SCS Special 2016 – Higher, faster, better

Editorial

Dear Readers,

 

Data keeps companies competitive: If used correctly, it makes processes more efficient, opens up opportunities for flexibility and speed, and supports companies in transforming traditional underlying business models.

If analyzed and interpreted correctly, data can be turned into key figures that can be used not only to control company processes better and then to continue to optimize them systematically, but these numbers and this information can also be comprehensively turned into new business models. This is an effect that will continue to grow in times of increased digitization and automation.

Which data is the right data? Which processes can be made more efficient with data and key figures? What kind of new business models result? What prerequisites are needed, what technical infrastructure, which type of company organization? And, what can we do today, and what is worth doing?

Many companies have not yet been able to develop any solutions or strategies in this area. There are, however, certainly some interesting approaches as to how data and key figures can be used, with or without the support of technology, to improve processes and thus increase value creation.

Collecting, analyzing, and optimizing – and then evaluating – data from processes is the core business of our center for applied research. That is why, for this issue of SCS Special, we have decided to pursue these questions with some of our partners from practice, while being well aware how complex, networked, and diverse the world of corporate data already is. For a clearer overview, the ideas and projects presented here are oriented towards the elementary stages of the value-creation process, from production and warehouse, transport, and distribution activities to the customer’s door. The articles are marked accordingly.

We hope to be able to offer you not only some interesting reading, but also a clear way of shining some light on the question of how today’s technologies and methods can be used to produce data and key figures that will improve your company’s efficiency and turnover tomorrow.

Kind regards,
 

Prof. Dr. Alexander Pflaum
Head of Fraunhofer Center for Applied Research on Supply Chain Services SCS

Dr.-Ing. Roland Fischer
Managing Director of Fraunhofer Center for Applied Research onSupply Chain Services SCS

Contents

SMART NEW WORLD

How digitization is changing companies

01 PRODUCTION

THE STATE OF PLAY

Industry 4.0 in Production

INDUSTRY 4.0 YOU CAN TOUCH

A hall for intelligent processes

SMART SERVICE FACTORY

From key figure, to cloud, to new service

02 WAREHOUSE

HARD AND SOFT KEY FIGURES IN THE WAREHOUSE

How warehouse performance and employee motivation are connected

DIGITIZATION IN THE WAREHOUSE

The new type of order picking with »pick-by-local-light«

PRACTICAL TEST OF THE ORDER-PICKING SYSTEM PICK-BY-LOCAL-LIGHT PBLL

Interview with Andreas Rögnitz, BSH Hausgeräte GmbH

ANALOG GOES SMART

Container management of the future

THE FUTURE IS SMART

Container management in times of digitization - Interview with Mario Graßy, Böllhoff GmbH and Peter Steyer, Bosch Rexroth AG

03 TRANSPORT

BETTER PURCHASING

Comparison of freight costs in the chemicals industry – Interview with Stefan Bartens, BASF

FREIGHT COST BENCHMARKING

For more efficiency and lower costs

PUTTING LOGISTICS COSTS AND MARKET COSTS TO THE TEST

From peering into a crystal ball to a key figures-based cost forecast

TRANSPORT LOGISTICS 4.0

How data (could) revolutionize the transport process– Interview with Matthias Braun, Volkswagen AG

THE FASTER PATIENT

Transport optimization with a difference

 

04 SALES

SALES CONTROL IN CONTRACT LOGISTICS

Optimizing Sales with key figuresand benchmarks  

 

05 COSTUMER

THE USER AS A DATA PROVIDER

Co-creation in the open innovation lab JOSEPHS®

REPORTS FROM PRACTITIONERS

Lessons learned – Interview with Thomas Harmes, Mifitto GmbH

MORE BUSINESS THANKS TO THE RIGHT DATA

How process data changes business models

A LOOK TO THE FUTURE

The importance of data in the value-creation networks of tomorrow

WHAT WE’RE READING

Recommended reading