Awarded to Kainos Software Ltd

Start date: Monday 28 February 2022
Value: £3,000,000
Company size: large
Food Standards Agency

Data Science, AI and Data Engineering support for delivery of a Strategic Surveillance Service

8 Incomplete applications

8 SME, 0 large

17 Completed applications

10 SME, 7 large

Important dates

Wednesday 8 December 2021
Deadline for asking questions
Wednesday 15 December 2021 at 11:59pm GMT
Closing date for applications
Wednesday 22 December 2021 at 11:59pm GMT


Off-payroll (IR35) determination
Contracted out service: the off-payroll rules do not apply
Summary of the work
The Food Standards Agency requires a supplier to deliver work packages to achieve continuous improvement of current services and designing and delivering new data science use cases. We will require a highly skilled multi-disciplinary individuals/teams to deliver these outputs.
Latest start date
Monday 14 February 2022
Expected contract length
24 Months
No specific location, for example they can work remotely
Organisation the work is for
Food Standards Agency
Budget range
£3,000,000.00 (Ex VAT) Limit of Liability. The Authority can make no offer of guarantee that this limit will be met or that work packages are guaranteed.

About the work

Why the work is being done
Our goal is to take a more proactive approach to mitigating risk, by identifying evidence of direct impacts on food safety such as a microbiological risk, but also indirect factors such as food crime, changes in consumer attitude to food, changes in business models, and technical advancements in the production of food and how we all engage with it. Demand from the FSA and its stakeholders for data-driven insights and predictive capability in these areas is established and growing.
Problem to be solved
We need to deliver data science and AI projects that make the best use of data to identify food and feed risks before they become a public health concern. We have a number of existing products in this space that we need to operationalise, maintain and continuously improve, as well as new use cases for which solutions need to be developed, and a new data platform that is still in the early development stage.
Who the users are and what they need to do
As the competent authority in charge of regulating the food and feed sector, the FSA needs to be aware of risk affecting UK consumers, whether related to food and feed safety or to authenticity, and develop a predictive capability within the Agency, so that we can take action to mitigate those risks.
Early market engagement
Any work that’s already been done
The Strategic Surveillance Service was set up in 2017 to inform an intelligence-led, predictive approach to risk identification through the application of cutting-edge data science skills and techniques. Having demonstrated beyond doubt the value of data science in a range of areas, the team has matured into an established service that provides colleagues across the agency with data driven products and advanced analysis. We are looking for a supplier to support the delivery and operationalisation of new use cases, and the maintenance and continuous improvement of existing ones. Examples of our work can be seen here:
Existing team
The supplier will be working with an in house team consisting of:

1 * Head of Data
1 * Senior Data Scientist
5 * Data Scientists

The supplier will also work closely with a team of data architects and engineers, although we also expect them to contribute expertise in these areas. The team is situated within a wider directorate that also contains our digital, IT and information security and governance functions. We work in partnership with these teams to deliver data science solutions for stakeholders across (and beyond) the agency.
Current phase

Work setup

Address where the work will take place
There is no requirement for the supplier to be based in any particular location within the UK, although some travel may be required to attend key meetings at one of the FSA's offices (London, York or Birmingham). As FSA staff are highly dispersed and home working levels will remain high at least for the foreseeable future due to the pandemic, it is important that the supplier is able to build the necessary stakeholder relationships to deliver successful data science outputs through remote and hybrid ways of working.
Working arrangements
The supplier will submit individual statements of work for each project. They will be expected to provide regular progress updates and liaise as appropriate with internal and external stakeholders throughout the projects they are undertaking. They will be expected to work openly and collaboratively on digital channels (eg slack, MS Teams, Office365 etc). You will be expected to attend key project meetings, virtually or at FSA offices, and be involved in catch-up calls, organise and run user testing sessions, and present findings.
Security clearance
All supplier team members will need to be cleared to Baseline Personnel Security Standard, and may be requested to sign a non-disclosure agreement (NDA). SC clearance may be required to work with some datasets.

