calculated.   Mike: So we've been transforming our consumer price statistics for some time, and we've been acquiring a wide range of data sources with the aim of improving the quality and granularity of our consumer price statistics. So in recent years, we've used administrative data for rail fares and second hand cars, and we will be incorporating grocery scanner data for 50% of the grocery market, where we will be moving from using around 25,000 prices for those retailers to 300 million derived from the sale of over a billion products, so much more granular and rich information on the prices within those retailers. Importantly, as well, we not only have the price of everything within a store, so we move away from the sample that Jonathan described. So taking the price of a small number of products within each store to collecting all of the prices within store, from supermarket checkouts to also getting a better understanding of how much of each product people are purchasing. So that gives us a much clearer picture of inflation by using these large administrative data sets.   Miles: Because the purpose here is to get a sense of how the cost of living is changing for people as well, isn't it? And presumably, if you're just checking the same prices of the same goods month after month, you're not understanding about how price changes are influencing people's purchasing decisions. Does it help with that?   Mike: Yeah, so the scanner data, as I said, gives us a complete kind of picture of all the prices within a store, and it gives us the underlying quantities, so how much of each particular product is being purchased, it also gives us the price at the till, rather than the price on the shelf. So that captures a number of different things that we were unable to capture with the sample data. So the first being if consumers switch from a premium to a value brand, for example, in response to cost of living rising. We pick that up in the scanner data and also discounting, we can better reflect that particularly store cards, because we now understand for a particular product, total spending on that product and the quantity of that product sold, which allows us to get an average price for that product. So we better capture store discount cards, which are available in many of the supermarkets.   Miles: And so by getting a sense of the changing availability of products and what people are actually spending on them, it becomes much more useful then as a cost of living index as well as simply a measure of price change. Yes.   Mike: So the way we currently produce our inflation statistics is that we have a large virtual shopping basket of goods and services. There are 760 items in that basket. We set the weights at the start of the year, and we set the basket, and then we track the prices of those 760 representative items throughout the year. What the scanner data allows us to do at a very detailed level for certain is what we describe as consumption segments. So a consumption segment would be rice for example, is to reflect change in consumer spending patterns within that consumption segment. So for example, if somebody changes the type of rice that they're buying, they decide to buy microwave rice instead of basmati rice, or they decide to switch from a premium rice product to a value rice product, then we'd capture that in the scanner data on a monthly basis, whereas in the previous approach, we'd just monitor the price of a small number of products. So maybe we would monitor the price of microwave rice and basmati rice just over the year. But now with the scanner data, we have the price of all rice sold within a store, and we can reflect people's changing consumer spending patterns when purchasing a particular consumption segment, which I've described here as rice. Miles: And that in turn, I guess, can also influence the way you weight the index as well in future, because that's a fundamental part of calculating inflation that perhaps a lot of people don't fully appreciate. Mike: Yeah, so it'll still be a fixed basket, but the lowest level of aggregation, so that the most detailed data that we have -  that data that's coming in from retailers, where we have the kind of total sales plus the quantity, which allows us to derive a price or a unit cost within

    34 min

  2. 27 JAN

    The road ahead for the ONS: a conversation with Darren Tierney

    Late last summer, Darren Tierney stepped into the newly created role of Permanent Secretary at a pivotal moment for the organisation. In a new episode of Statistically Speaking our host Miles Fletcher sits down with Darren to talk about what happens next.    TRANSCRIPT   MILES FLETCHER Hello and welcome to another episode of Statistically Speaking, the official podcast of the Office for National Statistics. I'm Miles Fletcher.   Now, if you've followed the UK news much over the past year, you'll know the ONS has been under more scrutiny than at any point in its history, questions about trust, priorities, its core economic data and whether the organisation has simply been trying to do too much at once, have all been very publicly aired.   Today's episode is about what happens next. Late last summer, Darren Tierney stepped into the newly created role of Permanent Secretary at a moment when some of the UK's most relied upon statistics, especially those based on the Labor Force Survey, were under real pressure. In this conversation, we'll talk about Darren's background in government, running large, complex public services and helping to craft and enact key policies. We'll explore how data has shaped his career so far, and what he found when he arrived at the ONS. We'll also dig into some of the hardest questions facing the organisation, and what absolutely has to be fixed first, what may need to stop, how user expectations are being balanced with that and how full confidence in official statistics can be restored. This isn't just an internal reset. What the ONS does and how well it does it matters to policymakers, businesses and the public alike. So join us as we talk about focus, priorities, and the road ahead.   So then Darren, to begin at the beginning, you're not an economist or statistician by profession yourself. What motivated you to take leadership of what is the central organisation in UK statistics?   DARREN TIERNEY Sure, well look as a non-statistician you can imagine I was a little bit daunted when this prospect first came along for precisely that reason.  I was kind of worried that maybe not being a statistician or an economist might be a real drawback but as I thought more about the job, and more about what was needed for the organisation at the time, and with the split of the roles, I thought actually, I can really help. But what really drew me to the role was that although I'm not a statistician, Iv'e been an avid consumer of ONS products for the 25 years that I've been a policy wonk in Whitehall. And going from a good policy professional to a great one, requires both access to good data and also a real understanding of it and knowing how to use it. And it's that background that kind of helped me and really got me into it, and so I saw it as a real opportunity to come and help an organisation that really couldn't be any more consequential for the UK.   