Author: dsa_admin

“Innovation is going beyond state of the art – which means risk” – Anton Demarmels, Swissmem

“Innovation heisst, die Grenzen des State of the Art zu überschreiten – und das bedeutet Risiko” – Anton Demarmels, Swissmem.

The well-known song, 12 Days of Christmas, is heard around this time of year, just as we at the Databooster were “gifted” 12 idea talks at the every first Project Day and Christmas Lounge event. The Databooster ideas were in various phases of development across the data clusters “Industry 4.0”, “Smart Services”, “Ethics”, and “Sustainability”.

Das bekannte Lied “12 Days of Christmas” hört man um diese Jahreszeit, und auch wir beim Databooster wurden am ersten Project Day und der Weihnachtslounge mit 12 Ideenvorträgen “beschenkt”. Die Databooster-Ideen befinden sich in verschiedenen Phasen der Entwicklung in den Datenclustern “Industrie 4.0”, “Smart Services”, “Ethik” und “Nachhaltigkeit”.

What set this event apart from usual success stories was the melting pot of – at first glance – bizarre but brilliant future innovation ideas generated during several rounds of breakout sessions. Sure, data can be used for predictive maintenance on infrastructure, and sensors could detect changes in living organisms such as plants. But what happens if we let the boundaries of normal brainstorming fall away to broaden the group idea horizon? Imagine a technology that would allow sustainable, plant-based or wooden infrastructure, such as bridges, to be built, which would employ drones to survey potential maintenance spots, fire off a signal to the relevant sensors, and the plant-based infrastructure could regrow those areas of concern.

Was diese Veranstaltung von den üblichen Erfolgsgeschichten abhebt, war der bunte Mix aus – auf den ersten Blick – skurrilen, aber spannenden Ideen für Zukunftsszenarien, die in mehreren Runden von Breakout Diskussionen entwickelt wurden. Klar, Daten können für die vorausschauende Wartung von Infrastrukturen genutzt werden, und Sensoren könnten Veränderungen in lebenden Organismen wie Pflanzen erkennen. Aber was passiert, wenn wir die Grenzen des normalen Brainstormings ausdehnen, um den Ideen-Horizont der Gruppe zu erweitern? Stellen Sie sich eine Technologie vor, die den Bau nachhaltiger, pflanzlicher oder hölzerner Infrastrukturen wie z. B. Brücken ermöglicht, bei der Drohnen eingesetzt werden, um potenzielle Wartungsstellen zu überwachen sowie Signale an die entsprechenden Sensoren zu senden, so dass die pflanzliche Infrastruktur die betreffenden Bereiche regenerieren könnte.

Why bother generating such wild ideas across separate industries? Because innovation can’t happen without bold steps. And bold, risk-oriented action can’t happen with a limiting mindset or an isolated environment. The Databooster puts the right people together to enable limits to fall away, ideas to be tested, pushed, and refined into tangible innovation.

Warum macht man sich die Arbeit, solch wilde Ideen quer durch verschiedene Branchen zu kreieren? Weil es ohne wagemutige Schritte keine Innovation geben kann. Und kühnes, risikokalkuliertes Handeln kann nicht mit einer einschränkenden Denkweise oder einer isolierten Umgebung geschehen. Der Databooster bringt die richtigen Leute zusammen, damit Grenzen wegfallen und Ideen getestet, vorangetrieben und zu greifbaren Innovationen weiterentwickelt werden können.

A painting is made up of both broader as well as finer brush strokes. Likewise, gaining an insider’s perspective on the broad range of stages in the ideas’ development enabled the participants to see the bigger picture of the Databooster program – with stumbling blocks experienced and successes celebrated.

Ein Gemälde ist ein Werk, das sowohl aus breiteren als auch aus feineren Pinselstrichen besteht. Genauso ermöglichte die Insider-Perspektive auf das breite Band der Ideen-Entwicklungsphasen den Teilnehmern, das Gesamtbild des Databooster-Programms zu erkennen – samt erlebten Stolpersteinen und gefeierten Erfolgen.

Let’s get into the specific talks.

Ideas such as “Predictive Maintenance for wind machines” by SSM Schärer Schweiter AG and “Cavity pressure-based machine learning for advanced injection molding processes” by Kistler Group have already conducted Deep Dives and evaluated their data. SSM found that their data does not yet allow for any conclusions to be drawn about future failures, so they must explore further avenues. URMA AG Tools and Machining have also already dug extensively into their idea; collected, evaluated and gained insights from initial data gathered.

