actionable analytics why, how?

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Actionable Analytics: why? how? TIM MENZIES, YE YANG, YOU... [email protected] [email protected] LINCOLN, NEBRASKA, Nov, 2015 http://action15.github.io 1

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Page 1: Actionable analytics  why, how?

Actionable Analytics: why? how?

TIM MENZIES, YE YANG, [email protected]@gmail.com

LINCOLN, NEBRASKA, Nov, 2015http://action15.github.io

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Page 2: Actionable analytics  why, how?

How we got here

2001

● “Stop telling me what is. Tell me what to do.”

● -- Gruff user, NASA, dismissing a decision tree

2007

● Norman Fenton, PROMISE keynote

● “Most metrics irrelevant to the industrial mix.”

2012

● ICSE Goldfish bowl panel on predictive analytics.

● “Enough mere prediction. Give us something we can use.”

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Page 3: Actionable analytics  why, how?

The collapse of prediction?

BEFORE

● Plan-driven process-based estimating approaches

● Requirements => analysis (sizing, effort, schedule) => number (2.71 years)

● E.g. waterfall model, Spiral, RUP, etc.

NOW

● Feature-based development

● Recognition / exploring/ reaction to opportunity

● No longer:

● “We will craft this diamond with these capabilities.”

● Rather:

● “We will explore N possible features, and will deliver M < N”

● “Every feature is an experiment.”

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Page 4: Actionable analytics  why, how?

End of the era of“the” prediction

● Rather:● PredictionS● Plural

● Range of options ● assessed via criteria ● learned interactively with

business users

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Page 5: Actionable analytics  why, how?

Exact predictions are spurious?

● Less numbers, more insight● Burak Turhan’s “The graph”● circle = reported to● red = error report● green = error fix● blue = report+fix in the same team

● More coarse grain control

● (“ontime”, “aLittleLate”, “wayOverdue”)● E.g.. Predicting delays in software projects using

networked classification● Choetkiertikul et al. ASE’15 (Thurs morning)

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“What’s that?”(anomaly detection)

● E,g, Keogh’s SAXrepresentation

● Monitors (e.g.) thousands of on-board rocket sensors

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“What if”:e.g. Bayes nets

● All links bi-directional

● Tickle anything to see impact on anything else

● E.g. Fenton et al., TSE, 2000, Misirli et al, TSE 2014

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Page 10: Actionable analytics  why, how?

“What if”e.g. Pareto clustering

● Range of options

● assessed via criteria

● learned interactively with business users

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“What to do” (e.g. contrast set learning)

● Not predictors for separate classes

● But deltas between classes (much shorter)

● Minwal, STUCCO, TAR2, TAR3

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