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Adapt, Adopt and Thrive
MIKE PALLADINO, PMP, CSM
- PAST PRESIDENT & EXECUTIVE VP, PMI-DVC CHAPTER
- ADJUNCT PROFESSOR, VILLANOVA UNIVERSITY
- HEAD, AGILE CENTER OF EXCELLENCE, BRISTOL-MYERS SQUIB
- AUTHOR, DATA MANAGEMENT UNIVERSITY
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Adapt, Adopt and Thrive
MIKE PALLADINO, PMP, CSM
- PAST PRESIDENT & EXECUTIVE VP, PMI-DVC CHAPTER
- ADJUNCT PROFESSOR, VILLANOVA UNIVERSITY
- HEAD, AGILE CENTER OF EXCELLENCE, BRISTOL-MYERS SQUIB
- AUTHOR, DATA MANAGEMENT UNIVERSITY
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Flying Cars!!!
Travel to Mars!!!
Perfect bodies!!!
Welcome to 4th Industrial Revolution!!!
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In-depth Research
Watched one movie
The Matrix (1999)
Earned $460M worldwide
Critics liked it
Won 4 Academy Awards
The movie will tell me everything I need to know!
So, what becomes of the humans?
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Batteries for Robots
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Conclusion?
The Robot Overlords will take over in the future
Nothing we can do to stop them
Nothing we do now will prevent this future
Some time in the
future
Humans are
Free
Human are Batteries
StopPMDay
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Not Good Enough
Therefore, more research is needed!
i.e. watch more movies!!!
Great excuse to tell my wife. “I’m doing research”
She was very supportive!
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Results
539 Futuristic Movies
Negative outlook
Happy outlook532
7
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Got Me Thinking
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Value of Humans
What value do humans bring?
Randomness
Irrationality
Creativity
Managing unstructured data
Adapt to environment
Adopt new change
Thrive in the future
Some time in the
future
Humans are
Free
Human are Batteries
Stop
Humans adapt,
adopt and thrive
X
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Areas that are Difficult to Automate
Manual Manipulation
Surgeons, makeup artists, chiropractors
Creativity
Choreographers, art directors
Social Perception of People
Nurses, coaches
Common Sense
Desire/Drive
Run a business, have independence, perform social good
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Stand Up for all Humans!
And besides, As Dylan Thomas says, people
“Do not go gently into that good night”
“Rage, rage against the dying of the light”
Or, “Just Close the Door”
Wall Street Journal, Nov 10, 2017 “How to Survive a Robot Apocalypse: Just Close the Door”
“Robots are mastering math, but hand-eye coordination continues to elude them”
Or, “Don’t Rely on AI Alone”
Wall Street Journal, Aug 22, 2018, “Wall Street Finds Limits with Current AI Applications”
AI algorithms are easily fooled and therefore it’s difficult to rely on them. “It’s not clear that these models are learning or just memorizing the data,” Mr. Sukla said
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“Without Humans, Artificial Intelligence
is Still Pretty Stupid” – WSJ Nov 12, 2017
In late 2017, Facebook doubles moderators from 10 000 to 20 000
The more we ask AI to do, the more AI needs to be supplemented with
humans
Computers are fast, but require a lot of data. Humans are slower, but can
identify patterns based on very little information
AI programs don’t “learn” in any human sense. They gradually adopt their
inner workings to match patterns embedded in “training” data supplied
by human judgments
Patter recognition is a symptom of intelligence, but by no means defines
intelligence
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Additional Articles - Concerns
“Labor vs machines. An employment puzzle”
“A revolutionary decade in machinery emphasizes anew the discarding of men displaced in history”
“President ranks automation first as job challenge. Burden of finding work for youths and those displaced by machines”
“Automation report sees vast job loss”
“In concrete constructing, building materials are mixed, like dough, in a machine and literally poured into place without the touch of a human hand”
What about guards who open and close subway train doors? Elevator operators? Turn stile workers who accept metro tickets?
The author was worried about machines taking over
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Jun 1,
1930
Feb 15,
1962
Feb 26,
1928
New York Times
Sometimes We Forget Past Revolutions
Gunpowder
Horses vs cars
Sewing machines
Printing Presses
Transistors
Radio
Airplanes
Mobile phones
What happened to the previous jobs?
