Award

PS21196 - Bayesian Synthetic Population Algorithm Development, for National Buildings Model

UK SHARED BUSINESS SERVICES LIMITED

This public procurement record has 2 releases in its history.

AwardUpdate

20 Jan 2022 at 14:52

Award Notice
Award

06 Jan 2022 at 17:21

Award Notice
Summary of the contracting process

The UK Shared Business Services Limited is the buying organisation responsible for the recent procurement process titled "PS21196 - Bayesian Synthetic Population Algorithm Development, for National Buildings Model". This contract falls within the services category, specifically research and development consultancy services. The procurement has been officially awarded, with an award value of £49,375, and the contract period is set from 29 November 2021 to 31 March 2022. The relevant procurement method was a selective tender, following a mini-competition under the Crown Commercial Services Research Marketplace dynamic purchasing system. The procurement process concluded with the award notice published on 6 January 2022.

This tender presents growth opportunities for businesses specialising in data analysis, statistical inference, and software development, particularly those familiar with Bayesian methods. Companies capable of developing synthetic data generators and experienced in the use of programming languages like Python may find this contract particularly suited to their expertise. Given the focus on non-domestic building energy use, businesses involved in research and development in environmental studies or related fields should consider competing for future opportunities of a similar nature that may arise from this project.

Find more tenders on our Open Data Platform.
How relevant is this notice?

D3 Tenders Premium

Win More Public Sector Contracts

AI-powered tender discovery, pipeline management, and market intelligence — everything you need to grow your public sector business.

Start Free Trial Book a Demo
All Features Pricing

Notice Information

Notice Title

PS21196 - Bayesian Synthetic Population Algorithm Development, for National Buildings Model

Notice Description

***** THIS IS AN AWARD NOTICE, NOT A CALL FOR COMPETITION ***** This procurement is being concluded following a mini competition under the RM6018 - Crown Commercial Services Research Marketplace DPS This Invitation to Tender aims to procure, on behalf of the BEIS Secretary of State, an implemented methodology for producing synthetic population sample data from multiple overlapping data sources, relating to non-domestic buildings' energy use in the UK. The BEIS National Buildings Model (NBM) makes use of disclosive property survey data to represent the diverse building population of the UK. While data of this type is richly detailed and necessary for building physics simulation, the sensitivity and relatively small sample sizes present a dual challenge. Data protection compliance requires that the "stock" datasets derived from surveys are not published, preventing external replication of BEIS analysis even once the NBM itself is published. Simultaneously, BEIS wishes to reconcile the weighted survey data with other trusted information that has been collected on the same population. These alternative data sources are diverse, from national aggregate statistics to meter-point data collected for most individual UK properties. We propose that a synthetic dataset can resolve both issues. Synthetic data generators are algorithms for condensing the important properties of a dataset into a set of cross-correlations (a modelled distribution of traits). From this, a new "sample" can be drawn which preserves the key relationships we wish to infer from the original data, while scrambling everything else. Applied to a single dataset, this can ensure that private information is not disclosed, while maintaining the format of a detailed survey. The synthetic data concept can be extended, producing a single generating algorithm from multiple otherwise incompatible datasets. The resulting "samples" would be a population of imaginary building records which are nonetheless collectively consistent with everything we (think we) know about the true population. This project will procure expert assistance in the creation of this generating algorithm. The scope will be limited to non-domestic buildings energy use, but the approach taken is expected to be eventually extended to cover domestic buildings (which have their own unique data inputs) and potentially other domains as well. Therefore, flexibility and modularisation are important factors in the implementation. The model will be developed and implemented in an appropriate programming language (Python 3 is preferred for compatibility with the NBM, but tenderers may make a case for alternatives, such as R, if they think it necessary). Development will be version controlled using Git. The contractor will therefore need expertise in both software development and statistical inference/machine learning. Bayesian procedures have featured heavily in the exploratory work conducted so far (see below).

Notice Details

Publication & Lifecycle

Open Contracting ID
ocds-b5fd17-ef3d8adc-7b82-475a-b713-4465b0cebb3a
Publication Source
Contracts Finder
Latest Notice
https://www.contractsfinder.service.gov.uk/Notice/8ed62523-4148-43db-b6c6-26869d194a61
Current Stage
Award
All Stages
Award

Procurement Classification

Notice Type
Award Notice
Procurement Type
Dynamic
Procurement Category
Services
Procurement Method
Selective
Procurement Method Details
Call-off from a dynamic purchasing system
Tender Suitability
SME
Awardee Scale
SME

Common Procurement Vocabulary (CPV)

