The Future of Forecasting Business Forecasting & Analytics Forum San Francisco 1-2 March 2016

1. Topics to Watch

1.1. Big Data

1.1.1. Relevance

1.1.2. Relevance

1.2. Machine Learning - probable future trend

2. Reading List

2.1. "Playing to win"

2.2. Innovating on the Z-axis

2.3. "Measuring the Digital World" by that Gary Angel

2.4. "Analysis without Paralysis"

2.5. "Supply chain: metrics that matter"

2.5.1. Reader

2.6. People to Follow 1

2.6.1. Reader

3. Action Priorities

3.1. Get Finance involved in the S&OP Process

3.2. Matrix of performance competencies to set expectations for analyst skills and abilities. (From "average" to "world class".

3.3. "Waterfall" reports as a standardization technique and benchmarking forecasting expertise

3.4. Capturing structured data from non-traditional/unstructured sources

3.5. "Raise the bar, keep things fresh"

3.6. Building Visualization tools for reviewing/analyzing forecasting drivers

3.7. Implementing a Checklist of Foreccast Tasks

3.7.1. Why

3.7.2. Who

3.7.3. How

3.8. Multidisciplinary Collaboration with other horizontal functions (sales, marketing, operations, planning, etc.)

3.8.1. Diversity of Data Sources, Types and Tools for Analysis

3.9. Rethink and rebuild processes for today's business

3.10. Revisit KPIs - find more "leading" indicators to balance reliance on "lagging" indicators

3.11. Use externally correlative KPIs (ex. GDP leading indicator for sales growth)

3.12. Review Current Strategy Execution against "Closed-Loop" Diagram

4. Trends to Share

4.1. Penetration of Data-Driven Decision-Making into Executive Suite

4.2. Cultural Aspects of Forcasting

4.3. External (as well as internal) Collaboration (Suppliers, customers)

4.4. Migration away from traditional forecasting to collaborative business partner

4.5. Migration to the cloud due to cost savings, scalability and centralization

4.6. Customer-centric techniques are being embedded in forecasting

4.7. Move away from the annual/manual forecast to more continuous, rolling forecasts

4.8. Quality consistency across the enterprise of data integrity and business processes

4.9. Stakeholder-outcome driven KPIs are becoming more important than internal financial ones.