Additional information

Additional terms and conditions

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
  • Describe your experience of understanding stakeholder requirements, and validating them via positive challenge.
  • Describe your experience of delivering against stakeholder requirements, and how you have generated and added value.
  • Describe your experience to rapid prototyping (i.e. taking a ‘use case’ and delivering a Minimum Viable Product in a limited time window)
  • Describe your experience of discovering, ingesting and cleaning structured and unstructured data from a range of sources (e.g. database, API, web scraping)
  • Describe the best practices you employ in discovering, ingesting and cleaning data
  • Describe your experience of building clear, simple to use dashboards to deliver insight and data visualisation, using tools such as Shiny, Power BI, or equivalents
  • Describe your experience of designing, implementing, using and maintaining data ingestion and transformation pipelines.
  • Describe your experience of deploying machine learning solutions on cloud platforms such as Azure or AWS
  • Describe your experience of building predictive models to solve business problems
  • Describe your proficiency and experience in using key-programming languages (R, Python and SQL) and open-source frameworks and libraries for data-manipulation (e.g. dplyr, pandas) and machine learning (e.g. scikit-learn, tensorflow, pytorch)
  • Describe your experience of applying natural language processing to unstructured text
  • Describe your experience of collaboration and version control using Git/GitHub
  • Describe your experience of implementing code testing with standard testing frameworks (e.g. pytest or testthat)
  • Describe your experience using MLOps to manage the machine learning lifecycle
Nice-to-have skills and experience
  • Give an example in which you have achieved buy-in from stakeholders who were resistant or sceptical, and how you convinced them of the value of data-science to their business processes
  • Describe your experience of working with different (technical and non-technical) teams across an organisation to deliver data science solutions
  • Describe your experience of implementing machine learning solutions using Azure data science tools such as Azure Machine Learning and Databricks
  • Describe your experience of ingesting and transforming data using Azure data engineering tools such as Azure Data Factory and Azure Synapse
  • Describe your experience of deploying containerised applications via Azure App Service
  • Describe your experience of building data-driven apps using other web frameworks such as Django and React
  • Describe your experience of building a data catalogue or implementing solutions for metadata storage and data discovery

How suppliers will be evaluated

All suppliers will be asked to provide a written proposal.

How many suppliers to evaluate
Proposal criteria
  • Describe your approach/methodology for delivering-innovative data-science-projects to inform our understanding of feed and food-risk. Include how you will manage the work and quality-assure-outputs (including dashboards/reports/analyses/any code used to produce them)
  • Describe your approach to ensuring that all AI work is carried out in an ethical and transparent way, and any frameworks you follow or have developed in this area
  • Describe your approach to ensuring that solutions are made of components that will be reusable across other projects
  • Describe the steps you would consider-necessary to take a product such as a dashboard or model from-MVP-into production, and your-approach to building data-pipelines/tools/dashboards or apps that can be considered 'production-grade'
  • Describe your proposed team set-up for this contract (including roles and experience) and outline what capacity you have to adapt the team to changes in size or required skillsets
  • Demonstrate your approach to transferring skills and knowledge from your team to our in-house team
  • Identify any risks and dependencies that you foresee in developing and deploying data science solutions, and offer approaches to manage them
  • Describe how your proposal will optimise costs and deliver good value for money through the lifetime of the contract.
Cultural fit criteria
  • Demonstrate and evidence how you will be transparent and collaborative when making decisions
  • Demonstrate experience of successful collaborative working as part of a multi-supplier agile delivery team, sharing knowledge and experience within the team
  • Demonstrate the ability to challenge the status quo and use persuasion skills to achieve business buy-in
  • Demonstrate the ability of taking responsibility for your work, a no-blame culture and encourage people to learn from their mistakes
  • Demonstrate the ability to bring an agile mindset and principles into a developing organisation
  • Please describe the commitment your organisation will make to achieve all the social value Model Award Criteria (MAC); MAC 3.3 Modernising delivery and increasing productivity, in relation to this contract?
  • Please describe the commitment your organisation will make to achieve all the social value Model Award Criteria (MAC); MAC 1.5 Workplace Conditions, in relation to this contract?
Payment approach
Capped time and materials
Additional assessment methods
  • Case study
  • Reference
Evaluation weighting

