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SUPERWEEK 2019
REPETITIVE TASKS
ARE SLOWLY
KILLING US FROM
WITHIN
01. February 2019
01.
INTRODUCTION
• Danny Mawani Olsen
• Copenhagen based
• Lead analyst at IMPACT EXTEND
• 2nd Superweek
• Worked with Analytics for 5 years (Thanks Steen)
I’m Danny! The guy
always asking
questions on
#measureslack
@dannymawani
100% focus on digital
commerce Long customer relations 7 x Gazelle
A A R H U S – C O P E N H A G E N -
L I S B O A
1 2 6 E M P L O Y E E S
E S T A B L I S H E D I N 1 9 9 8
Market leader in commerce
Established in 2018 17 Employees Aarhus - Copenhagen
Part of IMPACT A/S
Clients: Largest retailers in the
nordics
Focus is on datadriven marketing
WHAT DO WE WORK
WITH?
Datacollection
Marketings
initiatives and
userbehaviour
• Making data avaliable
• Telling the right story
Consolidating data
• Work with multiple datasources
• Make sure that they can tell the right story
Dataarchitechture
• Development of KPI
frameworks
• GTM
• Mapping out datastructures
Data
aggregation
A lot of GDPR in
the mix
Make sure that what we do is legal
• Permissions
• GDPR flows
• Mapping data the right way
Visualization
@dannymawani
Lead Analyst
THE
TEAM
Analytics and tracking specialist
Analytics & Dashboard specialist
CEO
Head of BI & Statistic modelling
Head of traffic & Inisights
DANNY OLSEN RASMUS
CHRISTIANSEN
CHRISTIAN
VERMEHREN
MAIKEN TORRILD THOMAS RODE DENIS HANSEN
What is the definition of automation, and what can we learn from the
past?
02.
AUTOMATION AS A
CONCEPT
”Automation is the technology by which a process or
procedure is performed with minimum human assistance.”
Groover, Mikell (2014). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems.
”Automation is the technology by which a process or
procedure is performed with minimum human assistance.”
Groover, Mikell (2014). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems.
THE INDUSTRIAL
REVOLUTION
The industrial RevolutionModern age
1780 1850
Contemporary age
FROM RURAL TO URBAN
SOCIETY
From farming
to factory
STEAM ENGINE
From Factory
to office
From office
to modern
office
THE NEXT STEP
From modern
office to
collaboration
with
machines
WE ARE ALWAYS AFRAID
OF BEING REPLACED
AUTOMATION IS
ESSENTIALLY?
03.
HOW TO START
AUTOMATING
YOUR WORK
This is my fiancé Sandra
• She automated having to put the plate back
and on the table
• Also build in a spill tray for toast crumbles
and cheese
• By reducing her time reaching the plate for
the plate, she can save the mental energy to
withstand me!
How I got
started: This
is me at my
first Senior
job
• Mainly worked with GA and
GTM implementations
• Used some javaScript but
didn’t know how it was all
connected
Business
unit A
Business
Unit B
Business
Unit C
X = 36 SEO REPORTS
A task was given: Create the same SEO report
for the client
This is me
when after
the brief
SO I
BEGAN A
JOURNEY
LEARNIN
G R
FIRST I LEARNED HOW TO
PULL GA DATA
LEARNED GGPLOT2
FINALLY CREATING A
RMARKDOWN DOCUMENT TO
BE SEND TO THE CLIENT
I SPEND A RIDICULOUSLY
AMOUNT OF TIME BUILDING
IT, BUT IT GOT ME STARTED
TO BE BETTER AND FOCUS
ON MORE FUN PROJECTS
HOWEVER, ALSO REDUCING
THE TASK FROM 2 ANALYST
WORKING 3 DAYS TO ME
SPENDING 3 HOURS A
MONTH
SINCE THEN WE
HAVE TRIED TO
BUILD
FRAMEWORKS
For plug and play to
things like cost uploads
For things that the tools
doesn’t support and to
transform the data
For storing data and
large calculations
R Cron jobs: Ubuntu R server in Google Cloud
Master machine boots the ”slave machines” when needed. A cost price around 25 euros a month.
When it is set up. We only use VM with the capacity needed in order to reduce costs.
