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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2018

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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

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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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