Award

Provision of External Support to Project Data Analytics

  • Ministry of Defence

F15: Voluntary ex ante transparency notice

Notice identifier: 2022/S 000-011714

Procurement identifier (OCID): ocds-h6vhtk-03345f

Published 5 May 2022, 2:36pm



Section one: Contracting authority/entity

one.1) Name and addresses

Ministry of Defence

Kentigern House, 65 Brown Street

Glasgow

G2 8EX

Contact

James Smith

Email

james.smith868@mod.gov.uk

Country

United Kingdom

NUTS code

UK - United Kingdom

Internet address(es)

Main address

https://www.gov.uk/government/organisations/ministry-of-defence

one.4) Type of the contracting authority

Ministry or any other national or federal authority

one.5) Main activity

Defence


Section two: Object

two.1) Scope of the procurement

two.1.1) Title

Provision of External Support to Project Data Analytics

Reference number

703832450

two.1.2) Main CPV code

  • 72316000 - Data analysis services

two.1.3) Type of contract

Services

two.1.4) Short description

• Advise and peer review the Department’s optimism bias policy. Advise and peer review the Department’s approach to cost growth and cost escalation.

• Introduction of a reference class forecast for Defence projects, to prevent approval of overly optimistic projects.

• Conduct Reference Class Forecasting (RCF) on a minimum of 100 projects/programmes to provide benchmarking and forecasting on live and future MOD projects, enriched with RCF data from projects from around the world (e.g., US DOD).

• Develop detailed RCF from comparing individual project work breakdown structures.

• Identify solutions to blocks in the Department’s current data landscape that prevent end-to-end oversight of projects from Head Office to suppliers.

• Run two experiments on selected and agreed MOD programmes to better understand cost and schedule gaps by mapping granular project-level data from the various fragmented systems for domains such as cost and time etc and applying pre-built unique Artificial Intelligence / Machine Learning (AI/Ml) algorithms.

• Propose solutions that can help the Department move from descriptive analytics to predictive analytics with portfolio data.

The above will provide the MOD with better Project Delivery Data Analytics such as:

a. Enhanced LFE to support forecasting at project initiation and through life.

b. Reduced cost of projects – delivering more for less.

c. Reduced duplication of work across common projects.

d. Improved delivery performance and confidence.

e. Continuous improvement.

f. Improved pan-MOD and MOD-Industry collaboration.

g. Increased transparency.

two.1.6) Information about lots

This contract is divided into lots: No

two.1.7) Total value of the procurement (excluding VAT)

Value excluding VAT: £200,000

two.2) Description

two.2.3) Place of performance

NUTS codes
  • UK - United Kingdom

two.2.4) Description of the procurement

• Advise and peer review the Department’s optimism bias policy. Advise and peer review the Department’s approach to cost growth and cost escalation.

• Introduction of a reference class forecast for Defence projects, to prevent approval of overly optimistic projects.

• Conduct Reference Class Forecasting (RCF) on a minimum of 100 projects/programmes to provide benchmarking and forecasting on live and future MOD projects, enriched with RCF data from projects from around the world (e.g., US DOD).

• Develop detailed RCF from comparing individual project work breakdown structures.

• Identify solutions to blocks in the Department’s current data landscape that prevent end-to-end oversight of projects from Head Office to suppliers.

• Run two experiments on selected and agreed MOD programmes to better understand cost and schedule gaps by mapping granular project-level data from the various fragmented systems for domains such as cost and time etc and applying pre-built unique Artificial Intelligence / Machine Learning (AI/Ml) algorithms.

• Propose solutions that can help the Department move from descriptive analytics to predictive analytics with portfolio data.

The above will provide the MOD with better Project Delivery Data Analytics such as:

a. Enhanced LFE to support forecasting at project initiation and through life.

b. Reduced cost of projects – delivering more for less.

c. Reduced duplication of work across common projects.

d. Improved delivery performance and confidence.

e. Continuous improvement.

f. Improved pan-MOD and MOD-Industry collaboration.

g. Increased transparency.

two.2.11) Information about options

Options: No

two.2.13) Information about European Union Funds

The procurement is related to a project and/or programme financed by European Union funds: No


Section four. Procedure

four.1) Description

four.1.1) Type of procedure

Award of a contract without prior publication of a call for competition in the cases listed below

  • The procurement falls outside the scope of application of the regulations

Explanation:

Under PCR Regulation 32 b) ii:-

Foresight Works has pre-built unique Artificial Intelligence / Machine Learning (AI/Ml) algorithms that address MOD project delivery system objectives such as early warnings or predicting & preventing risk drivers. Foresight Works also have a unique database for reference class forecasting to compare MOD projects against various global benchmarks.

Foresight Works tooling is capable of connecting to MOD datasets, but also its multiple dataset providers (SharePoint, MS Power BI, Office365, MS Project, Oracle Primavera, Oracle E-Business).

four.1.8) Information about the Government Procurement Agreement (GPA)

The procurement is covered by the Government Procurement Agreement: No


Section five. Award of contract/concession

Contract No

703832450

Title

Provision of External Support to Project Data Analytics

A contract/lot is awarded: Yes

five.2) Award of contract/concession

five.2.1) Date of conclusion of the contract

5 May 2022

five.2.2) Information about tenders

The contract has been awarded to a group of economic operators: No

five.2.3) Name and address of the contractor/concessionaire

Foresight Works Ltd

64 New Cavendish Street

London

W1G 8TB

Email

aa@foresight.works

Country

United Kingdom

NUTS code
  • UK - United Kingdom
National registration number

11330700

The contractor/concessionaire is an SME

Yes

five.2.4) Information on value of contract/lot/concession (excluding VAT)

Initial estimated total value of the contract/lot/concession: £200,000

Total value of the contract/lot/concession: £200,000

five.2.5) Information about subcontracting

The contract/lot/concession is likely to be subcontracted


Section six. Complementary information

six.4) Procedures for review

six.4.1) Review body

Ministry of Defence

Kentigern House, 65 Brown Street

Glasgow

G2 8EX

Country

United Kingdom