Detalle de oportunidad

P106384 STATISTICAL CAPACITY BUILDING CHANGE AND REFORM FOR THE DEVELOPMENT OF STATISTICS PROJECT Note: If you have difficulties in reading the below procurement announcement, please select the link below to retrieve the notice as an MS Word document. ---------------------------------------------- INDONESIA IBRD LOAN NO. 8038-IND/TRUST FUND 093092/TF098283 STATISTICAL CAPACITY BUILDING CHANGE AND REFORM FOR THE DEVELOPMENT OF STATISTICS PROJECT ID NO. P106384  Consulting services for the design and implementation of Integrated Statistical Information System (Reference # B-178/BPS/2140/04/2016)  REQUEST FOR EXPRESSION OF INTEREST (REOI)    The national statistics office of Indonesia, Badan Pusat Statistik (BPS), is the central government agency primarily responsible for the production of Indonesia''s official statistics. These statistics include social, agriculture, national accounts, price indexes and economic conditions of the country. These data are used by government policy makers, global capital markets, foreign investors, businesses and the public in making decisions that directly impact the economy of Indonesia and the welfare of its people. BPS is on its journey to modernize its operations to move towards an integrated statistics production system in line with international leading practices. To this end, BPS seeks consulting services from large and mid-sized consulting firms ( Consultants ) for the design and implementation of an Integrated Statistical Information System ( System ) to support and manage the timely production of high quality integrated statistics. Please refer Annex-A for System abstract details. The assignment period is approximately 2 years. BPS is headquartered in Jakarta and has over 500 regional offices around the country, with a total workforce of almost 16,000 employees. The objectives of the STATCAP-CERDAS includes:   Improving statistical quality as well as improving user satisfaction and confidence in BPS products and services.   Increasing the efficiency of statistics operations through the application of information and communication technology. The consulting services sought under this REOI (hereinafter as, services ) include: To design, build and implement a System that help BPS to support their business processes such as data collection, processing, analysis and dissemination.   To configure, customize, build and integrate Core services to enable data collection, data processing, data analysis and data dissemination and   Common services such as metadata, sampling frames, survey management, geospatial data, content management, data ingestion, working databases and data warehouses. The design and implementation of this System should be flexible, modular, extensible and scalable. This System may comprise statistical Commercial-off-the-Shelf (COTS) applications and/or custom build statistical applications. Consultants should recommend and prefer COTS. BPS invites eligible consultants to express interest to provide the requested services. Interested consultants must provide information to prove their qualifications to perform the services. Expressions of interest must contain:   Information about the Consultants.   Experience of Consultants in similar assignments in the last 5 years, to be described in the template provided in Annex-B of this document.   Consultants experience in the design and implementation of similar areas will also be considered for this assignment, such as:   Enterprise Applications including Transaction Processing System, Decision Support System (Business Intelligence, Data Warehouse / Data Mining, Big Data).   Enterprise Products and / or COTS Applications.   Enterprise Application Integration.   BPS envisions the primary expertise required for this assignment is Systems Integration. Consultants may associate with other organizations, such as Statistics Institutions and/or vendors of Middleware, Data Warehouse and Statistical Applications to enhance their qualifications. Consultants will be selected in accordance with the procedures set out in the World Bank''s Guidelines: Selection and Employment of Consultants by World Bank Borrowers dated May 2004, Revised Oct 1st 2006 & May 1st 2010  ( Consultant Guidelines ), setting forth the World Bank''s policy on conflict of interest. Expressions of interest should be received by BPS no later than May 4th 2016 at 4 pm Jakarta Time. Consultants who had expressed their interests in response to the original REOI published in UNDB on Feb 5th 2016 are not required to submit the expression of interest again. But, consultants may choose to do so to provide additional information and / or to update their qualifications information. All consultants will be informed of the outcome of their expression of interest upon completion of the short-listing process.   