Digital transformation definition

Digitalization is generally understood to mean a digital conversion and representation or implementation of information and communication or the digital modification of instruments (Gabler Lexicon). “ The digital transformation is understood as the exponential and permanent change of society and companies based on technology “(Lindner and Leyh 2018). Petry (2016) sees the rapid technological development as the basis of digitization, which has become faster and faster in recent years and therefore speaks of the age of acceleration. Hoffmeister’s book also states that the basis of digitization is also a kind of domino effect: Existing technologies pave the way for further technologies.

The digital transformation describes change processes, due to digital technologies at high speed. Many sources cite changes in customer requirements as the driving force behind this digitization, which can only be served with digital technologies. A good example of this is the Spotify streaming service, which makes music accessible anytime, anywhere, anytime and inexpensively (to a certain extent even for free).

Overall, the academy differentiates between enablers and actors. “Enablers” are more or less “enablers” and include the following:

• to the first digital technologies (cloud computing, …),
• digital infrastructures (protocols, …) and
• Last but not least, digital applications (online banking, …).

On the basis of these “enablers”, new exploitation potentials arise in new areas. Companies are starting to explore these and try them out in initial pilot projects. Examples are: digital business models and digital value networks. Digital business models describe the change from analog to digital models. A good example here is the Deutsche Bahn online ticket. Digital value creation networks are, for example, virtual teams.

The digital transformation affects many People: Entrepreneurs, researchers and employees as well as numerous other citizens of the Federal Republic and beyond its borders. They can now communicate with each other in real time or share events from their lives with others in the live stream. Just yesterday I networked with my toothbrush. However, these new possibilities also have their downsides: A lack of data protection and information overload are just two of the negative consequences.

Are a different actor Companies . Here work is changing into so-called digital work – business models are also changing fundamentally. Are also affected Science and teaching in the form of new possibilities for archiving, publication and preparation of research as well as e-learning. Also offers the digitalization Numerous challenges for governments: The main task here will be to steer this transformation through laws and guidelines as well as the own transformation of official processes.

Driver of the digital transformation

But why are we talking about digital transformation now of all times – why is the speed fast enough right now? To answer this question (s) has Petry (2016) the following diagram as well as drivers for the digital transformation provided. At the beginning there is the exponential growth of companies with the core topics of networking, AI and Big data . The main consequences are changes in work itself, in customer behavior and in the general competitive situation.

But we’ve been digitizing for 50 years!

Currently, the greatest criticism of the thesis on digital transformation is that we have been digitizing ourselves for many years. That is correct and it hits the nail on the head. However, if you look at current literature or directly at the company, you will notice a major difference: While many years ago we were largely digitalising on the surface, companies are now moving towards more profound digitalisation. A good example is going to the hairdresser: Here I book my appointment using an app. This approach is definitely digital. However, the actual cutting process is still carried out in the same way. Classic people business is therefore not scalable, as one employee is required for each customer. Similar to consulting, in which many tools support the advisor, but the actual advice still takes place in analog form and the advisor has not yet been digitized. You can find more about this in the article about Consulting 4.0 . This shows two examples of classic people business. Of course, there are still no direct answers to these questions, but there is currently a clear trend towards deeper digitization with fundamental changes in behavior. Digital transformation is therefore a profound social change in people’s behavior through digital technologies. One example that already exists is remote work instead of traditional attendance.

Evolutionary stages of the digital transformation

In the blog of Social Collaboration Academy I also found a nice “statement” on the criticism that we have been in a digital transformation for ages: According to the article, there are 4 levels of digitization – but we have only been talking about a digital transformation since we tried it To network the real world and the digital world.

• The first evolutionary stage lasted from approx. 1990 – 2000 and dealt with the networking of computers.
• In the second evolutionary stage from approx. 2000 – approx. 2015 it was primarily about general acceptance and general everyday introduction and use of mobile devices.
• The one in front of us now third evolutionary stage The duration of which experts estimate will be around 2015-2030, focuses on topics such as the general maturity of systems and the Internet of Things.
• With the fourth evolutionary stage , which should start from around 2030, there could be a complete merging of the real and digitally networked world.

