1. Modern Data Strategy
By Dan
5 Design Factors
Daniel Sexton, Red Chip Ventures© 2017

2. Audience
2
Ideas
For
Data
Strategy
Non-technical executives, tech-savvy managers
and technical people who want fresh ideas and
perspectives on modern enterprise data strategy
and design.
Daniel Sexton, Red Chip Ventures© 2017

3. Abstract
3
Ideas
For
Data
Strategy
Abstract: As infrastructure and services rapidly
commoditize, IT is being asked to assume a more
strategic and proactive role in most large businesses.
This document introduces a set of concepts and tools
that may be helpful in integrating and aligning a data
strategy with the overall enterprise.
Five key factors that have proven relevant to the survival
of firms and strategies are introduced along with five
practical tools that can be used to consider integrative
strategies from a robust set of perspectives.
Daniel Sexton, Red Chip Ventures© 2017

4. Modern Data Strategy
Table of Contents
Laying The Foundation
1. Revisiting The Basics
2. AWS Basics
3. Design Snapshot in AWS
5 Factors in Data Strategy
1. Movement
2. Uncertainty
3. Defensibility
4. Responsiveness
5. Alignment
4
5 practical tools
to prepare for
the rise of the machines
Daniel Sexton, Red Chip Ventures© 2017

5. Revisit The
Basics Often
Data Strategy: A plan
designed to improve all of
the ways data is acquired,
stored, managed, shared
and used.
▪ What is truly valued at the organization?
▪ What does the competitive landscape look
like?
▪ What does the company do well?
▪ What are the strategic opportunities for
growth?
5
https://hbr.org/2015/03/why-strategy-execution-unravelsand-what-to-do-about-it
https://hbr.org/2015/01/we-still-dont-know-the-difference-between-change-and-transformation
http://dataconomy.com/2014/11/why-organizations-need-a-data-strategy/
https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/5-essential-components-of-data-strategy-108109.pdf
Daniel Sexton, Red Chip Ventures© 2017

6. Why revisit the
“obvious” basics
often?
New brain research
indicates that there are two
distinct modes of thinking--
focused and diffuse.
The transition between
modes is the key to
creativity and productivity.
1. Brain Science:
Breakthrough ideas are more
likely to come during casual
reflection after new
technologies and information
have been absorbed.
6
Source Prof Barbara Oakley :http://tdlc.ucsd.edu/educators/educators_webinar_oakley_031213.html
NIH Study: https://www.ncbi.nlm.nih.gov/pubmed/24904169
The Innovator’s Mindset: http://georgecouros.ca/blog/archives/5715
Science of Creativity: https://blogs.scientificamerican.com/beautiful-minds/the-real-neuroscience-of-creativity/
Focused Diffuse
Prefrontal cortex, concentrated Diffused, dispersed
Writing code, spreadsheets Big picture, mind wanders
Deadlines, functionality,
complexity
Revisit basics, reflection,
simple solutions, more with less
Daniel Sexton, Red Chip Ventures© 2017

7. Why revisit the
“obvious”
basics often?
According to research, it is
not possible to be in both
thought modes at the
same time.
Planning activities that
encourage relevant modes
of thinking at different
stages may lead to more a
effective dynamic.
7
Implementation & Execution: https://hbr.org/2015/03/defining-strategy-implementation-and-execution
5 Pillars of Strategy: https://www.cebglobal.com/blogs/the-five-pillars-of-strategy-execution/
Strategy
Analysis
Strategy
Formation
Strategy
Execution
Measure & Observe
Results
Daniel Sexton, Red Chip Ventures© 2017
No plan
survives this
More
Diffuse
Thought
More
Focused
Thought

8. Why revisit the
“obvious”
basics often?
Modern strategies
are integrative
2. Collaboration helps strategy
8
70% fail: https://www.forbes.com/sites/insead/2016/01/08/five-reasons-most-companies-fail-at-strategy-execution/#e0ef3c33480a
Strategy Execution: https://hbr.org/2015/03/why-strategy-execution-unravelsand-what-to-do-about-it
4A Model: https://ideas.darden.virginia.edu/2015/09/beyond-strategy-three-lessons-and-four-ingredients-of-execution/
According to research, at least 70% of
corporate strategies fail. Strategy execution
often breaks down across departments.
Revisiting basics provides a common
ground that people with diverse
backgrounds can understand and contribute
to.
This can facilitate communication,
teamwork, and a collaborative culture which
can improve strategic analysis, formation
and execution.
Strategy
Analysis
Strategy
Formation
Strategy
Execution
Daniel Sexton, Red Chip Ventures© 2017

9. Why revisit the
“obvious” basics
often?
3. Discretion is key
▪ Change often happens faster than execution
▪ > 60% of IT projects fail
9
Source: https://www.linkedin.com/pulse/why-45-all-software-features-production-never-used-david-rice
50% fail: http://www.cio.com/article/3068502/project-management/more-than-half-of-it-projects-still-failing.html
Daniel Sexton, Red Chip Ventures© 2017

