PWS for_Green_Data Engineering-Analytics and Governance Services.docx

Statement of Objectives for “Green” Data Engineering, Analytics, and Governance Services A Statement of Objectives (SOO) is a government-prepared document incorporated into the solicitation that outlines the overall performance objectives and desired outcomes. It is used in solicitations when the government intends to provide the maximum flexibility to each offeror to propose an innovative approach. That portion of a contract that establishes a broad description of the government’s required performance objectives for acquisition data and its use to advance and inform leaders’ decision making.

(1) Purpose: The purpose of this contract is to provide human-centered design and testing services to the Department of Warfare (DoW) in support of its digitizing acquisition initiative. These services focus on workstream design, workflow modernization, and testing digital and artificial intelligence (AI)-based systems to enhance the acquisition domain’s ability consistently measure and quickly deliver effective capability across the lifecycle, from S&T to decommissioning.

(2) Background: The Department’s acquisition domain relies on antiquated legacy data systems whose primary purpose is compliance and oversight, rather than analysis and effective decision making. Each major organization (e.g., Military Service) in the Department also operates in a silo and organizations often misunderstand the value of technology. The result is unreliable, insufficient data for analysis as well as emerging technologies like artificial intelligence, undefined or misaligned strategies, and outdated risk-avoidant (organizational and system-based) structures that hinder measurable transformation. This work supports the USW(A&S) Digitization Acquisition Initiative under the SECWAR Acquisition Transformation Plan, which will execute the POTUS Executive Order 14265 to Modernize Defense Acquisitions. Both the US and FMS will be under this work supporting Presidential Executive Orders (EO), including EO 14275, Restoring Common Sense to Federal Procurement and EO 14268, “Reforming Foreign Defense Sales to Improve Speed and Accountability.”

The Deputy Assistant Secretary of War for Rapid Warfighting Support (RWS) is chartered to “enable transparent, integrated data-driven processes for OSW and the Defense Acquisition System to enhance efficiency, reduce uncertainty, and enable proactive adaptation to emerging challenges.” RWS will lead the integration and modernization effort for data acquisition. It will provide Enterprise acquisition tools for budgeting, reporting, and analytics. These efforts will drive data curation and exploration of existing data, informing OSW’s acquisition decisions and systems. Additionally, these efforts will support statutory and regulatory reporting and oversight requirements. Paramount to this responsibility is the rescoped functionality of Acquisition data systems and workflow to support SECWAR’s Acquisition Transformation.

(3) Scope and mission: The scope of this effort is to provide Data Engineering for software and AI development, sustainment, and operational support for the data Acquisition suite of capabilities. This suite includes front-end applications, as well as critical back-end solutions such as data schemas, ETL, process data repositories, API’s and the underlying data framework. The mission is to deliver and maintain a secure, high-performance, and interoperable environment that empowers the DoD acquisition workforce and its partners with the data and tools necessary to make informed, data-driven decisions.

The DoW requires timely access to accurate, authoritative, and reliable acquisition data to support insight, analysis, and decision-making. It requires easily accessible front-end applications, data repositories, capabilities, system to system integration, and a well-defined and managed data framework to offer perspective and context for the use of Acquisition data. AI2 supports the DoD Acquisition community and its partners, providing an integrated foundation that delivers improved security, performance, reusability, interoperability, scalability, and maintainability of Acquisition data.

There are three main areas of focus listed below:

a. Data collection: The collation, consolidation, and verification of data that is utilized and ingested into enclaves such as ADVANA and GovCloud.

b. Data integration: Integrating data from disparate systems, ensuring consistency and accuracy while building a robust data foundation that enables acquisition transformation.

c. Visualizations and analysis: Dashboards and other decision-making solutions that utilize the validated, collected, and integrated data described above.

3.1 Engineering Objectives

a. Software:- utilize DoW software tools in already established infrastructure and enclaves such as ADVANA or GovCloud. The software will be built in Government owned infrastructure however commercial tools that are needed can be brought as needed to build the best possible outcomes.

b. Systems Engineering Process: The required structure will leverage the commercial industry’s existing tools and products as much as possible. However, recognizing that there will be limits to this as much of DoD’s data has not been used or trained on commercial systems, modifications will need to be made to make the data and its outputs meaningful. The following teams will need to work on building out the required end needs.

c. Data Engineering:

1. Data Engineering to build out the data pipelines, Data Schema’s, API’s, ETL processes, RPA tools and other microservices as required to easily move required data or access it. The most important part is to build modularity and microservices in the back end to enable the addition and subtraction of tools as needed over team to fill needs.

2. Repositories for unstructured, semi-structured and structured data

3. Deliver easily catalogued data types with an easy ability to find, locate and share information to the variety of personas involved.

4. Database/repositories for acquisition domain and data ecosystem activity artifacts and workflows.

d. AI/ML and Analytics:

1. Data Science/ AI Engineering team to deliver algorithms, and AI tools required to solve problems. It must be explainable and follow DoD AI Ethic Principles. All work be able to be provided to a T&E partner for validation and verification.

