Department for Education

Open Leo Data Service -DfE

7 Incomplete applications

7 SME, 0 large

0 Completed applications

Important dates

Published
Friday 13 May 2022
Deadline for asking questions
Friday 20 May 2022 at 11:59pm GMT
Closing date for applications
Friday 27 May 2022 at 11:59pm GMT

Overview

Off-payroll (IR35) determination
Contracted out service: the off-payroll rules do not apply
Summary of the work
Department for Education requires a supplier team to lead on development and delivery of a technological solution to enable open access to Leo dataset whilst preserving individual anonymity. Closest delivery approach would be Beta with focus on MVP only.
Latest start date
Friday 1 July 2022
Expected contract length
9 months
Location
No specific location, for example they can work remotely
Organisation the work is for
Department for Education
Budget range
The services are to be delivered over a contract period of 9 months. The indicative value for the full 9-month contract is £750,000.

Suppliers shall be asked to provide quotation for each stage of the required work, with an exit option at each stage, should we choose not to proceed.

Each SOW will outline the work required, associated budget and payment approach, CTM, T&M etc. Suppliers will need to provide clear costs to enable tracking.

DfE does not commit to any minimum or maximum spend at this point.

A pricing template will be provided to shortlisted suppliers at proposal stage

About the work

Why the work is being done
The Department for Education's newly formed Unit for Future Skills (UFS) is tasked to lead a cross-Government programme to transform how jobs and skills data is used to inform learners, training providers, and policymakers and support a responsive skills ecosystem and enable a wider change in the use of data in DfE policymaking and delivery.

To facilitate the delivery of these aims, the Unit’s ambition is to develop data infrastructure and new online product(s)/service where the jobs and skills data can be brought together, easily visualised and made securely available to individuals and institutions operating in jobs and skills markets with ability to share underlying data where possible with our users or via third-party service providers.
Problem to be solved
The longitudinal educational outcomes (LEO) dataset forms the backbone on which most of Units analysis and insights rest, it has shown itself to be a significant data resource to provide insight in the supply of skills across the country and their value in the labour market. The current channels for sharing the LEO data are limited and restrictive. Widening the access to the LEO dataset is part of the DfE broader strategy of making data more available, to increase the potential for insights to be developed and acted upon.

To facilitate the delivery of these aims, the Unit’s ambition is to set-up Open Leo data service to bridge this gap, making granular data available in accessible formats for all our users, with flexibility to query, extract and visualise data to meet needs for all our users, whilst preserving individual anonymity and compliance with departmental privacy requirements for publishing and sharing of data in the public domain.
Who the users are and what they need to do
The service will be used by broad range of users, which will include but not be limited to learners and their parents, adult learners/citizens, career advice services, employers, and employer representative bodies (ERBs), MCAs/local bodies, providers, research and academic community, internal DfE skills policy colleagues and private organisations interested in pathways between skills, qualifications and employment outcomes
Early market engagement
N/A
Any work that’s already been done
The department has undertaken some work previously on sharing Leo dataset. We would like the service providers to work together with department to build upon and validate user insights in support of delivering MVP.
Existing team
"There is no existing team for this work. The DfE Teams will include Head of Data and Digital Services/ Service Owner, Product Owner and analytical team members who will agree SoW and sign-off on the deliverables".
Current phase
Beta

Work setup

Address where the work will take place
Mainly Remote working. Supplier to attend in person for work progress update, user group, and contract management meetings in DfE’s London and Manchester Piccadilly office as and when required.
Working arrangements
Department for Education requires a supplier team to lead on development and delivery of a technological solution to enable open access to Leo dataset whilst preserving individual anonymity.

The specialist supplier will have expertise in development and testing of automated disclosure control / privacy preserving algorithm (e.g. differential privacy) on complex datasets.

We expect the services will be outcome based with pre-agreed deliverables for each stage as per agreed statement of work.

The work will be time and cost capped.
Security clearance
The successful supplier must be able to demonstrate that all proposed team members have been subject to Baseline Personnel Security Standards checks. Suppliers will also be required to complete a supplier security assurance form to ensure they meet the required standard for DfE e.g. Cyber Essentials

Additional information

Additional terms and conditions
Standard Framework and Call Off Terms and Conditions. Expenses must be pre-agreed and comply with CCS Travel and Subsistence Policy. Any expenses shall be submitted in line with DfE standard T&S policy. Primary work location stated in SoW will not attract expenses. Contract and Vendor Management will form a key part of governance and suppliers will be expected to complete cyber security questionnaire.

Suppliers must provide sufficient guarantees to meet the requirements of GDPR in line with Procurement Policy Note 03/17 Changes to Data Protection Legislation & General Data Protection Regulation

Skills and experience

Buyers will use the essential and nice-to-have skills and experience to help them evaluate suppliers’ technical competence.

Essential skills and experience
  • Expertise in successfully developing, testing, and deploying automated disclosure or privacy preserving algorithms (e.g., differential privacy) on complex datasets
  • Demonstrable experience in designing and delivering end to end scalable cloud-based data science, machine learning/ artificial intelligence solutions including tooling within government or private sector.
  • Experience in deploying easy-to-use dashboards, apps, and data visualisation tools
  • Capability to implement machine learning data models utilising links to open data sets and model libraries.
  • Good understanding of data privacy regulations for publishing data in public domain
  • Capability to build and deploy models and tooling using departmental infrastructure.
Nice-to-have skills and experience
Experience and understanding of educational datasets and digital services

How suppliers will be evaluated

All suppliers will be asked to provide a written proposal.

How many suppliers to evaluate
4
Proposal criteria
  • Expertise in successfully developing, testing, and deploying automated disclosure or privacy preserving algorithms (e.g., differential privacy) on complex datasets
  • Demonstrable experience in designing and delivering end to end scalable cloud-based data science, machine learning/ artificial intelligence solutions including tooling within government and/or private sector.
  • Experience in deploying easy-to-use dashboards, apps, and data visualisations
  • Capability to implement machine learning data models utilising link to open data sets and model libraries, so as to avoid use of proprietary models.
  • Good understanding of data privacy regulations for publishing government data in public domain.
  • Capability to build and deploy models and tooling using departmental infrastructure.
Cultural fit criteria
  • Experience of transferring knowledge to permanent staff within a client organisation
  • Experience of working within multi-vendor teams
  • Describe how your organisation encourages diverse representation of under-represented groups in the workforce, e.g. Women, Black, Asian and Minority Ethnic, Disabled, LGBTQ+ and how you monitor and measure this (10%)
Payment approach
Capped time and materials
Additional assessment methods
  • Case study
  • Work history
  • Reference
  • Presentation
Evaluation weighting

Technical competence

50%

Cultural fit

20%

Price

30%

Questions asked by suppliers

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