1.
Grow Your Own:
How to Create a Data Culture at Your
Organization
Emperitas Webinar June 14th
2016
www.emperitas.com / 801.810.5869 / 4609 South 2300 East Suite 204, Holladay, UT 84117

2.
Hi, I’m Luciano Wheatley Pesci…
Founder & Director, Utah Community Research Group (UTAHCRG), Univ. of Utah
• Teach microeconomics, statistics, applied research & data analytics, and American
economic development & history.
Co-Founder and CEO, EMPERITAS
• Team of analysts, data scientists, and economists who find actionable business
intelligence through marketing analytics and agile research, to help our clients beat their
competitors for the most profitable customers.
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3.
My Basic Argument Today…
• Entering The Data Age: If you’re not using data daily, then you’re
falling behind - personally and professionally.
• Types of Data Talent: Specialization is necessary, which means you
need to understand the types of talent that can solve your problems.
• Culture & Goals: Cooperation is the cornerstone of specialization,
which requires transparency, accountability and clear responsibilities.
• Think Small, Grow Big: Data doesn’t have to be big to be useful.
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4.
Entering The Data Age

5.
Welcome to the Data Age!
• Era of human evolution where everyone is using massive
amounts of information to inform daily decision-making.
• Personal Life: Fitbit, mobile data, home automation.
• Professional Life: Forecasting sales, validating marketing
effectiveness, identifying profitable customer personas,
building competitive strategies.
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6.
Human + Machine = Success
• The Data Age was made possible through huge advances in
digital technology.
• Human to Human, Machine to Human, and Machine to
Machine communication all captured now.
• Machines need to assist, not replace, humans. Your gut still has
a HUGE role to play.
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7.
Types of Data Talent

8.
Caveat Emptor
• There are no data science unicorns. Data science is
a team effort and requires specialization & cooperation.
• Most data failure is the result of hiring, and
improperly utilizing, the correct type of data talent.
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9.
Different Types of Data Talent
• Data Detectives (Analysts & Researchers)
• Data Guardians (DBAs & ETLs)
• Data Scientists (Statisticians & Programmers)
• Data Translators (Visualizers & Storytellers)
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10.
Culture & Goals

11.
Creating a Team of Superforecasters
• The purpose of using information is to make better
decisions for the future (you can’t change the past,
but you can learn from it).
• Superforecasters – people who can process a lot of
information, are flexible in their beliefs, and perform
exceptionally in teams when taught how to cooperate.
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12.
Cooperative Culture is the Key
• Specialization in data projects requires a well-functioning, highly
coordinated team, that’s involved in creating the strategy and agreeing on
measures of success & failure.
• “Planning is valuable, a plan is useless.” This means flexibility to
pivot the strategy over time is paramount.
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Building Blocks of a Cooperative Culture
• Transparency – Expectations, goals, milestones, and KPIs should be clearly
visible to everyone at all times.
• Roles & Responsibilities – Clear lines of responsibility and freedom to
execute is the only way specialization works.
• Resources & Training – People need (ever-evolving) tools to succeed.
• Accountability – Merit is the ultimate motivator, but that
means balancing reward and punishment equally.
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14.
Think Small, Grow Big

15.
“Small Data” Is Usually Enough
• Data doesn’t have to be “big” to be useful.
• Start small. Begin with qualitative information then
use what you’ve learned to find larger quantitative data.
• You need to be connecting insights across data sources,
regardless of their size.
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16.
Let’s talk…

17.
The Conversation Doesn’t Have to End Here…
luciano@emperitas.com / 801-810-5869/ EmperitasSG / 4609 South 2300 East Suite 204, Holladay, UT 84117