Consultants shall either upload their expressions of interest into BPS drop box account or submit a hardcopy to the following address: Badan Pusat Statistik Attn: Procurement Committee of Package 2B Sub Direktorat Pengembangan Basis Data, Building 1, 2nd Floor, Jl. Dr. Sutomo No 6-8 Jakarta 10710, Indonesia Phone: +62-21-384 8741       Email: procurement2statcap@bps.go.id   BPS drop box URL: https://box-statcapcerdas.bps.go.id/      Please email your request to obtain user name and password for the BPS drop box account --------------------------------------------------------------------------------------------------------------------------------   Annex – A: Abstract on Integrated Statistical Information System   The objective of Consultants'' is to design, build (configure, customize and develop) and implement an efficient Integrated Statistical Information System to address the growing users'' demands. This system supports the core business processes of BPS and ensures homogenization of data and integration of statistical processes through different surveys and census.   This system consists of applications to support an integrated value chain, which includes the collection, processing, analysis and dissemination of data. This system also need common services such as metadata, sampling frames, survey management, geospatial data, content management, and data ingestion, working databases and data warehouses.   The design of this system should be based on layered or horizontal approach. The general impression of the system is as depicted below figure. In general terms, the survey information life cycle can be classified into logical grouping as: # Grouping Phases 1 Survey Preparation   In broader terms, the survey designers make decisions such as objective of the survey, users need, design concepts, users and data providers who will participate in the survey, methodology, assess survey inputs and dissemination outputs and build procedures for the transformation.     Specify Needs: In this phase, need for new survey and or census is identified, or feedback about current statistics is initiated. This includes activities associated with engaging users and data providers to identify statistical needs, proposing high level solution options and preparing business cases to meet these needs.   Design: This phase describes the development and design activities, and any associated practical research work needed to define the statistical outputs, concepts, methodologies, collection instruments and operational processes.   Build: This phase builds and tests the production solution to the point where it is ready for use in the Live or Production environment. The outputs of the Design phase direct the selection of reusable processes, instruments, information, and services that are assembled and configured in this phase to create the complete operational environment to run the process.   2 Survey Operation   In broader terms, the objective is to transform the elementary data, collected from different channels such as CAPI (Computer-assisted personal interviewing), CATI (Computer-assisted telephones interviewing), CAWI (Computer Aided Web Interviewing), PAPI (Paper-assisted personal interviewing) into valid and valuable information, store in database for processing, analysis and dissemination.   The results of the survey should be made available in a user-acceptable form via appropriate distribution channels. In principle, a survey production cycle is complete once the survey results are disseminated.   Collect: This phase collects or gathers all necessary information, using different collection channels from field and includes extractions from statistical and administrative sources, databases and internet sources and store into appropriate environment for further processing.   Process: This phase describes data cleansing and preparation for analysis. This phase has sub-processes such as check, cleanse, and transform data so that the data can be analyzed and disseminated in the form of statistical output.   Analyze: In this phase, statistical outputs are produced, examined in detail for the coherency and made ready for dissemination. It includes preparing statistical content (including commentary, technical notes, etc.), and ensure outputs are fit for purpose prior dissemination.     Disseminate: This phase manages the release of the statistical products to users. It includes all activities associated with assembling and releasing a range of static and dynamic products via common channels such as media, maps, desktop, web, mobile and multimedia. These activities support users to access outputs released by the statistical organization.   3 Survey Evaluation   In broader terms, the inputs are gathered throughout the different phases to evaluate the statistical business process, identifying and prioritizing potential improvements.   Evaluate: This phase manages the evaluation of statistical business processes and products. This phase, logically takes place at the end, but relies on inputs gathered and improvement areas for the continuous improvement.     In broader terms, the functional description of core systems and common services - applications and or systems are as outlined below: Collection System: The objective of this system is to facilitate the development of electronic and paper questionnaires design standards and procedures (reuse of standard questions, general instructions and layouts appropriate for data collection). This system is used to collect data from heterogeneous channels such as paper, form-based applications (CATI, CAWI, CAPI) different format files provided by third-party administrative sources and internet sources. This system also facilitates in selecting samples from the sampling frames.   