Transformation, change, evolution or revolution?

There are many terms for digital transformation and just as many opinions everywhere. Is it a digital transformation or not? A transformation has a beginning and an end. A change stands for a state that changes into another state. Evolution stands for the peaceful further development of something and revolution for a fundamental, often violent, innovation of a respective status quo. Also read my on this Article on the digital r (evolution) . Many also simply refer to the digital transformation as “digitization”. However, this would simply mean: something analog becomes digital. What do you think: which “label” should we give to digital change?

Digitization in German companies

Digitization is not a new topic in the German corporate landscape. Processes have been digitally supported or even fully automated for a long time. The main difference in the current discussion is the increased speed and complexity of the change processes, which can meanwhile result in profound process changes and even job losses (Lindner 2019).

I have already identified some examples in my PhD in Lindner (2019): Siemens to automate over 7000 jobs in administration by 2020 (Heise 2018). Deutsche Telekom is also testing the use of chatbots in customer service, which could change numerous jobs (Handelsblatt 2018) and DHL has been experimenting with the delivery of parcels with drones since 2014 (DHL Paketkopter T3N 2018). Another example is the efforts to create self-driving cars at Audi, VW and Daimler, which could fundamentally change all mobility in Germany (Manager Magazin 2018).

These few examples show that, according to the practical literature, digitization could bring about numerous far-reaching changes.

What is digital transformation?

Many companies have been driving the digitization of society for a long time. We are now talking about digital transformation because of the speed and profound digital changes. While digital technologies were previously often only used “on the surface”, there are now profound changes right through to the original business model. In summary, we are also talking about a digital change or a digital evolution or revolution. You can also read mine at this point Article on the digital (r) evolution – another recommendation is that Book by Petry .

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Digital readiness index

To determine digital readiness, the “Neuland” initiative created a digital readiness index. This measures the arrival of companies in the digital world on the basis of 150 criteria. The study speaks of a digital Darwinism which lets companies “die” if they miss the digital transformation. The large consulting houses also offer their own metrics and methods to measure this readiness. Sentences like “It is time to completely digitize processes in which the user is the focus” or “No question about it: this experience will also change the expectations of customers in terms of communication, services and product offers with and from companies fundamentally change. ” However, these studies do not currently provide an answer to this digital transformation. There are certainly numerous methods of counteracting the propagated digital Darwinism. In the following, the structural change from companies to agile companies will be examined under the heading “digital agility”.

Digital agility

There is already an article on the Tham digital agility on the blog. Technology must not be an end in itself, the new type of added value counts in the transformation. Only agile companies can, for example, adequately meet the challenges of faster markets and technology in the future. The markets and the technological possibilities require companies not only to be able to react agilely and evolutionarily to environmental changes, but also to react quickly and adequately. From pioneer to settler, as can be seen in the illustration of Brandes. There is also one for this Article about leading digital with more explanation. Digital and agile companies are currently very popular. Concepts around Holocracy, Democracy and Sociocracy determine the management world and promise to revive companies and free them from complexity. However, all of the concepts have not yet been applied to digital transformation and do not yet provide a clear answer. We are currently in the process of researching with companies exactly the feasibility for digital transformation.
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We understand “digital Darwinsmus” when technology and society change faster than companies are able to adapt to them (Kreutzer / Land).

Adapt or die

Survival of the fittest: Darwin’s theory can best be transferred to the digitization of companies. Because the struggle for survival also takes place there. The strongest is the one who manages to react quickly to technological changes, adapts his business model to customer expectations, uses knowledge profitably and outperforms his opponent (start-up scene).
So the success factor seems to be the speed of your own digitization. Kreutzer and Land speak of a change from CEO to CDO (see figure). According to the two authors, a modern CDO should aim to “destroy” what already exists in order to make room for the “new and digital”. I already have a further article on the subject Leading digital released.

Me, everything, everywhere, immediately … – digital business

The new “connected, informed and all powerful consumer” has clear expectations: “I, everything, instantly and everywhere” (Kreutzer / Land). These challenges and changes in customer requirements can be counteracted in a targeted manner by means of digitization. Customer wishes as a digital business. More examples can be found in my article too digital change.

