We are super excited that we had the opportunity to showcase our newest development ECEP at the ODI Summit in London. We demoed our newest analytical capability of analyzing specific technology and business trends in countries like Germany and UK – thanks to Open Data. The project team of ECEP at Implisense enjoyed listening and talking to high profile speakers such as Sir Tim Berners-Lee (creator of the World Wide Web), Sir Nigel Shadbolt (AI expert) and Martha Lane Fox (Lastminute.com founder).
Meeting Tim Berners-Lee at the Summit
Businesses, governments, charities, banks, supermarkets and many more are empowered by the web of data to become more open, more efficient and better connected. The summit began on 31 October with open data workshops, followed by an exciting day of talks, stories and demos from key influencers in open data on 1 November and an award ceremony for using open data to make a difference.
Occurrence of newspaper articles writing about “open data”, based on current Implisense news index for Germany
Being a leading B2B Sales Intelligence and Marketing Automation provider in Germany Implisense offers services critically relying on public and open data, e.g. company websites, register data, industry data and geo-data. With our ODINE-Project, the European Company Explorer Platform, ECEP, we want to offer our users a new analytical tool to monitor existing trends and to detect new trends in the European company landscape.
Due to the present and future importance of open data for ECEP – and Implisense in general – it is critical to us to have a solid and concurrent understanding of the European open data landscape. This contribution marks the beginning a series of blogs centred around open data in Germany. It is based on our experiences when building our open data network. It shall also raise the concerns of a previously rather silent, but important group of open data stakeholders: small innovative businesses.
Next in this series, we will use our Big Data Analytics to identify and analyse further companies and firms being part of the German Open Data ecosystem.
Open Data Ecosystem in Germany
Engaging into open data we have encountered different types of players in the German open data ecosystem. We distinguish between politicians and clerks, civil organizations, small innovators and large enterprises just starting to discover the potential of open data. Hence, we will use this distinction to discuss the current status of open data provision in Germany.
Politicians and Civil Servants – Decision Makers
In recent times, we have experienced a noticeable uplift in open data activities in Germany, especially after the constitution of G8 Open Data Charta. Politicians start to treat this topic more seriously. Both the Ministry of Economic Affairs and the Federal Ministry of Transport and Digital Infrastructure have launched large-scale funding programs for data-driven projects and companies partially covering open data business models: the Smart Data fund and the mFund programmes. The first draft of the Open Data Law has been worked out and we are feverishly awaiting its release. Given the rising popularity of Big Data Analytics more and more large enterprises begin to realize the potential of open data as one important source of intelligence for their businesses.
Yet, from our point of view as a B2B startup, there are several serious problems with opening data in Germany, which partially drives us to expand to a new market, the UK, as early as possible.
In particularly, we struggle with:
the lack of economically highly relevant open data, e.g. financial company data
the restricted coverage or depth of relevant open data, e.g. industry import-export statistics on for different levels industrial classification
the lack of legal clarity regarding the provision of certain open data, some data are announced to be fully open soon, in practice however there are still barriers to their access, e.g. company register data
the lack of “open data thinking”, understanding open data as a comprehensive concept and setting open data defaults, rather than a random provision of very different data sets
From our perspective many reasons for these shortcomings lie the nature of the German political system, depend on the individual skills and motivation of the responsible civil servants and are boosted by the undifferentiated public privacy concerns about publishing data of what kind so ever.
For instance, we experienced various workshops on open data where communal politicians complained about the lack of incentives for providing open datasets to the public. Typically, it is done by enthusiastic civil servants, who are willing to invest the final hours of a long working day to create some additional benefits for the community. There is no legal obligation for doing so as the current norms only recommend public authorities to provide data in an open format and if this is in line with the feasible expenditures of doing so, see this PDF. In addition, communal clerks often lack the skills or an easy-to-handle platform to make the data available in a suitable way.
Moreover, due to the federal system the responsibility to open up administrative data is scattered over several ministries, of which some are state specific. This leaves always the option to deny the responsibility for stagnating open data provision and multiplies any effort to engage into a full scale coordinated open data agenda.