CPV Divisions

73 - Research and development services and related consultancy services

79 - Business services: law, marketing, consulting, recruitment, printing and security

CPV Codes

73200000 - Research and development consultancy services

79300000 - Market and economic research; polling and statistics

Notice Value(s)

Tender Value
£49,375 Under £100K
Lots Value
Not specified
Awards Value
£49,375 Under £100K
Contracts Value
Not specified

Notice Dates

Publication Date
20 Jan 20224 years ago
Submission Deadline
3 Nov 2021Expired
Future Notice Date
Not specified
Award Date
7 Dec 20214 years ago
Contract Period
29 Nov 2021 - 31 Mar 2022 1-6 months
Recurrence
Not specified

Notice Status

Tender Status
Complete
Lots Status
Not Specified
Awards Status
Active
Contracts Status
Not Specified

Buyer & Supplier

Contracting Authority (Buyer)

Main Buyer
UK SHARED BUSINESS SERVICES LIMITED
Contact Name
Available with D3 Tenders Premium →
Contact Email
Available with D3 Tenders Premium →
Contact Phone
Available with D3 Tenders Premium →

Buyer Location

Locality
SWINDON
Postcode
SN2 1FL
Post Town
Swindon
Country
England
Major Region (ITL 1)
TLK South West (England)
Basic Region (ITL 2)
TLK7 Gloucestershire and Wiltshire
Small Region (ITL 3)
TLK71 Swindon
Delivery Location
Not specified
Local Authority
Swindon
Electoral Ward
Rodbourne Cheney
Westminster Constituency
Swindon North

Supplier Information

Number of Suppliers
1
Supplier Name

RED SCIENTIFIC

Further Information

Notice Documents

Open Contracting Data Standard (OCDS)

View full OCDS Record for this contracting process

Download

The Open Contracting Data Standard (OCDS) is a framework designed to increase transparency and access to public procurement data in the public sector. It is widely used by governments and organisations worldwide to report on procurement processes and contracts. 