Customer trust instead of customer touch

It is no longer enough to simply build relationships with prospects and customers, with each being enriched with more information from level to level. Rather, it is important to build up more trust from level to level in order to be able to make increasingly targeted and therefore more relevant offers, especially by providing suitable information and convincing services (Kreutzer / Land). These trust points are therefore a success factor for digital business.

Despite all the euphoria about the engagement in social media, Kreuzter and Land point out the 1: 9:90 rule. Studies show that – across borders – approx. 1% of Internet users are very active and, for example, Post your own contributions in blogs or online communities. 9% of Internet users react to such entries – while a “silent majority” of 90% are only active as reading, according to Kreutzer and Land.
That is why the two authors recommend that we particularly recognize the 1% of opinion leaders on the Internet and ideally win them over. As a blogger, I also notice that many users read very actively. According to various studies, users only read a blog between 3-12 months before they actually comment or react to it. However, many companies stop the “ agile marketing “due to the low response rate. However, in this case it is important to persevere. It is therefore important to give the readers a channel through content in order to trust the company or, in my case, the research project.

The will to become an agile company

The advancing digitization demands a structural change in companies towards agile and evolutionary companies. Evolutionary means here the adaptation to changes. The Laloux’s theses complement each other very well with those of Kreutzer / Land. According to both, companies have the task of constantly adapting to new markets and customer requirements. Agile includes topics like Work 4.0 , New Work and agile leadership . But the exact change and the interpretation are still highly controversial. Also note my other book suggestions for the digital transformation.
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• Technically this means the preparation of information for storage in a digital technical system.
• in the Overall context It means the technologicalization of entire industries in a profound sense, so strategy, organization and socioculture are also affected. For a further definition, read the soon as well Article on digital transformation.

On the one hand, these changes are profound and, on the other hand, they have been developing for years. In this sense, many speak of a digital (r) evolution. For this reason, the aim of this article is to examine arguments for the digital revolution as well as for the digital evolution.

Digital revolution

A revolution means a radical change in “one step”. The term revolution is even often associated with armed violence or a brutal coup. Representatives of this thesis include the aforementioned authors on digital Darwinism. “Adapt or die” say the authors in their numerous keynotes and call for radical changes to ensure the survival of companies. Many companies such as Kodak have already felt this revolution. Established manufacturers in the automotive market are also being attacked with Apple and Google. Here, too, there is a “head to head” race to digitize the automobile.

Digital evolution

On the other hand, digitization has been emerging for a long time. Companies such as Apple and Google have been dedicated to the digitization of our society for years and are making progress with it. So isn’t it a direct revolution but simply the “next step” in the evolution of companies? So are companies just slowly transforming into so-called “digital corporations”?

Digital (r) evolution

Regardless of whether it is a digital evolution or a digital revolution, one thing is certain: companies have to act. In his book on Digital Leadership, Petry uses the Chinese proverb: “When the wind of change blows, some build protective walls and others build windmills”. The digital transformation is coming to German companies and is forcing them to digital change. In the course of the research project, the special influence on the structure of companies towards agile and evolutionary companies is examined.

Medium-sized companies in the digital (r) evolution

I think the main themes of digital transformation are like Consulting 4.0 , Work 4.0 and Industry 4.0 are still in the formulation phase. Most of my practice partners are currently in the phase of testing the first digital and agile lighthouse projects or trying out frameworks in individual teams. This is due to the fact that medium-sized companies are slowly noticing that employee turnover is increasing and customers are no longer as easy to win as they used to be.

Corporations in the digital (r) evolution

Can you compare the pressure on medium-sized companies with corporations? Absolutely! The only difference is that companies get more or less time depending on their size. In a small company, missed trends quickly become noticeable and immediately put it on the wrong side, while a large corporation can often generate business successfully for years afterwards. But this also poses a great danger: How can a company, for example, precisely measure fluctuation? There may be a constant number of employees, but we have to ask ourselves: Are they the best people who switch to innovative startups or medium-sized companies because there are better and digital working conditions there? So many large corporations are currently in crisis. A famous example are our banks or, possibly, our major automobile brands soon. Large banks now have problems with the hyped Number26 and Tesla is also attacking our renowned automobile brands from the USA. What was unthinkable in the past is a reality today. Or did you ever think that startups would attack corporations and Apple build cars?

