Auf der diesjährigen PEX2019 Konferenz in Berlin habe ich über unsere Erfahrungen mit Process Mining (Celonis) gesprochen.

1. CUSTOMER JOURNEY &
PROCESS MINING FÜR
FAKTENBASIERTE
ENTSCHEIDUNGEN
6. JAHRESFORUM
PROCESS EXCELLENCE
DACH 2019
GUNNAR OBST
29.01.2019

2. ZALANDO

3. 3
PLATFORM STRATEGY
BRANDS CONSUMERS
ENABLER

4. WHY PROCESS
MINING?

5. 5
EXPECTATION

6. 6
REAL WORLD

7. 7
TRANSPARENCY
PROCESS
IMPROVEMENT
DATA
INFORMED
DECISION
MAKING
CUSTOMER
JOURNEY
ANALYSIS
PURPOSE FOR ZALANDO

8. 8
ZALANDO
PLATFORM
Event
Bus
Data
Lake
Big
Query
Event
Log
Others
DATA PROCESSING @ ZALANDO
ANALYTICS
PROCESS
MINING
PROCESS
MONITORING
GOOGLE
ANALYTICS
OTHERS...

9. PROCESS MINING
USE-CASE I

10. 10
USE-CASE:
Identify the root-causes why customers did not order after registration (specific countries)
Registration
started
Address
information
Order
created
REGISTRATION
ADDRESS
SELECTION
SHOPPING
REGISTRATION PROCESS &
ONSITE TRACKING
Extract
data and
push it to
Celonis
ANY
REGISTRATION
START
REGISTRATION
FINISH
ANY
DROP OFF
ORDER
CREATED
DATA VISUALIZATION
~70% ~30%
CHECKOUT / REGISTRATION PROCESS

11. 11
25%
22%
12%
8%
Payment Selection Pageview
Cart Pageview
Confirm Order
New Account Pageview
8%Address-Default overview pageview
4%Address - Edit/add home pageview
Exit Points
Next Steps Deep Dive Analysis
A-B Testing
CHECKOUT / REGISTRATION PROCESS

12. PROCESS MINING
USE-CASE II

13. 13
Return in cep
network
Return order
created
Return refund
successful
Return in cep
network
Payment
reminder sent
900
50
Return order
created
850
Refunds
completed 850
Customer
return
Return in
Warehouse
Refund
RETURN PROCESS & BUSINESS
EVENT TRACKING
USE-CASE:
Identify optimization potentials in the return process (one specific shipping country).
DATA VISUALIZATION
Extract
data and
push it to
Celonis
RETURN PROCESS

14. 14
IMPACT
● Customer Contact
Cost
● NPS
● Potential financial
loss
ROOT CAUSE
Hypothesis:
● Parcel gets lost on
the way or in our
facilities
● Return order
created event is
not written
SOLUTION
Parcel delivered
to customer
Customer
returned: Return
in cep network
Return in
Warehouse
Manual refund
● Follow up project
with our Business
Excellence team
RETURN PROCESS - FINDING

15. CHALLENGES &
SOLUTIONS

16. 16
BUY INSCOPEDATA
● Knowledge about data
missing
● Data quality insufficient
● Too much data
● Long data processing
time
● Deep domain
knowledge missing
● Unclear expectations
● KPI to be influenced
missing
● Prioritisation conflicts
● Commitment from
project members
missing
● Management buy in
missing
CHALLENGES FOR ZALANDO

17. 17
SOLUTION APPROACHES
Zalando AWS account
Celonis
Application
Server
DB*
Data
Models
Pre-
Discover
Data
DATA DISCOVERY
*Mega Eventlog with billions of
datasets, different identifiers, …
PROJECT SETUP
● Moved from process discovery
towards very concrete questions
● Upfront defined KPIs which we
want to influence
● Put the stakeholder into the
drivers seat

18. CONCLUSION

19. 19
● ...use real data from the process itself
● ...can be combined with six sigma &
lean principles
● ...especially for process heavy topics
● ...fast where standard data connectors
to mining tool are available
POWERFUL TECHNIQUE
● ...right data (must fit your needs)
● ...data quality (complete and correct)
● ...tooling (mining & data processing)
● ...expertise (domain, data & mining)
PREREQUISITES

20. 20