Digitalization As Opportunity for Service Logistics Innovation

ISLA Focus Day – Service Logistics Innovation Digitalization as opportunity for Service Logistics Innovation

Dr. Frank Debus HC SV CS ML

Frei verwendbar © Siemens Healthcare GmbH, 2017 Spare Parts Logistics Scenario 2025 Our view from 2013 depends on digitalization

Main action fields had been defined for service logistics in the Picture of the future Scenario 2025:

• Glocalization • End2End visibility • Portfolio Enhancements • Regulatory • Additive Manufacturing • Battle for talents

Of which all have digitalization aspects to them…

Dr. Frank Debus | HC SV CS ML 2 Frei verwendbar © Siemens Healthcare GmbH, 2017 #csml2021 describes the way how to reach the vision - and every Focus Topic covers digitalization aspects

Expand Portfolio Develop our core business • Establish new CS ML services • Improve Managed Logistics Processes • Offer planning as a service via SCO solutions • Use state of the art End2End BPM • Support new digital services by offering to solutions (PEGA) operate the digital supply chains • Develop Robotic Process Automation to improve performance and productivity #csml2021 Be open and transparent Act agile & lean • Establish SCM content in LifeNet • Implement Lean solutions • Order (and material) transparency via • new tools e.g. Tracking app or new Reduce complexity technologies e.g. Digital Locker Box • Use data analytics methods for cabinets onsite optimizations

Empower our people Empower our people • Create cooperative work environment • Foster employee satisfaction • Test agile working methods in pilots e.g. • Position CS ML as attractive, future-oriented employer marketplace

Dr. Frank Debus | HC SV CS ML 3 Frei verwendbar © Siemens Healthcare GmbH, 2017 Automation of logistic processes is one of the main driver of digitalization along the service supply chain

• provides major benefits from digitalization for logistical processes • optimizes reaction time, reduces handling errors, or frees resources for more complex tasks • addresses different layers, e.g. ERP systems, Business Process mgmt tools or smaller macros

#csml2021 Develop our Automation core business

Dr. Frank Debus | HC SV CS ML 4 Frei verwendbar © Siemens Healthcare GmbH, 2017 Various Levels in IT integration can be utilized to automate supply chains processes

IT automation (BPA): End-to-End thinking required Robotic Automation (RPA): Point-to-Point thinking (high investment threshold) required (low investment threshold)

 Processes that have escaped automation (until now) y t

i  “Quick & dirty” (tactical deployment) beats the

x ERP

e perfect plan l p  Solutions are process agnostic (deployment across m • Automation on o ERP towers possible) c database layer

e Add-ons

g • Improved core

n BPM

a functionality • Closing Cockpits h

C • System consolidation • Workflows RPA Macros • Template approaches • OCR/ matching ƒOperations platforms ƒBackend integration

IT expertise Critical skills Process expertise

Dr. Frank Debus | HC SV CS ML 5 Frei verwendbar © Siemens Healthcare GmbH, 2017 Various Levels in IT integration can be utilized to automate supply chains processes

CS ML areas of application

IT automation (BPA): End-to-End thinking required Robotic Automation (RPA): Point-to-Point thinking (high investment threshold) required (low investment threshold)

Business Process Management (BPM): CS ML is using the end-to- Robotic Process Automation (RPA): automation without end business service processes on the standard middle-layer changing existing processes or systems/platforms. platform (PEGA) across multiple ERP, in total 7 processes ƒ CS ML is using a combination of SAP & VBA scripting established, e.g. ƒ Service parts Escalation process capabilities to automate tasks like master data administration ƒ Return clarification

SAP as the core of the CS ML business operation. Several tools have been established to automate and enhance repetitive processes, e.g. ƒ SIMORA, the transactional processing of returns is fully automated within the P41 platform ƒ Supply chain optimizer (SCO) improves the planning capabilities ƒ Automatic preference check

Dr. Frank Debus | HC SV CS ML 6 Frei verwendbar © Siemens Healthcare GmbH, 2017 We leverage small robotics solutions to improve performance & productivity in service logistics

Software robots: Macros/Scripts Source report - Daily source process steps: VBA/SAP scripting can be done by CS ML employees using Excel, Access or other easy to use desktop applications. The desktop solution used on global level (>20planers DE, BE, CN)