What do you think?

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As early as in the coalition agreement, the governing parties commit themselves to preserving and regaining technological sovereignty. The focus is on alternatives to current US providers, which often offer cloud and software solutions without sufficient transparency. Due to the fact that we will become more and more dependent on technologies in the future, the sovereignty over their administration should lie in the hands of the German entrepreneurs.

This article shows current risks in the cooperation with large US providers and explains the use of open source software as an alternative solution for creating digital sovereignty.

Risk 1: Vendor LockIn

The reason for the frequent focus on one provider is obvious: Providers such as Apple and Microsoft often optimize their own components and it is difficult to link them with solutions from other manufacturers. One speaks of a vendor lock-in:

With vendor lock-in, a customer cannot replace a used service or product with an equivalent solution from another provider without increased effort. This is mostly due to the use of proprietary technologies that are incompatible with those of competitors.

Lindner et al. (2020)

The risks of such a vendor lock-in are often high costs and license fees, as there is a strong dependency on the individual provider.

Risk 2: Data in the cloud – but how are you?

Another risk is the storage of the data, which is often in the provider’s cloud. Cloud is defined as:

The term includes the interaction of several servers over the Internet. All servers share tasks among themselves. If one server fails, another server takes over. The cloud user does not have an overview of the individual servers. His data or applications run somehow (cloudy) in the cloud.

Lindner et al. 2020

You notice that the data in the cloud is therefore often not stored transparently and therefore it cannot be 100% guaranteed that the data is adequately protected from third party access. Such storage also often violates order data processing agreements (ADV) with important key customers.

Digital sovereignty

sovereignty is defined as the ability of a natural or legal person to have exclusive self-determination. The ability to self-determination is shaped by the self-reliance and independence of the individual and is the middle way too External control and self-sufficiency.

Delimitation: Sovereignty does not mean that a company has to do everything itself ( Self-sufficiency ) but that a company is able to act and can decide for itself what it does. It is able to choose between alternatives using powerful software.

The Digital sovereignty For me, stands for independence from a provider as well as self-determination as to which components I can use to digitally support a certain activity in the company. Furthermore, I have complete transparency about my data.

In the following I would like to show an example from my current experience for companies as well as private households.

Open source as an alternative for companies

For almost every task there is free, so-called open source software, which often does not have to hide behind commercial applications. Open source software is software whose source code is freely available and can be downloaded from the Internet and used free of charge within the framework of open source license models. By publishing the source code, the user can understand that data is not used without the consent of the user (Lindner at al. 2020).

Let’s take the example of Office 365 from Microsoft, which is used in numerous companies for the following activities:

• Writing program (Word),
• Tables (Excel),
• Presentations (PowerPoint),
• Notes (OneNote),
• Videoconference (Skype),
• Email (Outlook) and
• File sharing (OneDrive).

Microsoft Office 365 combines various online services with classic desktop office software. Office 365 is available in different scope of services. The web applications can be used via a browser on computers with any operating system (Lindner at al. 2020)

There is also a secure alternative for Office 365. The various services could also be obtained on the basis of open source software. Through e.g. On premise installation (own server or free choice of data center) and a large number of administration and security features, entrepreneurs have full control over their data and are compliant with the GDPR (Lindner at al. 2020). The following figure shows the implementation by ownCloud with Collabora in the browser as an alternative to Microsoft Word and OneDrive.

Similarly, the entire functionality of Office 365 can now be recreated using individual open source variants. My advice is:

• Writing program, tables and presentations (OnlyOffice),
• Notes (Joplin),
• Videoconference (Kopano),
• User administration (Univention)
• Email (Open XChange) and
• File sharing (ownCloud).

These functions can be set up flexibly and integrated into the existing open source infrastructure. You can also exchange individual components at any time (no Verdor LockIn) and have transparent source code.