MILES FLETCHER The Devereux review said that what was needed was someone with really serious operational experience, having run serious civil service operations, and you bring plenty of that. Could you just detail some of that? You've had a very strong rise, you know, through the ranks of the civil service. Just trace that for us, if you would.   DT Yeah. So I started life in what was the old Prescott empire of DETR, which was environment and transport in the regions as a policy wonk working on aviation. I then went and joined the Ministry of Justice, where I spent three years in the private offices of Harriet Harman, Jack Straw and Ken Clarke, and that kind of real frontline policy making, as it were, is the thing that I did a lot of in the first half of my career.   The second half of my career, which is much more relevant to the ONS, was centred around transformation and change. And again, I spent about 12 years or so in the MOJ, and my senior career there was about transforming systems and running big programs. And I went from there to international trade, just after the Referendum, where like a lot of officials at the time, I was quite keen to run to where the energy or the fire was after Brexit. But I didn't fancy working DExEU, and this new department called Trade seemed quite interesting. So I went there, and again, this was a kind of brand new department, and it grew from a few hundred people to about four and a half thousand. And so that kind of building and running the department as a strategy director for investments and exports,  I guess those two experiences in justice and trade are the two that I rely on most in this role.   MF So you spent time in the corridors of power then, the ministerial heights of the civil service, but also having to try and make the machine run efficiently as well, and to deliver public services and achieve policies in the real world. What role has data played in that? And what sort of statistics were you using? What sort of insights were you getting? Can you share some experiences of how that's shaped your career, and your understanding, particularly of the job in hand here at the ONS.   DT Sure, I guess the job where it was most relevant was when I was in justice, where I worked in civil and family policy, Legal Aid and supporting on prison reform, and particularly on youth justice reform, and maybe that's a good example to pull out. Justice is one of those areas where people have very strong views about what the right policy prescription is, but there's often quite a lack of evidence that goes behind some of these strong policy positions, if I can put it like that, and one of the things that bedevilled us was trying to turn very strong ministerial desire for action across the human justice system into something that was evidence based, and where we could point to proof that these things would work, and we did that several times in the youth justice system.   Perhaps the one that I look back on most fondly in the youth estate...We were constantly telling ourselves, and indeed the world, that kids in the youth estate were getting thirty hours a week of education, and that was true in the sense that that's what we were buying. We were procuring thirty hours a week from providers, but the kids in the estate were not getting thirty hours a week and we didn't really know until we sent in a team of researchers from the MOJ analytical team to do some surveys, and then we also analysed some of the ROI coming out of that estate. And of course, what we discovered was that although we were buying thirty hours of education, it was always being disrupted by all the other services that these kids needed to access. So every dentist, every doctor, every lawyer that was coming in to interact with those kids, that was happening during what would otherwise be the school day, but we didn't really know that. And for years, we were kind of running this system and telling ourselves and indeed telling the world, that this was what was going on, but having analyzed that system and got ourselves some real data we were able to change that system so that it was education first, and all of those other ancillary services would take place outside of the school day. So sometimes it can be quite basic bits of analysis that can result in the biggest changes.   MF I guess the lesson there is, we always need to never totally trust the data we've got and find better insights and better ways of looking at things. And I guess that leads us into the challenge here at the ONS. What were your first impressions when you took the plunge in, suffice to say, quite interesting circumstances in the earlier part of 2025. What did you make of your earliest days here at the ONS and formulating what needed to be done?    DT  Your characterization of it is right. Before I even arrived, I was talking to a lot of the stakeholders, including Robert Devereux and others, and in doing that and in reading around the issues, I ended up getting quite a negative view of what was going on, perhaps understandably, because that was what was being reported. So I was expecting an organization that was perhaps much more kind of browbeaten than the one I found. And that's not to sound complacent at all, but the thing that I was surprised at when I arrived was just the desire for progress, for action, for us to kind of turn the page, and for us to get back to being a respected NSI. And that that sort of energy that I found amongst the senior team was great because I was expecting to have to do quite a lot of jigging up of the system to get us into that mode, but actually, when I arrived, people were already there. So that was my first impression. My second impression really was just the quality of the people here, the skills, the experience and the expertise here at the ONS is genuinely inspiring. And I said this to Civil Service World a few weeks ago. We abuse the phrase "world class" in Whitehall, we often claim things are world class when they're not, but we do have some genuine world class expertise in the ONS and I was genuinely inspired when getting to meet some of those people during the first few days and weeks.   MF It sounds as though people had a good idea of what needed to be done, what was coming out in the media, and of the various inquiries that took place last year, was that the general feeling was that ONS had become spread too thin, and needed to prioritize on those things that ONS is best known for. It does have a worldwide reputation for, crucially, what people most rely upon it to get it right, prioritizing those. Was that what emerged?   DT It really was. And that sense that getting back to the core business of an NSI (National Statistical Institute) was what people were people were really hungry for us to do. I think there is a danger when saying something like that, of sounding like no one valued that hugely innovative work that h

