1. Project Overview

2. Project Timeline

Phase Duration Weeks Key Deliverables
Discovery and Planning 2 weeks 1-2 Project charter, detailed requirements document
Data Integration and Modeling 8 weeks 3-10 Integrated data warehouse, data quality report, predictive models, optimization algorithms
Dashboard Development 6 weeks 11-16 Interactive Power BI dashboard
Testing and Refinement 4 weeks 17-20 Test reports, refined models and dashboard
Training and Handover 4 weeks 21-24 Training workshops, user guides, final presentation

3. Detailed Task Breakdown

Phase 1: Discovery and Planning (Weeks 1-2)

  • Conduct kick-off meeting
  • Gather and analyze requirements
  • Develop project charter
  • Create detailed project plan
  • Identify key stakeholders

Phase 2: Data Integration and Modeling (Weeks 3-10)

  • Collect and consolidate data from various sources
  • Implement data quality checks and cleansing procedures
  • Develop machine learning models for demand forecasting
  • Create optimization algorithms for inventory management

Phase 3: Dashboard Development (Weeks 11-16)

  • Design dashboard wireframes
  • Develop interactive Power BI dashboard
  • Incorporate real-time data feeds
  • Integrate predictive insights into the dashboard

Phase 4: Testing and Refinement (Weeks 17-20)

  • Conduct thorough testing of models and dashboard
  • Refine models based on test results
  • Optimize dashboard performance
  • Prepare test reports

Phase 5: Training and Handover (Weeks 21-24)

  • Develop training materials and user guides
  • Conduct workshops for key stakeholders
  • Provide hands-on training sessions
  • Prepare and deliver final presentation

4. Budget Allocation

Total Budget: $450,000

Category Amount Percentage
Professional Services $400,000 88.9%
Software Licenses $30,000 6.7%
Travel and Expenses $20,000 4.4%

Payment Schedule: - 25% upon project initiation: $112,500 - 25% at midpoint (Week 12): $112,500 - 50% upon project completion: $225,000

5. Resource Allocation and Management

Team Members and Roles

  1. Sarah Johnson, Ph.D. - Lead Data Scientist
    • Responsibilities: Overall project leadership, advanced analytics, model development
    • Time Allocation: 100% throughout the project
  2. Michael Chen, M.S. - Supply Chain Analytics Specialist
    • Responsibilities: Supply chain optimization, inventory management algorithms
    • Time Allocation: 100% during Phases 2-4, 50% during Phases 1 and 5
  3. Emily Rodriguez - Data Engineer
    • Responsibilities: Data integration, data quality, ETL processes
    • Time Allocation: 100% during Phases 1-3, 50% during Phases 4-5
  4. David Park - UI/UX Designer
    • Responsibilities: Dashboard design, user experience optimization
    • Time Allocation: 25% during Phase 1, 100% during Phase 3, 50% during Phases 4-5

Resource Management Strategies

  1. Weekly team meetings to ensure alignment and address any issues
  2. Bi-weekly progress reports to track individual and team performance
  3. Use of project management software to track tasks, deadlines, and resource utilization
  4. Regular check-ins with BAC Industries stakeholders to ensure satisfaction and gather feedback
  5. Flexible resource allocation to address any unforeseen challenges or changes in project scope

6. Risk Management

  1. Data Quality Issues
    • Mitigation: Thorough data profiling and cleansing in early stages
  2. Scope Creep
    • Mitigation: Clear definition of project boundaries, change control process
  3. Technology Compatibility
    • Mitigation: Early assessment of BAC’s IT infrastructure, contingency plans for integration challenges
  4. Knowledge Transfer
    • Mitigation: Comprehensive documentation, hands-on training sessions, post-project support plan

By following this project plan, Al Gross Consulting aims to deliver a successful data analytics solution that meets BAC Industries’ objectives for supply chain optimization.