Processing System: The objective of this system is to process data cleansing and prepare data for analysis. These systems check, cleanse, validate and transform input data, so that they can be analyzed and disseminated as statistical outputs. The system should facilitate classification, editing and imputation, derivation, weighting, estimation and aggregation.   Analysis System: The objective of this system is to produce statistical outputs, examine and prepare the output for dissemination. This includes preparing statistical content including notes, commentary and ensure outputs are fit for purpose prior to dissemination to statistical data users. This system also ensures that primary or residual disclosure of confidential data does not occur when the data is processed and or disseminated.   Dissemination System: The objective of this system is to manage and release the statistical products such as tabulation, publications, GIS. The system manages activities associated with assorting and releasing a range of static and dynamic products via a range of channels such as media, maps, kiosk, desktop, web, mobile, multimedia and APIs.   Data Ingestion / ETL System: The objective of this system is used for extract data from channels such as field, administrative authority or from internet sources and load the data onto databases. The system should have the flexibility to deal with different data formats, support configuration of business rules for cleansing, filtering, splitting joining, transposing and transforming data.   Metadata System: The objective of this system is to store and manage the life-cycle of variables, activities, references or classifications. This system is the backbone and enables the integration of the different views of statistical data during the information life cycle by facilitating searching, querying, and reporting, sharing and accessing through all statistical phases and processes.   Survey Management System: The objective of this system is to support the planning, monitoring and control of surveys throughout all phases of the statistical process; support quality checkpoints to streamline efficient and optimized scope, schedule, allocation, budget and resources. This system will collect and store operational data for later use and support the provision of progress reports. This system also manages survey logistics, coordinate data providers, enumerators and / or survey field force, allow data quality checks, link training materials, knowledge and information required to perform survey.   Frame and Register Systems: The objective of this system is to manage the sampling frames and registers such as administrative areas, census block master frame, household master frame and statistical business register. These system have the capability to store, retrieve and interface with other systems.   Geospatial System: The objective of this system is to manage the geospatial sampling frame by capturing, storing, retrieving, and updating geospatial information for surveys; and build the statistical GIS for dissemination.     Content Management System: The objective of this system is used to store, share, manage and track electronic content across all phases and activities.   Working Database: This is a staging database and the objective is to store the data collected and or received in form of data sets, allow operations requiring manipulation before it is transferred to the Input Data Warehouse; facilitates operations such as data validation, editing and imputation tasks, complex set transformations and may be of a highly interactive or ad-hoc nature.     Input Data Warehouse: The objective is to facilitate the subsequent statistical analysis and integration of information by providing multidimensional variables sharing common dimensions and / or integrated with older data of the same survey or even data from different surveys; facilitates operations such as weighting, aggregation, micro and macro-editing of data. The data from Input Data Warehouse will be transferred to Output Data Warehouse.   Output Data Warehouse: The objective is to facilitate the subsequent statistical analysis and integration of information by providing multidimensional variables sharing common dimensions and / or integrated with older data of the same survey or even data from different surveys. This data warehouse uses disclosure control process to protect the confidentially of the data before transferred to Dissemination Data Warehouse.   Dissemination Data Warehouse: The objective is to extract corresponding metadata and create suitable products report, ranging from predefined reports and statistical publications to ad-hoc queries, using a dissemination system and disseminate to various channels.  ---------------------------------------------------------------------------------------------------   Annex – B   Consultant''s relevant experience for this assignment   Assignment name:       Value of the contract (in the contract currency):     Client name:         Duration of assignment (months):     Country services were performed in:       Name and form of associated consultancies, if any:   Start date (month / year):       Completion date (month / year): Description of project and services provided to client:               Note: Please provide details for all fields as per the template.