SETUPPIPELINE: R
Master Machine
(Always online)
Cron Job (starts
and stops
machines)
Refund Data
Pulls script from
storage
Formats data and
uploads it to GA
COGS upload
Pulls script from
storage
Formats data and
uploads it to GA
Datawrangling
Pulls script from
storage
Formats data and
sends it to the right
places
Datavalidation
Pulls script from
storage
Checks for
deploys, and does
an audit should
there be changes
Sends an email if
there are issues
and also creates a
task in asana
GDPR Check
Pulls script from
storage
Checks if there are
GDPR challenges
Sends an email
and creates a task
in asana
GOOGLE
ANALYTICS
VALIDATION Generates an Google Analytics audit based on
API parameters
 Makes it into a formatted PDF
QA ON DATA
 Check the data quality after a deploy
 Should something have happened, then it will
send an email and create a ticket mentioning the
errors it have found
Event To Google Analytics
Category: Deploy | Action: Jira ticket
Did something happen with the data?
Yes No
UPLOAD OF
REFUNDS
 Daily upload of refunds
Data from cient
VM With R
Upload toGA
COGS UPLOAD
 Monthly upload of product purchase prices to
see how much is actually earned on marketing
expanses
Data from cient
VM With R
Upload toGA
GDPR CHECK
 If there are any issues with the data send that
shows PII (differs from client to client), we
identify it across datapoints
 In GA, should there be any issues we delete the
user affected
Data from client
VM With R
Check for GDPR breaches
Datasourc
e
MA Tool
Google Big
Query
BI ToolGoogle Cloud
Storage
Google
Compute Engine
Other sources
R studio
server
Attribution
tool
Action on data
Fra tool to action
1. Datasource is established and
connection is set up
2. It is then added to BigQuery on
a client project they have control
over
3. Data is then pushed to either
the marketing automation tool if
a consent is given for the user
4. For dashboards and attribution
that same dataset gets
encrypted to ensure that people
cannot identify users if they do
not have the right permissions
ONCE THAT IS IN PLACE, WE CAN
START TAKE ACTIONS
AND DO STATISTICAL SEGMENTING
THAT IS NOT POSSIBLE IN THE
AUTOMATION TOOL
TO SEE HOW OUR CLIENT
SEGMENTS PERFORM
AND PUSH CALCULATED
DATA INTO RULES FOR THE
MA PLATFORM
HOWEVER, IT
DOESN’T HAVE
TO BE THIS
COMPLICATED
IF THIS THEN
THAT
ZAPIER
UPLOAD TO
GA
I F C H A N G E S I S
M A D E TO A
T H E N S E N D T H AT
I N F O R M AT I O N TO G A
ALERTS
I F G A S E N D S A N
E M A I L A L E RT
T H E N C R E AT E A TA S K I N
A S A N A W I T H A L L P R O P E RT I E S
A N D S I T E S A F F E C T E D O N C E A
ZAPIER
ALERTS
I F G A S E N D S A N
E M A I L A L E RT
T H E N C R E AT E A M E S S A G E I N
S L A C K W I T H A L L P R O P E RT I E S
A N D S I T E S A F F E C T E D O N C E A
• Rasmus eksempel
ZAPIER
OTHER
TOOLS
REMEMBER,
DO WHATS
AVALIABLE TO
YOU• This is our Brilliant Lead
SEO spcialist (Being a
lead is like being a head
of an department without
having to talk politics,
pay and employer
conversations)
• He is not a tech guy and
can’t code
• He is really great with
excel
• Ranked #1 on the danish
words for Loan and New
year meals
• What he did was to take
the data that he needed to
do an SEO report
CHRISTOPHER
S WAY TO
AUTOMATION
POW
ERBI
• Takes google Ads
data and combines
that with the
position to see how
much value that is
in each search term
POW
ERBI
• Use the other tool to
assess how other
companies rank for
all of the clients
search terms
ALL HE HAS
TO DO TODAY
• Download the data
• Add it to the powerBI
template
• And do a little adjustment
for outliers etc.
• A process that has taken
days and know only
takes a few hours
• In the future it will be
faster as we are working
on making API
connections to all the
search tools
04.
DUMB WAYS TO
DIE AT WORK
FOR NOT
AUTOMATING
MAKING YOURSELF
UNREPLACABLE ON THE
WRONG FOUNDATION
• Not involving your team mates in
your activity or highligting what
processes that you handle
• Not documenting any of your work
BEING AFRAID TO ASK
QUESTIONS
• People in this community
are smart – Scary smart
• It is quite easy to think
that you are stupid and
that you are embarrassing
yourself
• The same can be said for
answering questions,
sometimes it can be
frightening to answer
questions because you
are afraid of being
ridiculed
NOT
DOCUMENTING
YOUR WORK• This is Maiken one of
our junior analyst
• Her job is mainly to help
with GA and GTM tasks
• For tasks she has not
done before, we
document that task for
next time, or use the
existing documentation
to do the work
NOT
OUTSOURCING• We can all agree that
Hussein is a smart guy!
