Consultancy Services- Technical Assistance to update the statistical business register and improve the quality and coverage of business statistics

GOVERNMENT OF SAINT LUCIA MINISTRY OF ECONOMIC DEVELOPMENT AND YOUTH ECONOMY

Request for Expressions of Interest Consulting Services — Firms Selection

Project: OECS Data for Decision Making Project — Saint Lucia Component

Project ID: P174986

Credit / Financing No.: 71120

Procurement Reference No.: SLU-DDM-TECADVISR-CSO-QCBS-26

Notice Date: October 28, 2026

Assignment: Consultancy to Provide Technical Assistance to the CSO to Upgrade the Statistical Business Register IT Infrastructure and Improve the Coverage and Quality of Business Statistics The Government of Saint Lucia has received World Bank financing for the OECS Data for Decision Making Project and intends to use part of this financing for the consulting services described below. The Ministry of Economic Development and Youth Economy, through its Project Implementation Unit, invites eligible consulting firms to submit expressions of interest. Assignment scope The firm will support the Central Statistics Office (CSO) in improving the completeness, coverage, content and functionality of its Statistical Business Register (SBR), upgrading its IT environment and strengthening the production and use of quality business statistics. The services comprise: Assessment and improvement planning: Review legislation, protocols and practices used by custodians of economic administrative records; assess the maturity of the CSO’s SBR; and prepare recommendations and an SBR Improvement Plan aligned with relevant international standards and frameworks. SBR systems upgrade and data integration: Implement approved improvements to the existing SQL-based client-server relational database system; update features and functionality; and use Enterprise Census and economic administrative data to improve coverage, content and business survey sampling frames. Classification consistency and migration: Promote consistent use of the International Standard Industrial Classification (ISIC), concepts and definitions across the CSO and custodians of economic administrative data; review guidance for ISIC Revision 5; and prepare an ISIC 5 migration plan. Business statistics and quality assurance: Strengthen statistical business processes and protocols for producing structural and business demography statistics, developing metadata and assuring quality, with reference to the System of National Accounts 2008/2025, UN statistical business register guidelines and the UN National Quality Assurance Framework 2019. Deployment, documentation and knowledge transfer: Test and deploy the upgraded SBR; address defects and incorporate CSO feedback; prepare systems documentation, a Service Level Agreement, a maintenance manual and a user guide; and facilitate at least two consultation, training and sensitisation workshops for the CSO and custodians of economic administrative records.

Principal outputs include an inception report and work plan; a Situational Analysis Report incorporating the SBR Improvement Plan, ISIC Improvement and Migration Plan, and proposed uses of SBR data; a functioning and tested SBR; a deployed “go live” SBR with approved features, systems documentation, Service Level Agreement, maintenance manual and user guide; and a Final Summary Report covering the work performed and consultancy deliverables. Duration: Six (6) months from contract signing. Tentative commencement: January 2027. Most work will be home-based, with occasional travel to Saint Lucia according to a mutually agreed timetable. The firm will report to the CSO Director of Statistics and liaise closely with the Deputy Project Coordinator and the Permanent Secretary, Department of Economic Development. The detailed TOR accompanies this notice. Firm qualifications and shortlisting criteria Interested firms should provide evidence of their relevant experience and capacity to field the multidisciplinary team specified in the TOR. Shortlisting will consider: Experience developing or upgrading statistical business registers, administrative register systems or relational databases, and implementing IT systems that use administrative records. Technical capacity in database management systems, including SQL Server, MySQL or PostgreSQL, and in the design, implementation, testing, deployment and maintenance of register systems. Experience applying international standards and frameworks for statistical business registers, including the UN Guidelines for Statistical Business Registers and the UN Maturity Model for Statistical Business Registers. Experience applying ISIC and the Central Product Classification, supporting classification revisions or migration, and promoting consistent statistical concepts and definitions across institutions. Experience analysing official business statistics and producing technical reports or policy briefs on structural and business demography statistics, using relevant international frameworks and quality assurance standards. Experience consulting with diverse stakeholders and delivering training, sensitisation workshops, technical guidance and knowledge transfer. Capacity to mobilise and manage a team covering SBR systems development, statistical classifications, and structural and business demography statistics, as specified in the TOR.

Shortlisting will assess the firm’s qualifications, relevant experience and organisational capacity. Individual Key Experts will be assessed at the proposal stage rather than during shortlisting. The TOR identifies a Lead Expert / Statistical Business Register Expert, an ISIC Expert, and a Structural and Business Demography Statistics Expert; their detailed education, experience and skills requirements are set out in the TOR. Information to submit Submit a signed expression of interest in English, a firm profile describing its core business and years of operation, and details of relevant completed assignments. For each assignment, identify the client, country, dates, scope, services performed, completion status and a reference contact. Describ