The case of the company register data illustrates some additional problems. The intention to provide register data is prominently stated by the Federal Ministry of Economic Affairs. However, the provision of the company data is split across various local courts, the data input is manually maintained displaying countless spelling mistakes and inconsistencies. The task of providing an access to the data is delegated to a commercial provider having a monopoly for the register data, especially financial company data. Hence, preserving a totally outdated and unproductive business model at the cost of slower innovation through analytics with company data.
Nonprofits – Facilitators
The second group of open data players in Germany are non-profit institutions and foundations. There is an increasing number of think tanks, NGOs and such alikes that discover this topic for themselves. These players try to help politicians to address the issues above. However, for us Berlin based non-profit institutions and foundations played a key role in creating an open data network. For instance, one of the most active local institutions in the field of Open Data is the Technologiestiftung Berlin. It hosted numerous events around the usage and provision of open data, like the OD-Day Berlin in may 2016. Moreover, it has published some often referred to publications on the value (“Digital Gold”) and practical use of open data (“Open Data in Practice”).
Recently, the Konrad Adenauer Stiftung has also engaged into the topic of open data. The KAS is the party foundation of the Christian Democrats. It focuses on the overall economic value of open data and on Open Government topics. The involvement of a think tank so close to the biggest German party is important for the provision of open data. It also shows that this topic is at the verge of being taken seriously by politicians.
One of the first institutions working on the subject of open data was the Stiftung Neue Verantwortungin Berlin. To our knowledge this foundation engaged into the open data with a workshop in fall 2015, primarily focusing on Open Government and the issue how to open German administrative data faster. This foundation operates on federal level and was able to bring together some interesting Open Data stakeholders from civil society and politics.
There are many other institutional players that we have encountered on various events. Some of them concentrate not only on the promotion of open data but also provide, use and / or generate public value from them, e.g. Wikimedia or the Forschungszentrum Informatik in Karlsruhe, providing research for the Smart Data Program by the German Federal Ministry of Economic Affairs (BMWi). We also do not to mention the critical efforts of the Open Knowledge Foundation in developing an open data ecosystem in Germany.
Small Companies and Startups – Value Creators
These businesses typically generate value from open and public data by providing analytical services or simply information for specific B2C, B2B use cases. There is an increasing number of publications on this subject. For instance, the study by the Technologiestiftung mentioned above or the “Open Data”, a publication by the KAS including positive examples on the use of OD. Many of these companies create value out of open data and naturally have a strong interest in a better provision of these. Yet, they are tentatively small and have few influence on this process. Apart from Implisense a strong interest in the provision of machine-readable register data could have similar B2B Analytics providers. Examples for such businesses are Kantwert, a company focusing on link graph analysis of firms, and IPlytics, a market intelligence platform focusing on IP. Importantly, one should also account for other startups creating innovation using services based on such data and, hence benefiting indirectly from them, for instance, Spotfolio, a matching platform for high tech companies. There are also international stakeholders to opening German company register data, like Dato Capital or Open Corporates.
As opposed to these rather innovative companies, there is a not too small group of SMEs which is still building their business models simply on reselling links to company data available at the company register, e.g. unternehmensverzeichnis.de and moneyhouse.de. More surprisingly, even leading German business information providers, like Bürgel Wirtschaftsinformationen, are still relying on manually verifying company information through interviews instead of focusing on analytics and data mining.
Yet, particularly companies without extracting additional public data pools and or providing additional analytics, i.e. not innovating, are prone to changes in this domain. Accordingly, they are potential opponents to the provision of more open data.
Large Companies – Consumers (and Suppliers)
There are two types of open data players in this segment. Firstly, large companies actively exploring the disruptive potential of open data, for instance, Deutsche Bahn with DB Systel. Secondly, we consider large companies that start to realize the potential of open data to boost the efficiency or effectiveness of their core enterprise functions. This group of stakeholders is nicely reflected by the leads of our business, large enterprises from ICT, finance and publishing.
