1. Thinking Dave Davis PMP, PgMP, PBA 2. Icebreaker 3. A Little
About My Career Alliance Data Project Manager Enhanced Mobile
Loyalty Suite Nationwide Insurance Benefits Realization Advisor
Project Manager for Consumer Energy Program Manager for AT&T
eBonding Projects Adjunct Instructor Knowledge Management Advisor
University Academic Advisor 4. And yes.. 5. PMI Talent Triangle(SM)
Hard skills Certification Common Glossary Application of Best
Practices Soft skills Behavior Changes Influence Advisement
Emotional Intelligence Decision Making Acumen Products and Services
Quality Process / Workflow 6. How We Think People Think Its a
question of focus Facts Logic Truth 7. Basic Functions of a Human
Thinking Make sense of the world Analyzing Judging Comparing
Synthesis Feeling Tells us how we are doing Happy Sad Included /
Excluded Stressed / Calm Wanting Drives us to act the way we do The
Rule of Remarkability Goals Purpose Agenda 8. Analytics vs.
Analysis is a multi-dimensional discipline. There is extensive use
of mathematics and statistics, the use of descriptive techniques
and predictive models to gain valuable knowledge from data - data
analysis. The insights from data are used to recommend action or to
guide decision making rooted in business context. Analytics is not
so much concerned with individual analyses or analysis steps, but
with the entire methodology. There is an increasing use of the term
advanced analytics, typically used to describe the technical
aspects of analytics, especially predictive modeling, machine
learning techniques, and neural networks. Analytics 9. Analytics
vs. Analysis is the process of breaking a complex topic or
substance into smaller parts to gain a better understanding of it
Business Analysis is the practice of enabling change in an
organizational context, by defining needs and recommending
solutions that deliver value to stakeholders. Requirements analysis
encompasses those tasks that go into determining the needs or
conditions to meet for a new or altered product, taking account of
the possibly conflicting requirements of the various stakeholders,
such as beneficiaries or users. Traditionally involves creating a
null hypothesis and then validating that with data or test results.
Analysis 10. DIKW Model 11. What are Analytics Discovery and
communication of meaningful patterns in data. analytics relies on
the simultaneous application of statistics, data extraction tools,
and operations research to quantify performance. Analytics often
favors data visualization to communicate insight (knowledge) 12.
Critical Thinking Knowledge Skills To be a professional of any kind
in the next 20 years, or even an enlightened citizen, will require
a complicated set of thinking skills, more than reading and
writing. The world isnt filtered as it once was. Kids are thinking.
What were trying to do is have them do it well.
PeterScharf,Professorof SocialEcology 13. Circumstance 1
Observations You wake up in the morning and the lawn is wet. You do
not have a sprinkling system, hose, or other watering capability.
The street is also wet What can you guess happened last night? 14.
Circumstance 1 Conclusion It rained overnight 15. Circumstance 2
Sara and her Mother drove to the computer store. Sara had her money
she had received for Christmas and the money she had saved. She
waited a long time for this day. Finally, she would be able to look
up all the things she needed for school on a computer and email her
friends. What happened next? 16. Circumstance 2 Conclusion Sara
bought a computer 17. Circumstance 3 If x = 4 And if y = 1 Then
what does 2x + y equal? 18. Circumstance 3 Conclusion 2x + y = 9
2*4+1=9 19. Be Careful The inferential process can be valid even if
the premise is false: Lets use the deduction sited below: There is
no such thing as drought in the West. California is in the West.
California need never make plans to deal with a drought. 20. Be
Careful In the example, though the inferential process itself is
valid, the conclusion is false because the premise, There is no
such thing as drought in the West, is false. A syllogism yields a
false conclusion if either of its propositions is false. A
syllogism like this is particularly insidious because it looks so
very logicalit is, in fact, logical. But whether in error or
malice, if either of the propositions above is wrong, then a policy
decision based upon it (California need never make plans to deal
with a drought) probably would fail to serve the public interest.
21. Six Thinking Hats For Success Green Hat the creative side:
alternatives, out-of- the-box ideas. What additional possibilities
are there? What else can we try? Blue Hat the organizing view:
Manage the thinking process. How should we think about this? Red
Hat The emotional view: feelings, hunches, intuition. Whats your
gut reaction? How do you feel about this? Black Hat The downsides:
caution, difficulties, weaknesses, barriers. Why cant we do this?
What might not work? What are the dangers and risks? White Hat
Facts and figures. What information are available and needed?
Yellow Hat The upsides: benefits, values, positive outcomes. How
can we do this? What are the potential returns? Why is it worth
doing? 22. preconceived judgment or opinion an adverse opinion or
leaning formed without just grounds or before sufficient knowledge
This is a characteristic based on an individual opinions Prejudice
November 2008 David L Davis, PMP 28 23. deviation of the expected
value of a statistical estimate from the quantity it estimates
systematic error introduced into sampling or testing by selecting
or encouraging one outcome or answer over others This is an
individual characteristic based on altering things to determine an
outcome Bias November 2008 David L Davis, PMP 29 24. Major Concepts
Data / Information Context Lake Filter, sort, view Pattern Matching
Guessing Trends Historical (Lagging) Predictive (Leading)
Prescriptive (Multiple Action) 25. Analytics 26. Business
Intelligence Demographics / categories Terms such as profiling,
segmentation, or clustering, and they fall under descriptive
analytics. What is the behavior and who is doing it? 27.
