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Data Democracy

Dec 06, 2016

Data Democracy

 

The following contain the original notes for my Current Trends in Data Organization presentation.  See the video at:

https://www.youtube.com/watch?v=jwbhXxV_0W4

Introduction

The 2016 presidential election contained intrigue, many insults, and controversy.  The results seemed to surprise all the experts and the Clinton campaign lack words to explain why they lose.  However, the Trump campaign always seemed confident and never seemed to lose its focus.

Why is Donald Trump assembling a Cabinet?
In a word:  Data!

The Republican party invested heavily in database marketing programs which the candidate used to drive voter turnout which elected Donald Trump.

 

The following presentation provides an overview of the current trends in data organization.

 Database Key for Trump Win

The Republican National National Chairman, Reince Prebus, discussed the organization’s investment in data on the MSNBC cable program, Morning Joe, November 8th.

https://www.youtube.com/v/XEoq1fgyJVc?version=3&start=76&end=98&autoplay=1&hl=en_us&rel=0

Database Key for Election Campaigns

The interview went on to discuss how Big-Data played a key role in the wins by Presidential elections.  The Obama for America campaigns utilized numerical scoring to rank voters.  The scoring system was created to gauge how likely a person was to vote and what types of issues would influence their decision.

Some examples for the scoring system ranked what a person reads, buys, where they get their news, etc. Pairing this data with voter registration roles allow the political analyst to show specific ads to individual voters that are tailored to appeal to their views. 

I volunteered for a State-wide campaign and observed this much smaller campaign utilize these same Micro-Targeting techniques.  This innovation appears to become more affordable, with the State-Wide campaigns adopting, which indicates that Big Data may become affordable for small and mid-size businesses.

Big-Data History

Big-Data had its origin in the 1960’s when direct marketing began at a macro level which created a broad distribution of mail designed to driver mass appeal.  Zip Codes and two character state coding system began in 1963 which is a key component required for direct marketing.

Relational Database was developed in the 1970’s, personal computer use expanded in the 1980’s and both of these innovations fueled DataBase Marketing.  Customer Relationship Management  took off in the 1990’s and the 2000’s brought innovations such as iPhones, social media, blogs, wikis, networking .

These events help to create the infrastructure to support Big Data and it is expected that adoption will increase as costs decrease.

Big Data Start

Big Data use cases exist, but how does a company infuse the innovation into the business culture?  The following McKinsey Group paper outlines the initial steps to transform one’s company and use Big Data as an asset.

http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/three-keys-to-building-a-data-driven-strategy

Big Data can add competitive differentiation in an age when technology enables competitors to replicate new products and services.  McKinsey advocates executives to focus on targetted efforts and use the following model as they engage Big Data.

 Keys to building data-driven capabilities:

  1. Choose the right data
    1. Bigger and better data gives the company a broader and granular view of their business environment
    2. Source Data Creative
      1. What decisions could we make if we had all the information we need?
    3. Get the Necessary IT Support
      1. Prioritize Data Requirements
         
  2. Build Predictive Models that Optimize Business Outcomes
    1. Identify the Business Opportunity and determining how the model can improve performance
    2. Hypothesis-led modeling generates faster outcomes
    3. Roots models in practical data relationships that are more broadly understood by managers
       
  3. Transform your Company’s Capabilities
    1. Resolve Mismatches between existing culture & capabilities vs emerging tactics to exploit analytics
    2. Develop business relevant analytics that can be put to use
      1. Complement existing decision-making processes
    3. Develop capabilities to exploit big data
      1. Managers must view it as central to solving problems and identifying opportunities