SOO_Data_Engineering_Science_Analytics_and_Governance_Services.pdf

Acquisition Analytics Program

“Greenlight Contract”

Statement of Objectives for Data Engineering, Science, 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 data engineering, data science, data analytics, data governance, and change management services in support of its digitizing acquisition and portfolio scorecards initiative(s) to the Department of War (DoW) Data & Digitization Transformation Program. These services will empower the DoW to make faster, accurate, and data-driven decisions across its acquisition domain.

(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for analysis as well as emerging technologies like artificial intelligence, undefined or misaligned strategies, and outdated risk-avoidant (organizational and system-based) structures that hinder measurable transformation.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 enables Executive Order 14265 to “Modernize Defense Acquisitions” and the Secretary of War’s Acquisition Transformation Strategy (ATS), specifically, the Under Secretary of War for Acquisition and Sustainment’s (USW(A&S)).

initiatives to digitize the acquisition system and implement portfolio scorecards.

Additionally, this work supports Executive Order 14275 “Restoring Common Sense to Federal Procurement” and Executive Order 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 the rapid integration of capabilities for Office of the Secretary of War (OSW) and the Warfighting Acquisition System to enhance efficiency, mitigate risk, and proactively enable opportunities that adapt capabilities to emerging challenges. As a part of the RWS charter, the organization leads the digitization efforts for the USW(A&S) which aims to digitize and then modernize/transform acquisition work streams. RWS enables the enterprise data governance, acquisition data ecosystem which includes data systems, tools, and applications used for analytics and decision-making.

(3) Objective(s) and Scope: The scope of this contract includes providing data governance, data engineering, data science, data analytics, and change management services in support of the initiatives referenced in Section (1) and (2). The objective(s) and scope for each area is provided below.

1. Data Governance Services

1.1. Objective(s):

1.1.1. Establish a formal and executable, enterprise-wide Acquisition Data Governance Framework within 6-months. Then, execute and evolve the framework, as required. This framework will be codified by a cross-functional charter, a fully operational data governance council, and published data governance artifacts for the acquisition data sub-domains. The primary goal is to transform data from an unreliable byproduct into a governable, trusted, and discoverable strategic asset.

1.2. Scope:

1.2.1. Develop a data governance charter: define the mission, scope, roles, responsibilities (e.g., Data Owners, Data Stewards), and decision-making authority for managing the Department's acquisition data.

1.2.2. Establish and execute the Acquisition Data Council (ADC): form and manage a cross-functional body of leaders from the Military Services and 4th estate entities to ratify data standards, resolve data issues, and transform workflows.

1.2.3. Define and document data standards in an enterprise repository: In partnership with the ADC, create and maintain standards for data quality, data definitions, metadata management for key data elements, and data system interface requirements.

1.2.4. Develop an enterprise data catalog: manage a solution to inventory, classify, and define all critical acquisition data assets and artifacts, making it easy for users to find and understand the data available to them.

1.2.5. Institute enterprise data quality monitoring: establish processes, tools, and automated (business) rules to monitor, measure, and the quality of data, and recommend system/workflow transformation(s) to remediate identified issues.

2. Data Engineering Services -

2.1. Objective(s):

2.1.1. To iteratively design, build, and implement a scalable and secure Acquisition Data Ecosystem within 12-months. This ecosystem shall successfully integrate acquisition data systems, automating at least 80% of the manual data collection/aggregation workflows currently used for portfolio reporting, thereby increasing data timeliness and reducing errors. Within 24-months, the primary goal is to automate 95% of manual data collection/aggregation workflows.

2.2. Scope:

2.2.1. Architect and deploy data ecosystem in the enterprise data warehouse: design and implement a modern, cloud-based data structures that will serve as the foundation for all work stream analytics.

2.2.2. Develop robust data pipelines (ETL/ELT): build, test, and deploy automated pipelines to extract data from information systems with minimal data loss (<0.1%), transform it according to defined business rules and metadata standards, and load it into the enterprise data warehouse for consumption by analytic users.

2.2.3. Implement data modeling, data structuring, and ontologies:

transform raw, unstructured source data into well-defined, analysis-multi-dimensional data models and ontologies that are optimized for reporting, analytics, machine learning, and artificial intelligence.

2.2.4. Enable data security and access controls: implement role-based access controls (RBAC), attribute-based access control (ABAC), and required system security protocols to ensure that users can only access the data they are authorized to see, and granular data access is flexible/responsive.

2.2.5. Create and maintain an API Layer: develop secure Application Programming Interfaces (APIs) to allow other authorized systems and tools to programmatically access (read/write) the curated data within the designed data ecosystem.

3. Data Science and Analytics Services -

3.1. Objective(s):

3.1.1. To develop and deploy a suite of analytics tools, including the mandated USW(A&S) Portfolio Scorecards, that delivers actionable insights and achieves a 75% adoption rate among target Service Acquisition Executives (SAE) and Portfolio Acquisition Executive (PAE) within 12-months. Within 24-months, the primary goal is to achieve a 95% adoption rate across SAEs, PAEs, Program Executive Offices (PEO) (or equivalent), and programs within 24-months. This service will shift the focus from manual report generation to proactive, forward-looking, workflow driven analysis.

