data strategy - strategic data matrices

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STRATEGIC DATA MATRICES redchipventures.com 1 Daniel Sexton, Red Chip Ventures© 2017

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Page 1: Data Strategy - Strategic Data Matrices

STRATEGIC DATA MATRICES

redchipventures.com

1Daniel Sexton, Red Chip Ventures© 2017

Page 2: Data Strategy - Strategic Data Matrices

Strategic Data MatricesThis presentation provides an overview of a new way of measuring corporate defensibility-- strategic data matrices.

I hope you find this information useful!

If you have any comments, suggestions or improvements, please email me:

Thanks!Dan

Page 3: Data Strategy - Strategic Data Matrices

Is your company finding it harder to compete on cost?

Of course it is! (unless you work for Amazon or Apple). Here’s why: Globalization is nearly complete.

In 1975, 600mm people participated in the global economy which was 14.6% of the world’s population.

Today 6.4 billion people or 84% of the current world’s population participate. New market opportunities, cost advantages, and impenetrable brands are slim pickings.

Page 4: Data Strategy - Strategic Data Matrices

Data is the new defensibility.

As generic data itself commoditizes, strategic value will be found in data that fits these three criteria:

1. Defensible: it’s hard for your competitors to get their hands on this data

2. Experimental: Can be used by data scientists to run (real) experiments– marketing, strategy, operations, etc

3. Strategic: The data aligns with the strategy of the company– values, opportunities, and capabilities

Page 5: Data Strategy - Strategic Data Matrices

Strategic Data Matrices

3 Axes

Defensibility of Data

It should be difficult or impossible for others to recreate the content and capabilities of strategic data.

The data itself should be defensible.

Fitness To Modeling

The data and design should allow for data scientists and statisticians to test valid hypotheses.

Hypotheses tested against defensible data can provide strategic advantages.

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Robustness to Strategic PossibilitiesThe data and design should be robust to an organization’s strategy and possible future scenarios. Hypothesis testing should align with strategy.

Data & design should allow a wide range of viable options to be tested and explored.

Daniel Sexton, Red Chip Ventures© 2017

Page 6: Data Strategy - Strategic Data Matrices

Strategic Data Matrix

6Daniel Sexton, Red Chip Ventures© 2017

Page 7: Data Strategy - Strategic Data Matrices

Data For Growth

Defensible data can provide a strategic advantage.

Strategic data provides an advantage for growth -- scaling, acquisitions, entering new markets, and innovation.

7Daniel Sexton, Red Chip Ventures© 2017

Page 8: Data Strategy - Strategic Data Matrices

Strategic data focuses in two primary areas

Current Technologies

Designing defensible data using current technologies with respect to future use.

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Future Technologies

Designing for defensible data in the future with future technologies with respect to future use

Daniel Sexton, Red Chip Ventures© 2017

Page 9: Data Strategy - Strategic Data Matrices

What types of data will be collected?

What types of data should be collected to prepare for the future?

9Daniel Sexton, Red Chip Ventures© 2017

Page 10: Data Strategy - Strategic Data Matrices

Defensibility of Data

Examples

source: redchipventures.com

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Poor Defensibility Strong Defensibility

Brand and market data is undifferentiated

Generic Clickstream Data

Marketing Surveys

Product marketing data tied to market

Data tied to brand or company is differentiated from market data

Clickstream Data Tied to A/B Marketing Tests

Neuromarketing test results

Trust-oriented marketing data tied to brand

Data source is unique to company

Daniel Sexton, Red Chip Ventures© 2017

Page 11: Data Strategy - Strategic Data Matrices

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Examples

source: redchipventures.com

Defensible Data

eBayAmazonAirbnbFacebookLinkedInShutterstockNetflixYelp

Position & Design

GrouponZyngaSocial Living

Source: https://www.bipsync.com/blog/three-moats-defensible-scalable-internet-startup/

Daniel Sexton, Red Chip Ventures© 2017

Page 12: Data Strategy - Strategic Data Matrices

Fitness to Experimental Modeling

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Bad Data Science Situation Ideal Data Science Situation

Weak or no hypothesis

Same data to form hypothesis is used to interrogate hypothesis

Clearly Defined Data Hypothesis specified a priori

Access to rich and varied data sets in various phases of design

Limited access to Experimental Design

Retrospective data or only observational data (not random)

Population is wrong

Sparse or proxy data

Control of Experimental Design

Data is robust, complete. A/B Testing, Randomization, Stratification

Can interrogate Hypothesis Clean Data.

Random Sample Data

Fragile Conclusions Unclear Decisions Opaque Knowledge

Clear Conclusions Decision is Obvious Parsimonious Knowledge

source: Brian Caffo, PhD, Professor, John’s Hopkins University Daniel Sexton, Red Chip Ventures© 2017

Page 13: Data Strategy - Strategic Data Matrices

DataDefensibility

X Experimental

Modeling

13Daniel Sexton, Red Chip Ventures© 2017

Page 14: Data Strategy - Strategic Data Matrices

Send improvements and suggestions to

Thanks! Dan