Kommen wir nun zu den einzelnen Vorträgen.

Ideen wie das Thema “Predictive Maintenance for wind machines” der SSM Schärer Schweiter AG und “Cavity pressure-based machine learning for advanced injection molding processes” der Kistler Gruppe haben bereits Deep Dives durchgeführt und ihre Daten ausgewertet. SSM hat festgestellt, dass ihre Daten noch keine Aussagen über zukünftige Ausfälle zulassen, weshalb sie weitere Ansätze untersuchen müssen. Auch die URMA AG Tools and Machining hat sich bereits intensiv mit ihrer Idee auseinandergesetzt, erste Daten gesammelt und ausgewertet. Sie konnten bereits daraus Erkenntnisse gewinnen.

Certain ideas are at the stage where the technological feasibility is investigated and the data models to be used are being researched. One of the start-ups, Vivent, talked about a plant stress algorithm and sensors that would read the electric radiation emitted from plants to detect the stress situation of the plants, e.g. even in mild droughts, to alert commercial farmers. Such projects are particularly exciting, as they have great innovation potential due to the research still being conducted.

Einige Ideen befinden sich in der Phase, in der die technologische Machbarkeit untersucht wird und die zu verwendenden Datenmodelle erforscht werden. Eines der Start-ups, Vivent, sprach über einen Algorithmus zur Erkennung von Pflanzenstress und Sensoren, die die von den Pflanzen abgegebene elektrische Strahlung messen könnten, um die Stresssituation der Pflanzen zu erkennen, z.B. bereits bei milden Dürreperioden, um Landwirte zu warnen. Solche Projekte sind besonders spannend, da sie aufgrund der noch laufenden Forschung ein hohes Mass an Innovationspotenzial haben.

Lastly, there were early-stage idea stories by Swiss Re and Thinkgate, currently in the Databooster Shaping Stage. They mapped out the stakeholder’s and customers’ needs and laid out exactly how their data-based innovation projects bridge them. The overviews respectively included automating benefit identification in insurance, and centralizing data on flight irregularities and mitigating services thereof on a platform for consumer convenience.

Schliesslich gab es noch Ideengeschichten von Swiss Re und Thinkgate, die sich derzeit in der Databooster Shaping Stage befinden. Sie erarbeiteten die Bedürfnisse der Stakeholder und Kunden und schilderten konkret, wie ihre datenbasierten Innovationsvorhaben diese überbrücken. Zu den jeweiligen Ideen gehörten die Automatisierung der Leistungsidentifizierung in der Versicherungsbranche und die Zentralisierung von Daten über Flugunregelmässigkeiten und deren Abhilfe in einer Plattform, um den Verbrauchern die Neu-Orientierung zu erleichtern.

The festive apèro, dotted with fine Christmas “Guetzli”, led to the participants mingling, exchanging their impressions, and gave rise to the opportunity for further synergies. The event closed with feedback from the participants.

Der festliche Apéro, bestückt mit feinen Weihnachtsguetzli, bot den Teilnehmerinnen und Teilnehmern die Möglichkeit, sich zu begegnen, ihre Eindrücke auszutauschen und weitere Synergien zu knüpfen. Die Veranstaltung schloss mit einem Feedback der Teilnehmer.

“The Databooster builds a platform to guarantee exchanges.”“One always sees the same ideas being presented – except here! It’s astounding how unusual some of the innovation ideas across the panel were.”“It’s interesting how the applications proceeded in how they are able to move ideas forward across such a variety of industries. Coming to this event, one truly sees that there’s a real community to help you”.

“Der Databooster baut eine Plattform, um den Austausch zu garantieren.””Man bekommt immer die ähnlichen Ideen präsentiert – ausser hier! Es ist beeindruckend, wie originell einige der Innovationsideen im gesamten Forum waren.””Es ist spannend, wie die Bewerbungen verlaufen sind, wie sie Ideen in so unterschiedlichen Branchen vorantreiben können. Bei dieser Veranstaltung sieht man, dass es eine echte Gemeinschaft gibt, die einen unterstützt”.

Thank you to the participants for their active engagement! Missed out? Don’t worry, we are hosting the next Project Day on April 18, 2023!

Vielen Dank an die Teilnehmer für ihr aktives Engagement! Sie haben es verpasst? Keine Sorge, wir laden Sie herzliche zum nächsten Projekttag am 18. April 2023 ein!