3.2. Scope:

3.2.1. Develop interactive Portfolio Scorecards: partner with stakeholders to define KPIs and then design, build, and deploy dynamic, self-service scorecards in a business intelligence (BI) tool (e.g., Tableau, Qlik).

3.2.2. Create operational dashboards: build dashboards for various user levels (from program managers to executive leadership) to monitor the health and performance of acquisition programs in near-real-time.

3.2.3. Conduct exploratory and ad-hoc analysis: perform deep-dive analyses to answer complex business questions, identify trends, and uncover root causes of issues that are not visible in standard reports.

3.2.4. Develop Proof-of-Concept (PoC) predictive models: apply data science and machine learning techniques to curated datasets to build algorithms/models for challenges like mission risk, cost-overrun prediction, schedule risk analysis, or supply chain vulnerability.

3.2.5. Generate strategic insights and canned data products: synthesize analytical findings into clear, concise data products to support senior leader decision-making

4. Change Management & User Enablement Services -

4.1. Objective(s):

4.1.1. To cultivate a data-centric culture and drive an 80% adoption rate of the new analytics platform and scorecards among the target user base within 12-months. This will be achieved by executing a comprehensive change management and training plan throughout the program's lifecycle, ensuring the workforce is not just given tools, but is empowered to use them effectively. Within 24-months, the goal is a 90% adoption rate.

4.2. Scope:

4.2.1. Develop and execute a strategic communications plan: create a multi-channel communication plan to build awareness, articulate the vision, manage expectations, and celebrate wins throughout the program.

4.2.2. Conduct stakeholder analysis and engagement: identify all key stakeholders, map their personas, influence, and interest, and develop a targeted engagement plan to ensure buy-in at all levels.

4.2.3. Create a Comprehensive Training Curriculum: develop and deliver role-based training materials (e.g., user guides, videos, workshops) that teach users how to access the platform, interpret the scorecards, and leverage data in their daily work.

4.2.4. Establish a user support function(s): create a help desk process or a "Center of Excellence" to provide ongoing support, answer user questions, and troubleshoot issues.

4.2.5. Facilitate user feedback and continuous improvement: establish regular forums (e.g., user groups, surveys) to gather feedback on the tools and data, and use that input to prioritize future enhancements and improvements.

(4) Contract Data Requirements List (CDRL)

CDRL NO. Title SOO / PWS REF. Frequency / Due Date

A001 Program Management Plan General 30-days of award or option Exercise

A002 Monthly Status Report Monthly A003 Quarterly Program Review

Briefing Quarterly

Data Governance Services B001 Acquisition Data

Governance Framework

1.1.1 Initial, NLT 6-months from

contract award B002 Data Governance Charter 1.2.1 Initial, NLT 4-months from contract award B003 Acquisition Data Council

(ADC) Meeting Minutes & Action Items

1.2.2 Within 3 business days after

each meeting

B004 Data Standards and Interface Requirements Document

1.2.3 Initial, NLT 6-months from

contract award, then quarterly

B005 Enterprise Data Catalog & Management Plan

1.2.4 Monthly

B006 Enterprise Data Quality Monitoring Report

1.2.5 Monthly

Data Engineering Services C001 Data Ecosystem

Architecture & Design Document

2.2.1 Initial, NLT 4-months from

contract award, then as requested

C002 Data Pipeline Performance & Data Loss Report

2.2.2 Monthly and/or At Event

C003 Data Model & Ontology Documentation

2.2.3 Initial, NLT 9-months from

contract award, then monthly

C004 Security & Access Control Plan

2.2.4 Initial, NLT 6-months from

contract award, then quarterly

C005 API Specification & Documentation

2.2.5 As Developed

C006 Data Aggregation Automation Progress Report

2.1.1 Quarterly

Data Science and Analytics Services D001 Interactive Portfolio

Scorecard

3.2.1 Initial, NLT 6-months from

contract award, then as requested

D002 Operational Dashboards (By Work Stream)

3.2.2 As Requested / Per Project

Plan

D003 Ad-Hoc Analysis & Deep Dive Reports

3.2.3 As Requested / Per Project

Plan

D004 Predictive Model Proof-of- Concept Report

3.2.4 As Requested / Per Project

Plan

D005 Strategic Insights & Canned Data Products Report

3.2.5 As Requested / Per Project

Plan

D006 Platform Adoption Rate Report

3.1.1 Monthly

Change Management and User Enablement Services E001 Strategic Communications

Plan

4.2.1 Initial, NLT 3-months from

contract award, then as requested

E002 Stakeholder Analysis & Engagement Plan

4.2.2 Initial, NLT 3-months from

contract award, then monthly

E003 Comprehensive Training Curriculum & Materials

4.2.3 Initial, NLT 6-months from

contract award, then as required

E004 User Support Performance Report (Help Desk Metrics)

4.2.4 Monthly

E005 User Feedback & Continuous Improvement Report

4.2.5 Quarterly

E006 Tool Adoption Rate Report 4.1.1 Monthly