Descriptive Analytics This is all about knowing what is going on,
the more real-time the better. What is the past 30-day response
rate and conversion rate for a specific campaign? How did the
response curve move through time? When is the optimal day part for
email blast or ad broadcast? What is the ROI? What channel and
product offering is the winning combination? This can be in a form
of dashboard reporting or any other conventional reporting, but
many call it simply analytics. 28. Optimization Analytics Requires
a complex type of modeling, where what if type of questions are
answered. What if we spend more money on mass media than on direct
channel? What would be the most optimal combination of marketing
spending that yields maximum return? What would be the ultimate
ROI? This type of question is typically answered by marketing
agencies, and it involves econometrics modeling. This type of
analytics calls for different types of data in comparison to
typical predictive modeling for 1-to-1 marketing, but the whole
process is also called analytics. 29. Predictive Analytics we start
asking questions in future tenses. Who will respond to this
campaign, and for what product and through what channel? What are
the potential values of each customer and prospect? Who will stop
subscription of your service, and when would that be? When it comes
to predictive analytics, we need carefully structured statistical
models, which will return scores that define likelihood of
customers behaving a certain way in the future. In terms of
complexity, this is the most demanding type of analytics, where
trained statisticians work with specifically designed marketing
databases with all kinds of custom variables. 30. Prescriptive
Analytics The emerging technology of prescriptive analytics goes
beyond descriptive and predictive models by recommending one or
more courses of action -- and showing the likely outcome of each
decision. "Prescriptive analytics is a type of predictive
analytics, "It's basically when we need to prescribe an action, so
the business decision-maker can take this information and act.
Prescriptive analytics doesn't predict one possible future, but
rather "multiple futures" based on the decision- maker's actions.
In addition, prescriptive analytics requires a predictive model
with two additional components: actionable data and a feedback
system that tracks the outcome produced by the action taken. "Since
a prescriptive model is able to predict the possible consequences
based on different choice of action, it can also recommend the best
course of action for any pre-specified outcome" 31. Adapting to
what's happening Company Data Recording Data Tactical Analytics
Predictive Analytics Social Media Sentiment Strategic Analytics How
many we sold How many we sold last year How many well sell next
quarter How people feel about them Steve Lucas, SAP's SVP of
database technology Behavior Change based on Analytics 32. Thinking
Can be considered an open-minded process of: discovery and
understanding analysis and application synthesis and evaluation
Grouping Information based on data Extracting Knowledge from
Information Applying wisdom using Knowledge 33. Reasoning The
relationship between thinking and overall human genetics in the
application of reasoning between what is known and what is unknown.
Different types of reasoning: Inductive reasoning Deductive
reasoning Predictive reasoning 34. Human Deficiencies As human
beings we are blessed with the ability to be creative and random in
our ability to determine a root cause analysis. However this
ability also comes with several defects that can hamper good
analysis. Distinguishing between a symptom and a cause Dealing with
our own bias and prejudices as a factor in the root cause analysis,
not the factor. Dealing with the illusions that can be created
between cause and effect Understanding Reasoning Understanding
filters and how they can cloud defining the problem Reducing false
conclusions that were obtained by faulty reasoning. 35. Ursa Major
Great Bear Navigation by Polaris North Credit: Stellarium.org
Credit: Graham Bryant Hampshire Astronomical Group 36. Types of
Thinking Critical thinking is the mental process of objectively
analyzing a situation by gathering information from all possible
sources, and then evaluating both the tangible and intangible
aspects, as well as the implications of any course of action.
Implementation thinking is the ability to organize ideas and plans
in a way that they will be effectively carried out. Conceptual
thinking consists of the ability to find connections or patterns
between abstract ideas and then piece them together to form a
complete picture. Innovative thinking involves generating new ideas
or new ways of approaching things to create possibilities and
opportunities. Intuitive thinking is the ability to take what you
may sense or perceive to be true and, without knowledge or
evidence, appropriately factor it in to the final decision. 37.
Higher Order Thinking System Thinking Higher-order thinking
essentially means thinking that takes place in the higher-levels of
the hierarchy of cognitive processing. Blooms Taxonomy is the most
widely accepted hierarchical arrangement of this sort in education
and it can be viewed as a continuum of thinking skills starting
with knowledge-level thinking and moving eventually to
evaluation-level of thinking. "Size up and define a problem that
isn't neatly packaged. Determine which facts and formulas stored in
memory might be helpful for solving a problem. Recognize when more
information is needed, and where and how to look for it. Carry out
complex analyses or tasks that require planning, management,
monitoring, and adjustment. Exercise judgment in situations where
there aren't clear-cut 'right' and 'wrong' answers, but more and
less useful ways of doing things. Step outside the routine to deal
with an unexpected breakdown or opportunity." Thought "Every day
thinking, like ordinary walking, is a natural performance we all
pick up. But good thinking, like running the 100-yard dash, is a
technical performance. 38. Power of Negative Thinking Bobby Knight
didnt win games as much as he didnt lose them Avoid the mistakes Be
prepared Be thoughtful of what could go wrong 39. Critical thinkers
tend to: 1. Be capable of taking a position or changing a position
as evidence dictates 2. Remain relevant to the point 3. Seek
information as well as precision in information 4. Be open minded
5. Take the entire situation into account 6. Keep the original
problem in mind 7. Search for reasons 8. Deal with the components
of a complex problem in an orderly manner 9. Seek a clear statement
of the problem 10. Look for options 11. Exhibit sensitivity to
others feelings and depth of knowledge 12. Use credible sources 40.
Critical thinkers are intellectually curious 41. Critical thinkers
know how to use anecdotes (stories) effectively 42. A factor not
THE factor Bias Prejudice 43. David L. Davis Speaker, Storyteller,
Santa PMP, PgMP, PMI-PBA, MBA Senior Program Manager Quick
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