Math for Business Operations

Applied Accounting with Excel

UNIT04 - Lesson 8

PBL Milestone 1: Project Definition

45–60 minutes
Lesson Overview

Lesson Focus

Define problem, scope, metrics, risks; set up Excel workbook skeleton

Key Unit Objectives

Enduring Understandings:

  • Data-driven decisions provide competitive advantages in business operations
  • Statistical analysis reveals patterns that guide inventory and staffing optimization
  • Forecasting models enable proactive business planning and risk management
  • Outlier identification prevents skewed analysis and faulty business conclusions

Lesson Activities

Activity 1: Project Framing
10 minutes

Clarify business goals and constraints with authentic context

Details:

  • Write problem statement tied to ≤3% weekend waste target
  • Identify stakeholders and success metrics
  • Confirm scope and timelines for prototype and presentation
Activity 2: Data Inventory & Plan
12 minutes

Plan data sources and file conventions

Details:

  • List dataset columns and cleaning steps (TRIM, Remove Duplicates)
  • Establish file naming convention and folder structure
  • Assign roles for data import and cleaning
Activity 3: Excel Workbook Skeleton
18 minutes

Create tabs and validations for future automation

Details:

  • Tabs: Data, Clean, Charts, Forecast, Dashboard, Audit
  • Add basic validations and error checks placeholders
  • Document assumptions and risks in an Audit/Notes area
Activity 4: Milestone 1 Check & Submit
5 minutes

Quick readiness review and brief submission

Details:

  • Confirm acceptance criteria met (brief + skeleton started)
  • Peer check‑in for clarity and feasibility
  • Upload brief and workbook draft
Required Materials
  • Milestone 1 acceptance checklist
  • Data inventory template
  • Workbook skeleton guide
  • Group dataset links (g1–g6)
Differentiation Strategies

For Struggling Students

  • • Guided Analysis Templates: Step-by-step worksheets for statistical calculations
  • • Simplified Datasets: Smaller, cleaner data samples for initial practice
  • • Visual Learning Supports: Screencasts demonstrating Analysis ToolPak procedures
  • • Peer Mentoring: Partner with students strong in statistical analysis
  • • Alternative Presentations: Poster session format instead of elevator pitch

For Advanced Students

  • • Multiple Regression Models: Explore relationships between multiple variables
  • • Seasonal Trend Analysis: Investigate more complex time-based patterns
  • • Statistical Significance Testing: Apply t-tests and confidence intervals
  • • Advanced Visualization: Create interactive dashboards or animated charts
  • • Consulting Role: Support other teams while completing their own analysis

For English Language Learners

  • • Statistical Vocabulary Support: Bilingual glossary of key terms with examples
  • • Visual Communication Emphasis: Focus on charts and infographics over verbal presentations
  • • Collaborative Team Roles: Pair with native speakers for presentation support
  • • Template-Based Writing: Structured formats for analysis documentation and reflection