Treasury BEP RFI: Bureau of Engraving and Printing (BEP) Data Management and Forecasting Initiative

Notice ID: BEP031524

Bureau of Engraving and Printing (BEP) is seeking data and analytics technical professional(s) who can advise and provide trustworthy solutions and converge processes, models and technology, forecast mechanism to inform mission and operational decision making, increase collaboration across our data community, and achieve efficiency savings across our investments.

BEP’s IRS Procurement Branch is requesting information via this RFI as a means of conducting market research to identify parties having an interest in and the capability to provide professional support to determine BEP’s data requirements, mechanisms and approaches to formulate the projectile to deliver success.

The main objective of this contract is to obtain technical services for data and analytics technical professional(s) who can advise and provide trustworthy solutions and converge processes, models and technology, forecast mechanism to inform mission and operational decision making, increase collaboration across our data community, and achieve efficiency savings across our investments.

The Office of Enterprise Solutions requires a Contractor to provide all necessary professional services to fulfill the goal to develop a comprehensive understanding of BEP’s data growth needs over the next 3-5 years. This will be accomplished through a combination of data analysis, interviews with key stakeholders, and benchmarking against industry peers. We are primarily interested in the following engagement from the service provider:

Data analysis: The Contractor will analyze the BEP’s historical data to identify trends and patterns in data growth. This will include analyzing data from a variety of sources, such as databases, application logs, and website traffic logs.

• Enforce Data Privacy and Analytics Model Security Practices as Part of Wider D&A Governance
• Design integrated, modular, data pipeline to support diverse data and analytics use cases.
• Design data architectures with access, virtualization, federation and semantic-layer features to encourage stakeholders to leverage the enterprise-sanctioned analytics portfolio and abandon shadow analytics.
• Reduce overlap within analytics domains by retiring slow, expensive, and unwieldy products, and by investing in new capabilities where more speed and agility are key to analytics success.
• Enable advance self-service analytics developers to citizen data scientists by embracing autoML model development toolkits.
• Extract insights from unstructured data using deep learning techniques.

Stakeholder interviews: The Contractor will interview key stakeholders to understand their needs and expectations for data growth.

• Develop a Training and Communication Strategy and Plan to increase adoption, buying and improved ways of working
• Implement analytics training to increase data literacy and analytics proficiency.

Industry benchmarking: The Contractor will benchmark data growth against industry peers. This will help to identify best practices and areas for improvement.

• Adopt the agile method that best meets the needs of the data science team and the organization. Adapt this agile process through regular retrospectives to make it fit for purpose.
• Formulate data strategy framework based on a holistic approach that encompasses people, processes, technology, and data and to move BEP forward with the experience and adaptation of the promise and power of data-driven decision intelligence …

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