The establishment of our company was favoured by the realization of the potential of (big) data analytics for sales departments. This, in turn, led to the acceptance for analyzing external data sources for internal MI and BI purposes. Now, we observe that open data being part of our analytical services are increasingly recognized as a valuable source helping to establish a more effective sales process. To be more clear, more open data, like information on financial statements, could contribute to a more accurate segmentation of potential B2B customers for our clients. A better segmentation leads to higher conversion rates. Rising the conversion rates for a few B2B products of a large scale company by a few percentage points can quickly turn into two-digit million dollars of additional profits. In short, there is a free lunch waiting for the big boys, and they are just realizing it is there.
Accordingly, we believe that large enterprises could be key stakeholders to opening up more data in Germany. Whether it is for the increase in efficiency in B2B sales or a higher usability for private consumers as long as large companies are beginning to understand the value of open data to their businesses the demand for the provision of open data will increase as well. At the same time these large companies have the political weight to affect the political process of opening data sustainably. Examples for such companies can be found by looking at the mFund and Smart Data programs.
Some Lessons Learned
We do not claim that our experiences are fully representative. Yet, we think that they offer a valuable first impression about how the German Open Data ecosystem looks like. From the perspective of a B2B startup we arrive at the following key insights:
Despite a positive dynamics the process of opening more data in Germany lacks political coordination and incentivization. Especially, in the B2B domain this favours outdated business models, hinders innovation and the creation of economic added value. This is particularly the case for company register data. This does not only apply to technologies directly using open data, but also for any downstream innovation building on these services, for instance in the case of Spotfolio.
There are also implicit barriers to this process, particularly the lack of open-data awareness both in the private and the public sectors. Companies do not realize open data as a coherent concept. They use open data without referring to them as such which gives away an opportunity to highlight the benefits from open data. Meanwhile, the public administration works towards a broader open data provision without having a comprehensive strategy. Thereby, they miss out on the opportunity to set defaults for providing the existing data in a higher quality (coverage and depth) and opening up more data sources with maximum social and economic utility in the future, e.g. by harmonizing data standards and data provision processes as well as linking future (non-administrative) open data sources.
Large enterprises might play a key role in fostering the provision of open data, as they are in the process of understanding the value of open data. They would have the necessary resources, incentives and political weight to do so.
Note that there is a lot that could and should be done in the political domain about a better provision of open data. However, there are also responsibilities and opportunities that lie within the private sector.
In our next blog article, we will show results from our prototypical “Open Data Radar Germany”. For that we will analyze our open and public company data sources to find further companies and institutions being part of the German open data ecosystem. We also will show what distinguishes them from other companies in Germany. If you have any feedback on this article, do not hesitate to contact us. You can also meet us in person at the this year`s IOCD in Madrid and the ODI-Summit in London.
Occurrence of newspaper articles writing about “open data”, based on current Implisense news index for Germany
Being a leading B2B Sales Intelligence and Marketing Automation provider in Germany Implisense offers services critically relying on public and open data, e.g. company websites, register data, industry data and geo-data. With our ODINE-Project, the European Company Explorer Platform, ECEP, we want to offer our users a new analytical tool to monitor existing trends and to detect new trends in the European company landscape.
Due to the present and future importance of open data for ECEP – and Implisense in general – it is critical to us to have a solid and concurrent understanding of the European open data landscape. This contribution marks the beginning a series of blogs centred around open data in Germany. It is based on our experiences when building our open data network. It shall also raise the concerns of a previously rather silent, but important group of open data stakeholders: small innovative businesses.
Next in this series, we will use our Big Data Analytics to identify and analyse further companies and firms being part of the German Open Data ecosystem.
Open Data Ecosystem in Germany
Engaging into open data we have encountered different types of players in the German open data ecosystem. We distinguish between politicians and clerks, civil organizations, small innovators and large enterprises just starting to discover the potential of open data. Hence, we will use this distinction to discuss the current status of open data provision in Germany.
Politicians and Civil Servants – Decision Makers
In recent times, we have experienced a noticeable uplift in open data activities in Germany, especially after the constitution of G8 Open Data Charta. Politicians start to treat this topic more seriously. Both the Ministry of Economic Affairs and the Federal Ministry of Transport and Digital Infrastructure have launched large-scale funding programs for data-driven projects and companies partially covering open data business models: the Smart Data fund and the mFund programmes. The first draft of the Open Data Law has been worked out and we are feverishly awaiting its release. Given the rising popularity of Big Data Analytics more and more large enterprises begin to realize the potential of open data as one important source of intelligence for their businesses.