Open source as an alternative for the home

In private, too, you should pay more attention to the sovereignty of your own data. Similar to companies, providers such as Dropbox or Microsoft also give private users little transparency in the storage of their own data.

For example, I connected two hard drives (4TB) to a Raspberry PI at home. The hard drives are redundant so that data loss is not possible if one hard drive fails. The whole set will cost you around 250 euros. Since commercial clouds often cost 10 euros per month, this investment is worthwhile after 2 years. However, this was not my primary goal because I wanted to achieve sovereignty of my data.

I then installed the ownCloud software on my Raspberry PI. Because of the open source end, I could be sure that nobody would have access to my data. I also know exactly that the data is on my hard drives, which are on my desk.

Reading tip: read mine Instructions on how to set up such a cloud !

The alternative is to buy your own NAS station. For example, I still have a Synology NAS. Long established in PC circles, Synology is one of the leading manufacturers of NAS servers. The fully configured version is particularly suitable for beginners and requires very little knowledge. Components can be installed and set up with a click. They are not completely free, however, unlike Dropbox and Co., they have their own hardware. Here is my recommendation: Synology NAS DS-218 with 2 Seagate hard drives .

Conclusion

Digital sovereignty is an essential topic for companies. As more and more technology is being established in companies, the topic should also become more and more important. The main dangers are the dependency on a provider and the associated high costs as well as the lack of transparency of the data.

For almost every task there is free, so-called open source software, which often does not have to hide behind commercial applications. The use of such software can be an alternative to commercial providers and increase the digital sovereignty of companies and private households.

Tip: Read my new book: The way to the cloud at Springer Gabler or book me for a talk .

Image source: Pixabay

source

Lindner, D., Niebler, P., & Wenzel, M. (2020). The way to the cloud – a guide for entrepreneurs and decision-makers . Heidelberg: Springer Gabler.

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On the other hand, we also have good news. Volkswagen would like to create 2,000 new jobs at the same time, Siemens also wants to create around 2,500 new jobs and also Thyssenkrupp wants to create 1,000 new jobs.

In total, more than 65,000 jobs were cut in German corporations this year, but the job market is still going more than 700,000 skilled workers searched. But how does that fit together?

Downsizing in Germany

Ever more intelligent machines are changing our working world and demanding new skills or automating entire professions. Robots do not need a vacation and do work without fatigue and grumbling. Of course it will take a while until this vision becomes reality, but the first consequences are already visible.

ING-Diba has examined 4 million jobs and made an initial forecast for the next 10 years, which professions are particularly at risk and could be eliminated. Take a look at the statistics.

They notice that occupations in administration and unskilled labor as well as counseling are at risk. This is often due to intelligent software, forecasting tools and chatbots. But intelligent robots could also provide a remedy for physically strenuous work in the construction industry and handicrafts.

Lack of skilled workers in Germany

According to the Federal Employment Agency, companies are currently looking for 700,000 skilled workers in the fields of industry, retail and the service sector. But which professions are future-proof from the current point of view?

The Boston Consulting Group examined which professions are least at risk from digitization and analyzed 7.7 million employees. In the following I will show you a statistic about this.

Of course, professions that are difficult to digitize, such as care for the elderly, crafts, teachers, lawyers, educators or protected professions such as tax consultants or notaries will still exist for a long time. On the other hand, you will also notice how professions with human competence such as empathy and empathy are still future-proof. These are executives, business consultants, medical professions, and educators. On the other hand, the IT industry will also grow strongly and IT competence in general will become increasingly important.

Conclusion

A lack of skilled workers is becoming one of the greatest obstacles to growth in the age of digitization. We are changing from the classic industrial society to the digital society. The consequence is that, on the one hand, jobs are massively cut and, on the other hand, they are also being built up again.

In endangered professions, it is important to consistently develop further with the help of new IT skills and to change the job profile. For example, a clerk can use IT skills to configure the automation software or a construction worker can operate intelligent machines.

As employees, we should start to take 100 percent responsibility for occupational safety #Employability, as companies can no longer assume this responsibility for employees. Nor can you rely on the educational systems in companies, you have to continue your education through active learning in your free time. Already a Haufe survey shows that more than a third of over 1,000 employees surveyed already receive further training on the weekend and in their free time.

