Professor Arjan van Weele on Supply Network Collaboration: companies unaware of how dependent they are

On October 30th, the Data2Move community will meet again to explore Supply Network Collaboration. In this two-part article, Arjan van Weele, professor of Purchasing and Supply Chain Management, shines some light on this thought-provoking topic: “Companies can no longer ignore the fact that good collaboration is vital.”

Many of us are not aware of this, but we are all completely dependent on others. For our survival, for peace, for prosperity. Especially now that the world is becoming more and more interconnected. We have to learn how to collaborate in networks,” says Professor Van Weele.

Companies often don’t realize how dependent they are. Until there’s a flood in Thailand, leaving three factories under water that produce semiconductors, required by companies here to make Printed Circuit Boards – who then send people home, because the process grinds to a halt.”

Competition is becoming a myth

Based on our research, we can now see that competition is becoming a myth,” he states. “One supermarket competing with another… That’s not really what’s going on. It’s these companies’ supply chains that are competing. Look at the automotive world: it’s the suppliers of Volkswagen that define the quality of their cars.”

By now, we have realized that companies are so dependent on their supply chain partners, for the quality of their products and services, as well as their reputation, that they can’t ignore the fact that good collaboration is vital. It is ASML’s network that enables the company to realize the innovations they need in order to survive. They have to innovate every 18 months. Moore’s Law. You can’t make that happen with a loosely coupled system. Supply Network Collaboration is about companies, their suppliers, their customers and knowledge partners, all joining forces in a network.”

Different approaches to Supply Network Collaboration

The interesting thing is that you can approach it from different angles. From the innovation side, or from the operations side. From the logistics side, of course: how do we optimize the flow of goods? From the procurement side – how do the various parties deal with each other in terms of contracts? Or what about the IT side: how do we exchange data, how do we make sure all partners are connected?”

And, last but certainly not least, there is the human side of enterprise: how can we get people from different companies in different sectors, all with different company cultures, to work together without any obstacles?”

It’s far from easy,” says Professor Van Weele, and he smiles: “Well, that’s the theme of the day!”

Next week: part 2, on companies who are doing this well, and the first steps you can take on the way to Supply Network Collaboration. Data2Move members: be sure join us on October 30th!

Data2Move event report: Data-Driven Inventory

June 14, 2018 – hosted by community partner SAP in s’Hertogenbosch

During the interviews with our community members, the Data-Driven Inventory charter unequivocally raised most interest. The event was thus focused on sharing the first research insights on this common theme.

Opening with SAP and Sarah Gelper on the Data2Move Community

After a short welcome by Jan-Theodoor Wiltschek from SAP, Sarah Gelper from TU/e caught up on Data2Move’s progress: from the brainstorming sessions during the kick-off in September 2017, via the Data Ambition Session of February, to presenting the first results today and towards defining joint projects as a next step.

The First Results! – Insightful reports from 3 research projects

Time (in)efficiencies in demand planning by Nazli Akgül (Valeant)

How can demand planners use their time more effectively to obtain better forecasts and reduce backorder value? Using the Lean Six Sigma methodology, Nazli Akgül found that while time spent on forecasting increases accuracy, time spent on reports, meetings and data quality issues decreases accuracy. Her study also showed that time spent on backorder analysis and meetings with product managers decreases backorder value, while time spent on data quality issues increases backorder value. These results emphasize the need for integrated data quality systems.

Advised versus actual orders by Bob van Beuningen (Jumbo)

Why do store managers order different quantities than suggested by the order advise system? Bob van Beuningen found that the four most important reasons for such deviations are: second placings, changing weather, improving the store view and inventory collection. While store managers thus have good reasons to make order adjustments, these adjustments are often incorrect – especially when the actual order exceeds the adviced order. As a next step, he will investigate whether there are differences between product categories.

Starting with demand forecasting by Bas Buijse (TKT)

Which type of time series model best predicts demand for laundry? Bas Buijse conducted an extensive forecast method comparison, including external variables such as the mean temperature, humidity, sunshine duration and the GoogleTrends results of the search term ‘hotel’. His analysis shows that forecasts which take external variables into account can be very powerful and can help to better assign resources.

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Bas Buijse explaining the results of his research

Masterclass Mashup – Deep dive into one of the three key concepts in Data-Driven Inventory

Big Data to Mitigate the Bullwhip Effect by Zümbüt Atan (TU/e)

Zümbül Atan gave a masterclass on a very important phenomenon in inventory management: the bullwhip effect. There are some structural causes of the bullwhip effect, but there are also behavioral reasons caused by human decision making. She explained these causes by showing the results of a real-life experiment: the beer game. Although big data cannot entirely eliminate the bullwhip effect, integrating large and various sets of data in real time, sharing data and interacting in a collaborative manner can help to reduce the bullwhip effect.