By Jürg Meierhofer, ZHAW

Successful Databooster presentations at the “smart maintenance insights” conference

On November 23, the “smart maintenance insights” conference was held in collaboration with easyfair. The Databooster framed the event with presentations by Andrew Paice and Jürg Meierhofer, who highlighted the focus topic “Dilemma between value creation and value destruction with data”.

Andrew Paice opened the presentation series with the topic “What data is enough for smart maintenance?”. The presentation started from the common view that data is seen as a panacea – “If I have enough data, I can do anything with machine learning – e.g. smart maintenance”. He outlined that, in contrast, more information does not necessarily lead to better decisions. These issues are particularly pressing in maintenance, where you really need the right data to make good decisions. How do you know if you have the right data or enough data? In the presentation, the use of machine learning was discussed and explained with examples from research.

After two very interesting industrial contributions by Thomas Faulhaber from Membrain Switzerland and Dominik Doubek from Sonic Technology AG, Jürg Meierhofer closed the arc with his presentation “How do Smart Service create sustainable value?”. Even if sufficient data of good quality is available, business-relevant value is not automatically created for the economic actors. When using so-called smart services (data-driven services), the goal must be to increase performance and reduce risks for the diverse actors in an ecosystem. In addition, smart services allow providers to differentiate themselves and strengthen customer relationships. Thus, the use of data for novel services has great strategic importance. However, without knowing the value of their data, it is difficult for companies to make the decision for the potentially large investments in its collection and processing.
The presentations are available on youtube:  https://www.youtube.com/watch?v=Sh7VxTTFpYY&t=10s

Dilemma zwischen Wertschöpfung und Wertzerstörung mit Daten

Von Jürg Meierhofer, ZHAW

Erfolgreiche Databooster Präsentationen an der Konferenz “smart maintenance insights”

Am 23. November fand in Zusammenarbeit mit easyfair die “smart maintenance insights” Konferenz statt. Der Databooster umrahmte den Anlasse mit Präsentationen von Andrew Paice und Jürg Meierhofer, welche das Fokusthema “Dilemma zwischen Wertschöpfung und Wertzerstörung mit Daten” beleuchteten.

Andrew Paice eröffnete die Vortragsreihe mit dem Thema “Welche Daten reichen für smart maintenance?”. Das Referat ging aus von der verbreiteten Ansicht, dass Daten als Allheilmittel angesehen werden – “Wenn ich genug Daten habe, kann ich mit Machine Learning alles machen – zB Smart Maintenance”. Er legte dar, dass hingegen mehr Informationen nicht unbedingt zu besseren Entscheidungen führen. Diese Fragen sind besonders dringlich in der Instandhaltung, wo man wirklich die richtigen Daten braucht, um gute Entscheidungen zu treffen. Wie weiss man ob die richtigen oder genügend Daten hat? Im Vortrag wurde der Einsatz von maschinellem Lernen diskutiert und anhand von Beispielen aus der Forschung erläutert.

Nach zwei sehr interessanten Praxisbeiträgen von Thomas Faulhaber von Membrain Switzerland und Dominik Doubek von Sonic Technology AG schloss Jürg Meierhofer den Bogen mit seinem Referat “Wie schaffen Smart Service nachhaltig Wert?”. Auch wenn genügend Daten in guter Qualität vorliegen, entsteht nicht automatisch Business-relevanter Wert für die wirtschaftlichen Akteure. Beim Einsatz sogenannter smart Services (Daten-getriebener Dienstleistungen) muss das Ziel darin bestehen, für die diversen Akteure in einem Ecosystem die Leistung zu steigern und die Risiken zu reduzieren. Zudem können sich die Anbieter mit smart Services differenzieren und die Kundenbeziehung stärken. Die Nutzung von Daten für neuartige Services hat somit grosse strategische Bedeutung. Ohne den Wert ihrer Daten zu kennen, ist es für die Unternehmen aber schwierig, den Entscheid für die potenziell hohen Investitionen in deren Erhebung und Verarbeitung zu treffen.

Die Vorträge sind auf youtube verfügbar: https://www.youtube.com/watch?v=Sh7VxTTFpYY&t=10s

By Nicolas Lenz, Litix, Stefan Keller, OST, and Reik Leiterer, ExoLabs

The Expert Group Spatial Data Analytics used the 2022 General Assembly of the Data Innovation Alliance in Zurich to organise an expert meet up beforehand – and 18 experts from research and industry took the opportunity and participated in the event. The aim of this event was, on the one hand, to identify topics of particular interest for the spatial data community, which will then be taken up at special events in 2023. On the other hand, current trends in the field of geodata and applications/solutions related to geodata were presented and discussed. The meeting was concluded with the presentation of exciting data sets and tools that are of great importance in the current work of the participants.

