high-impact analytics for mortals
TRANSCRIPT
The steps you need to follow for analytics success
2- Step-by-Step
Some special methods for maximizing results
3. Tips & Tricks
The ROI of Analytics.
1- ROI
Time for questions from the audience.
5. Questions
A collection of free resources for High-Impact Analytics for
Mortals!.
4. Free Resources
AGENDA
WHERE HAVE THESE TIPS WORKED?Past clients and employers
IMPORTANT: All views expressed are solely my own, and should not be taken as being those of current or past employers, clients or others.
TIPS SOURCESWhere do the recommendations originate?
197 Kaggle Winner
Interviews
How did they win?
50 In-depth Case
Studies
Which factors mattered
25,000 Head-to-Head
Tests
What made the difference?
TWO PURPOSES FOR ANALYTICSIf your analytics don’t meet one or both, you’re doing analytics wrong.
ANSWERS, “SO WHAT?”
Why are your analytics important?
BOOSTS ROI…
…or whatever your key object might be.
SOURCE: Nucleus Research, 2014http://nucleusresearch.com/research/single/analytics-pays-back-13-01-for-every-dollar-spent/
HIGH-IMPACT ANALYTICS: The Hard ROI NumbersDoes this sound familiar to anyone?
SOURCE: Nucleus Research, 2014http://nucleusresearch.com/research/single/analytics-pays-back-13-01-for-every-dollar-spent/
HIGH-IMPACT ANALYTICS: The ResearchSource and Methodology
HIGH-IMPACT ANALYTICS: Stage 1 ROIStage 1: Automating Reports (ROI of 188%)
188%
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
200%
Stage 1- Automating Reports
Analytics ROI by Stage
SOURCE: Nucleus Research, 2012http://nucleusresearch.com/press/roi-of-business-analytics-increases-significantly-as-solution-matures/
HIGH-IMPACT ANALYTICS: Stage 2 ROIStage 2: Improve Decision-Making (ROI of 389%)
188%
389%
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
Stage 1- Automating Reports Stage 2- Improve Decision Making
Analytics ROI by Stage
SOURCE: Nucleus Research, 2012http://nucleusresearch.com/press/roi-of-business-analytics-increases-significantly-as-solution-matures/
HIGH-IMPACT ANALYTICS: Stage 3 ROIStage 3: Strategic Analytics (ROI of 968%)
188%
389%
968%
0%
200%
400%
600%
800%
1000%
1200%
Stage 1- AutomatingReports
Stage 2- Improve DecisionMaking
Stage 3- Strategic Analytics
Analytics ROI by Stage
SOURCE: Nucleus Research, 2012http://nucleusresearch.com/press/roi-of-business-analytics-increases-significantly-as-solution-matures/
HIGH-IMPACT ANALYTICS: Stage 4 ROIStage 4: Extended to Partners and Social Media (ROI of 1209%)
188%
389%
968%
1209%
0%
200%
400%
600%
800%
1000%
1200%
1400%
Stage 1- AutomatingReports
Stage 2- ImproveDecision Making
Stage 3- StrategicAnalytics
Stage 4- Partners &Social Media
Analytics ROI by Stage
SOURCE: Nucleus Research, 2012http://nucleusresearch.com/press/roi-of-business-analytics-increases-significantly-as-solution-matures/
SOURCE: Barn Raisers, 2015http://barnraisersllc.com/2015/11/16-case-studies-companies-proving-roi-of-big-data/
HIGH-IMPACT ANALYTICS: The Bad NewsA full one-third of companies are losing money on Big Data initiatives
WHAT DRIVES THE ROI DIFFERENCES?
• Senior executive project champion• Low-hanging fruit• Clear, defined outcomes• “Phased-Gate” approach to investments:
focus on “Do what you can, with what you have, where you are right now.” (Quote: Theodore Roosevelt)
POSITIVE ROISuccess Factors
• Large initial capital investments• No clear financial targets• “Swing for the fences”• Complex initial projects
NEGATIVE ROIFailure Factors
Create a list of potential projects and targets. Brainstorm with decision-makers to get initial buy-in.
STEP 1. Pick targets.
Check to see which targets have:• Either/ or outcomes• Reliable, detailed data• Significant potential organizational
impact
STEP 2. Evaluate targets.
Use data preparation process to identify both a clear outcome and potential inputs. This is often the key to success or failure!
STEP 3. Wrangle the data.
Be ruthless in determining what makes sense and what will have impact.
STEP 5. Evaluate results.
Here’s where the power of analytics can have the most impact- use pivot tables and/ or predictive models.
STEP 4. Pivot and/ or model.
STEP-BY-STEP: The “No-Fail” ChecklistFeatures
• Rationale:
• Expands list of available algorithms
• Reduces complexity
• Reduces error
• Increases interpretability
• Methodology:
• Presence of condition being studied (fraud, response, attrition) caries value of 1, others carry 0
• Convert continuous dependent variables into thresholds/ bins/ buckets
• If dependent variable is missing, remove the record
TIP: Convert Problem to Either/ Or Outcome
• Rationale:
• Algorithms are “stupid and greedy”
• They need to focus on what you don’t already know, or you don’t need an algorithm
• If you don’t account for this step, you will never find the really “interesting” patterns.
• Methodology:
• ALWAYS run EDA (Exploratory Data Analysis first.
• Remove cases where you “know” the outcomes with a reasonable certainty.
TIP: Follow The Painfully Obvious Theorem
• Rationale:
• Models work best identifying coherent patterns leading to a single outcome.
• If widely different patterns lead to the same outcome, you can “confuse” the model.
• Separating the use cases solve this issue.
• Methodology:
• Run a tree-based classifier when beginning a project.
• If your tree uses completely different variable classes after the first splitter, consider creating multiple models.
TIP: Confirm The Number of Problems You’re Solving
• Rationale:
• Models are useless if you can’t apply them.
• Don’t engage in a modeling strategy that uses data, processes or target variables that will prevent you from using what you learned.
• It is much easier to fix this on the front end.
• Methodology:
• Get an understanding of how you want to use your model first.
• Work backward from those constraints to create your modeling strategy.
• Hold planning meetings with stakeholders BEFORE modeling.
TIP: Begin With The End In Mind
• Rationale:
• Complex systems have many more mail fail points than simple ones.
• If you don’t understand it when it works, how will you fix it when it breaks?
• Methodology:
• Get an understanding of how you want to use your model first.
• Work backward from those constraints to create your modeling strategy.
• Hold planning meetings with stakeholders BEFORE modeling.
TIP: Aim for Simplicity
Moving Away From… Moving Toward…
TIP: Think “Crafts-person-ship”Less “Assembly Line,” More “Fine Craftsmanship”
FREE RESOURCES:100 Free Data Science BooksAn entire resource library at no cost
SOURCE: LearnDataSci, 2015http://www.learndatasci.com/free-data-science-books/
FREE RESOURCES: 88 Data Science Resources PDFPDF of other free resources
SOURCE: Elite Data Sciencehttps://elitedatascience.com/wp-content/uploads/2016/11/Supercharge-Your-Data-Science-Career-1.pdf
FREE RESOURCES: Best BlogAn entire resource library at no cost
SOURCE: Analytics Vidhyahttps://www.analyticsvidhya.com/
FREE RESOURCES: Best Free Software StartIBM Watson Analytics
SOURCE: IBM Watson Analytics, 2017https://www-01.ibm.com/marketing/iwm/dre/signup
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