    35 min

  3. 21/10/2025

    Crime data: Numbers, narratives and nuance

    In "Crime: Numbers, Narratives and Nuance" our host Miles Fletcher speaks with Nick Stripe, Joint Head of Crime Statistics at the ONS and John Rentoul, leading commentator on crime, policing, and the media, about the challenges in interpreting crime data.    Transcript   MILES FLETCHER  Hello and welcome to another episode of Statistically Speaking – the official podcast on the UK's Office for National Statistics. The time we're returning to the scene of a major statistical topic we've touched on before but amid a new and sometimes highly polarised public debate, one we think fully bears further investigation: how best to understand and interpret the crime figures produced and published by ONS.   Helping us with our enquiries is Nick Stripe, Joint Head of Crime Statistics at the ONS. It's his job to assemble and present the complex statistical picture of crime revealed in two very large and sometimes conflicting data sources. We also have an independent witness in the highly experiences shape of John Rentoul, Chief Political Commentator for the Independent and visiting professor at Kings College London. He'll be talking about the use and possible abuse of crime figures in the media and political debate. Are the statistics and those who produce them doing enough to enable the public to understand properly the prevalence and nature of crime in our society today?  Nick, a big question to start with, some people think crime is going down, other people insist it's going up. Who's right?     NICK STRIPE  Well, it's a question that sounds simple, doesn't it? And it's a question I get asked quite a lot. But if you think about the concept of crime, you soon realize that it covers a really huge range of actions and behaviours. If I was a chief constable trying to reduce crime in my area, I'd want to know what kinds of crimes are causing the biggest problems.  So, is it theft, robbery, violence? Domestic abuse? sexual offenses? Maybe it's fraud. And even if you tell me it's theft, then there's still a broad spectrum. So, is that burglary from houses? Is it theft of vehicles? Is it people having things snatched off them in the street? Is there a new thing about theft from doorsteps? Each of those types of theft would have its own trends, patterns and challenges. So, what I'm really saying is that whilst I understand your desire for a single answer, the real stories are in the detail of those different crime types.     But I will come back to your question, is crime going up or down? Broadly speaking, I would say we're experiencing much less crime now than we did 20 or 30 years ago. Many crime types have been declining at a fairly steady rate since the mid 1990s and in more recent years, probably since we started to emerge from the pandemic, crime levels have broadly flattened out at that lower level.     But some types of crime are rising now, some are still falling, and some are changing in ways that reflect shifts in society, shifts in technology and shifts in policing.     MF  That's the complex and highly nuanced picture, and it's the one that is designed to best serve those who make policies around crime, those who try to contain crime, those who try to fight it?    NS  That's right, Miles. And it's a picture that we get from drawing on several different data sources. There are two main ones. One is police recorded crime, and the second one is our independent survey of crime across England and Wales. And then we can use other data sources to provide richness for certain crime types, or to triangulate what we're seeing in those main data sources. And when we pull all of that together, we try and give a rich, nuanced, accurate picture for policy and policing.     MF  That's the aim of the statistics, but when it comes to public debate and public perceptions, do we risk misleading people by not being able to come up with a single barometer of crime? You can't go on the ONS website and see whether overall offending is up or down for example, or is that a completely pointless exercise?    NS  Well as I said, different crime types will have different things acting on them at any one point in time. But what we can do, for example through the crime survey, that has measured what I'm going to call traditional types of crime experienced by us as the public. So that's things like theft, that's things like violence, that's things like criminal damage, and in the last 10 years or so, that also includes fraud. And when we look at those types of crimes, we can see that, if you want a single figure, the numbers have come down. And that's when I say that over the last 30 years, there's been a big reduction in crime. If you take violence, theft and criminal damage, about 30 years ago, four in 10 of us, about 40% of us, every year would experience one of those types of crime. Now it's one in 10 of us. So, I can give you that picture for certain types of crime, but there are different ways of measuring and different data sources are better for certain types of crime, so coming up with that overall number is actually quite difficult.     MF  John, when it comes to political and media debate around crime, there are no simple answers, and yet those are to arenas where we want simple answers.      JOHN RENTOUL  Well, I think Nick did give a fairly simple answer, which is that if you ask people an open-ended question - have you been the victim of crime over the past 12 months - then the number of people saying yes to that question has gone down very dramatically over the last 30 years. So, in that very simple sense, crime has gone down hugely over the past 30 years.    But of course, people don't feel that, because that requires comparative memory...collective memory over a long period of time, and people are worried about what they read in the papers and what they see on social media. So, people, just as they always think that Britain is becoming a more unequal society, they always think that crime is rising, and it's very difficult to contradict that with simple statistics.     MF  Isn't that because there's always  some aspect of crime, some type of crime that's always rising and it's opposition politicians, headline writers, particularly...of course you'll find lots of sophisticated, nuanced debate in the media...But those who write the headlines like to seize on the negative, don't they? Bad news sells. And you can see how people get these impressions because it's just the scary stuff they're hearing about.     JR  Well, possibly, although I think it's probably deeper than that. I think it's just human nature to feel fearful about the threats in society and the way of dealing with that psychologically is to assume that those threats are worse now than they used to be.      When you ask people has crime increased, they're not really giving you a statistical answer. They just say yes I'm afraid of various sorts of crime. And, you're quite right, the sorts of things that stick in people's minds are phone thefts and shoplifting, the sorts of things that get highlighted on social media all the time.     MF  As they used to say at the end of Crime Watch every week, these types of crimes are rare,  don't have nightmares. Yet, that's no good if you've had your phone nicked or witnessed a shoplifting incident.    JR  That's right, and what's interesting about those two is that witnessing a shoplifting incident wouldn't be recorded in the crime survey because you personally are not the victim of that crime. So that's an example of an incident that has gone up, but that wouldn't be captured in the survey statistics, although having your phone nicked is something we probably would remember.     MF  And how responsible would you say our political leaders have been over the years? How responsible perhaps are they being now in the way that they present crime statistics?     JR  Well, it's very difficult, isn't it, because it's always partisan between government and opposition because ministers are always saying that crime has gone down, just as they're saying more nurses and doctors are employed in the NHS and all that. It's one of those statistics that well, certainly for the past 30 years, has been true, but opposition politicians have to try to argue the opposite, and they point to the sorts of crimes that have gone up, such as shoplifting and phone theft. So, it is a constant battle between what sounds to the public like just rival political claims, and the public will just discount more or less what any politician says and just choose to believe what they want to believe.     MF  Like many big statistical topics, once again, people can argue diametrically opposing things and both be right in a sense...    JR  Yes, exactly    MF   ...and have some statistical basis for saying it. So it's the job of this podcast to help people untangle those sorts of complexities and decide for themselves.     Let's embark on a little journey then around how the crime statistics, these are the ONS crime statistics for England and Wales, how they are put together, how best to interpret them. And nobody better to guide us through that than yourself Nick, as joint head of crime. Starting at the beginning, because this would have been the original source for crime statistics going back a very long time indeed, and that is police recorded crime. And that sort of conjures up an image of The Bill, doesn't it, or Dixon of Dock Green for older listeners of a desk sergeant sitting there and dutifully recording offenses. Is that what it's like?     NS  I'm pretty old myself Miles, but that's stretching i

