Students will enter the role of financial planners by analyzing a Brooklyn small-business scenario, identifying who is affected by rising costs and changing financial patterns, and producing an initial challenge frame, end-user profile, and inquiry questions grounded in evidence.

Students will investigate Brooklyn small-business financial data, interviews, and case evidence to determine when exponential models fit revenue and debt situations, graph and interpret those models, use logarithms to solve timing questions, and develop an evidence-based proposal for a forecasting tool that responds to stakeholder needs.

Students will turn earlier research and math analysis into a usable forecasting dashboard concept by studying strong models, planning their build, drafting testable predictions, creating and revising prototype components, and documenting how stakeholder and peer feedback shape stronger repayment and growth recommendations for Brooklyn small businesses.

Students will implement and test their community business forecasting dashboard with sample or partner-informed Brooklyn small-business scenarios, collect evidence on how well their exponential and logarithmic models support repayment and growth decisions, and use feedback to refine recommendations before the final share phase.

Students will present the story of how their Brooklyn small-business forecasting dashboard developed through research, exponential and logarithmic analysis, stakeholder feedback, and revision, then document how their mathematical reasoning, professional communication, and community-focused decision making grew across the project.