The document outlines a seven step method for applying big data patterns to decision making: 1) Understand existing data assets, 2) Explore the data to find patterns, 3) Design new decisions or business models based on patterns, 4) Design a data-driven business model if useful, 5) Transform business processes to leverage new insights, 6) Consider governance and security implications, and 7) Develop metrics and incentives to encourage fact-based decision making. The method involves building on each step with the goal of better decisions, new business models, or optimized processes.

1. FOR APPLYING
BIG DATA PATTERNS
TO DECISION MAKING
STEPSFOR APPLYING
BIG DATA PATTERNS
TO DECISION MAKING
STEPS

2. The method for applying
big data patterns to decision-
making consists of seven steps,
each step building on the
one before.

3. Depending on your end goal,
you may need to spend more
time and energy on some
of the steps than others,
but it is important to consider
each step in turn.

4. UNDERSTAND
DATA
ASSETS

5. Locate, catalog, and assess the
potential of all relevant data
assets. These assets could be
inside or outside the
organization.
1. UNDERSTAND DATA ASSETS

6. EXPLORE
THE DATA

7. 2. EXPLORE THE DATA
Explore the data assets
discovered in Step 1,
applying a rigorous
methodology of searching
for statistical significance.

8. DESIGN
THE FUTURE

9. 3. DESIGN THE FUTURE
Use the implications of the
data exploration to either make
better decisions, design a new
business model, or redesign
current business processes.

10. DESIGN A
DATA-DRIVEN
BUSINESS
MODEL

11. If appropriate, design a business
model to take advantage of the
new data discovery.
4. DESIGN A DATA-DRIVEN
BUSINESS MODEL

12. TRANSFORM
BUSINESS
PROCESSES
FOR THE
DATA ERA

13. If appropriate,
redesign existing
business processes
to capitalize on the
new insights from
Steps 1 and 2.
5. TRANSFORM BUSINESS PROCESSES
FOR THE DATA ERA

14. DESIGN FOR
GOVERNANCE
AND
SECURITY

15. 6. DESIGN FOR GOVERNANCE
AND SECURITY
Understand the impact
of leveraging new
insights and data
assets, comprehending
the implications of
privacy and data usage.

16. SHARE
METRICS AND
INCENTIVES

17. 7. SHARE METRICS AND INCENTIVES
Develop a system to ensure that
appropriate key performance
indicators are measured and
that stakeholders continue to
leverage fact-based decision-
making or utilize new findings.

18. For more on
identifying patterns
in data and applying
patterns to decision
making, check out
BIG DATA
REVOLUTION
ROB THOMAS & PATRICK MCSHARRY