Forecasting: Algorithm vs Human by Sarah Gelper (TU/e)

Sarah Gelper gave a masterclass on forecasting, focusing on the difference between algorithmic forecasting models and forecasting done by experts. Using her own research, other research and industry experience, she concluded that neither type of forecasting is better. Rather, a combination of algorithmic models and human expertise is virtually always the better option regarding demand forecasting.

Inventory and Transportation by Luuk Veelenturf (TU/e)

Luuk Veelenturf’s masterclass focused on transportation. The importance of online shopping over regular shopping is increasing and the role of transportation in online shopping plays crucial role. He highlighted the need for efficiency in transportation by increasing volume utilization and hit rates. In order to achieve this, the role of data science in transportation is very important. He also mentioned different kinds of data which can be used in transportation such as volume, travel & services time and delivery location. He concluded his presentation with the privacy issues in data that can be used in transportation for delivery optimization model.

Keynote Data-Driven Inventory in practice by Dori van Hulst (Pipple)

Dori van Hulst from Pipple took us on a treasure hunting trip. Just like on an actual treasure hunting trip, multiple elements are required for a successful data-science project: a clear goal, a crew, the data you want to use, knowledge and insights to gain from the data, deciding if the treasure is in line with company goals and data science techniques which are needed to find the treasure. All attendants defined these elements for their own treasure hunt, enabling them to take the first next steps.

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The community filling out their own treasure hunt list

Partners on Stage – Meet three community partners and their practice

CTAC has facilitated the new online platform called ‘Movement’. The community can use this platform to share updates on research projects, discuss ideas to benefit from each other’s expertise and keep the knowledge flowing in between meet-ups. Jordi Peters pointed out the importance of working together and their willingness to collaborate.

De Persgroep is a new member of the Data2Move community. Gerda van der Poel explained the challenges De Persgroep currently faces in light of the evolving landscape of news consumption, and the way their business is changing. As exploring data can help them to set up a new logistics strategy, De Persgroep is excited to improve their distribution with the help of Data2Move.

Siel Vroman introduced the Data2Move community member Pro Alliance. She explained the benefits of Zuckerberging your supply chains, thereby introducing the theme of next event: Supply Network Collaboration.

 

Logistics researchers present Data Ambition Matrix

How can you as a company make use of Big Data the upcoming years to work more effectively  in a supply chain? And where are you now? These questions can now be answered using the Data Ambition Matrix, developed by research community Data2Move.

Data2Move is the leading community on the interface of Big Data, Internet of Things, logistics and supply chain management. Academics from Eindhoven University of Technology, Tilburg University and the Jheronimus Academy for Data Science work together with companies like Den Hartogh, Jumbo, Nabuurs, SAP and Philips to find new solutions.

Formulate ambitions

“The community focusses on the usage of data to improve your organization and your supply chain,” says Paul Grefen, member of Data2Move and professor at the School of Industrial Engineering at Eindhoven University of Technology. Data2Move kicked-off in September 2017 and now presents their first tool: the Data Ambition Matrix. Inspired by the industry, Grefen tells: “Based on our collaborations with industry we saw that many companies do understand the importance of data, but have difficulties to formulate focused ambitions and to determine how to realize these ambitions.“

The Data Ambition Matrix is a framework that consists of two dimensions. Grefen: “A horizontal dimension that shows the level of integration of data, and a vertical dimension that shows the realization of this integration. We ask companies to plot themselves three times in the matrix: where are they now, where do they want to be in two years, and in five years?”

Looking beyond silo’s

“At the moment we see that many companies stay stuck at using data in silo’s within their own firm. The Procurement department collects data, the Manufacturing department also collects data, but they are not connected to each other. Then, it could be the case, for example, that the Procurement department purchases too much material because it is unclear what the Manufacturing department needs. The Data Ambition Matrix creates awareness of the opportunities that exist. On the realization axis, you can move forward to the usage of real-time data. On the integration level you can work to market-data-integration.”
“Traditionally materials, finance and workforce were the pillars of a successfull firm. Now data is the unneglible fourth pillar,” states Grefen. “In the very near future supply chains will be dynamically shaped by data. If you don’t respond to this as a company, you will lag behind.”

Watch the full video about the Data Ambition Matrix

Introducing Movement

Movement is our new platform, where the latest projects and updates are shared. As a member of Data2Move you are eligible to join this platform. The platform provides detailed information on each ongoing project and has contact details for both partners and students participating within Data2Move.

The platform also includes more detailed information on each charter and possible project directions.

Go to movement

Inquire about partnership

Event Summary of the D2M Community Meeting in February

20 February 2018

The second Data2Move Community event, with partners from industry and from Eindhoven University of Technology, took place on 20 February 2018.