Technical competence


Cultural fit




Questions asked by suppliers

1. Do you need experience in all theist languages (R, Python and SQL) and the framework (sikit,pytorch,tensor)?
We would expect to see experience in R, Python and SQL, as these are all languages we work with a lot. It is not necessary to have experience of all the frameworks and libraries.
2. What does ‘Model Award Criteria (MAC)’ and how do you evaluate it ?
"Model Award Criteria is the criteria used in the Government Social Value Model. This will be evaluated in line with the DOS Guidance of 0- Not met
1- Partially met
2- Met
3- Exceeded

This will be assessed at stage 2 and the following guidance will be provided: ( "
3. Can the authority confirm if there is an incumbent already working with FSA in this area please?
Yes, there is an incumbent working in this area.
4. Is there an incumbent?
Yes, there is an incumbent.
5. How many work packages does the buyer anticipate this requirement will be split into?
The contract will be set up as a call-off contract in which work packages will be drawn down from up to the limit of £3,000,000.00. The number of work packages is dependant on business need. The Authority can make no offer of guarantee that this limit will be met or that a set number of work packages are guaranteed.
6. How many users are there?
This contract has no set users, each work package is specific and could be aimed at anything from a couple of users on a bespoke tool to every local authority in the country (i.e. 400+).
7. Can you provide any more details on the Incident management system and technologies that are currently in the Stack?
The team currently utilise the tools available within Microsoft365 and the Azure cloud platform.
8. In regard to the existing use cases in the section “any work that’s already been done”, have these been built within the intended cloud environment using cloud native tools or in legacy toolsets. If legacy can you let us know which tools?
The existing use cases referred to in 'Any work that's already been done' have been developed using Python or R. The dashboards are mostly Shiny dashboards deployed onto the web through a third party hosting service, although some are hosted on our own cloud. The use cases were developed locally and vary in the extent to which they have been migrated to cloud native tools.
9. Which data science tools are already in use by the existing team in the Food Standards Authority? Are you open to expanding that toolset to include other tools?
Our coding languages are R, Python and SQL. We use the data science tools available to us through Microsoft Azure, such as Azure Machine Learning and Azure Data Factory. We aspire to use the best tool for the job.
10. What proportion of existing data science models are developed using R v’s Python? Is there a direction or preference in language selection in the Food Standards Agency for the development of data science models?
We use R and Python as appropriate to the task, and as such our codebase encompasses both. There is no plan to choose one over the other going forward.
11. Aside from R, Python and SQL are other languages used in the development of optimised models (e.g. PySpark, C#, C++)? Are the FSA open to the use of other languages to optimise solutions as required?
We are open to the use of any other languages or tools that will help us to improve the work that we do.
12. Is this proposal for teams or would individuals also be considered.
The Food Standards Agency requires a supplier to deliver work packages that will require highly skilled multi-disciplinary teams to deliver these outputs. A sole individual would not be able to perform the level of work required for all the whole requirement.
13. Has an operating model already been defined for how the joint team of the successful vendor and the Food Standards Agency will operate or is this to be determined with the successful vendor? If already defined can this be shared?
The operating model defined will be in line with an outsourced service where work packages will be presented to the supplier to deliver as they see fit, the finer contract specific details are to be decided with the successful supplier once awarded and prior to signature.
14. Are there any aspirations as to how the service will develop or where future use cases will come from?
We aim that the Strategic Surveillance service keeps addressing new use cases proposed to us by the business (FSA colleagues) and explore the art of the possible in the world of data and data analytics. At the same time we anticipate than some of the new cases will evolve into services that will be offered to FSA colleagues and relevant stakeholders.
15. Total volume and daily update? How close to real time are we looking to achieve?
The total volume of work packages is not set and is dependant/ subject to business need, we would expect weekly updates on work packages to monitor delivery and each work package will be sent for quotation and timescales agreed between the winning supplier and buyer.