Dear Data to Insight colleagues –
Please find below another bundle of news, within which I hope you’ll find something of interest. As always, if you want to talk about this stuff, or have ideas for how we can do useful things – or how you’d like to get involved – then reply to this email and let us know what you’re thinking about.
ChAT and Benchmarking Tool updates
Population data in our tools (and in DfE data releases)
Early Help benchmarking – Q2 collection and feedback workshops
Upcoming events
Data Science Community Showcase
Early Help data partnership reflective workshops
SSD show and tells
Next open house
Python workshops
Credits
1. ChAT and Benchmarking Tool updates
In recent weeks DfE published their “Children in Need 2023” dataset (the same data release as was last year called “Characteristics of children in need”), and then their “Children looked after in England including adoption: 2022 to 2023” dataset, and we’ve updated the Benchmarking Tool accordingly, and pulled these datasets into a new version of the ChAT alongside some other small changes.
We’ve also added a new option in the ChAT for you to import your latest RIIA quarterly dataset to help extend some of the historical comparator trend lines. We haven’t directly loaded the RIIA data into the ChAT – because we don’t want to risk LAs sharing each other’s individual RIIA data with other parties – so you’ll need to follow the instructions on the “RIIA Data Import” tab of ChAT to paste in the aggregate data from the RIIA Benchmarkiing Tool. Visibility of this data is controlled by an option dropdown on the ChAT home tab, so you can choose whether or not to use it.
We hope it will be really useful to LAs to pull the comparator benchmarking data up to date for charts where the RIIA dataset can help with that – if you have feedback on this or any other aspect of ChAT/RIIA, do let us know.
(3.40) Added Cumberland and Westmorland and Furness LAs to calculation sections
(3.40) Updated ONS all age population and density figures 2012-2022 based on revised ONS mid-year estimates (affects very few calculations)
(3.40) Amended CLA net gain data
(3.40) Fixed issue with "latest" input box on charts tabs
(3.39) Fixed missing figure for SGO
(3.38) Fixed % age breakdowns in new CLA data (was previously showing numbers)
(3.37) Updated to include Children looked after in England including adoption 2022 to 2023 data as per DfE publication of 16/11/2023
(8.0) Amended an issue where adding in custom groups was flagging a circular error.
(8.0) Added lookups
(8.0) Added the ability to import RIIA quarterly data for internal reporting
(8.0) CiN Census 2023 data added
(8.0) 903 Data 2023 Added
(8.0) Added Cumberland and Westmorland and Furness LAs to calculation sections
(8.0) Updated ONS all age population and density figures 2018-2022 based on revised ONS mid-year estimates.
(8.0) Population base for in-year data (i.e. those data calculated from lists) has been altered to use ONS mid-year 2022 release
(7.11) Fixed formula error in new care leaver charts on page 18 (18 year olds' pathway plans)
As always, if you spot anything amiss, or have ideas for how to further improve this or any of our tools, please do get in touch.
2. Population data in our tools (and in DfE data releases)
I’ve written previously to point out that ONS’ revision of historical mid-year population estimates has raised some challenges for us – welcome as the update is! – around how to present data changes in our tools. You may have noted that certain rate figures were omitted from the CLA data release this year; this is because DfE’s CLA statistics team decided not to calculate these until ONS had published their updated population estimates.
Now that those data are available, this is what we think is happening with each of the key datasets and tools we work with:
The ChAT and Benchmarking Tool now contain the revised all ages population data, but this is used for very little, because most rates are calculated using the DfE-selected population figures. In order to maintain parity between our tools and DfE published figures, we don’t want to forcibly overwrite figures DfE has published in our tools.
The RIIA Benchmarking Tool is now using the latest available mid-year population estimates for any rates it calculates, to provide the most accurate possible in-year data.
Where rates are published by DfE, we have left those rates as published by DfE so as to avoid confusion when comparing our tools with DfE original sources. We appreciate this isn’t ideal, but we think it’s the best compromise.
For CLA data, the DfE CLA statistics team intend to revise their publication in light of the revised population estimates, including revising figures for recent years. When this revision is published, probably mid-December, we will incorporate it in the Benchmarking Tool and notify you.
For CIN data, the DfE CIN statistics team used the 2021 mid-year estimates for their publication, and have no current plan to revise their publication in light of the revised population estimates. They will review this following the ONS publication and communicate any future changes.
You can check how significantly your LA trend data is likely to be affected by these changes in population estimate by checking the “Benchmarking” tab of the ChAT (cells F929 and F930).
We don’t yet know what this means for the “Outcomes” publication due in the new year, but we will tell you as soon as we do know.
3. Early Help Benchmarking – Q2 collection and feedback workshops
It’s quarterly returns time again, and we’re busily collating RIIA datasets from each region as well as now gathering early help datasets from participating regions and individual LAs. In Q1 we had a fantastic response to our first collection, with 50 submissions of Q1 data, and more authorities/regions are joining from Q2.
The deadline for Q2 submissions is today, 27/11/2023, but do still get in touch if you’d like to join in. You can use last quarter’s template or, if submitting for the first time, the submission workbook in the Tools section of our website.
We’re also running a couple of workshops on Teams in January to reflect on the collection to date – looking at how the submission process has been, whether the measures are the right ones, and whether clarifications are needed for the definitions. It would be great to get as many people as possible attending. The dates are:
8th January 2024 11:00 – 12:30
15th January 2024 11:00 – 12:30
Please drop John an email if you’d like to attend.
This collection is open to any LA, and we’ll be collecting Q2 data in October/November. Completed returns should go to Georgie, who is also the person to contact for more information about the collection process or the indicators themselves.
We’re working through existing site members at www.datatoinsight.org to try and ensure that everyone working at a participating LA will have access, but if you need to add more members you can do so by emailing us for help.
4. Upcoming events
(Tomorrow, Tuesday 28th November)
Early Help data partnership reflective workshops
(8th and 15th January)
Standard Safeguarding Dataset show-and-tells
(Thursday 7th December at 2pm)
D2I open house / core tools workshops – email John for an invitation to either
(Next open house: Wednesday 17th January at 13:00)
Python workshops – email Will for an invitation
(Running weekly on Thursday and Friday afternoons)
Tomorrow Will’s running a workshop as part of the Office for National Statistics’ Data Science Community Showcase. Our session is about collaborative learning; how our Python projects have worked to turn funding into skills and learning opportunities as well as exciting new data tools. To sign up to attend, follow this link.
As mentioned above, John’s running some workshops in January to reflect on the quarterly early help collection. Please drop John an email if you’d like to attend.
We’re still running monthly show-and-tells for our Standard Safeguarding Dataset project, which is now in the process of developing pilot data extracts with partner councils. The next session has moved to the 7th December and you can email me for a copy of the invitation.
Our “open house” meeting is a regular chance to drop in on a D2I team meeting where we share what we’re working on and talk about how best to help with data work. We try to cover a mix of “technical” and other work. We don’t yet have an agenda for the January session, so if you have particular requests, do let us know.
And separately, Will continues to run Python drop-in workshops on Thursday and Friday afternoons. For more information, please email us.
5. Credits
Credit for recent improvements to our data tools and project work is due to colleagues in:
Derbyshire
Wandsworth
Hull
Wirral
Durham
York
Havering
Birmingham
East Sussex
Blackpool
Essex
Reading
Nottingham
North Lincolnshire
Bournemouth, Christchurch and Poole
Oldham
Cumberland
Swindon
Waltham Forest
Thurrock
South East Sector-Led Improvement Programme
Department for Education
That’s it! If you have any comments, queries or ideas that you want to share, just let us know.