DPM UK: Stealing Project Management Lessons from Artificial Intelligence

Meri Williams, ChromeRose @Geek_Manager
STEALING PM LESSONS FROM
ARTIFICIAL INTELLIGENCE
DPM:UK
Manchester, Jan 2015

http://www.flickr.com/photos/kodomut/3667608102/

Artificial
Intelligence
Project
Management
MY RESEARCH

https://www.flickr.com/photos/tbisaacs/4083598572/

TRADITIONAL PROJECT
MANAGEMENT OFTEN SEEMS OF
THE OPINION THAT
THE PROCESS IS SOUND AND
ADHERENCE IS THE PROBLEM

https://www.flickr.com/photos/imagesbywestfall/3658162161/

ROBOTS/AGENTS HAVE NO PROBLEMS
BEING PATIENT, LOGICAL OR RATIONAL,
AND CAN WORK 24/7/365…
… BUT IT STILL DIDN’T WORK

1) AUTONOMY (AGENTS)
2) MASTERY (MACHINE LEARNING)
3) RE-CREATION (MACHINE
INTELLIGENCE)

1) FIRST LET’S LOOK AT
AUTONOMY AND AGENTS

ENABLING AGENTS TO
MAKE DECISIONS AND
ACT INDEPENDENTLY
BUT
ALWAYS TOWARDS A COMMON
GOAL LEADS TO
COMPLEX, SUCCESSFUL ACTION

FOCUS ON THE WHY (THE GOAL)
AND ENABLE THE WHAT AND
THE HOW TO BE DEFINED BY
THOSE DOING THE WORK, AS
MUCH AS POSSIBLE

THIS IS WHY I LOVE USER STORIES
As a <type of user>,
I want to
<do something>,
So that
<some value is
created>.
https://www.flickr.com/photos/psd/8591351239/

CLUE / SKILLS MATRIX

http://www.flickr.com/photos/8250578@N06/8625641442/

http://www.flickr.com/photos/provoost/2246718091/

https://www.flickr.com/photos/wonderlane/37531816/

HUMAN SKILL DEVELOPMENT

2) HOW DO MACHINES
LEARN?
MASTERY & MACHINE
INTELLIGENCE

MACHINE LEARNING IS FASCINATING
• Supervised (teacher-student model)
• Unsupervised (learn-from-data model)
• Reinforcement (learn-by-doing model)
• Developmental (learn-enough-to-set-
up-more-learning-for-yourself model)

WE’RE GOOD AT WHAT WE
PRACTISE, PROVIDING WE CAN
LEARN FROM IT

DELIBERATE PRACTICE
• You must be motivated to attend to the task and
exert effort to improve your performance.
• The design of the task should take into account your
pre-existing knowledge so that the task can be
correctly understood after a brief period of
instruction.
• You should receive immediate informative feedback
and knowledge of results of your performance.
• You should repeatedly perform the same or similar
tasks.

MODELS OF DELIBERATE PRACTICE
• Sports Model – analogous to conditioning
• Chess Model – what did the grand master do?
• Music Model – chunking & mental rehearsal

IS THE WORK DESIGNED IN A WAY
THAT MAKES IT EFFECTIVE
DELIBERATE PRACTICE?

https://www.flickr.com/photos/psd/8451589322/

https://www.flickr.com/photos/psd/8002453131

AS AN ASIDE…
DO RETROSPECTIVES DURING
PROJECTS RATHER THAN POST
MORTEMS AFTER
FOR A POST MORTEM,
FIRST SOMETHING HAS TO DIE

3) RE-CREATION (MACHINE
INTELLIGENCE)

MACHINES ARE LIMITED.
SO ARE PEOPLE, WHEN WE
TREAT THEM LIKE MACHINES.

WE ALL HATE BAD
BOSSES
WE DESCRIBE THEM AS
• Clueless
• Empty suits
• Pointless
• Seagulls

Across industries, across
countries, the best
performing teams
answer certain
questions positively

Predictors of High Performance
1. Do I know what is expected of me at work?
2. Do I have the materials & equipment I need to do my work right?
3. At work, do I have the opportunity to do what I do best every day?
4. In the last 7 days, have I received recognition or praise for good work?
5. Does my supervisor, or someone at work, seem to care about me as a
person?
6. Is there someone at work who cares about my development?
7. At work, do my opinions seem to count?
8. Does the mission/purpose of my company make me feel like my work is
important?
9. Are my co-workers committed to doing quality work?
10. Do I have a best friend at work?
11. In the last 6 months, have I talked with someone about my development?
12. At work, have I had opportunities to learn and grow?

UNDERSTAND
MOTIVATION
• Purpose
• Autonomy
• Mastery

MOTIVATION =
+ PURPOSE (Do I believe in WHY?)
+ AUTONOMY (Do I get a say in WHAT?)
+ MASTERY (Am I proud of HOW?)
- ANY NEGATIVE FACTORS THAT DETRACT

Predictors of High Performance (remix)
PURPOSE
• Does the
mission/purpose of my
company make me feel
like my work is
important?
AUTONOMY
• Do I know what is
expected of me at
work?
• At work, do my
opinions seem to
count?
MASTERY
• Do I have the materials & equipment I
need to do my work right?
• At work, do I have the opportunity to do
what I do best every day?
• Is there someone at work who cares about
my development?
• Are my co-workers committed to doing
quality work?
• In the last 6 months, have I talked with
someone about my development?
• At work, have I had opportunities to learn
and grow?

And What Else?
OTHER FACTORS:
• In the last 7 days, have I received recognition or praise for good work?
• Does my supervisor, or someone at work, seem to care about me as a
person?
• Do I have a best friend at work?
ESSENTIALLY, AM I RESPECTED & REWARDED HERE?
CAN I BE MYSELF AND SUCCEED HERE?
I CALL THIS INCLUSION.

The Most Important Question
Best predictor of recruitment AND retention?
Someone’s ability to agree with:
“Someone like me can be
successful here”

CREATE SPACE FOR YOUR TEAM TO
BE THE BEST THEY CAN BE
Your job as a project manager…

As a PM, Ask Yourself
• Do my team know WHY we are doing
this?
• Do my team get a say in the WHAT? In
doing the right thing?
• Do my team get opportunities to do the
thing right? And to get better at the
HOW?
• Do we do a good job of making all our
different people feel included & like
they BELONG HERE?
(PURPOSE)
(AUTONOMY)
(MASTERY)
(INCLUSION)

EVERY
ROLE IS
CAPABLE OF
VIRTUOSITY

SPACE TO BE AWESOME =
+ PURPOSE (Do I believe in WHY?)
+ AUTONOMY (Do I get a say in WHAT?)
+ MASTERY (Am I proud of HOW?)
+ INCLUSION (Do I BELONG HERE?)
- ANY NEGATIVE FACTORS THAT DETRACT

TO RECAP: KEY LESSONS WE CAN
STEAL FROM AI AND USE IN PM

KEY LESSONS
1. Autonomy matters (because change happens)
2. Communicate purpose & goals (why & what)
3. Let individuals define the how (bonus:
motivation!)
4. Help design work as deliberate practice
5. Help teams assess & improve as they go (retros
> post mortems)
6. Awesome = purpose + autonomy + mastery +
inclusion

https://www.flickr.com/photos/colmsurf/144455160/
YOU CAN’T HOLD BACK THE OCEAN,
BUT YOU CAN LEARN TO SURF

DPM UK: Stealing Project Management Lessons from Artificial Intelligence

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