Dr Peter Schulz-Rittich from Deutsche Post DHL presents Operational Intelligence and Analytics use cases at SplunkLive! Munich 2019

1. Dr. Peter Schulz-Rittich | Deutsche Post DHL
26 March 2019 | SplunkLive!
Splunking Parcels
Operational Intelligence and
Business Analytics for
B2C E-Commerce Logistics

2. Deutsche Post DHL 2
Deutsche Post DHL – the world’s largest and most international
Mail and Logistics company
No. 1 in contract logistics
Leader in the forwarding business
Europe’s largest postal service
No. 1 in international express delivery
Partner for e-commerce and a pioneer
in secure digital communications
 520.000+ employees in more than
220 countries and territories
 Group revenues EUR 61.6bn
 Germany
 57m mail items/day
 5m parcels/day
 Globally
 #1 in TDI express
 #1 in air freight
 #2 in ocean freight
 #1 in supply chain
outsourcing
SplunkLive! | 26 March 2019

3. Deutsche Post DHL 3
DPDHL Digital Transformation Framework
Packstation
Automated booths for
self-service collection of
parcels and oversize letters
PostBOT
Autonomous transportation
support for mail couriers
On Demand Delivery
Customized delivery
for Express customers
Saloodo
Virtual B2B transport
marketplace
SmartTrucking
IoT-enabled trucking solution
across pan-India linehaul
express road network
Resilience 360
Cloud-based end-to-end risk
management solution
Business
Exploration I
Technology
Exploitation i
Culture & Capabilities
SplunkLive! | 26 March 2019

4. Deutsche Post DHL 4
Scan Events
“B2C E-Commerce Logistics” … ?
Our core business is transporting, sorting and delivering parcels
Customer/Shipper Sorting Hub Delivery Depot Consumer/Recipient
Encoding and Dim weight scanning at Hub
Destination Depot processing
Last Mile delivery attempt
SplunkLive! | 26 March 2019
Customer pre-alerting of shipment

5. Deutsche Post DHL 5
South East Asia – how we started
SplunkLive! | 26 March 2019

6. Deutsche Post DHL 6
Problem statement: growing pains
• Strong business growth
• Suboptimal transparency of key business drivers
• Manual and error-prone reporting, no analytics
Time
Monthly
revenue
 Granular and real-time
transparency of key
business drivers
 Flexible, user-friendly and
scalable data platform
 Start journey towards
data-driven organization
Need to act – key objectives
SplunkLive! | 26 March 2019

7. Deutsche Post DHL 7
Splunk deployment and architecture
 3 countries in South East Asia
 11 mn events/day
 2 GB/day
 Small team of initially 2-4
 Net project duration ~ 6
months
 Community across functions
and markets
 15 power users
 10s to 100s of users
Real time
(log files)
Real time
(log files)
Batch
(SFTP)
Real time
(API)
Core
Ops
Last Mile
Ops
Data sources
Data platform
Use cases
Interfaces
SAP
Interactive
reporting
(Browser)
PDF/CSV
Automated
standard reporting
(Email)
Trigger-based
alerts
(Email)
!
Reference
DB
SplunkLive! | 26 March 2019

8. Deutsche Post DHL 8
Use cases
Operational Intelligence
• End-to-end transparency of
parcel logistics process
• Automated operational
intelligence for process
optimization
 Delivery productivity
 Service quality
 Parcel ageing
Business Analytics
• Deeper understanding of
customer behaviour
• Automated business analytics
for customer portfolio
optimization
 Shipping profiles
 Revenue assurance
 Pricing analytics
Real-time Visibility (future)
• Monitoring and alerting for
critical business processes
• Key operational and customer
KPIs in real time
 Peak management
 Process disruptions
 Proactive customer
service
SplunkLive! | 26 March 2019

9. Deutsche Post DHL 9
Example: understanding delivery productivity
Operational Intelligence
 Daily management dashboard
 Delivery productivity by Depot
against target
 Drill-downs from country to
regional to individual depot
view
SplunkLive! | 26 March 2019

10. Deutsche Post DHL 10
Example: understanding service quality
Operational Intelligence
 Interactive dashboard
 Service quality by origin/
destination, date, customer
cluster
 Drill-downs to date, destination
depot
SplunkLive! | 26 March 2019

11. Deutsche Post DHL 11
Example: understanding shipping profiles
Business Analytics
 Daily management dashboard
 Overview of last business day,
last 7 days, last N weeks
 Shipping profiles for Top 10
customers
 Drill-downs to date, customer
SplunkLive! | 26 March 2019

12. Deutsche Post DHL 12
Example: peak management
Real-time Visibility
 Real-time monitoring of hub
volumes
 Hourly volume distribution
 Regional volume distribution
SplunkLive! | 26 March 2019

13. Deutsche Post DHL 13
Key results thus far
Business value (early stage)
 Peak management – service quality, cost
 Analyst effectiveness via automation of reporting
Key learnings
 Standard SW platform, internally hosted
 rapid prototyping, data stays in-house, scalable
 Agile and incremental development
 driven by business value, based on available data
 Cross-functional team is key to start
 scale via community approach
SplunkLive! | 26 March 2019

14. Deutsche Post DHL 14
Next steps
SplunkLive! | 26 March 2019
Production grade platform
 Scalable and secure Splunk-aaS offering via
internal IT shared services organization
Use case scaling
 More use cases
 More data sources
Data analytics community
 Power users as multipliers in functions and markets
 Democratization of data and analytics

15. Deutsche Post DHL 15
Thank you!
SplunkLive! | 26 March 2019
peter.schulz-rittich@deutschepost.de
https://www.linkedin.com/in/dr-peter-schulz-rittich-05a1186/
@psrittich