• Total workload: 1.323 hours/years • Suitable for robot: 1.234 hours/years (93%) • Automation effort: 30 hours • Estimated maintenance: 10 hours/year

Dr. Frank Debus | HC SV CS ML 7 Frei verwendbar © Siemens Healthcare GmbH, 2017 Smart inventory planning gets more integral in the end-to-end supply chain – “Planning-as-a-Service”

• will become more integrated into end-to- end supply chain by including further levels (e.g. depots, trunk stock) • considers growing data volume in continuous planning • increases CSML offerings by flexible Planning-as-a- Service for internal customers

#csml2021 Develop our core business & Smart Planning Expand Portfolio

Dr. Frank Debus | HC SV CS ML 8 Frei verwendbar © Siemens Healthcare GmbH, 2017 Service parts planning in countries – Today and tomorrow

Today Solution Tomorrow

• No transparency about service parts in countries (e.g. • Optimal fit between availability & inventory old materials) • Offer a standard tool (SCO Light) for service parts planning (in-vivo &in-vitro) • No standard IT solution in place to support service SCO light: parts planning in P58 • Availability 24/7 & easy usage Globally connected • Different maturity/skill levels in countries • Locally planned Planning of complete Deliver network: • Usage of outdated master data - local warehouse - depots / up-time-depots • No global solution available (in-vivo & in-vitro) - CSE trunk stocks • Time intensive and complex activity • Transparency /Exchange about planning of • No good practice exchange (are the correct parts different countries planned)

Dr. Frank Debus | HC SV CS ML 9 Frei verwendbar © Siemens Healthcare GmbH, 2017 Track & Trace along the supply chain provides transparency to field teams and customers

• enables better planning and dispatching of field teams due to detailed delivery information • goes mobile with iOS/Android • positions CSML as transparent partner of customers and regional units

#csml2021 Be open and transparent & Track & Trace Develop our core business Dr. Frank Debus | HC SV CS ML 10 Frei verwendbar © Siemens Healthcare GmbH, 2017 Digitalization in the Service Transport Chain of Siemens Healthineers

2017 Digital Onsite The digitalized freight volume Locker increased significantly between 2017 Boxes 2001 and 2016 from 150,000 to Delivery 950,000 shipments, digital Tracking 2017 App response rate increased from 2013 DGD online 35% to ca. 94% 2011 Paperless Dangerous Proactive transmis- Goods 2009 messaging in sion of ex- 2007 Automatic case of port do- Electronic cuments 2006 export de- irregularities proof of ex-port claration (SCEM) Electronic (accepted by (ATLAS) 2001 2002 provision Automated Fiscal Transport 2001 of customs Authorities) ordering and freight data (GSCD) Local TMS Crediting confirma- NB, Hays, tion via Schenker EDIFACT

Dr. Frank Debus | HC SV CS ML 11 Frei verwendbar © Siemens Healthcare GmbH, 2017 Delivery Tracking App for Service Orders – Mobile, Comprehensive and Pro-active

Where do we come from ? • Only limited visibility for technicians on the status of their service parts deliveries • Communication efforts/interface and additional cost Americas: PDT App Short term mission: Parts Delivery Tracker • Provide easy and mobile tracking as well as proactive delay messaging of parts for CSE worldwide Long term strategy: • Develop a real, globally available Delivery Tracking App • Link the Tracking App to Service IT device RoW: Web-App – to Benefits for Siemens Healthineers and our Customers: be integrated into • Faster information and better planning upon parts delivery iOS/Android • Avoidance of extra cost for travel and search times in hospitals or other drop-off points in case of delays

Dr. Frank Debus | HC SV CS ML 12 Frei verwendbar © Siemens Healthcare GmbH, 2017 Digital Locker Box Cabinets Onsite – A Smart Way to Deliver Our Service Parts

Technology Benefits • Our new concept for digital locker • Total cost of ownership is lower box cabinets is based on a compared to ordinary in-room or ‘Bluetooth’ and battery solution - offsite locker deliveries operated by an App on the • Transports at any time until early technician’s smart- or iPhone morning and not during rush • Parts are scanned in and out of hours – Especially helpful in the locker box and captured via congested cities and big hospitals GPS on a central dashboard with limited parking • Engineers know exactly where to find their parts – no wasting time and risking the SLA

Dr. Frank Debus | HC SV CS ML 13 Frei verwendbar © Siemens Healthcare GmbH, 2017 Work 4.0 puts new concepts around modern work environment into use