Yet, from our point of view as a B2B startup, there are several serious problems with opening data in Germany, which partially drives us to expand to a new market, the UK, as early as possible.
In particularly, we struggle with:
the lack of economically highly relevant open data, e.g. financial company data
the restricted coverage or depth of relevant open data, e.g. industry import-export statistics on for different levels industrial classification
the lack of legal clarity regarding the provision of certain open data, some data are announced to be fully open soon, in practice however there are still barriers to their access, e.g. company register data
the lack of “open data thinking”, understanding open data as a comprehensive concept and setting open data defaults, rather than a random provision of very different data sets
From our perspective many reasons for these shortcomings lie the nature of the German political system, depend on the individual skills and motivation of the responsible civil servants and are boosted by the undifferentiated public privacy concerns about publishing data of what kind so ever.
For instance, we experienced various workshops on open data where communal politicians complained about the lack of incentives for providing open datasets to the public. Typically, it is done by enthusiastic civil servants, who are willing to invest the final hours of a long working day to create some additional benefits for the community. There is no legal obligation for doing so as the current norms only recommend public authorities to provide data in an open format and if this is in line with the feasible expenditures of doing so, see this PDF. In addition, communal clerks often lack the skills or an easy-to-handle platform to make the data available in a suitable way.
Moreover, due to the federal system the responsibility to open up administrative data is scattered over several ministries, of which some are state specific. This leaves always the option to deny the responsibility for stagnating open data provision and multiplies any effort to engage into a full scale coordinated open data agenda.
The case of the company register data illustrates some additional problems. The intention to provide register data is prominently stated by the Federal Ministry of Economic Affairs. However, the provision of the company data is split across various local courts, the data input is manually maintained displaying countless spelling mistakes and inconsistencies. The task of providing an access to the data is delegated to a commercial provider having a monopoly for the register data, especially financial company data. Hence, preserving a totally outdated and unproductive business model at the cost of slower innovation through analytics with company data.
Nonprofits – Facilitators
The second group of open data players in Germany are non-profit institutions and foundations. There is an increasing number of think tanks, NGOs and such alikes that discover this topic for themselves. These players try to help politicians to address the issues above. However, for us Berlin based non-profit institutions and foundations played a key role in creating an open data network. For instance, one of the most active local institutions in the field of Open Data is the Technologiestiftung Berlin. It hosted numerous events around the usage and provision of open data, like the OD-Day Berlin in may 2016. Moreover, it has published some often referred to publications on the value (“Digital Gold”) and practical use of open data (“Open Data in Practice”).
Recently, the Konrad Adenauer Stiftung has also engaged into the topic of open data. The KAS is the party foundation of the Christian Democrats. It focuses on the overall economic value of open data and on Open Government topics. The involvement of a think tank so close to the biggest German party is important for the provision of open data. It also shows that this topic is at the verge of being taken seriously by politicians.
One of the first institutions working on the subject of open data was the Stiftung Neue Verantwortungin Berlin. To our knowledge this foundation engaged into the open data with a workshop in fall 2015, primarily focusing on Open Government and the issue how to open German administrative data faster. This foundation operates on federal level and was able to bring together some interesting Open Data stakeholders from civil society and politics.
There are many other institutional players that we have encountered on various events. Some of them concentrate not only on the promotion of open data but also provide, use and / or generate public value from them, e.g. Wikimedia or the Forschungszentrum Informatik in Karlsruhe, providing research for the Smart Data Program by the German Federal Ministry of Economic Affairs (BMWi). We also do not to mention the critical efforts of the Open Knowledge Foundation in developing an open data ecosystem in Germany.