10. Industry
Trends
10
MicroservicesMonolith
CloudOn-Premises
Daniel Sexton, Red Chip Ventures© 2017

11. Industry
Trends
11
Microservices
Cloud
Daniel Sexton, Red Chip Ventures© 2017
?
?

12. Industry
Trends
Getting too far
ahead…
12
?
?
Daniel Sexton, Red Chip Ventures© 2017
???
???

13. Monolith to
Microservices
Cloud platforms
encourage
modern design
such as
microservices.
i.e. AWS Lambda
coerces serverless,
microservices
13
Monolith Microservices
Scaling
Vertical
Harder
Expensive
Horizontal
Simpler
Cheaper
Release Cycles
2-6 weeks,
Error-prone
1-7 days
Decoupled
Deployment
Model
Simple, Unified Discrete
Design
Contracts
Refactoring Large Codesets Strong Module Boundaries
Degradation
Binary Failure
100% Limits- CPU, Memory,
Disk
Graceful
AWS Lambda, S3
Adapting
Technologies
Technology Monoculture Technology Diversity
Teams
Larger, Diffuse Responsibility
- UI Team
- App Logic Team
- DBA Team
Smaller, More Vertical
- Accounts Team
- Personalization Team
- Mobile Team
Strangling the Monolith: https://developer.ibm.com/tv/microservices-tv-episode-16-strangling-monolith/
Monolith to Microservices: https://www.nginx.com/blog/refactoring-a-monolith-into-microservices/
Microservices: http://microservices.io/patterns/microservices.html
https://www.youtube.com/watch?v=oRIYtOsAlzk - Monolith to Microservices, AWS Daniel Sexton, Red Chip Ventures© 2017

14. Modern Data
Design
Overview
Some
Key
Activities
14
Source
Data
Analytics &
ETL
Data
Ingestion
Business
Intelligence
Analytics
Data
Onsite
Data
Metadata &
Delta
Capture
Service
Discovery
Lifecycle
Management
Data Governance
Daniel Sexton, Red Chip Ventures© 2017

15. Modern Data
Design using
AWS
Current
Snapshot
See Index
15Daniel Sexton, Red Chip Ventures© 2017

16. 5 Factors in a
Modern
Data
Strategy
the machines are coming
16
Movement Defensibility
Uncertainty
Alignment
Agility
Daniel Sexton, Red Chip Ventures© 2017

17. Factor 1
Movement
17
Movement
Movement is the changing of
technology, its place in the
business cycle, and its use
and adoption. The best
strategies and designs
anticipate movement.
● Commoditization
● Convergence
● Technology Adoption
Daniel Sexton, Red Chip Ventures© 2017

18. Commoditization
is the process by which
technologies that are at
first innovations-- scarce,
expensive and
distinguishable -- become
commodities-- ubiquitous,
inexpensive, homogenous,
interchangeable.
This curve depicts the path
that all business activities
follow from inception to
commodity.
18
Movement
As value chain components move
up commoditization curve, the
associated project loses strategic
value.
Innovation
Commodity
Inputs
Highly
Differentiated
Products
Strategic
Advantages
Less
Differentiated
Products
Services,
Commodities
Buy,
Outsource,
Cheap
Build,
Assemble,
Higher Costs
Prevalence
Maturity
Moore’s Chasm
Daniel Sexton, Red Chip Ventures© 2017
Agile
Six Sigma
Geoffrey A. Moore, Crossing the chasm (Chichester: Capstone, 1998).
Rogers, Everett M. Diffusion of innovations. New York: Free Press, 2005.

19. The Value Chain
is the set of inputs or
components that are
used to deliver a
product or service.
Each of these components
exists somewhere along
its lifecycle on this curve.
Where these components
are on their lifecycle is
critical to overall strategy,
design, marketing and
other activities.
19
Movement
Example Project Value Chain
Prevalence
Maturity
Daniel Sexton, Red Chip Ventures© 2017
Predictive Analytics
Salesforce
Search,
Solr
IoT
Commodity
Inputs
Strategic
Advantages

20. Value Chain
12-18 months later
20
Movement
Competition increases as it
becomes cheaper and easier
to enter market
Prevalence
Maturity
Daniel Sexton, Red Chip Ventures© 2017
Predictive Analytics
Salesforce
Search,
Solr
IoT
Buy?
Build

21. Value Chain
Costs
21
Prevalence
Maturity
Daniel Sexton, Red Chip Ventures© 2017
Difficultly/Cost
Maturity
$1000
$10
$0.10
$1
Build
Buy
$100
Services, Commodities