    38 min

  4. 23/07/2025

    Migration: The needle in the data haystack

    With migration continuing to make headlines in the media, we unpack what actually defines a "migrant", and how the UK's largest producer of official statistics goes about counting them.  We also shed light on the misuse of migration figures.    Transcript    MILES FLETCHER  Hello and a very warm welcome to a new series of Statistically Speaking - the official podcast of the UK Office for National Statistics. This is where we hear from the people producing the nation's most important numbers, about how they do it and what the statistics are saying.   Now it's hard to think of one statistic that could be said to have been more influential these past few years than net international migration. Suffice to say it's the one ONS statistic that probably draws more media attention than any other.  But to fully understand the migration figures, and the swirling debate around them, we'd say it pays to know a little about how they are put together. And the first thing you need to know about that is what, or who, is a migrant in the first place. As usual, to unpack and explain the migration statistics we have the top experts from the ONS and beyond. Mary Gregory is director of population statistics here at the ONS. Madeleine Sumption is director of the Migration Observatory at the University of Oxford, and new chair of the National Statistician's Advisory Panel on Migration. And to help us understand how the numbers are used and abused in public debate, we're also delighted to welcome Hannah Smith, senior political journalist at fact checking charity Full Fact. Welcome to you all.   Madeleine, to start with you if I may, with that fundamental question, quite simply, what is a migrant?    MADELEINE SUMPTION  Well, there are actually lots of different definitions of a migrant and we use different definitions at different points in time. The standard definition of migration that we use in this country is long term migration, so people moving for at least 12 months, and so the Office for National Statistics figures on immigration, emigration and net migration are all using that definition. And people in that data, they're migrants regardless of whether they are British or not British. So you could have a British person who's gone to live overseas for a few years and coming back they would be counted, in theory, at least in the data, as a migrant. There are other definitions though that are very useful for policy. So sometimes people talk about migrants, meaning people who don't have British citizenship, and the value of that is that these are people who are subject to immigration control, effectively that the Home Office is regulating their status. But it's also sometimes quite useful not to look at whether someone's a citizen now, because of course people can change their citizenship, and many migrants to the UK do become British citizens. So it can be useful to look at whether someone has migrated in the past. The standard definition for that is whether someone is born abroad. But now we've got all these exciting new data sets from administrative data, and so there's a new definition that's creeping in and being used a lot, which is someone who was a non-citizen at the time they registered for their National Insurance Number, regardless of whether they've subsequently become a British citizen. So it's a bit confusing sometimes for the external user, because for various reasons, we have to have all of these different definitions. You just have to know which one you're looking at at any point in time.     MILES FLETCHER  But the basic headline definition, as far as the ONS is concerned -and I guess internationally too because it's important that these figures are comparable- is that it is a person traveling from one country to another for a period of 12 months.   MADELEINE SUMPTION  That's right  MILES FLETCHER  And I guess that is something that is perhaps not widely understood. People understand that migration has a degree of permanence, so they move from one country to another, and yet you can be a migrant in quite a sort of transient way.    MADELEINE SUMPTION  That's right, we have short term migrants as well. So we have a lot of people who come to this country to do seasonal work. For example, they spend up to six months in the country. Then you have people who are long term migrants by the ONS definition and they may spend two to three years here, for example, if they're a worker or an international student. So you're right. I think in people's minds, often when they think about who is a migrant and who comes to mind, they will typically think of someone who is moving permanently. But actually a lot of migrants to the UK only stay for a couple of years.    MILES FLETCHER And none of these people, when it comes to measuring them, none of these people arrive Paddington Bear style with labels around their necks saying "I am a migrant". The ONS in measuring migration has to classify whether these people qualify or not.    MADELEINE SUMPTION  That's true, and that is very tricky. And it's something I think the non-technical user of the statistics finds it difficult to appreciate quite how hard it is for ONS to work out who is a migrant or not. Because we have millions of people crossing our borders every year, most of them not migrants. We have tourists or people who come in to visit family members. There are all sorts of people and reasons why those people come and go, so ONS is really looking for the needle in the haystack, and a relatively small share of people who are crossing the borders are actually migrating.    MILES FLETCHER  Well, that seems a good moment to bring in the person who is in charge of finding that needle in the haystack statistically. Mary, tell us how we approach this task. Perhaps start off by explaining how we used to do it. MARY GREGORY  Previously we used a survey called the International Passenger Survey, and there we would ask a sample of people as they came into the country, or as they left the country, what their intentions were, and we'd be able to provide very early estimates based on people's intentions to stay or to leave.    MILES FLETCHER  This is people at airports and other ports of entry, ferry ports, for example, simply approaching people as they wander along the corridors, almost in a random sort of way.    MARY GREGORY  Exactly that, you might have seen them. If you have travelled through an airport you may have seen a desk that sometimes says Office for National Statistics. And there would sometimes be people there with very carefully scheduled timetables to make sure that we collect a good cross section of people.    MILES FLETCHER  So the International Passenger Survey is essentially a big sample survey. Nothing wrong with that, and yet, the number of people being stopped at airports who did actually identify themselves as being migrants was quite small, and that made for some very broad-brush estimates didn't it?    MARY GREGORY  Yes, as you can imagine, people travel through airports or ports for many different reasons, and a lot of those people traveling will be traveling for a holiday or business or to visit family. And so the proportion of those people who are actually going to become residents or leaving for more than 12 months is very small, which makes it really difficult to pick up a good sample of those people.    MILES FLETCHER  And because it's fair to say the International Passenger Survey was never set up to measure migration in the first place, and that was something ONS found itself pointing out for a long, long time before things actually changed. MARY GREGORY  For a number of years we made clear that it was being stretched beyond its original purpose, and that it was the best measure we had at the time but now we think we can do better. And I think one other really important aspect of that is understanding that the survey was asking about people's intentions, and intentions don't always match reality of what we then see.    MILES FLETCHER  Because you might arrive as a student, end up working, settling, starting a family...    MARY GREGORY  Yes. Or you might find that you've arrived planning to stay for a year and then change your mind and you've left again. So it could go in either direction.    MILES FLETCHER  So the case for change was strong. What has changed? How is migration measured now?    MARY GREGORY  So now we have a variety of different ways to measure depending on the nationality of the people arriving. So for anybody from outside the EU, we have good data around visas from the Home Office, so we can use that to understand who is coming and what their reasons for travel are, and we can come on to that a little bit later. For people within the EU, that was a bit more difficult because prior to exiting the EU nobody needed a visa. And so at the moment, we use administrative data, so that's data collected for other purposes, and we use data from DWP, so the Department for Work and Pensions, to understand who has come into the country and who is staying in the country for more than 12 months. And for British nationals, we still, at the moment, use the International Passenger Survey, but we hope to change that very soon.    MILES FLETCHER  And essentially, the last use of the IPS, as far as migration is concerned, is to capture British passport holders leaving the country because nobody else is counting them out.    MARY GREGORY  That's right, and it's actually just stopped collecting that data. So we will move to the new methods very soon.    MILES FLETCHER  Okay, so how successful would you say this shift has been?    MARY GREGORY  I think we've definitely improved the data we can provide. It's a better reflection of people's behaviours. We know that be