Small Companies and Startups – Value Creators
These businesses typically generate value from open and public data by providing analytical services or simply information for specific B2C, B2B use cases. There is an increasing number of publications on this subject. For instance, the study by the Technologiestiftung mentioned above or the “Open Data”, a publication by the KAS including positive examples on the use of OD. Many of these companies create value out of open data and naturally have a strong interest in a better provision of these. Yet, they are tentatively small and have few influence on this process. Apart from Implisense a strong interest in the provision of machine-readable register data could have similar B2B Analytics providers. Examples for such businesses are Kantwert, a company focusing on link graph analysis of firms, and IPlytics, a market intelligence platform focusing on IP. Importantly, one should also account for other startups creating innovation using services based on such data and, hence benefiting indirectly from them, for instance, Spotfolio, a matching platform for high tech companies. There are also international stakeholders to opening German company register data, like Dato Capital or Open Corporates.
As opposed to these rather innovative companies, there is a not too small group of SMEs which is still building their business models simply on reselling links to company data available at the company register, e.g. unternehmensverzeichnis.de and moneyhouse.de. More surprisingly, even leading German business information providers, like Bürgel Wirtschaftsinformationen, are still relying on manually verifying company information through interviews instead of focusing on analytics and data mining.
Yet, particularly companies without extracting additional public data pools and or providing additional analytics, i.e. not innovating, are prone to changes in this domain. Accordingly, they are potential opponents to the provision of more open data.
Large Companies – Consumers (and Suppliers)
There are two types of open data players in this segment. Firstly, large companies actively exploring the disruptive potential of open data, for instance, Deutsche Bahn with DB Systel. Secondly, we consider large companies that start to realize the potential of open data to boost the efficiency or effectiveness of their core enterprise functions. This group of stakeholders is nicely reflected by the leads of our business, large enterprises from ICT, finance and publishing.
The establishment of our company was favoured by the realization of the potential of (big) data analytics for sales departments. This, in turn, led to the acceptance for analyzing external data sources for internal MI and BI purposes. Now, we observe that open data being part of our analytical services are increasingly recognized as a valuable source helping to establish a more effective sales process. To be more clear, more open data, like information on financial statements, could contribute to a more accurate segmentation of potential B2B customers for our clients. A better segmentation leads to higher conversion rates. Rising the conversion rates for a few B2B products of a large scale company by a few percentage points can quickly turn into two-digit million dollars of additional profits. In short, there is a free lunch waiting for the big boys, and they are just realizing it is there.
Accordingly, we believe that large enterprises could be key stakeholders to opening up more data in Germany. Whether it is for the increase in efficiency in B2B sales or a higher usability for private consumers as long as large companies are beginning to understand the value of open data to their businesses the demand for the provision of open data will increase as well. At the same time these large companies have the political weight to affect the political process of opening data sustainably. Examples for such companies can be found by looking at the mFund and Smart Data programs.
Some Lessons Learned
We do not claim that our experiences are fully representative. Yet, we think that they offer a valuable first impression about how the German Open Data ecosystem looks like. From the perspective of a B2B startup we arrive at the following key insights:
Despite a positive dynamics the process of opening more data in Germany lacks political coordination and incentivization. Especially, in the B2B domain this favours outdated business models, hinders innovation and the creation of economic added value. This is particularly the case for company register data. This does not only apply to technologies directly using open data, but also for any downstream innovation building on these services, for instance in the case of Spotfolio.
There are also implicit barriers to this process, particularly the lack of open-data awareness both in the private and the public sectors. Companies do not realize open data as a coherent concept. They use open data without referring to them as such which gives away an opportunity to highlight the benefits from open data. Meanwhile, the public administration works towards a broader open data provision without having a comprehensive strategy. Thereby, they miss out on the opportunity to set defaults for providing the existing data in a higher quality (coverage and depth) and opening up more data sources with maximum social and economic utility in the future, e.g. by harmonizing data standards and data provision processes as well as linking future (non-administrative) open data sources.
Large enterprises might play a key role in fostering the provision of open data, as they are in the process of understanding the value of open data. They would have the necessary resources, incentives and political weight to do so.
Note that there is a lot that could and should be done in the political domain about a better provision of open data. However, there are also responsibilities and opportunities that lie within the private sector.
In our next blog article, we will show results from our prototypical “Open Data Radar Germany”. For that we will analyze our open and public company data sources to find further companies and institutions being part of the German open data ecosystem. We also will show what distinguishes them from other companies in Germany. If you have any feedback on this article, do not hesitate to contact us. You can also meet us in person at the this year`s IOCD in Madrid and the ODI-Summit in London.