22. Value Chain
Costs
22Daniel Sexton, Red Chip Ventures© 2017
Custom-built provides
competitive advantage
Costs justify the
results?
Products
cheaper/better than
building

23. Value Chain
Costs
Example: Big data
strategy moves into
ancillary components.
23Daniel Sexton, Red Chip Ventures© 2017
Hadoop ecosystem,
2005
Hadoop ecosystem,
2012
Hadoop ecosystem,
2020
BI driven by business
more than IT

24. Convergence
is the tendency for
different technological
systems to evolve
toward performing
similar tasks.
This appears to happen
when new technological
value chains emerge to
address customer needs
at a viable value
proposition level.
24
Movement
As technologies change,
different systems may
converge towards solving
similar tasks.
Daniel Sexton, Red Chip Ventures© 2017

25. 25
Movement
Daniel Sexton, Red Chip Ventures© 2017
Technology
Adoption
refers to the adoption of
a new technology
according to the
demographic and
psychological
characteristics of
defined adopter groups.
Technology Adoption Lifecycle
Geoffrey A. Moore, Crossing the chasm (Chichester: Capstone, 1998).
Rogers, Everett M. Diffusion of innovations. New York: Free Press, 2005.

26. 26
Movement
Daniel Sexton, Red Chip Ventures© 2017
Technology
Adoption
Custom-built IT projects
and their value chains
also have adoption
lifecycles. Where are
your projects on the
lifecycle? What type of
consumer are you?
Moore’s Chasm refers to
the marketing problem
of driving adoption
across populations
(mostly) with tech
startups.
Technology Adoption Lifecycle
Pace of Adoption: https://hbr.org/2013/11/the-pace-of-technology-adoption-is-speeding-up
IoT
Predictive
Analytics
Solr Salesforce

27. Factor 2
Uncertainty
Strategy, design
and organizational
structure should
handle several
possible future
scenarios.
27
Uncertainty
Trends and movement, such as commoditization,
are somewhat predictable. Other factors are not.
Technology solutions are
vulnerable to uncertain
future scenarios.
Daniel Sexton, Red Chip Ventures© 2017

28. 28
Company-Level Examples
Daniel Sexton, Red Chip Ventures© 2017

29. Factor 3
Defensibility
Being big doesn’t
work anymore
29
Defensibility
Democratization of technology is
moving defensibility for large
enterprises away from
engineering costs into other areas.
Threat of substitutes and new
entrants is high as value chains
commoditize.
Data is the asset. The data itself
should be defensible.
Democratization: Amazon Data Center
Daniel Sexton, Red Chip Ventures© 2017
Defensibility: https://techcrunch.com/2016/09/15/defensibility-creates-the-most-value-for-founders/
Design, Technology and Design: https://www.bipsync.com/blog/three-moats-defensible-scalable-internet-startup/

30. Strategic
Data Matrix
30Daniel Sexton, Red Chip Ventures© 2017

31. 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.
31
Robustness to
Strategic
Possibilities
The 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

32. Factor 4
Agility
32
Agility is the ability to adapt quickly and effectively to:
● Markets
● Competitors
● Threats, including security threats
● Technology Movement
Agility
Daniel Sexton, Red Chip Ventures© 2017

33. Factor 4
Agility
Market favors
those who
execute quickly.
33
Agile software development is an
important part of overall agility.
Agility
Daniel Sexton, Red Chip Ventures© 2017

34. Factor 5
Alignment
the machines are coming
34
Alignment
Daniel Sexton, Red Chip Ventures© 2017

35. Factor 5
Alignment
35Daniel Sexton, Red Chip Ventures© 2017
Time
New studies
say time is
a factor
Traditional
Alignment
Factors
McKinsey
7S
Strategy
Structure
Systems
Skills
Style
Staff
Shared
Values
Internal
&
External
Mini-
Innovation

36. Timelines can
be misaligned
McKinsey
Three
Horizons
Moore’s
Zone To Win
36Daniel Sexton, Red Chip Ventures© 2017
Time
Horizon 1 - 0-12 Months
Horizon 2- 12-36
Months
Horizon 3- 36-72
Months
Three Horizons:
http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/enduring-ideas-the-three-horizons-of-growt
h
Moore. 2015. "Zone To Win: Organizing To Compete In The Age Of Disruption". Slideshare.Net. Accessed June 29 2017.
https://www.slideshare.net/rstrad1/zone-to-win-organizing-to-compete-in-the-age-of-disruption.
Many companies struggle taking
Horizon 2 projects to market.
TotalReturns
Time
A common misconception is that
companies fail because they fail to
innovate.
If all of a company’s effort and
resources are tied up in
operations, disruptions will
eventually put it out of business.

37. Thanks!
Hope you found this SlideShare helpful in
generating ideas for your own Data Design!
Please send helpful comments and suggestions
to
Thanks! Dan