In the area of trends, possible thematic clusters of particular interest were outlined, developments in methodological approaches were presented and new approaches to solutions and applications were discussed.

In the context of the UN’s Sustainable Development Goals (SDGs), the Disaster Mitigation and Response theme complex stands out – themes, that are also of central importance in Switzerland and where geodata and their use/analysis are key to protecting the environment, infrastructure, and the population. This is linked to the wide field of Location Intelligence, e.g., visualizing (You all know heat maps, don’t you?) and analysing volumes of spatial data (often linked with non-spatial data), to enable holistic planning, insights for problem-solving, and advanced spatio-temporal forecasting.

Regarding data acquisition and evaluation, many new sensors, algorithms, and software packages are currently being developed in the field of 3D representation. This applies not only to the functionalities in existing solutions (e.g., 3D-GIS), but also to the linking of spatially explicit information with, e.g., the classic 3D model approaches in infrastructure planning (BIM) – with which we have gained another concept in the spatial universe: GeoBIM.

A lot of data means new possible approaches – and more and more use is being made of Machine Learning (ML) methods. But ML has very specific requirements for the data to unfold its full potential. One way to meet these requirements is to generate so-called Synthetic Data. This can not only help with an insufficient data basis, but also anonymise data in such a way that an exchange beyond the boundaries of one’s own organisational unit is possible even when working with sensitive information.

Also very exciting are the developments around SaaS applications and No-Code platforms, which will certainly lead to a strong increase in the use of spatial data. With the Metaverse, an additional field of development has opened in the last few months, which enables the spatialisation and visualization of our online activities. Hype, bubble, or opportunity – we will see.

New ideas, research projects and exciting applications were discussed in the subsequent exchange session: from the data pooling of freely available data (by Nicolas Lenz – Litix) and the integration of cloud computing services into locally running applications (by Dominique Weber – WSL), via interactive platforms for the joint work on requirements relating to the development/planning of spatial systems (Luis Gisler – cividi), to the power of customized machine learning tools in applied research (by László István Etesi – FHNW/ATELERIS). At this point, thanks to the presenters for the exciting insight!

You missed the Expert Day? – Don’t worry, there will be another one next year, along with several other exciting events on the topic of Spatial Data Analytics. Simply visit the website – and join the meet-ups where you can exchange ideas and initiate new collaborations with experts from research and industry. We are looking forward to you!

By Jürg Meierhofer, ZHAW

Since it’s origin in 2018, the Smart Services Summit has created a lively and relevant community of practitioners and researchers, with a relevant focus topic every year. Several implementation projects and other value creating initiatives emerged from this network.

On October 21, we got together for the 5th time to join industrial and academic experts to share ideas, this time with the focus topic „smart services creating sustainability“. The summit was hosted by Oracle at their excellent location in the Circle convention center at airport Zurich. We had a rich and extensive conference program and were able to establish excellent new contacts for future co-creation.

We will take this on to the 6th edition in 2023. The relevant topics are far from being exhausted, indeed they never run out, as in a dynamically changing context new opportunities and also urgent needs for the generation of benefits with smart service-oriented approaches are constantly arising.

By Jürg Meierhofer, ZHAW, and Philipp Schmid, CSEM

Almost 30 attendees actively participated at the workshop “Data Driven Innovation”. After an insightful introduction to the promising transition from predictive management to predictive quality by Philipp Schmid, Jürg Meierhofer gave insights into approaches for economic value creation. Upon this, the attendees gathered in small breakout groups and elaborated the data driven value creation patterns at their own case study examples. Some very interesting project ideas which could be further followed came out of this workshop. The databooster process provides a very helpful platform for further developing these ideas into implementation projects.

By Jürg Meierhofer, ZHAW

In the late afternoon of September 27, 2022, the Expert Group Smart Services gathered at ZHAW in Zürich. We enjoyed a presentation by Shaun West about the topic “Contracts for Advanced Services”.

Shaun West provided hints and tips on how to design and deliver advanced services based on expert know how and best practice. This is relevant for firms who are integrating digital with their traditional product and service offerings.

