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Proactive Analytics

A presentation that covers the science of answering questions before they're asked.
by

Jermaine Wilkins

on 13 March 2013

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Transcript of Proactive Analytics

Mastering the Science of Answering Questions before they're Asked Proactive Analytics vs. Predictive Analytics Proactive Analytics Increases internal efficiencies
Increases Client/customer satisfaction
Greater competitive advantage for organization with sound anticipation ability
leads to a faster, simpler solution
Provides strategic, data driven insight
Resulting in better decision making Proactive Analytics evaluates historical and current state data and provides solutions to potential issues

Predictive Analytics evaluates historical and current state data and provides solutions to identified issues

Organizations that can provide both have a comprehensive approach to analytics

Organizations that provide Proactive Analytics have a competitive Advantage Proactive Analytics:
a more creative approach
approach based on past experience
vast industry experience as well as cross-industry exposure
Understanding of client preferences Provide actionable direction before issues arise and cause harm
The science of anticipation
anticipation based on derivatives of available data
forgoes a reactionary approach for a proactive approach Proactive Analytics Proactive vs. Predictive Predictive Analytics:
Uses information about previous patterns to predict future outcomes
indepth knowledge of a variety of analytic tools Proactive Analytics Risk Management is the practice of proactive analysis
the use of foresight to proactively address risks and opportunities, business enterprises protect and create value for their stakeholders Examples of Proactive Analysis Proactive vs Reactive characteristics Proactive Analysis - Risk Management Deep expertise in proactive modeling when assessing risk
simulation analysis
stochastic optimization (use of random variables in optimization...
decision analysis Predictive Example: PPoM category Apologize/Acknowledge (APAC) has never performed consistently at or above goal since PPoM inception The graph above is an illustration of how incremental Predictive Analysis is used to provide guidance on how to reach goal over time Proactive Example: Category performance is driven by CSR behavior, correct??? (or is it?)
It may be affected by auditor scoring tendencies
it is a concern that has not been poised as a question, yet
Auditor scoring tendencies may be skewing category performance reporting
Addressing the possibility is an example of Proactive Analytics Proactive Example cont: Use of correlation hypothesis testing can be introduced to validate potential performance drivers
We need to identify the existence of auditor tendency and performance reporting correlation...
Measure impact...
drill down, identify auditor(s), identify tendency and frequency
Provide solution sooner than later Summary Analyticis is commonly applied to business data to:
describe performance
Predict performance
Improve performance
Proactive Analytics
uncovers opportunities/issues
is a statistically creative approach to the "what if"
is the science of anticipation Questions
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