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Horses in New York City - 1900
A Lot of Horses
200 000 horses in New York City – Including Public Transportation
Each horse can create 7 - 16 kg of manure (тор) per day. Weight of a small child
1.4 - 3.2 million kg of manure per day
1400 – 3200 tonnes per day
Must clean up every day. Don’t miss a day!!!
In 1880, 15 000 dead horses removed
New Jobs Created Grow hay to feed the horses
Clean stalls and remove manure from city
Manure 12-18 meters high
Was dumped in vacant lots
Sweep the street so people can cross the street
Horse shoes
Wagons
1908 Cars started to arrive – Panic. What will all these people do?
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Job Loss vs Job Gain
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New
Technology
Expand Lower Prices
Lost
Jobs
New
Jobs
New
JobsNew
Jobs
Tech
Suppliers
New
Industries
We Buy
More
We Buy
Other Things
Higher
Productivity
New Jobs and Industries Created
Cars
Materials
Tires
Roads
Road materials
Street lights
Street signs
Hotels
Fast Food restaurants
Vacation and Tourist destinations
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Quick Math - Driverless Car
If we start converting today, how long will it take?
In Bulgaria, 4 000 000 cars on the road
Typical replacement is ~1 % per year. ~38 000 vehicles per year
How long will it take to convert to driverless cars
4 000 000 / 38 000 = 105 years
Or, 210 years if only half the people convert to driverless cars
How do we manage 105 – 210 years of cars include both human and
automated drivers?
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Sewing Machines
First commercial models
John Fisher – 1844
Elias Howe – 1845
Isaac Merritt Singer – 1851
Due to problems with patent filings,
Singer won the benefits of the patent
Women spent time sewing clothes,
or hiring a seamstress
Only owned 1-2 shirts
Time to
Create
Before Sewing
Machines
After Sewing
Machines
Shirt 14 hours 1 hour 15 minutes
Dress 10 hours 1 hour
Pants 3 hours 38 minutes PMDay Bulgaria 2018
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The Great Sewing Machine Riots of 1830
1830, Barthelemy Thimonnier had a factory with over 80
machines
Factory was destroyed by a riotous group of French tailors
Afraid the sewing machine would cause the end of their trade
Which was mostly true
Nearly every home has a sewing machine
Over 100 years late, very few homes have a sewing
machine
Clothes are inexpensively made
Today, people own more than 1 or 2 shirts
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Problem with Predictions
Most predictions are scary, but needs to be taken in context
May not include the bigger picture
”Those who don’t know history are doomed to repeat it” –
Edmund Burke
“Those who cannot remember the past are condemned to
repeat it” – George Santayana
There is a danger of using a small data set and extrapolating
into the future
Example: What if we only use data from the past few months?
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The Great Sunlight Leakage Crisis
Started in June
Bulgaria is loosing about 2 minutes of daylight per day
A computer model predicts total darkness by July
Affects the entire Northern Hemisphere
Daylight is flowing to the Southern Hemisphere
They are gaining about 2 minutes of daylight per day
We must “Do Something”!!!!!!
If you give me Power/Money, I just might be able to reverse
the trend by mid DecemberPMDay Bulgaria 2018
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Time Savers - Prediction In Progress
40 years ago - Paperless Society
50 years ago - Laborless Kitchens
“I’ve had it with
this kitchen!”“I don’t think I’m quite ready for
society to go totally paper-less!”
“Ding. You’ve
got mail”
“436 unread
emails”
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Poor Track Record for Predictions
Wall Street Journal,
Every 6 months, they gathers data from many key economic indicators
Then try to predict if the economy is going up or down. That’s it.
52% accuracy
Professional stock pickers
As a joke, asked monkeys to throw darts at the wall to pick stocks
Results: On average, the monkeys performed better than the professional stock pickers
“How are those revised
projections coming along?”
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Poor Track Record for Predictions
American football predictions
Each division has 4 teams
Chances of picking the winning team: 25%
But, in general, it is obvious which team is the
worse. Therefore, the chances of picking the
correct team: 33%
The paid, professional Football analysts, who
predict for a living?
36% accuracy
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Predicting the End of the World
100 AD 2000 2018PMDay Bulgaria 2018
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The latest Predictions
- 2018 Lindsey – The 3rd Second Coming
- June 9, 2019, Weinland predicts Jesus will return on this day
- 2020 Dixon, Armageddon will begin. Updated from 1962
- 2021 Beshore. Jesus to return in 1988. Prediction was correct,
but definition of a biblical generation was incorrect
- 2026 Asteroid collisions
- 2017 to 2113: Asteroids
1000
Hu
nd
red
s
Accuracy?