Die Digitalisierung der deutschen Wirtschaft ist bereits im vollen Gange und wird in der nahen Zukunft immer mehr Bereiche mit einer immer stärkeren Intensität erfassen. Damit deutsche Unternehmen wettbewerbsfähig bleiben, ist es schon heute wichtig, Trends nicht zu verschlafen. Dazu zählen beispielsweise Big Data, Cloud Computing oder Internet of Things. Implisense entwickelt derzeit im Rahmen des Projekts ECEP ein Monitoring-Tool zur Erkennung von Trends in beliebig definierbaren Unternehmenssegmenten. Im Rahmen dieser Entwicklung hat Implisense den Grad der Digitalisierung des Maschinenbaus, einer der deutschen Schlüsselindustrien, untersucht.
Große Unterschiede zwischen Branchen
Um die Digitalisierung des deutschen Maschinenbaus in Kontext zu setzen, hat Implisense zunächst mithilfe seines Data-Mining-Ansatzes die Digitalisierung der gesamten deutschen Firmenlandschaft errechnet. Der Maschinenbaubranche (C28) nimmt dabei nur einen Platz im oberen Mittelfeld ein, mit einem Anteil Firmen von 53 Prozent, die hinreichende viele Hinweise auf die Digitalisierung ihrer Geschäftsmodelle haben. Digitalisierungsspitzenreiter sind – wenig überraschend – Firmen aus der IT Branche, speziell Informationsdienstleister (J63) und Erbringung von Dienstleistungen in der Informationstechnologie (J62). Die Versicherungsbranche (K65) ist digital ebenfalls gut aufgestellt, was dem zunehmenden Einsatz von Big Data Technologien zuzuschreiben ist. Führend in dem Bereich des produzierenden Gewerbes ist die Branche der Hersteller von Druckerzeugnissen, Ton-, Bild- und Datenträgern (C18), sowie Unternehmen der Elektroindustrie (C26 und C27). Überraschender ist, dass auch die Pharmabranche (C21) ein höheres Maß an Digitalisierung aufweist als der Maschinenbau.
Wie erkennt man Digitalisierung im Maschinenbau eigentlich?
Digitalisierung ist ein sehr abstraktes Konzept. Zunächst stellt sich also die Frage, wie sich Digitalisierung im Maschinenbau anhand von unserem Datamining Verfahren definieren, erkennen und bemessen lässt.
Implisense arbeitet in solchen Fällen mit statistischen Modellen von Termen, die besonders stark mit einem Überthema korrelieren. Die Berechnung dieser Modelle erfolgt implizit, indem unser Algorithmus die signifikanten Terme anhand einer Gruppe von Unternehmen berechnet, die z.B. eine Leittechnologie der Digitalisierung benutzen. Anhand eines iterativen Vorgehens können so immer weitere Digitalisierungsmerkmale erkannt und in das Modell aufgenommen werden. Auf diese Weise kann unser System abstrakte Themen wie die Digitalisierung ohne Vorwissen und ohne aufwändige manuelle Vorarbeit definieren und erkennen. Das finale Modell zur Erkennung von Digitalisierung im Maschinenbau (siehe Dendogram) erfasst unter anderem:
Merkmale, die Hinweise auf Begleitprozesse der Digitalisierung von Maschinenbauern liefern, v.a. Automatisierung und Robotization
Merkmale oder Indikatoren für Software und Dateninfrastruktur, wie der Fokus auf Big Data Analytik, die Nennung von Data Warehousing, die wahrscheinliche Verwendung von APIs
Leittechnologien und führende Marken der Digitalisierung wie etwa Supervisory control and data acquisition (SCADA), eine Technologie zur digitalen Überwachung und Steuerung von technischen Prozessen, oder Eplan, ein Softwaredienstleister im Bereich Ingenieurwesen, Wonderware, eine Firma, die SCADA und MES (Manufacturing Execution System) Software anbietet, und PCS7, ein Distributed Control System (DCS) von Siemens zur “durchgängigen Automatisierung”.
die Digitalisierung wichtiger Unternehmensfunktionen. Dabei scheinen die Digitalisierung von Vertriebswegen (Indikatoren: E-Commerce, Social Media, Community, Chat), die Optimierung des Nutzererlebnisses (Themenindikatoren: Apps und Embedded) sowie allgemein eine daten-getrieben Unternehmenssteuerung (Indikatoren für Business Intelligence und Web Analytics) eine besonders wichtige Rolle zu spielen.