2. Analytics Team to work with the Data Science Team to build and visualize the data outputs and create understanding for the human user. Develop data visualizations, reports, and dashboards to communicate insights and findings to senior leaders and stakeholders.

3. Use tools to generate reports as needed for various stakeholders.

e. Governance

1. Enable and run system processes for data governance to enable sharing of data within the system data ontology.

2. Provide support for data governance through support of policies, developing procedures and controls to manage acquisition data to ensure its data sources and repositories are accurate, secure and compliant.

f. Test and Evaluation: Test and Evaluation will be required of all work to ensure performance and other critical metrics are met.

(4) Performance objectives: The performance objectives allow the offeror the maximum flexibility to innovatively manage the projected schedule, performance, risks, warranties, subcontracts, and data to provide the goods or services that satisfy the government’s performance requirements.

4.1. Sustainment and operations

a. Availability: Ensure that Acquisition Data capabilities maintain a high uptime percentage during core hours, excluding scheduled downtime.

b. Recovery time: Maintain a low average recovery time from unplanned outages during core hours.

c. Maintainability: Deliver an integrated foundation that improves the maintainability of acquisition data for the DoD community.

d. Security: Deliver improved security for all applications and data.

4.2. Software development and enhancement

a. Agile delivery: Utilize agile development methodologies to deliver completed user story points in each development sprint. Conduct sprint review and planning, retrospectives, backlog refinements, and demonstrations that align with best agile practices, such as SAFe and scrum.

b. Automated testing: Achieve a high-percentage automated test coverage for capabilities. Provide recommended threshold and objective metrics to the government for reviews and tracking requirements.

c. Innovative solutions: Propose and implement creative, cost-effective solutions for system enhancements, leveraging industry best practices.

d. Modularity and interoperability: Develop a modular open systems architecture that supports the easy integration of new capabilities and ensures interoperability in DoW systems.

4.3. Data management and access

a. Data quality: Ensure the accuracy, reliability, and authority of all data within data Acquisition related capabilities.

b. Data framework support: Continuously mature the Data Governance process and needs Acquisition Data Framework to ensure data standards and alignment.

c. Data accessibility: Provide access to data repositories and front-end applications through a single, intuitive interface for authorized users. Develop data catalogue efforts to enable ease of data visibility, portability and transparency across the department.

4.4. Analytics and decision support

a. Analysis capabilities: Deliver enhanced capabilities that support strategic analysis, insights, and data-informed decision-making for DoD leadership.

b. Advanced analytics: Move deeper into data analytics, including the integration of predictive analysis and other advanced techniques.

c. Documentation: Produce clear, concise, and professionally written deliverables and documentation.

4.5 Contract Data Requirements List

Note: Days listed are based on business days and start once the contractor team is on-site and has sufficient credentials.

a. Possible CDRL’s off these objectives include:

a. Sprint & Backlog Planning: Within 30 days of reporting on site and receiving credentials along with accesses the vendor will deliver a project/sprint plan and initial backlog and provide regular dates as part of monthly reporting.

b. Test plans: Within 20 days vendor must provide a wireframe for their automation test plan and provide bi-weekly updates after gaining more guidance from stakeholders and understanding of the architecture.

c. System architectures (legacy and proposed new): initial current (legacy) architecture within 30 days of reporting on-site; initial future (new/objective) architecture within 15 days after legacy architecture. Associated updates as items change and at least quarterly.

d. Data Descriptions and mapping: initial current (legacy) data dictionary/mapping within 45 days of reporting on-site; initial future (new/objective) data dictionary/mapping within 15 days after legacy delivery. Associated updates as items change.

e. Data Schemas: Within 30 days, provide an initial draft data schema, with regular updates.

f. Lessons learned Within the first two months vendor must hold its first Lessons Learned Ceremony and develop a cadence to hold regular lessons learned ceremonies. Additionally, a Lessons Learned ceremony should occur within 30 days of contract end.

g. Prototype/Mockup: Within 15 days the vendor must provide a mockup of Acquisition System Prototype and provide updates monthly.

h. Phase 2: No later than 120 days, develop a Phase 2 Project Plan and Budget.

(5) Operating Constraints.

Legacy systems and code may need to be modified or eliminated. The new system must allow and enable current operations as the transition occurs. Human Center Design must be used to help usher in the change in the institution in terms of workflows, how people use the system and drive the product development. Data Governance is not in place, and these products and services should help inform these efforts as well as provide a feedback loop as these processes mature.

1. Project will be executed consistent with Ethical AI principles and the Agile Software Acquisition Pathway.

2. Project must consider and inform evolving defense acquisition guidance. Understanding of DoW Acquisitions as well as technology will be important.

3. Key persons and select engineers must be at a minimum to handle CUI information. There will be a need for a work at Secret and Top Secret.

4. Redhorse will require CACs, NIPR, SIPR, JWICS Accounts, and a DD-254 for classified discussions with stakeholders.