    33 min

  5. 02/08/2024

    Green Data: Measuring the Environment

    In this episode we explore how the ONS measures our natural environment and the green economy.        Relevant datasets: ONS Environmental Accounts    Transcript     MILES FLETCHER   Welcome again to Statistically Speaking, the official podcast of the UK's Office for National Statistics. I'm Miles Fletcher and this time we're getting back to nature as we explore the work of the ONS in measuring the economic and social value of the natural environment.   Is classical economic growth - as measured by gross domestic product or GDP - always achieved at the expense of the environment? What price can we put on the amenities our environment provides? What is the green economy and what are green jobs? And what are the key data to watch as policymakers strive for net zero carbon emissions, while also seeking to improve national prosperity?   Our guides through the rich and perhaps under explored landscape of environmental data are ONS's Deputy Director for Environmental Statistics Analysis, Ian Townsend; Head of Natural Capital Accounts, Gemma Thomas; and Sophie Barrand, Monetary Accounts lead in the Environmental Accounts team.   Welcome to you all.  Ian to come to you first. The ONS is mainly known for measuring the economy and the population of the UK. So, what exactly is its role when it comes to the environment? What are we seeking to achieve?  What do we do? What do we publish?    IAN TOWNSEND  So the environment is quite a broad topic that links with a lot of other issues and a lot of different national and devolved government departments and other related bodies producing statistics on the environment. And with all that range of statistics, we tend to focus at the ONS on the intersections between our environment and both the economy and society. This includes measuring what we call the Low Carbon and renewable energy economy, how many green jobs there are, the greenhouse gas emissions produced by different economic sectors, and valuing the services that nature provides to us, as well as providing rapid insights into what people and business think about climate change in the environment and their actions or indeed otherwise.     MF  And what are the major publications that come out of the ONS that people ought to be looking at to get a sense of what we're saying about the environment and its value?    IT  So I mentioned a couple in the introduction there - things like low carbon and renewable energy economy, green jobs, etc... and our emissions figures. But perhaps one that is quite worth bringing to the fore is our natural capital accounts. So, it's something we've done for several years, which basically looks at the value that ecosystems provide to nature and ecosystems provide to us, and the services that provides. So, we bring this out as a report every year - have done so for several years - and that looks beyond the economy, beyond gross domestic product, to look at all those natural resources and we found that in 2021, the total value of all those natural assets was around one and a half trillion pounds. It's such a big figure, I think it can be quite hard for people to grasp. But a useful comparison might be that it's not that far off the 1.7 trillion pounds that homes in the UK were valued at in 2021 as well.    MF  It's very difficult to arrive at a financial figure or value like that. Can you just give us a brief explanation of how it's calculated?     IT  Sure. So, there are internationally agreed guidelines that we follow around how to measure or indeed account for the current value of what natural capital could provide for us and our current and future generations. And all that process, all those guidelines are aligned with how we measure the GDP in the economy. It's really quite a complex exercise and includes things like the value of trees, rivers, peatlands, and many other habitats and natural resources in them. We've been developing and improving these approaches for probably at least 10 years, and probably have some of the most developed accounts in this form globally. Our estimates have improved over the years. But there are some things that we don't cover. So, in a way, this is probably best seen as a kind of partial and minimum value, even though it's already very large. And it's also part of a wider mission that the ONS has to capture the value of what's called missing capital, things that we don't currently measure so well in gross domestic product. So that's including social capital as well as natural capital. So that's called 'inclusive wealth' and that's another publication the ONS produces that people might be interested to have a look at.    MF  And it's important, I guess, to have this economic value of the environment so that can be compared against the traditional measure of economic progress and prosperity, which of course is GDP. And it's sometimes – and we've heard this in other podcasts - because GDP is like the big beast of the economic statistical world. It's very important, it's very influential, but of course it does have significant weaknesses and omissions, and notably its lack of account for environmental factors being notoriously one of those.    IT  Sure. And actually, there's a process going on right now internationally that would bring some of that into the way that we measure some of the key economic indicators. But I think one of the key things you say is putting out there is a measure of how our natural capital assets are doing. But I think the other real benefit of these statistics, and particularly the natural capital accounts, is that it helps literally to account for nature to give an estimate of some of the benefits that the environment does provide. So, when people make decisions, they can take that into account. We're not exactly saying that nature has this given value. It's more that that's the value that we've estimated so far that provides those. It helps people to make sure that when they're taking their decisions, they take into account what would happen if we reduced or depleted that natural capital, and indeed, the benefits we might get in the future if we were to increase that natural capital as well.    MF  Because – and this is the other side of the question – high per capita GDP often goes with high carbon emissions in an economy, doesn't it? This way, we can look at the other side of the balance sheet and say, well, yes, you might be achieving this high economic performance in traditional terms, but look at the cost on the other side and, as you say, this is part of a big international movement to recognize that called 'beyond GDP', which is a topic we've covered in previous podcasts already.      IT  Sure.  I think, just getting back to your point around GDP and emissions one of the things that we produce in the ONS is a piece around a different emissions measurements there are, and actually if you look at those, you'll see that over time, all those measures have been reducing. So there is an element to which whilst the economy is expanding, we are actually reducing emissions on all three different measures that are available.     MF  And we say the environment is - we're putting it at 1.5 trillion pounds – that's the capital value of the natural environment, broadly equivalent to the value of all the houses in the UK. Some people might say that's a low figure perhaps you can think we measure human capital being much, much greater than that but that's a debate for another time. But explain for us who is using this number, how does it inform decision making at the moment at national and local level? How might it influence policymakers in future do you think?     IT  Sure, I think it's not necessarily about the big number at the top although that is one that will get a lot of interest from people and as you say, it might be an underestimate. I mentioned that there are some aspects of nature that we don't currently measure. But in terms of how it's used lots and lots of detail that's available underneath that key figure in the natural capital accounts we publish every year, at kind of macro level. The figures we use are important considerations for decision making by UK and devolved governments. So Defra published a policy paper, for example, on the accounts, I think, a couple of years back, which looked at what the key takeaways for policy there were from there, and we think that some of the figures were used in some of the bids that departments put in for the 2021 Spending Review. I think at the micro level figures are definitely used in the analysis of costs and benefits that are used for judging different government projects. It's part of what Department for Environment, Food and Rural Affairs call enabling a natural capital approach - it is in that guidance, and that has a lot of impact at kind of micro level. We're also publishing more and more data from the natural capital accounts at a local level. And making that available means that councils and others can use that in their decision making as well. And we're also building our connections and encouraging use where we can and it's also something that's being worked on internationally as well, which we're part of working with other national statistics offices and the UN.    MF  Turning to Gemma then, you're the head of natural capital accounts at the ONS. Let's get into the nuts and bolts then of what contributes to this valuation, this figure, because by understanding that we can better understand what it contributes to the economy and what it contributes to our wellbeing. Talk us through those elements if you would.    GEMMA THOMAS  Yeah, of course. So as Ian mentioned, there's some international standards that we abide by, but essentially what we do is we say, okay, what services does nature provide to us? And we identify those services, and then we