When selling advanced services, the conceptual and contractual complexities of such contracts are all too often underestimated.  Experience shows that this is especially true when selling into traditional B2B markets. The developing and longer-term nature of advanced services and the need for collaboration between seller and buyer should be reflected in the contract.  For example, the traditional approach of using ‘specification and data sheets within specified operating parameters’ for service contracts will need to be replaced with contractual structures reflecting the dynamic, evolving nature of advanced service contracts.

This creates challenges for both sellers and buyers of advanced services:  traditional mind-sets must be overcome, high-level advanced services outcomes / measures have to be agreed, flexible / adaptable contractual framework should be developed, and collaborative structures are required in the contracts.

By Jürg Meierhofer, ZHAW

Data Science, machine learning, artificial intelligence etc. are hot topics and deserve undisputedly a lot of attention. However, we always need to pay attention to whether and how we create value for the diverse actors in the ecosystem. For businesses, this means of course primarily economic value, but by far not only. Data-driven solutions also need to address other value dimensions of individuals, e.g., social or emotional values. This discipline of  “Smart Service Engineering” provides us with a set of tools and applicable procedures to achieve this. In the CAS Smart Service Engineering / Data Product Design, we work with these tools and directly apply them to case studies that are self-chosen by groups of participants.

Data Science, Machine Learning, Künstliche Intelligenz etc. sind hoch aktuelle Themen und verdienen unbestritten viel Aufmerksamkeit. Wir müssen jedoch immer darauf achten, ob und wie wir Wert für die verschiedenen Akteure im Ökosystem schaffen. Für Unternehmen bedeutet das natürlich in erster Linie betriebswirtschaftlichen Wert, aber bei weitem nicht nur. Datengetriebene Lösungen müssen auch andere Wertdimensionen von Individuen adressieren, z. B. soziale oder emotionale Werte. Die Disziplin des “Smart Service Engineerings” stellt uns dafür eine Reihe von Werkzeugen und direkt anwendbaren Methoden zur Verfügung. Im CAS Smart Service Engineering / Data Product Design arbeiten wir mit diesen Methoden und wenden sie direkt auf Fallstudien an, die von Teilnehmendengruppen selbst ausgewählt werden.

After three months of course, we had the wonderful opportunity to take our well-prepared case studies to the very inspiring environment of the castle of Thun, where we were made very welcome by our host Fabrizio Laneve, who is the lively and energetic manager of the Mobiliar Forum Thun. Brilliantly moderated by Ina Goller, the groups successfully further developed the value creation by their smart service concepts – with a strong focus on value creation in the ecosystem, considering all relevant actors. Thanks to these two consecutive days of workshop, accompanied by a nice dinner and an overnight stay in the castle, we not only brought our service concepts significantly further, but also learned a lot about methodology and additionally, very much strengthened our team spirit.

Nach drei Monaten hatten wir die wunderbare Gelegenheit, unsere gut aufbereiteten Fallstudien in die sehr inspirierende Umgebung des Schlosses Thun zu bringen, wo wir von unserem Gastgeber Fabrizio Laneve, dem sehr aktiven und inspirirenden Manager des Mobiliar Forums Thun, sehr herzliche empfangen wurden. Brillant moderiert von Ina Goller entwickelten die Gruppen die Wertschöpfung durch ihre Smart-Service-Konzepte erfolgreich weiter – mit einem starken Fokus auf die Wertschöpfung im Ökosystem unter Berücksichtigung aller relevanten Akteure. Dank dieser zwei aufeinanderfolgenden Workshop-Tage, begleitet von einem schönen Abendessen und einer Übernachtung im Schloss, haben wir nicht nur unsere Servicekonzepte deutlich weiterentwickelt, sondern auch viel über die Methodik gelernt und zusätzlich unseren Teamgeist deutlich gestärkt.

By Jürg Meierhofer, ZHAW

In the afternoon of June 8, the Expert Group Smart Services gathered at Kistler in Winterthur. After the very friendly welcome by the Kistler team, we got insightful presentations about the digitalization initivatives at Kistler and, specifically, Kistler’s way of digitalizing service with a focus on pilot projects in various fields of advanced services. These presentations were rounded up by a presentation of a turn-key solution by the Kistler Innovation Lab. Many thanks to Marc Schaad, Philipp Schenkel, and Thomas Wuhrmann for their presentations.

The presentations were followed by a tour around the company in break-out groups and an apéro. We had the opportunity to develop many new contacts and inspire ideas that we will follow up on. It was an excellent Expert Group event and we got the feedback of many participants that we should follow up with similar activities.