0%
Padding Predictions With Extra Time
Predictions are made far into the future. Ensures the predictions will be
forgotten
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Nov 8, 2017 - Stephen
Hawking issues dire
warning: We have less
than 600 years until
Earth becomes a sizzling
fireball
“ NASA - Galaxies will
collide in 4 billion years”
“ - The END is Thursday.
- The END is Near.
( Amateur) ”
Excuses
“Unpredictable factors, such as the weather”
“No one else could have predicted …”
“My prediction was right, but my timing was off”
“The evidence was not incorrect, but was not fully
predictive of what was going on”
People’s fears don’t add up
80% of people think robots will take over 50% of the jobs
Yet, 80% of the people don’t think their job will be
replaced
So who’s jobs are they???
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Why Are We So Bad at Predictions?
Strong incentives to make extreme predictions
Chosen to be on television and the news
Must be original, different, and stand out
Those who were correct on one extreme position, had a lower percentage making other predictions
One correct extreme prediction overrides every other wrong prediction
What are the Penalties for bad predictions?
None
Romania to punish bad predictions - 2 years in jail
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Perspective – More Complicated
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“Something’s just not right – our air is clean, our
water is pure, we all get plenty of exercise,
everything we eat is organic and free-range, and
yet nobody lives past thirty.”“Should we pick up something for the
folks who don’t eat red meat?”
We Don’t Know What We Think We Know
Pyramids – 2750 BC Walking on the
Moon – 1969 ADCleopatra – 69 BC
Nationality Cleopatra lived 700 years closer to
present day than the pyramids PMDay Bulgaria 2018
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Greek!
We Don’t Know What We Think We Know
All 7 Billion people can fit comfortably within France with 80 sq.
meters each. Or 4 x Bulgaria with 64 sq. meters each
The United States alone has the ability to feed 9 Billion people
Each year for the next 100 years, the world can give back land
the size of France and plant all trees,
And still feed everyone
London took 76 years to get back to pre WWII war population
8.6 million in 1939 - 8.7 million in 2015
Berlin and Paris have not reached pre-WWII war populations
Paris 2.9 Million -1921 - Paris 2.2 Million - 2009
Berlin 4.3 Million – 1939 - Berlin 3.5 Million - 2015
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We Are not Good with Amounts and Sizes
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103 1015 1018106 109 1012 1021 1024
Grains of sand on all beaches
Stars in the visible universe
Insects for every human
Trees on Earth
Stars in the Milky Way Galaxy
Synapses in the brain
Atoms in a molar gram of matter200 x 106
100 x 109
3 x 1012
125 x 1012
1.0 x 1024
6.02 x 1023
7.5 x 1018
Irrational Decision Making
People make irrational decisions
”Gut” feel – I “Feel something in my stomach” that
tells me what to decide
Emotional appeal
Marketers use this to their advantage
People are programed to make relative decisions
People struggle to make absolute decisions
“How
Marketing
Works”
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Picking Magazines
Paper only Version:
Lev 100/year
Digital/web only
Version: Lev 207/year
Digital/web and Paper
Version: Lev 207/year
10% 0% 90%
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The Economist
Picking Magazines
Paper only Version:
Lev 100 /year
Digital/Web only
Version: Lev 207 /year
Digital/Web and Paper
Version: Lev 207 /year
60% 0% 40%
X
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The buying habits
changed
The Economist
Picking Magazines
Paper only Version:
Lev 100 /year
Digital/Web only
Version: Lev 207 /year
Digital/Web and Paper
Version: Lev 207 /year
10% 0% 90%
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The buying habits
reverted to the
original
Even though no
one buys the
Digital only Version
The Economist
Where Does This Leave Us?
The world is changing
It has always changed
People cannot reasonably predict the future
People have always worked together
And will continue to work together
How do we…
Interact better
Solve problems better
Communicate better
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Continual Learning
Are we continually learning in our
profession?
Are we continually learning in our industry?
Are we trying new approaches?
Are we improving existing techniques?
Or, are we ”too busy” to learn and
improve?
Question: What has been new in our
industry in the last 10-20 years?