    35 min

  6. 20/05/2024

    AI: The Future of Data

    With the public release of large language models like Chat GPT putting Artificial Intelligence (AI) firmly on our radar, this episode explores what benefits this technology might hold for statistics and analysis, as well as policymaking and public services.  Joining host, Miles Fletcher, to discuss the groundbreaking work being done in this area by the Office for National Statistics (ONS) and across the wider UK Government scene are: Osama Rahman, Director of the ONS Data Science Campus; Richard Campbell, Head of Reproducible Data Science and Analysis; and Sam Rose, Deputy Director of Advanced Analytics and Head of Data Science and AI at the Department for Transport.  Transcript MILES FLETCHER Welcome again to Statistically Speaking, the official podcast of the UK's Office for National Statistics. I'm Miles Fletcher and, if you've been a regular listener to these podcasts, you'll have heard plenty of the natural intelligence displayed by my ONS colleagues. This time though, we're looking into the artificial stuff. We'll discuss the work being done by the ONS to take advantage of this great technological leap forward; what's going on with AI across the wider UK Government scene; and also talk about the importance of making sure every use of AI is carried out safely and responsibly. Guiding us through that are my ONS colleagues - with some of the most impressive job titles we've had to date - Osama Rahman is Director of the Data Science Campus. Richard Campbell is Head of Reproducible Data Science and Analysis. And completing our lineup, Sam Rose, Deputy Director of Advanced Analytics and head of data science and AI at the Department for Transport. Welcome to you all. Osama let's kick off then with some clarity on this AI thing. It's become the big phrase of our time now of course but when it comes to artificial intelligence and public data, what precisely are we talking about?   OSAMA RAHMAN So artificial intelligence quite simply is the simulation of human intelligence processes by computing systems, and the simulation is the important bit, I think. Actually, people talk about data science, and they talk about machine learning - there's no clear-cut boundaries between these things, and there's a lot of overlap. So, you think about data science. It's the study of data to extract meaningful insights. It's multidisciplinary – maths, stats, computer programming, domain expertise, and you analyse large amounts of data to ask and answer questions. And then you think about machine learning. So that focuses on the development of computer algorithms that improve automatically through experience and by the use of data. So, in other words, machine learning enables computers to learn from data and make decisions or predictions without explicitly being programmed to do so. So, if you think about some of the stuff we do at the ONS, it's very important to be able to take a job and match it to an industrial classification - so that was a manually intensive process and now we use a lot of machine learning to guide that. So, machine learning is essentially a form of AI.   MILES FLETCHER So is it fair to say then that the reason, or one of the main reasons, people are talking so much about AI now is because of the public release of these large language models? The chat bots if you like, to simpletons like me, the ChatGPT's and so forth. You know, they seem like glorified search engines or Oracles - you ask them a question and they tell you everything you need to know.   OSAMA RAHMAN So that's a form of AI and the one everyone's interested in. But it's not the only form – like I said machine learning, some other applications in data science, where we try in government, you know, in trying to detect fraud and error. So, it's all interlinked.     MILES FLETCHER When the ONS asked people recently for one of its own surveys, about how aware the public are about artificial intelligence, 42% of people said they used it in their home recently. What sort of things would people be using it for in the home? What are these everyday applications of AI and I mean, is this artificial intelligence strictly speaking?   OSAMA RAHMAN If you use Spotify, or Amazon music or YouTube music, they get data on what music you listen to, and they match that with people who've been listening to similar music, and they make recommendations for you. And that's one of the ways people find out about new music or new movies if you use Netflix, so that's one pretty basic application, that I think a lot of people are using in the home.   MILES FLETCHER And when asked about what areas of AI they'd like to know more about, more than four in 10 adults reported that they'd like to know better how to judge the accuracy of information. I guess this is where the ONS might come in. Rich then, if I could just ask you to explain what we've been up to, what the Data Science Campus has been up to, to actually bring the power of artificial intelligence to our statistics.   RICHARD CAMPBELL Thanks Miles. Yeah, a few things that ONS has been doing in this very broad sphere of artificial intelligence, and it's really in that overlap area that Osama mentioned with data science, so I'd pick out a few sorts of general areas there. So, one is automation. You know, we're always keen to look at how we can automate processes and make them more efficient. It frees up the time of our analysts to conduct more work. It means that we are more cost effective. It means that our statistics have better quality. It's something we've done for years but AI offers some new opportunities do that. The other area which Osama touched on is the use of large language models, you know, we can get into the complexities of data. We can get much more out of data; we can complete tasks that would have been too complex or too time consuming for real data scientists. And this is good news, actually, because it frees up the data scientists to add real valuable human insights. Some of the places we've been using this. So, my team for example, which is called reproducible data science and analysis, and we use data science and engineering skills to develop computer systems to produce statistics where the data is a bit big, or what I tend to call a bit messy or a bit complex for our traditional computer systems. We use AI here through automation, as I mentioned, you know, really making sure that we're making systems as efficient and high quality as possible. Another thing we're interested in doing here is quite often we're doing something called re-platforming systems. So, this is where we take a system that's been used to produce our statistics for years and years and look to move it on to new technology. Now we're exploring with Osama's team the potential for AI to do a lot of the grunt work for us there to sort of go in and say, right, what is going on in this system? How is it working, how we can improve it? One other thing I'll mention, if Osama doesn't mind me treading on the territory of his team, is the Stats Chat function that we've used on the ONS website. So, this is using AI to enable a far more intelligent interrogation of the vast range of statistics that we've got, so it no longer requires people to be really knowledgeable about our statistics. It enables them to ask quite open questions and to be guided to the most relevant data.   MILES FLETCHER Because at the moment, if you want to really explore a topic by getting into the depths of the data, into the granular data, you've really got to know what you're looking for haven't you? This again is an oracle that will come up with the answers for you and just present them all ready for your digestion.   RICHARD CAMPBELL That's right. And I tend to think of these things as a starting point, rather than the whole answer. So, what it's enabling you to do is to get to the meat of the issue a lot quicker. And then you can focus your energy as a user of our statistics in doing the analysis that you want rather than thinking "how do I find the right information in the first place?"   MILES FLETCHER Osama, that sounds like an intriguing tool. Tell us precisely how it works then, what data does it capture, what's in scope?   OSAMA RAHMAN So the scope is publicly available documents on the ONS website. And there's a specific reason for that. So, these AI tools, you can have it look at the whole internet, you can have it look at subsets of data, you can point it to specific bits of data, right? And what's important for us is actually the work of the ONS, that statistics we produce are quality assured and relevant. And by providing these guardrails where you know, Stats Chat only looks at ONS published data, we have a degree of assurance that the data coming back to the user is likely to be of good quality and not based on who knows what information.   MILES FLETCHER Because when you use, to name one example, ChatGPT for example, the little warning comes back saying "ChatGPT can make mistakes, consider checking important information." And I guess that's fundamental to all this isn't it. These tools, as intelligent as they might be, they're only as good - like any system - as the information that's going in the front end.   OSAMA RAHMAN That's absolutely correct, which is why we have these guardrails where, you know, the functionality on Stats Chat is focused on published ONS information.   MILES FLETCHER That does mean that something that's offered by an organisation like the ONS does have that sort of inbuilt potential to be trustworthy and widely used. But of course, you might say, to have a really good tool it's got to be drawing on masses of information from right across the world. And it's interesting how, and you mentioned that it's open-source data, of course, that's most available for these tools at the moment, but you're seeing proprietary data coming in as well. And this week, as we're recording this, the Financial

    34 min

  7. 25/03/2024

    Communicating Uncertainty: How to better understand an estimate.