{
    "tag": [
        "compiled"
    ],
    "id": "ocds-b5fd17-ef3d8adc-7b82-475a-b713-4465b0cebb3a-2022-01-20T14:52:41Z",
    "date": "2022-01-20T14:52:41Z",
    "ocid": "ocds-b5fd17-ef3d8adc-7b82-475a-b713-4465b0cebb3a",
    "language": "en",
    "initiationType": "tender",
    "tender": {
        "id": "PS21196",
        "title": "PS21196 - Bayesian Synthetic Population Algorithm Development, for National Buildings Model",
        "description": "***** THIS IS AN AWARD NOTICE, NOT A CALL FOR COMPETITION ***** This procurement is being concluded following a mini competition under the RM6018 - Crown Commercial Services Research Marketplace DPS This Invitation to Tender aims to procure, on behalf of the BEIS Secretary of State, an implemented methodology for producing synthetic population sample data from multiple overlapping data sources, relating to non-domestic buildings' energy use in the UK. The BEIS National Buildings Model (NBM) makes use of disclosive property survey data to represent the diverse building population of the UK. While data of this type is richly detailed and necessary for building physics simulation, the sensitivity and relatively small sample sizes present a dual challenge. Data protection compliance requires that the \"stock\" datasets derived from surveys are not published, preventing external replication of BEIS analysis even once the NBM itself is published. Simultaneously, BEIS wishes to reconcile the weighted survey data with other trusted information that has been collected on the same population. These alternative data sources are diverse, from national aggregate statistics to meter-point data collected for most individual UK properties. We propose that a synthetic dataset can resolve both issues. Synthetic data generators are algorithms for condensing the important properties of a dataset into a set of cross-correlations (a modelled distribution of traits). From this, a new \"sample\" can be drawn which preserves the key relationships we wish to infer from the original data, while scrambling everything else. Applied to a single dataset, this can ensure that private information is not disclosed, while maintaining the format of a detailed survey. The synthetic data concept can be extended, producing a single generating algorithm from multiple otherwise incompatible datasets. The resulting \"samples\" would be a population of imaginary building records which are nonetheless collectively consistent with everything we (think we) know about the true population. This project will procure expert assistance in the creation of this generating algorithm. The scope will be limited to non-domestic buildings energy use, but the approach taken is expected to be eventually extended to cover domestic buildings (which have their own unique data inputs) and potentially other domains as well. Therefore, flexibility and modularisation are important factors in the implementation. The model will be developed and implemented in an appropriate programming language (Python 3 is preferred for compatibility with the NBM, but tenderers may make a case for alternatives, such as R, if they think it necessary). Development will be version controlled using Git. The contractor will therefore need expertise in both software development and statistical inference/machine learning. Bayesian procedures have featured heavily in the exploratory work conducted so far (see below).",
        "status": "complete",
        "classification": {
            "scheme": "CPV",
            "id": "73200000",
            "description": "Research and development consultancy services"
        },
        "additionalClassifications": [
            {
                "scheme": "CPV",
                "id": "79300000",
                "description": "Market and economic research; polling and statistics"
            }
        ],
        "items": [
            {
                "id": "1",
                "deliveryAddresses": [
                    {
                        "postalCode": "SW1H 0ET"
                    },
                    {
                        "postalCode": "SW1H 0ET"
                    }
                ]
            }
        ],
        "value": {
            "amount": 49375,
            "currency": "GBP"
        },
        "procurementMethod": "selective",
        "procurementMethodDetails": "Call-off from a dynamic purchasing system",
        "tenderPeriod": {
            "endDate": "2021-11-03T11:00:00Z"
        },
        "contractPeriod": {
            "startDate": "2021-11-29T00:00:00Z",
            "endDate": "2022-03-31T23:59:59+01:00"
        },
        "suitability": {
            "sme": true,
            "vcse": false
        },
        "mainProcurementCategory": "services"
    },
    "parties": [
        {
            "id": "GB-SRS-sid4gov.cabinetoffice.gov.uk/dXGP288m",
            "name": "UK SHARED BUSINESS SERVICES LIMITED",
            "identifier": {
                "legalName": "UK SHARED BUSINESS SERVICES LIMITED",
                "scheme": "GB-SRS",
                "id": "sid4gov.cabinetoffice.gov.uk/dXGP288m"
            },
            "address": {
                "streetAddress": "Polaris House, North Star Avenue",
                "locality": "SWINDON",
                "postalCode": "SN21FL",
                "countryName": "England"
            },
            "contactPoint": {
                "email": "professionalservices@uksbs.co.uk"
            },
            "roles": [
                "buyer"
            ]
        },
        {
            "id": "GB-COH-02462121",
            "name": "RED SCIENTIFIC LIMITED",
            "identifier": {
                "legalName": "RED SCIENTIFIC LIMITED",
                "scheme": "GB-COH",
                "id": "02462121"
            },
            "address": {
                "streetAddress": "1 Oriel Court,Oriel Business Park Omega Park ALTON Hampshire GU34 2YT GB"
            },
            "details": {
                "scale": "sme",
                "vcse": false
            },
            "roles": [
                "supplier"
            ]
        }
    ],
    "buyer": {
        "id": "GB-SRS-sid4gov.cabinetoffice.gov.uk/dXGP288m",
        "name": "UK SHARED BUSINESS SERVICES LIMITED"
    },
    "awards": [
        {
            "id": "ocds-b5fd17-ef3d8adc-7b82-475a-b713-4465b0cebb3a-1",
            "status": "active",
            "date": "2021-12-07T00:00:00Z",
            "datePublished": "2022-01-06T17:21:12Z",
            "value": {
                "amount": 49375,
                "currency": "GBP"
            },
            "suppliers": [
                {
                    "id": "GB-COH-02462121",
                    "name": "RED SCIENTIFIC LIMITED"
                }
            ],
            "contractPeriod": {
                "startDate": "2021-11-29T00:00:00Z",
                "endDate": "2022-03-31T23:59:59+01:00"
            },
            "documents": [
                {
                    "id": "1",
                    "documentType": "awardNotice",
                    "description": "Awarded contract notice on Contracts Finder",
                    "url": "https://www.contractsfinder.service.gov.uk/Notice/8ed62523-4148-43db-b6c6-26869d194a61",
                    "datePublished": "2022-01-06T17:21:12Z",
                    "format": "text/html",
                    "language": "en",
                    "dateModified": "2022-01-20T14:52:41Z"
                },
                {
                    "id": "2",
                    "documentType": "contractSigned",
                    "description": "PS21196 - RM6018-Letter-of-Appointment - Countersigned_Redactedv1",
                    "url": "https://www.contractsfinder.service.gov.uk/Notice/Attachment/47a0a410-f71f-4002-b86d-6d552100ab67",
                    "format": "application/pdf"
                },
                {
                    "id": "3",
                    "documentType": "contractSigned",
                    "description": "PS21196 - RM6018-Call-Off-Contract-Terms - Countersigned_Redactedv1",
                    "url": "https://www.contractsfinder.service.gov.uk/Notice/Attachment/4662db9c-f78a-4dbb-9817-26e08c80290b",
                    "format": "application/pdf"
                }
            ]
        }
    ]
}