1. The Forecaster’s Imperative | September 19, 2018
Forecasting and Credibility
The Forecaster’s Imperative | September 19, 2018

2. What is the most important feature of a forecast?

3. The Imperative and it’s Challenges
The Imperative is Credibility
The Cassandra Curse
The Dialectic of Credibility and Correctness
The Paradox of Evidence and Informativeness
Argumentum ad Verecundiam
Foxes and Hedgehogs
The Asymmetry of Trust and Distrust
Cognitive Biases

4. Substantiation Authority Source Dynamism Trustworthiness Record
CREDIBILITY S.T.A.R.S.
Substantiation
Justification, evidence, explanation
Authority
Experience, credentials, knowledgeability, mastery
Source Dynamism
Confident performance,
business athlete
Trustworthiness
Integrity, ethics, reliability, goodwill
Record
Performance, accuracy, correctness, track record 5

5. L.I.F.E. LAUNCH INTELLIGENT FORECAST ENGINE EMBRACING THE SCIENCE
AND THE ART OF PREDICTION

6. Intelligence Action Data LAUNCH INTELLIGENT FORECAST ENGINE
I have years of historical data, but no easy way to integrate it into my forecast
Action
I want to complete my forecasting cycle with an accurate baseline number and track the assumptions that were made
Intelligence
I want to learn from my data and become an empowered forecaster
Distinct historic
data patterns
ingested
Hidden insights
uncovered
Models tested
against real data
Outputs modified
by your
experience
Assumptions
tracked
Scenario Planning
Growth &
revenue
potential
Forecasting with the best of human and machine
Trends
quickly surfaced
Robust evaluation
The Launch Intelligent Forecast Engine improves business forecasts through the integration of machine modelling with human judgment into a structured process of prediction, assessment, and feedback. 6

7. L.I.F.E. SUBSTANTIATION
Analyze historical trend and seasonal patterns, test different forecast models, and apply intelligent model selection 7

8. L.I.F.E. TRUSTWORTHINESS
Launch’s people driven commitment to integrity, transparency, and goodwill

9. Jared “Professor Madness” Endicott
L.I.F.E. AUTHORITY
Jared “Professor Madness” Endicott
Principal Data Scientist
Advanced Analytics Manager
AI/ML Solution Architect
Launch Consulting
12+ years building predictive models
Certified Professional in Demand Forecasting
Member of the International Institute of Forecasters
Published case study in Hans Levenbach’s “Change & Chance Embraced”
Change & Chance Embraced
CASE STUDY: A PEER Demand Forecasting Process for Turkey Dinner Cost (Prepared by Jared Endicott following his participation in a CPDF Workshop in Istanbul.) 9

10. L.I.F.E. RECORD
Blend measures of precision and bias, and benchmark forecasts against alternatives to achieve optimized outcomes 10

11. Have the confidence to own your performance
L.I.F.E. SOURCE DYNAMISM
Have the confidence to own your performance

12. Energy Demand Forecasts
L.I.F.E. USE CASES
Energy Demand Forecasts
Data Source: Energy Information Administration (EIA)
Business Problem: Forecasts of energy utilization can vary significantly from month to month, year over year, and across locations and sectors. Inaccurate demand forecasts cause inefficient planning.
Solution: Automated monthly predictions of the retail sales of electricity, which capture seasonality and trend for each combination of location and sector.
Business Value: Increased the precision of 78% of 284 distinct forecasts, for an average improvement of 15%. Increased the credibility and thus the utility of forecasts. Better planning drove greater energy efficiency. 12

13. Potential Energy Forecast electricity production and load
DATA SCIENCE USE CASES
Potential Energy
Forecast electricity production and load
Forecast financials, sales and revenue
Root-cause analysis
Social listening and micro-targeting
NLP and sentiment analysis
Customer segmentation
Scenarios and simulations
Data integration and cleaning 13

14. THANK YOU

15. Jared Endicott Principal Data Scientist AI/ML Solution Architect
Advanced Analytics Manager 15