    The ONS podcast returns, this time looking at the importance of communicating uncertainty in statistics. Joining host Miles Fletcher to discuss is Sir Robert Chote, Chair of the UKSA; Dr Craig McLaren, of the ONS; and Professor Mairi Spowage, director of the Fraser of Allander Institute.    Transcript  MILES FLETCHER  Welcome back to Statistically Speaking, the official podcast of the UK's Office for National Statistics. I'm Miles Fletcher and to kick off this brand new season we're going to venture boldly into the world of uncertainty. Now, it is of course the case that nearly all important statistics are in fact estimates. They may be based on huge datasets calculated with the most robust methodologies, but at the end of the day they are statistical judgments subject to some degree of uncertainty. So, how should statisticians best communicate that uncertainty while still maintaining trust in the statistics themselves? It's a hot topic right now and to help us understand it, we have another cast of key players. I'm joined by the chair of the UK Statistics Authority Sir Robert Chote, Dr. Craig McLaren, head of national accounts and GDP here at the ONS, and from Scotland by Professor Mairi Spowage, director of the renowned Fraser of Allander Institute at the University of Strathclyde. Welcome to you all.   Well, Sir Robert, somebody once famously said that decimal points in GDP is an economist's way of showing they've got a sense of humour. And well, that's quite amusing - particularly if you're not an economist - there's an important truth in there isn't there? When we say GDP has gone up by 0.6%. We really mean that's our best estimate.     SIR ROBERT CHOTE  It is. I mean, I've come at this having been a consumer of economic statistics for 30 years in different ways. I started out as a journalist on the Independent and the Financial Times writing about the new numbers as they were published each day, and then I had 10 years using them as an economic and fiscal forecaster. So I come at this very much from the spirit of a consumer and am now obviously delighted to be working with producers as well. And you're always I think, conscious in those roles of the uncertainty that lies around particular economic estimates. Now, there are some numbers that are published, they are published once, and you are conscious that that's the number that stays there. But there is uncertainty about how accurately that is reflecting the real world position and that's naturally the case. You then have the world of in particular, the national accounts, which are numbers, where you have initial estimates that the producer returns to and updates as the information sets that you have available to draw your conclusions develops over time. And it's very important to remember on the national accounts that that's not a bug, that's a feature of the system. And what you're trying to do is to measure a very complicated set of transactions you're trying to do in three ways, measuring what the economy produces, measuring incomes, measuring expenditure. You do that in different ways with information that flows in at different times. So it's a complex task and necessarily the picture evolves. So I think from the perspective of a user, it's important to be aware of the uncertainty and it's important when you're presenting and publishing statistics to help people engage with that, because if you are making decisions based on statistics, if you're simply trying to gain an understanding of what's going on in the economy or society, generally speaking you shouldn't be betting the farm on the assumption that any particular number is, as you say, going to be right to decimal places. And the more that producers can do to help people engage with that in an informed and intelligent way, and therefore mean that decisions that people take on the basis of this more informed the better.      MF  So it needs to be near enough to be reliable, but at the same time we need to know about the uncertainty. So how near is the system at the moment as far as these important indicators are concerned to getting that right?    SRC  Well, I think there's an awful lot of effort that goes into ensuring that you are presenting on the basis of the information set that you have the best available estimates that you can, and I think there's an awful lot of effort that goes into thinking about quality, that thinks about quality assurance when these are put together, that thinks about the communication how they mesh in with the rest of the, for example, the economic picture that you have, so you can reasonably assure yourself that you're providing people with the best possible estimate that you can at any given moment. But at the same time, you want to try to guide people by saying, well, this is an estimate, there's no guarantee that this is going to exactly reflect the real world, the more that you can do to put some sort of numerical context around that the more the reliable basis you have for people who are using those numbers, and thinking about as I say, particularly in the case of those statistics that may be revised in future as you get more information. You can learn things, obviously from the direction, the size of revisions to numbers that have happened in the past, in order to give people a sense of how much confidence they should place in any given number produced at any given point in that cycle of evolution as the numbers get firmer over time.    MF  If you're looking to use the statistics to make some decision with your business or personal life, where do you look for the small print? Where do you look for the guidance on how reliable this number is going to be?    SRC  Well, there's plenty of guidance published in different ways. It depends, obviously on the specific statistics in question, but I think it's very important for producers to ensure that when people come for example to websites or to releases that have the headline numbers that are going to be reported, that it's reasonably straightforward to get to a discussion of where do these numbers come from? How are they calculated? What's the degree of uncertainty that lies around that arising from these things? And so not everybody is obviously going to have an appetite for the technical discussion there. But providing that in a reasonably accessible, reasonably findable way, is important and I think a key principle is that if you're upfront about explaining how numbers are generated, explaining about the uncertainty that lies around them in as quantified way as you can, that actually increases and enhances trust in the underlying production and communication process and in the numbers rather than undermining it. I think you have to give the consumers of these numbers by and large the credit for understanding that these things are only estimates and that if you're upfront about that, and you talk as intelligently and clearly as you can about the uncertainties - potential for revision, for example - then that enhances people's confidence. It doesn't undermine it.    MF  You mentioned there about enhancing trust and that's the crux of all this. At a time we're told of growing public mistrust in national institutions and so forth, isn't there a risk that the downside of talking more about uncertainty in statistics is the more aware people will become of it and the less those statistics are going to be trusted?    SRC  I think in general, if you are clear with people about how a number is calculated, the uncertainty that lies around it, the potential for revision, how things have evolved in the past - that's not for everybody, but for most people - is likely to enhance their trust and crucially, their understanding of the numbers that you're presenting and the context that you're putting around those. So making that available - as I say, you have to recognise that different people will have different appetites for the technical detail around this - then there are different ways of presenting the uncertainty not only about, you know, outturn statistics, but in my old gig around forecasts of where things are going in the future and doing that and testing it out with your users as to what they find helpful and what they don't is a valuable thing to be doing.    MF  You've been the stats regulator for a little while now. Do you think policymakers, perhaps under pressure to achieve certain outcomes, put too much reliance on statistics when it suits them, in order to show progress against some policy objective? I mean, do the limitations of statistics sometimes go out of the window when it's convenient. What's your view of how well certainty is being treated by those in government and elsewhere?     SRC  Well, I think certainly in my time as a forecaster, you were constantly reminding users of forecasters and consumers of that, that again, they're based on the best available information set that you have at the time. You explain where the judgements have come from but in particular, if you're trying to set policy in order to achieve a target for a particular statistic at some point in the future, for example, a measure of the budget deficit, then having an understanding of the uncertainty, the nature of it, the potential size of it in that context, helps you avoid making promises that it's not really in your power to keep with the best will in the world, given those uncertainties. And sometimes that message is taken closer to heart than at other times.    MF  Time I think to bring in Craig now at this point, as head of national accounts and the team that produces GDP at the ONS to talk about uncertainty in the real world of statistical production. With this specific example, Craig, you're trying to produce a single number, one single number that sums up progress or lack of it in the economy as a whole. What do you do to mak

