Predictive Analytics, Choice Architecture and Bespoke Education
Hub16: Why Bespoke Supply Chain Analytics?
Transcript of Hub16: Why Bespoke Supply Chain Analytics?
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Why BespokeSupply Chain Analytics?
Tom DavisMay 10, 2016
5© 2016 End-to-End Analytics, LLC
Why Bespoke Supply Chain Analytics? Introduction The Supply Chain Analytics Domain A Quick Look: Analytics in Practice Bringing Analytics to the Organization The Anaplan Connection
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5/10/20166© 2016 End-to-End Analytics, LLC
Founded in 2005Based in Palo Alto, CA
40+ professional staff12 Ph.D.’s from top universitiesResources in CA, MI, MA, Peru, Brazil
Over 75 clientsMore than 500 projects to date30+ published articlesMore than 15 patents
End-to-End Analytics: Who Are We?
Company
Team
Work
Specialist consulting firm focused on supply chain analyticsPreviously employed by top companies
Articles published in leading publications
Project work across leaders in many industries
HP Philips
McKinsey & Co. SAS Institute
Procter & Gamble Nestlé
Networking Equipment Food & Beverage CPG Medical & Healthcare
Automotive Semiconductors Cosmetics Internet Search
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Why Bespoke Supply Chain Analytics? Introduction The Supply Chain Analytics Domain
Planning Framework Data & Analysis Framework Roles
A Quick Look: Analytics in Practice Bringing Analytics to the Organization The Anaplan Connection
5/10/2016
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What Does “Analytics” Mean?
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What should we do?What will happen?What happened?
Descriptive
Predictive
Prescriptive
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The Classic S&OP Framework
Demand-Supply Matching
Financial Forecasting
Inventory Targeting
Capacity Planning
Demand Planning
Supply Planning
Production Scheduling
Material Planning
Core of S&OP
Holistic View of S&OP
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Promotion Planning
Planning Solution Architecture
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Data Layer
Analytics Layer
Interaction Layer
Visualization Layer
ERP
EDW
• Disseminating Information• Dashboards / Consensus Meetings• Exception Management
• Data management• Data preparation• Different from a data warehouse
• Making & Capturing Decisions• Data Manipulation (“Pivoting”)
• Calculation engine• Analytics tuning / solution development
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Demand Analysis vs. Demand Planning
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Step Analysis PlanningValidate and Prepare Data
• Access to EDW• Ability to insert and manage new signals
• Automatically loaded into a DP tool• Metrics and charts to validate data
Aggregate and Interpret
• Ad-hoc analysis and reporting for new signals
• Metrics and charts that support aggregation and drill-down
Explore • Sandbox to conduct ad-hoc analysis and reporting for new signals
• Comparison of multiple vetted signals in a single view
• Exception dashboards
Adjust • Adjust the models • Overwrite the default forecast
Define Modeling Strategy
• Sandbox to conduct segmentation strategies • Exception dashboards to determine when to override
Create & Run Forecast Models
• Sandbox to build models on the fly • Exception dashboards to determine when to override
Validate Forecasts • In and out of sample tests • Metrics and charts that support aggregation and drill-down
• Comparison against other signals and the business plan
Publish Results • Methodology for implementation in DP tool • Actual forecast
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Why Bespoke Supply Chain Analytics? Introduction The Supply Chain Analytics Domain A Quick Look: Analytics in Practice Bringing Analytics to the Organization The Anaplan Connection
5/10/2016
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Forecast “Reality Check”
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Past Sales forecasts were too high
Marketing forecast is in line with the statistical range.
Current Sales forecast looks optimistic again.
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Forecast Data Entry
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Forecast Analysis & Entry
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Forecast Entry
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Forecast Analysis & Entry
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Supply Planning Analytics
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Why Bespoke Supply Chain Analytics? Introduction The Supply Chain Analytics Domain A Quick Look: Analytics in Practice Bringing Analytics to the Organization
Visualize the Data Avoid Black Boxes Build Your Own
The Anaplan Connection
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Our Beliefs about Decision SupportVisual, intuitive interfaces are key
Interaction with the math is as important as the math itself Don’t just tell people the answer – show them why it’s the answer
Decision Support is best developed in an iterative manner Decision Support usually needs to be customized to your business Most software development is linear:
requirements – build – test – deploy But building good analytics needs multiple iterations:
mock-up – rapid prototype – try out and learn – revise prototype – repeat
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Avoid “Black Box” Syndrome
Many analytics projects fail because of the “black box” effectGood visualizations are key to helping stakeholders understand the calculations – and therefore buy in to the results
Drill Down
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Change policy and instantly see the impact on inventory and backlog
Building Often Better Than Buying
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Packaged Software
Perception Reality PerceptionReality
Custom Tools Building Your Own Can Improve the Result and Saves Time Solves your problem No unnecessary data gathering No “shoe-horning” problem into
a model that doesn’t fit Almost as fast to build as
configuring a packaged solution Stakeholders understand the
calculations and buy in to the results Result: Better outputs and more
efficient analysis outweigh potentially small increase in build / configure time
Off-the-Shelf Package Myths“One solution can solve every problem.”“With a little training, anybody can use it.”“It saves time.”
Configure Configure
Analyze
AnalyzeAnalyze
Analyze
Build BuildTota
l Effo
rt
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Typical Supply Chain Packages/Modules
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+ Candidate for atailored solution
x Best served“off-the-shelf”
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xxxx
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Why Bespoke Supply Chain Analytics? Introduction The Supply Chain Analytics Domain A Quick Look: Analytics in Practice Bringing Analytics to the Organization The Anaplan Connection
5/10/2016
25© 2016 End-to-End Analytics, LLC 5/10/2016
Smarter Planning for Numbers-Driven Companies
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