Pumpenbauer als Digitalisierungsführer?
Mit diesem Modell konnten wir von 16.300 uns bekannten Maschinenebauern 8.673 Firmen identifizieren, bei denen eine hinreichende Anzahl dieser Indikatoren anschlägt. (Firmen mit weniger als 500.000 Umsatz Euro im Jahr wurden nicht berücksichtigt.)
Bei einer differenzieren Betrachtung der Digitalisierung von Unterbranchen des Maschinenbaus stechen Herstellung von Pumpen und Kompressoren (C28.13) und die Herstellung von Büromaschinen (C28.23) besonders hervor. Während die starke Nähe von Computer- und Druckerherstellern zur Digitalisierung wenig überrascht, lässt dieses Ergebnis im Fall von Pumpenbauern aufhorchen. Tatsächlich aber ist die Pumpenindustrie besonders gekennzeichnet durch eine zunehmende computergestützte Vernetzung durch eingebettete Hardware/Software Systeme. Nicht nur integrierte Systeme machen diese Branche innovativ, sondern auch die Entwicklung und der Vertrieb von Apps zur Verbesserung des Kundenservices. Ein Paradebeispiel ist die Jung Pumpen GmbH, die gleich vier Apps anbietet, unter anderem für die Unterstützung beim Produktkauf, sowie als Wartungstool für die erworbenen Pumpen.
Ruhrgebiet als digitales Entwicklungsland
Auffällig ist der hohe Anteil an digitalisierenden Firmen im Raum Dresden. Dies könnte an dem dortigen Fokus auf Mikroelektronik liegen, sowie an dem Innovationsschub aus der dort florierenden Startup-Szene. Es ist eine kleine Niederlage für Berlin als die etablierte IT-Startup Hauptstadt Deutschlands, die bei dieser Analyse eher schlecht abschneidet. Auch der restliche Osten Deutschlands erscheint im Bereich Maschinenbau erwartungsgemäß wenig digitalisiert.
Die Unternehmen aus Bayern, Baden-Württemberg und Hessen, den Maschinenbau-Hochburgen unserer Republik, sind im Schnitt gut auf zukünftigen Entwicklung im digitalen Bereich vorbereitet.
Bemerkenswert ist die geringe Bedeutung des Themas im Ruhrgebiet, besonders als Region mit einem traditionell stark ausgeprägten Bezug zum Maschinenbau. Hier könnte für die Zukunft noch deutlicher Handlungsbedarf und ein großes Verbesserungspotential für die Digitalisierung bestehen.
Wir freuen uns, Ihnen heute den Relaunch unseres Blogs präsentieren zu können! Es hat nun seine eigene Domäne blog.implisense.com. Zusammen mit unserer Designerin und unserem Webmaster haben wir das Blog komplett neu gestaltet. Wir haben alle Kategorien und Schlagwörter überarbeitet und vereinheitlicht, so dass Sie auch ältere Beiträge problemlos auffinden können. Besonders beliebte Artikel finden Sie direkt rechts oben.
Wir hoffen, Sie finden Gefallen an unserem neuen Blog. Wir versprechen, es auch wieder häufiger mit neuen Artikeln zu füllen. In Kürze erscheint unser erster englischsprachiger Beitrag über unser neues Forschungsprojekt ECEP…
We are super excited that we had the opportunity to showcase our newest development ECEP at the ODI Summit in London. We demoed our newest analytical capability of analyzing specific technology and business trends in countries like Germany and UK – thanks to Open Data. The project team of ECEP at Implisense enjoyed listening and talking to high profile speakers such as Sir Tim Berners-Lee (creator of the World Wide Web), Sir Nigel Shadbolt (AI expert) and Martha Lane Fox (Lastminute.com founder).