    33 min

  8. 21/12/2023

    ONS: Year in Review 2023

    In this episode Miles is joined by the National Statistician, Sir Ian Diamond, to reflect on what has been a busy and transformative year at the Office for National Statistics.    Transcript     MILES FLETCHER  This is "Statistically Speaking", the official podcast of the UK Office for National Statistics, I'm Miles Fletcher. This is our 20th episode, in fact, a milestone of sorts, though not a statistically significant one. What is significant is that we're joined, once again, to look back at the highlights from another 12 months here at the ONS by none other than the National Statistician himself, Professor Sir Ian Diamond. Ian, thanks for joining us again. The year started for you with being reappointed as the national statistician. As 2023 developed, how glad did you feel to be back?    SIR IAN DIAMOND  Of course, you know, I was hugely privileged to be invited to continue. It's one of the most exciting things you could ever do and I will continue to do everything in my power to bring great statistics to the service of our nation.    MF  To business then, and this time last year, we sat in this very room talking about the results of Census 2021, which were coming in quite fresh then. And we've seen the fastest growth of the population, you told us, since the baby boom of the early 1960s. Over the course of the year much more data has become available from that census and this time, we've been able to make it available for people in much richer ways, including interactive maps, create your own data set tools. What does that say about the population data generally and the way that people can access and use it now? How significant is that there's that sort of development?    SID  Well I think we need to recognise that the sorts of things that we can do now, with the use of brilliant technology, brilliant data science and brilliant computing is enabling us to understand our population more, to be able to make our data more accessible. 50, 60, 70 years ago, 150 years ago, we would have just produced in about six or seven years after the census, a report with many, many tables and people would have just been able to look at those tables. Now, we're able to produce data which enables people to build their own tables, to ask questions of data. It's too easy to say, tell me something interesting, you know, the population of Dorset is this. Okay, that's fine, but actually he wants to know much more about whether that's high or low. You want to know much more about the structure of the population, what its needs for services are, I could go on and on. And each individual will have different questions to ask of the data, and enabling each individual to ask those questions which are important to them, and therefore for the census to be more used, is I think, an incredibly beautiful thing.    MF  And you can go onto the website there and create a picture...    SID  Anyone can go onto the website, anyone can start to ask whatever questions they want of the data. And to get very clearly, properly statistically disclosed answers which enable them to use those data in whatever way they wish to.    MF  And it's a demonstration of obviously the richness of data that's available now from all kinds of sources, and behind that has been a discussion of, that's gone on here in the ONS and beyond this year, about what the future holds for population statistics and how we can develop those and bring those on. There's been a big consultation going on at the moment. What's the engagement with that consultation been like?    SID  Well the engagement's been great, we've had around 700 responses, and it addresses some fundamental questions. So the census is a really beautiful thing. But at the same time, the census, the last one done the 21st of March 2021, was out of date by the 22nd of March 2021, and more and more out of date as you go on and many of our users say to us, that they want more timely data. Also by its very nature a census is a pretty constrained data set. We in our country have never been prepared to ask for example, income on the census yet this is one of the most demanded questions. We don't ask it because it is believed that it is too sensitive. And so there are many, many, many questions that we simply can't ask because of space. There are many more questions that we simply cannot ask in the granularity that we want to. We've been doing some work recently to reconcile the differences between estimates in the number of Welsh speakers from surveys with estimates on the number of people in the census who report they speak Welsh. Frankly, it would be better if we were able to ask them to get information in a more granular way. And so while the census is an incredibly beautiful thing, we also need to recognise that as time goes on, the technology and the availability of data allowing us to link data becomes much more of a great opportunity that we have been undertaking a lot of research, a lot of research which was asked for by the government in 2013, following the report by Chris Skinner, the late Chris Skinner, Joe Hollis, and Mike Murphy, which is a brilliant report. We said at the moment we need to do another census in 2021. That's what we have done and I believe it to be one of the best coverages there has ever been. And yet we need to assess whether administrative data could be used in future to provide more timely, more flexible and more accessible data and that's what the consultation is about. I will be making a recommendation to the UKSA (UK Statistics Authority) board in the future. In the near future we have to say, and I think it is worth saying that what the consultation says to us is that people are very, very, very much in favour of the direction of travel but at the same time as yet accepting our prototype, unconvinced about the data flows and the sustainability of those data flows to enable us to do it and so, we are looking at how to respond to other very important analyses and we will do so in the near future.    MF  When can the people who contributed to that consultation, roughly when should they expect to hear from us? SID  I think the expectation is we'll publish something by the end of quarter one in 2024.    MF  Surveys have continued to be a very important part of what the ONS does, these very large national surveys, and yet one of the biggest challenges of the has been maintaining coverage and particularly response rates and obviously, particularly with the Labour Force Survey recently that has been a particular issue for the ONS hasn't it. Where do things stand now as we move into modernising the traditional Labour Force Survey and moving to a new model because it's an issue statistics bodies around the world have been dealing with, it's harder to get people to complete surveys like they used to.     SID  I think it's a fair point that response rates globally are a challenge and response rates globally, not only in national statistics issues, but in the private sector organisations that also collect data, are a challenge. So we need to recognise that. A part of that is that historically, one could find people at home, knock on doors, have that conversation with people, and perhaps post pandemic people are less willing to have a conversation at the house. Also, people are very busy. They work in multiple occupations. They are not always in, they live in housing accommodation which is more and more difficult to access. This there is no kind of single magic bullet here that we could press all we would have. The first thing to say Miles is that we recognise that and that's why we worked with our colleagues at His Majesty's Treasury to provide a project to go to what we call a transformed Labour Force Survey. And I think that that's a hugely exciting project for a number of reasons. One, the labour force survey which has been around for a long time, the questionnaire had become a little bit unwieldy. And also we wanted to enable people to have much more flexibility at the time of which they answered the question. We are in the field with the pilots for that service. We've been pretty good. There are good response rates. There are also some challenges around getting the questions right. These aren't challenges that stress me, that's why you do a pilot, but at the end of the day we're hoping to be able to transform into that new Labour Force Survey early in 2024, in the first half of 2024. We're working very closely in doing that with our major stakeholders and the Bank of England, His Majesty's Treasury and the Office for Budgetry Responsibility (OBR), is you take a joint decision on when people feel comfortable that we have had enough dual running to enable us to move forward. The other question that I'd have to raise around surveys more generally, is on inflation, which we have all been subjected to in many, many areas in the last couple of years, inflation in survey collection has increased massively and so in the last year we've had to make real judgments about how we maintain quality. And in the next few years, we will really be needing to think through exactly how we conduct our surveys and the cost of doing so.    MF  Yes. Of all the people who should be aware of inflation are the people who report it, and certainly the impacts of those relatively high rates of inflation have impacted us as much as anybody else. The challenges not withstanding of running surveys, the interest of government bodies in getting that information directly from people does continue to underline the unique value of surveys. Some people say Oh, well, they surely they can get this information from other sources I've even seen it suggested that social media could provide the answers, but there is a unique value isn't there and actually getting a statistically representative sample of people and spea

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Statistically Speaking is the Office for National Statistics' podcast, offering in-depth interviews on the latest hot topics in the world of data, taking a peek behind the scenes of the UK's largest independent producer of official statistics and exploring the stories behind the numbers.

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  • Creator
    Statistically Speaking
  • Years Active
    2022 - 2026
  • Episodes
    28
  • Rating
    Clean
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    © 2024
  • Show Website
    Statistically Speaking

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