• When I was a junior i
used Odesk (Now
UpWork) to help me
with some of the tasks i
couldn’t do
• Because of this, I got
the job done fast and
with a lot of quality and i
could learn from his
solutions
NOT REALIZING WE ARE
WORKING WITH
ANNOYING SIZE DATA• Data on our computer is annoying
size, meaning that big data tools
doesn’t nessescarily be the best way
for us to work with data
• Divide and conquer your data to
ensure that it can be processed in a
good way
• Remember to use the right tools for
the right dataset
NOT BEING
LIKE PETER
MEYER
Q U A L I T Y A S S U R E L I K E
C R A Z Y
D O T H I N G S T H E R I G H T
W A Y A N D S T O P U S I N G
” N I N J A H A C K S ” E V E N
T H O U G H I T T A K E S
M O R E T I M E
M A K E S U R E T H I N G S
C A N B E S C A L A B L E I N
O T H E R P R O J E C T S
K E E P U S I N G N E W
T E C H N O L O G Y I N Y O U R
W O R K
05.
ROUNDING OFF
“Automation, It’s not necessarily a way to obsolete
the human equation, but instead thinking about how
we can spend our time better doing other things when
it comes to repetitive tasks, and by that saving time to
do awesome things instead of doing the same things
over and over again”
AUTOMATION: TO
ME
I
PROBAB
LY
DON’T
DO
THINGS
THE
SMARTE
ST WAY
BUT FOR EACH ITERATION I
GET A BIT CLOSER TO A
SMARTER SOLUTION
MY
BEST
ADVICE
D O N ’ T B E A F R A I D T O
U S E T O O L S
A U T O M A T E W H A T Y O U
C A N W I T H I N Y O U R
T E C H N I C A L
L I M I T A T I O N S
D O T H I N G S T H E P E T E R
M E Y E R W A Y
( S C A L A B L E , A N D
S T A B L E )
D O C U M E N T A L L C O O L
T H I N G S Y O U D O
A S K F O R H E L P W H E R E
Y O U C A N ’ T D O
E V E R Y T H I N G
Y O U R S E L F
K E E P L E A R N I N G A N D
I M P R O V I N G Y O U R
F R A M E W O R K S
AND REMEMBER TO
HAVE FUN
Repetitive tasks are killing us
from within
Do what is in your disposition to make the
best out of your work
By Danny Mawani Olsen
/dannymawani @dannymawani
Superweek2019 dmo presentation

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Superweek2019 dmo presentation

  • 1. SUPERWEEK 2019 REPETITIVE TASKS ARE SLOWLY KILLING US FROM WITHIN 01. February 2019
  • 3. • Danny Mawani Olsen • Copenhagen based • Lead analyst at IMPACT EXTEND • 2nd Superweek • Worked with Analytics for 5 years (Thanks Steen) I’m Danny! The guy always asking questions on #measureslack @dannymawani
  • 4. 100% focus on digital commerce Long customer relations 7 x Gazelle A A R H U S – C O P E N H A G E N - L I S B O A 1 2 6 E M P L O Y E E S E S T A B L I S H E D I N 1 9 9 8 Market leader in commerce Established in 2018 17 Employees Aarhus - Copenhagen Part of IMPACT A/S Clients: Largest retailers in the nordics Focus is on datadriven marketing
  • 5. WHAT DO WE WORK WITH? Datacollection Marketings initiatives and userbehaviour • Making data avaliable • Telling the right story Consolidating data • Work with multiple datasources • Make sure that they can tell the right story Dataarchitechture • Development of KPI frameworks • GTM • Mapping out datastructures Data aggregation A lot of GDPR in the mix Make sure that what we do is legal • Permissions • GDPR flows • Mapping data the right way Visualization @dannymawani
  • 6. Lead Analyst THE TEAM Analytics and tracking specialist Analytics & Dashboard specialist CEO Head of BI & Statistic modelling Head of traffic & Inisights DANNY OLSEN RASMUS CHRISTIANSEN CHRISTIAN VERMEHREN MAIKEN TORRILD THOMAS RODE DENIS HANSEN
  • 7. What is the definition of automation, and what can we learn from the past? 02. AUTOMATION AS A CONCEPT
  • 8. ”Automation is the technology by which a process or procedure is performed with minimum human assistance.” Groover, Mikell (2014). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems.
  • 9. ”Automation is the technology by which a process or procedure is performed with minimum human assistance.” Groover, Mikell (2014). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems.
  • 10. THE INDUSTRIAL REVOLUTION The industrial RevolutionModern age 1780 1850 Contemporary age
  • 11. FROM RURAL TO URBAN SOCIETY From farming to factory
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  • 15.
  • 17.
  • 18. THE NEXT STEP From modern office to collaboration with machines
  • 19. WE ARE ALWAYS AFRAID OF BEING REPLACED
  • 21.
  • 23. This is my fiancé Sandra • She automated having to put the plate back and on the table • Also build in a spill tray for toast crumbles and cheese • By reducing her time reaching the plate for the plate, she can save the mental energy to withstand me!
  • 24. How I got started: This is me at my first Senior job • Mainly worked with GA and GTM implementations • Used some javaScript but didn’t know how it was all connected
  • 25. Business unit A Business Unit B Business Unit C X = 36 SEO REPORTS A task was given: Create the same SEO report for the client
  • 26. This is me when after the brief
  • 27.
  • 29. FIRST I LEARNED HOW TO PULL GA DATA
  • 31. FINALLY CREATING A RMARKDOWN DOCUMENT TO BE SEND TO THE CLIENT
  • 32. I SPEND A RIDICULOUSLY AMOUNT OF TIME BUILDING IT, BUT IT GOT ME STARTED TO BE BETTER AND FOCUS ON MORE FUN PROJECTS
  • 33. HOWEVER, ALSO REDUCING THE TASK FROM 2 ANALYST WORKING 3 DAYS TO ME SPENDING 3 HOURS A MONTH
  • 34. SINCE THEN WE HAVE TRIED TO BUILD FRAMEWORKS For plug and play to things like cost uploads For things that the tools doesn’t support and to transform the data For storing data and large calculations
  • 35. R Cron jobs: Ubuntu R server in Google Cloud Master machine boots the ”slave machines” when needed. A cost price around 25 euros a month. When it is set up. We only use VM with the capacity needed in order to reduce costs. SETUPPIPELINE: R Master Machine (Always online) Cron Job (starts and stops machines) Refund Data Pulls script from storage Formats data and uploads it to GA COGS upload Pulls script from storage Formats data and uploads it to GA Datawrangling Pulls script from storage Formats data and sends it to the right places Datavalidation Pulls script from storage Checks for deploys, and does an audit should there be changes Sends an email if there are issues and also creates a task in asana GDPR Check Pulls script from storage Checks if there are GDPR challenges Sends an email and creates a task in asana
  • 36. GOOGLE ANALYTICS VALIDATION Generates an Google Analytics audit based on API parameters  Makes it into a formatted PDF
  • 37. QA ON DATA  Check the data quality after a deploy  Should something have happened, then it will send an email and create a ticket mentioning the errors it have found Event To Google Analytics Category: Deploy | Action: Jira ticket Did something happen with the data? Yes No
  • 38. UPLOAD OF REFUNDS  Daily upload of refunds Data from cient VM With R Upload toGA
  • 39. COGS UPLOAD  Monthly upload of product purchase prices to see how much is actually earned on marketing expanses Data from cient VM With R Upload toGA
  • 40. GDPR CHECK  If there are any issues with the data send that shows PII (differs from client to client), we identify it across datapoints  In GA, should there be any issues we delete the user affected Data from client VM With R Check for GDPR breaches
  • 41. Datasourc e MA Tool Google Big Query BI ToolGoogle Cloud Storage Google Compute Engine Other sources R studio server Attribution tool Action on data Fra tool to action 1. Datasource is established and connection is set up 2. It is then added to BigQuery on a client project they have control over 3. Data is then pushed to either the marketing automation tool if a consent is given for the user 4. For dashboards and attribution that same dataset gets encrypted to ensure that people cannot identify users if they do not have the right permissions
  • 42. ONCE THAT IS IN PLACE, WE CAN START TAKE ACTIONS
  • 43. AND DO STATISTICAL SEGMENTING THAT IS NOT POSSIBLE IN THE AUTOMATION TOOL
  • 44. TO SEE HOW OUR CLIENT SEGMENTS PERFORM
  • 45. AND PUSH CALCULATED DATA INTO RULES FOR THE MA PLATFORM
  • 46. HOWEVER, IT DOESN’T HAVE TO BE THIS COMPLICATED
  • 49. UPLOAD TO GA I F C H A N G E S I S M A D E TO A T H E N S E N D T H AT I N F O R M AT I O N TO G A
  • 50. ALERTS I F G A S E N D S A N E M A I L A L E RT T H E N C R E AT E A TA S K I N A S A N A W I T H A L L P R O P E RT I E S A N D S I T E S A F F E C T E D O N C E A
  • 52. ALERTS I F G A S E N D S A N E M A I L A L E RT T H E N C R E AT E A M E S S A G E I N S L A C K W I T H A L L P R O P E RT I E S A N D S I T E S A F F E C T E D O N C E A
  • 55. REMEMBER, DO WHATS AVALIABLE TO YOU• This is our Brilliant Lead SEO spcialist (Being a lead is like being a head of an department without having to talk politics, pay and employer conversations) • He is not a tech guy and can’t code • He is really great with excel • Ranked #1 on the danish words for Loan and New year meals
  • 56. • What he did was to take the data that he needed to do an SEO report CHRISTOPHER S WAY TO AUTOMATION
  • 57. POW ERBI • Takes google Ads data and combines that with the position to see how much value that is in each search term
  • 58. POW ERBI • Use the other tool to assess how other companies rank for all of the clients search terms
  • 59. ALL HE HAS TO DO TODAY • Download the data • Add it to the powerBI template • And do a little adjustment for outliers etc. • A process that has taken days and know only takes a few hours • In the future it will be faster as we are working on making API connections to all the search tools
  • 60. 04. DUMB WAYS TO DIE AT WORK FOR NOT AUTOMATING
  • 61. MAKING YOURSELF UNREPLACABLE ON THE WRONG FOUNDATION • Not involving your team mates in your activity or highligting what processes that you handle • Not documenting any of your work
  • 62. BEING AFRAID TO ASK QUESTIONS • People in this community are smart – Scary smart • It is quite easy to think that you are stupid and that you are embarrassing yourself • The same can be said for answering questions, sometimes it can be frightening to answer questions because you are afraid of being ridiculed
  • 63. NOT DOCUMENTING YOUR WORK• This is Maiken one of our junior analyst • Her job is mainly to help with GA and GTM tasks • For tasks she has not done before, we document that task for next time, or use the existing documentation to do the work
  • 64. NOT OUTSOURCING• We can all agree that Hussein is a smart guy! • When I was a junior i used Odesk (Now UpWork) to help me with some of the tasks i couldn’t do • Because of this, I got the job done fast and with a lot of quality and i could learn from his solutions
  • 65. NOT REALIZING WE ARE WORKING WITH ANNOYING SIZE DATA• Data on our computer is annoying size, meaning that big data tools doesn’t nessescarily be the best way for us to work with data • Divide and conquer your data to ensure that it can be processed in a good way • Remember to use the right tools for the right dataset
  • 66. NOT BEING LIKE PETER MEYER Q U A L I T Y A S S U R E L I K E C R A Z Y D O T H I N G S T H E R I G H T W A Y A N D S T O P U S I N G ” N I N J A H A C K S ” E V E N T H O U G H I T T A K E S M O R E T I M E M A K E S U R E T H I N G S C A N B E S C A L A B L E I N O T H E R P R O J E C T S K E E P U S I N G N E W T E C H N O L O G Y I N Y O U R W O R K
  • 68. “Automation, It’s not necessarily a way to obsolete the human equation, but instead thinking about how we can spend our time better doing other things when it comes to repetitive tasks, and by that saving time to do awesome things instead of doing the same things over and over again” AUTOMATION: TO ME
  • 70. BUT FOR EACH ITERATION I GET A BIT CLOSER TO A SMARTER SOLUTION
  • 71. MY BEST ADVICE D O N ’ T B E A F R A I D T O U S E T O O L S A U T O M A T E W H A T Y O U C A N W I T H I N Y O U R T E C H N I C A L L I M I T A T I O N S D O T H I N G S T H E P E T E R M E Y E R W A Y ( S C A L A B L E , A N D S T A B L E ) D O C U M E N T A L L C O O L T H I N G S Y O U D O A S K F O R H E L P W H E R E Y O U C A N ’ T D O E V E R Y T H I N G Y O U R S E L F K E E P L E A R N I N G A N D I M P R O V I N G Y O U R F R A M E W O R K S
  • 73. Repetitive tasks are killing us from within Do what is in your disposition to make the best out of your work By Danny Mawani Olsen /dannymawani @dannymawani

Editor's Notes

  1. 1882 – 1925 1876 telephone
  2. 1882 – 1925 1876 telephone
  3. All time periods have that in common that people got replaced, and that we need to be adaptive to follow along – we are on a revolution here, but i think that our current generations are more ready to adapt new ways of doing things over the course of time
  4. It doesn’t make sense to build things