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Agile Manifesto
Agile Manifesto
Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan
While there is value in the items on the right, we value the items on the left more
Манифест за Agile
Хората и взаимоотношенията повече от процесите и инструментите
Работещия софтуер повече от изчерпателната документация
Сътрудничеството с клиента повече от формализирането на договора
Реагирането на промяната повече от следването на плана
Ние разбираме, че нещата отдясно са важни, но повече ценим нещата отляво.
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Agile Principles – 3 of the 12
Our highest priority is to satisfy the customer through early and continuous
delivery of valuable software
Smaller phases
More demos
Welcome changing requirements, even late in development. Agile processes
harness change for the customer's competitive advantage
Lean Change Management Process
Encourage change early
Business people and developers must work together daily throughout the project
Better able to ensure requirements are clear
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Agile Principles – Another 3 of 12
Build projects around motivated individuals. Give them the environment and
support they need, and trust them to get the job done
Extend more trust
The most efficient and effective method of conveying information to and within
a development team is face-to-face conversation
True of waterfall projects
At regular intervals, the team reflects on how to become more effective, then
tunes and adjusts its behavior accordingly
Incorporate more, shorter lessons learned sessions throughout the project
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Communicating Clearly
Critical PM Skills
Ability to summarize data
Ability to present complex data in a simple way
Spend about 80% of time communicating and interacting with people
Understand and speak to the audience
Be short and to the point
Say what you mean. Mean what you say
Use simple, clear words, instead of long, fancy words
Careful use of jargon
Example: – On the next slides. Is this clear communications?
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Warning: Dangerous Chemical!!!!
Dihydrogen monoxide (DHMO)
Also known as hydroxyl acid, and is a major component of acid rain
Can cause sever burns
Contributes to the erosion of our natural landscape
Accelerates corrosion and rusting of many metals
May cause electrical failures and decreases effectiveness of automobile bakes
Often used in:
Industrial solvent
Nuclear power plants
Distribution of pesticides. Even after washing, the product remains contaminated by this chemical
Additive in certain junk food and other food products
Has been found in every single household around the world
http://www.dhmo.org
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More Warnings
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Unbelievable!!!
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Danger!!!
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Ban Dihydrogen Monoxide
Who will sign a petition with me to ban Dihydrogen Monoxide?
Di – hydrogen, Mono - oxide
2 Hydrogen, 1 Oxygen
2H, O
H2O
Water
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More Warnings
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WaterWater
Unbelievable!!!
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Water
Danger!!!
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Water
Water
Status Reporting
Audience: Targeted to the sponsors, stakeholders and executive leadership
10-30 seconds of their time
Usually 0-5 seconds if status reports are too long
What do I need them to do?
What do I need them to understand?
What are the key risks they need to know
What are the key issues they need to know
Be the source of truth. Be reliable
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Estimation – Why is this Important?
10 Months
Or
Lev 10 000 000
8 Months
Or
Lev 8 000 000
12 Months
Or
Lev 12 000 000
Actual workOriginal Estimate A Original Estimate B
Perceived Failure Perceived Success
Yet in both cases, the actual work was still 10 Months or Lev 10 000 000
The original estimation plays a large part in perceived success or failure
When starting a project, verify the estimates
Later in the project, re-verify the estimates
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Influencing Others
Still need to work with people
Build trust
Better in the beginning. Early and often
Pay huge dividends when stress hits the team
“Help me understand…” “помогни ми да разбера”
Useful phrase to ask questions without embarrassing others or
making them feel threatened
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Trust - Getting to Know Each Other
Initial Introductions
Vacation
Interest
Hobbies
Pets, kids
Town where they live and work. Tour their town in Google
Thank you card
Team “group photo”
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The Team!
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Conclusion - Predictions
So, don’t worry
Expect many things to change and be unrecognizable. This has been true for the past 20 years, 40 years, 100 years, 1 000 years, etc.
Top 10 jobs didn’t exist 10 years ago
“We are currently preparing students for jobs that don’t yet exist . . . using technologies that haven’t been invented . . . in order to solve problems we don’t even know are problems yet.” – Fisch and MeLeod
Beware of predictions made by “professionals”
Don’t assume they can predict the future better than you
Don’t assume you’re a genius either
Predictions have not much better than guessing
Typically, only the extreme predictions are amplified
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Conclusion – Our Benefits and Learning
Still comes down to how we interact
with people
Build trust
Work as a team
Communicate simpler
Continue learning to stay relevant
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Conclusion
Adapt
Adopt
And ThrivePMDay Bulgaria 2018
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Thank you!
Questions ???
Comments ???
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