• comprises different trends and new approaches to work • CSML puts empowerment in the focus

#csml2021 Empower Work 4.0 our people

Dr. Frank Debus | HC SV CS ML 14 Frei verwendbar © Siemens Healthcare GmbH, 2017 CS ML Marketplace

What Why • An intranet based platform to offer • As an additional motivation for people. jobs/tasks to people. • To utilize all capabilities and knowledge of • Reverse allocation of tasks within our people for CS ML. organization. • Better know-how transfer. • New approach how project teams should • To establish an agile organization culture. organize themselves and structure their work. • First step CS ML only. • As a change to the way we work today (max. 10% of working time).

Dr. Frank Debus | HC SV CS ML 15 Frei verwendbar © Siemens Healthcare GmbH, 2017 Other Work 4.0 examples at Siemens

Hackathons SSN Co-Creation Online Foren Working out loud Marketplaces Wikis MOOC Augenhöhe

Dr. Frank Debus | HC SV CS ML 16 Frei verwendbar © Siemens Healthcare GmbH, 2017 Big Data & Data Analytics can provide in-depth insights on the complete supply chain much quicker than in the past

• enables easy analysis and decision making – for everyone from dispatch to management • increases productivity by better transparency and information availability

Act Agile and Lean & Develop our core Big Data Analytics business

Dr. Frank Debus | HC SV CS ML 17 Frei verwendbar © Siemens Healthcare GmbH, 2017 Data Analytics & App-based decision support helps engineers to improve efficiency in field service

Managing service parts Ordering service parts Service Part Usage Dashboard

Troubleshooting and Non-Defect-Found Rates are Troubleshooting and Non-Defect-Found Rates are brought consolidated centrally to provide transparency and enable to field teams to improve decision making: benchmarking Order or not order a service part?

Dr. Frank Debus | HC SV CS ML 18 Frei verwendbar © Siemens Healthcare GmbH, 2017 Digital solutions helped to reduce troubleshooting returns dramatically

Global Troubleshooting Rate

30% Better information 25%

20%

Financial incentives 15%

10%

Consistent 5% communication 0% 0 1 2 1 2 3 4 5 6 7 8 9 0 1 2 1 2 3 4 5 6 7 8 9 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 ------4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Dr. Frank Debus | HC SV CS ML 19 Frei verwendbar © Siemens Healthcare GmbH, 2017 Digital service delivery operations is responsible for non- physical supply chains

• includes software distribution, license management • applies the mindset of physical supply chain management on non- physical deliveries

Operating digital supply chain Expand Portfolio

Dr. Frank Debus | HC SV CS ML 20 Frei verwendbar © Siemens Healthcare GmbH, 2017 Digitalization creates new services with opportunities for Service Supply Chains

Service parts logistics • Manufacturing • Warehousing • Order • Proof of delivery • Transport • Repair fulfillment • Order to cash

Service Supplier SOURCE DELIVER Customer Logistics

Non-physical

services • Programming • Server space • Order • Proof of delivery • IT Support • Data transfer • Data warehouse fulfillment • Order to cash • Application Training

Dr. Frank Debus | HC SV CS ML 21 Frei verwendbar © Siemens Healthcare GmbH, 2017 Software Update Delivery from Warehouse to Customer Digitalized Logistics

Reliability Real-time information for factories

Speed Fast in-time delivery over the internet

Cost-efficiency Electronic turn-over at system, customer installable

Dr. Frank Debus | HC SV CS ML 22 Frei verwendbar © Siemens Healthcare GmbH, 2017 Administration of Digital SCM Delivery Network essential Digitalized Logistics

Operations Ensure high availability

Administration User- and role management

Reporting Operational reports

• We further push digitalization along the entire Supply Chain and for all phases of the product lifecycle • Various IT strategies are chosen to respond to the different process requirements #csml2021 • Internet of Things, Big Data & Data Analytics offer further opportunities for higher transparency in our processes • It‘s a journey

Dr. Frank Debus | HC SV CS ML 24 Frei verwendbar © Siemens Healthcare GmbH, 2017 Thank you for your Frank Debus attention! Head of Customer Service Managed Logistics

HC SV CS ML Hartmannstrasse 16 91052 Erlangen

P +49 (9131) 84 72 61 M +49 (1522) 279 7958 E [email protected]