Intro by Tom Van Woensel
Prof. Tom Van Woensel opened the meeting talking about the past, present and future of Data2Move as a community. He emphasized the importance of data as part of a decision support mechanism and explained the opportunities of projects within Data2Move in order to make data-driven operations real.

Keynote SAS + DHL (Edwin van Unen & Hans Schut): “Data Analytics for better decisions in Logistics – A use case at DHL LLP”

Edwin van Unen (SAS) and Hans Schut (DHL) introduced the topic of data analytics and its importance in logistics. They showcased how their collaboration led to cost reduction, improvements in many operational areas and increased sustainability. Mr. van Unen underlined the importance of transforming a world of data into a world of intelligence in order to gain competitive advantage, and explained the steps of data preparation, building analytical models, executing them on data and monitoring the results. In the use case presented by Mr. Schut, he emphasized that HDL has aimed to finding the middle ground between using a fully analytical solution and heuristics, to find the right balance in terms of accuracy and practical use. All in all, entering the world of machine learning and artificial intelligence requires both a company-wide data-analytical mindset and an integrated data platform.

The first Data2Move projects poster session: Project charters and projects started at companies by students within the Data2Move community

The students presented an overview of each charter and details on each project. The attendees had the opportunity to ask all their questions. These projects will be carried out from February to June and the (interim) results will be shown at the next meetup of the community on 14 June 2018. Here’s an overview of the ongoing projects:

Data2Move event table

Prof. Paul Grefen introduced the Data Ambition Matrix (Figure 1) using Porter’s value chain model. He explained various stages of data integration within a company and even within a companies’ market. Additionally, various stages of data implementation got explained as well. Both integration and implementation got used as axes for the Data Ambition Matrix on which the partners identified their current and future positions during the breakout sessions.

Workshop Breakout Sessions

The attendants and their respective companies were placed into 5 breakout groups. The purpose of the assignment was for companies to place themselves on the matrix (figure 1 & 2) with three pawns. The first pawn would indicate where companies think they are now regarding data integration and implementation. The second pawn would be placed where companies saw themselves in 2 years’ time and the third pawn would be placed where companies wanted to be in 5 years.

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Figure 1: Data Ambition Matrix

 

Each group engaged in a discussion on the placement of pawns and the level of realism of the aspirations of the pawn placements for the present and the future. Once discussion ended the groups returned to the main hall where they would place 3 stickers with company logo on one giant matrix with their final positions. The workshop made companies aware that they have to take action now order to reach a higher maturity level regarding data integration and implementation, and gave an understanding to the companies about their position relative to others.

Concluding the Data Ambition Workshop

Prof. Grefen concluded the workshop by explaining his findings about the matrix. Not many companies placed themselves in the lower levels of the matrix right now and neither aspired to get to the highest levels in 5 years. However, most companies aim to make improvements on both implementation and integration levels. The goal of the Data2Move Community is to contribute to this ambition by working together on shared problems.

Click here to go to the DAM article and video

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Figure 2: DAM in action

 

Partners on Stage

Some partners have been particularly active in the Data2Move community. They were given the floor to talk about what they have meant for the community and what is planned for the future.

Data2Move Laundry by Léon Wennekes (TKT)

TKT has facilitated multiple projects already for the community and with this presentation and short movie Léon Wennekes introduced even more projects and opportunities in the laundry industry.

H&S group on Big Data in Supply Chain Management by Lex Dogterom

Lex Dogterom from H&S explained their projects regarding big data and what role it will play regarding supply chain management and what opportunities arise with using big data. They are among the partners who already initiated a project in Data2Move.

SAP on hosting the next event by Jan-Theodoor Wiltschek

Jan-Theodoor Wiltschek from SAP talked about the importance of integration and working together. Furthermore, he announced the next Data2Move meeting to be hosted by SAP in Den Bosch the 14th of June 2018.

Wrap-Up by Tom Van Woensel

To end the day, Prof. Tom Van Woensel recapped the learnings for the partners at the meetup and humorously explained his vision upon the data matrix and where companies positioned themselves. Prof. Van Woensel talked about the future, more opportunities for projects and the growth of the community. He also informed the partners about Data2Move Platform where partners can find all relevant information as well as any updates for Data2Move and the projects which will be set up by Data2Move partner CTAC. Besides he emphasized its importance as a collaboration platform. After all was said and done the day turned out to be a success and afterwards there was time for some drinks and relaxation.

Report written by:
Sam Smetsers
Bensu Ucar
Lisa van Lierop

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DATA2MOVE
The leading community in Internet of Things and Big Data in Logistics
and Supply Chain Management

Take a look at the video of the event below: