From being just hype to being business-as-usualDNA’s journey in data science & big data

Once upon a time, in a telco operator far far away….

Customers with “mokkula” (usbmodem)

?

Hockey-fanatic business manager:THE NHL IS STARTING!!!!11oneone

SO YOU WANT CHANGE, EIGH?

Not so long ago, same operator

Emphasis on content

Importance of speed

Importance of conn quality

Social media usage

Social media usageHigh use of self-service

“Customer 360” -> data across channels, across business areas, across qualitative and quantitative

What is our customer profile like?

dnatv+pin

What’s wrong?

What’s wrong?

Where to put networks?

Class: TV, LiigaRank: 0.87, 0.90

What happens in social media? What is talked

about?

Type x

Type y

?

?

John Doe Teemu Selänne

?

John Doe Teemu Selänne

A bunch of Teemus

?

Mark.Automation

FB, Insta, online ...

TV, Radio, printti.. DNATV

H2H (DNAK)

OB

John Doe Teemu Selänne

A bunch of Teemus (?)

Segmentti 1 Segmentti 2 Segmentti 3 Segmentti 4

Customer “delight”:How to get the most of what you already have bought, brought to you with the channel you prefer

1 0 1 1 0 1 0 0 1 1 1 0 1

Customer “delight”:How to get the most of what you already have bought, brought to you with the channel you prefer

1 0 1 1 0 1 0 0 1 1 1 0 1

THIS “MACHINE” RUNS MOST OF OUR ACTIONS!

SEE ALL ASPECTS IN REAL-TIME (1) AND BE ABLE

TO ACT IN REAL-TIME (2).

Looks good, right? Let’s look at the journey

The BIG THING(s)

1. Business: it was the omnichannel customera. the ever-more-demanding, influential and independent customerb. rise of need for analytical insight & datac. demanding inf. management and analytics to be operational, not

finance-drivend. stop sub-optimizing the system (customer)

2. Tech: it was cloud, open-source, and data sciencea. suddenly - endless scale & processing powerb. reduced time-to-environment from weeks to minutesc. reduced costd. ability to create intelligent data products that reduce time-to-insight and

time-to-action

System requirements- Infinite scale- Process 10’000++ messages per sec- Automated deploy & tests- Version control- Pay-for-use, not for-licence- Real-time pipeline, disaster recovery, exactly-once-quarantees- Real-time analytics, sub-second latency for everything- Infinite processing power for data science stuff & large analytical deployments- Array of libraries to make the data scientist’s life easier - Modular, i can change any part of it, being that software or hardware- Secure, EU referendums and Safe Harbour etc.- Pipeline and persistent storage & data platform can be done from scratch to

production in 6 months - Cant cost really anything, since had to scrape a small budget. 3 developers max.

OKAY! SOUNDS FAIR.

Business requirements- Understand the omnichannel customer- Reduce churn- Increase cross-sales- Increase product usage & increase retention- Increase marketing ROI- Insight should be real-time - Actions should be near-real-time and everyone can do them- Know where to put infrastructure better than before- Make sense of unstructured data & text & speech & so forth- Automate 80% of insight / data that was previously done by hand- Your system shall not cost anything- But it should deliver competitive advantage

OKAY! SOUNDS FAIR.

WHAT WOULD MACGYVER DO?

WHAT WOULD MACGYVER DO?

WOULD HE:a) go and buy a licence and servers

and then wait aroundb) build the damn thing from what

he happens to find with zero cost

WHAT WOULD MACGYVER DO?

YES!b) build the damn thing from what he happens to find with zero cost

COLLECTreal-time

batchomnichannel

COMBINEdigital to brick n mortar

digital to everythingcontext to everything

customer to everything

COMPUTErecommendations

analysisreports

segmentspredictionsdescriptions

next best actionscustomer journey

EXECUTEchurn prevention

cross-salestargeted marketing

customer service efficiencycustomer experience improvement

omnichannel optimizationreact in real time

product development

CONTROLcontinuous deploymentinfrastructure as code

COLLECT

AWSLambda

AmazonS3

AmazonS3

Snowplow

COMBINE

single source of truth

processing power >> hadoop

ease-of-use

near-real-time

structured, unstructured, qvali, qvanti

COMPUTE

machine learning

recommendations based on algorithms

real-time

operational

exploratory analytics

descriptive analytics

ease-of-collaboration

possibility to run R, Python, ...

COMBINE

high performance database for real-time

applications

load balanced

message queued

realtime data pipeline

efficient batch loading with automated

invoking

“code as ETL”

EXECUTE

CONTROLcontinuous deployment

infrastructure as code+ highly skilled

developers & data scientists

automating all the things

Understand the omnichannel customer

Reduce churn

Increase cross-sales

Increase product usage & increase retention

Increase marketing ROI

Insight should be real-time

Actions should be near-real-time and everyone can do them

Know where to put infrastructure better than before

Make sense of unstructured data & text & speech & so forth

Automate 80% of insight / data that was previously done by hand

Your system shall not cost anything

But it should deliver competitive advantage

marketing automation for optimization &

automation of actions

visualization, reporting

SILVER BULLET?

The thing is, we have many MacGyvers, and demos.

MacGyver = The thinker-doer

- Usually development methods split thinkers (project managers, scrum managers, product owners and the lot) with doers (developers, analysts)

- This is (mostly) shit- You’d need people leading who also do the stuff

- Saves money, time and nerves- People communicate better

- Thinker-doers can communicate with business and translate to development actions, even develop the things themselves

Demos & openness = The secret sauce to everything

- We sit on the “business floor”, right in between of basically everyone- And we almost always have something displayed on a screen- VPs, directors and the like stop and ask what we’re doing -> we show them ->

they’re like “WOW” -> we scale the thing to production and get business support

- We understand what the business needs, since we hear everything- We make it easy to come and talk to us- We make demos available to everyone

- This makes all the difference

Meetings!!11oneone

Since we started last summer, there has been fewer than 5 meetings arranged with the team or any subselection of that team.

Meetings vs communication?“You just sent your 23800th message”

Lessons learned

Understand the BIG THINGS (cloud, open source, omnichannel customer, data science, time-to-x)

Sit where business sits. And sit together.

Don’t use project managers who can’t code (or who are not really good in the subject domain).

Have a lot of data. If you don’t have it now -> create apps, loyalty programs or whatever. Get on the customer’s skin.

Apply advanced analytics to automate 80% of small decisions made all the time.

Continuous communication beats meetings. Don’t meet.

SEE ALL ASPECTS IN REAL-TIME = bigdata AND BE ABLE TO ACT IN REAL-TIME =

data science.

THANKS!

The thing is, we have many MacGyvers. -> and recruiting!