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1. Increase the level of maturity step by step

A company does not become a digital leader overnight. It is therefore important to first determine the current level of maturity. If invoices are currently still being written by hand, then it makes sense to first map them using a tool or to support them with a Word macro instead of “digitizing” them directly in an ERP system. On the one hand, this is cheaper and, on the other hand, it is less overwhelming for the employees. Therefore, always try to determine the current level of maturity of a process and then increase it step by step.

2. Do not tie digitization to one person

“Mr. / Ms. X. You are now responsible for digitization and the company-wide ERP system!” I have never seen such a position successfully drive digitization in the company. In my opinion, digitization cannot be tied to one person, but must be driven by each department itself. So give each team the task of “digitizing themselves” and only offer the support of a “digitization officer”.

3. Digitize unloved processes and ask employees

If you are just about to start your first digitization projects, then you should first and foremost ensure that you support processes that nobody wants to do analogue anyway. For example, for my former customer, that was the travel expense report. It also makes sense to simply ask the employees: “ What should we digitize for you? “The advantage is that there is no headwind from the employees and new solutions can be used directly.

4. Avoid holistic solutions

Avoid holistic solutions. These are usually not halves or whole. In addition, they cost a lot of money and contradict the trend to remain flexible. So take one tool for each process step and link the tools together in a meaningful way. I would like to give an example of this in the illustration. A typical sales process is digitized here. Each relevant step has a specific tool. It is now the task of your IT to link these together in a meaningful way (keyword: workflow).
Reading tip: Example of process digitization

5. Use managed services and trials

The advantage of this small tool chain is that, especially as an SME, you do not have to bring in any large tools. Try a few tools for a process step. These are often available in a 30-day trial version. A manager once said to me: “We’ll get the 30-day trial version and if no one is using it after 30 days, we’ll cancel it and get the next one. “Furthermore, many companies notice that IT tool operation is not a lot of fun, so that it is worth simply having all tools serviced by providers. Since the tools often cost between 5 and 100 euros a month, this can be easily paid for.
Reading tip: Example of an IT organization

Conclusion: digitization is trial and error

These are 5 tips I was able to take away from my time as a consultant. I have seen many SMEs that have successfully achieved great success despite small budgets. I think that the digital change is still trial and error and that you should try a lot quickly and easily. I hope that my tips can provide some impetus and help one or two managers with digitization. You can find more about trial and error in mine Articles on digital business models .
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What should a data scientist be able to do?

If you look at the job advertisements, a data scientist should usually be able to do the following:

• Analytical talent
• Expertise
• communication
• Urge to research
• Coordination talent

On the one hand, the scientist must recognize relationships in large amounts of data and be able to analyze them. Furthermore, he should also have business and specialist knowledge in order to understand the problems of the specialist areas. With the help of his communication skills, he can talk extensively with them and be in constant contact. His curiosity also allows him to solve difficult problems and work with hypotheses. But he is also a project manager and has to expand, manage and maintain the database.

What does a data scientist do?

There are many names for the new job profiles. The Computer week has already broken down some of it and defines it as follows:

• The (Big) Data Engineer is the master of the data supply.
• The management scientist is the mediator between the departmental worlds.
• The data scientist provides answers to analytical questions based on data.
• The data steward is responsible for monitoring data quality and integrity.

The data engineer is responsible for merging the data and knows where the data is and how it is merged. The management scientist then analyzes this data and defines the actual problems. She says to the data scientist Computer week : “The main task of the data scientist is to generate answers to analytical questions from data – with the help of analytical methods from the areas of statistics, machine learning or operations research.” The data steward monitors the data going there and ensures that it is technically correct.
So in the end there are numerous job descriptions and these terms are not always used and clearly separated. Therefore this is only used as an orientation. I don’t think that every company separates this so strictly and often everything is summarized under the umbrella of the data scientist or data analyst. The following figure shows the fields of application and provides the answer to the question: What does a data scientist do.

Conclusion: what does a data scientist do?

There are numerous terms and answers to the question: What does a data scientist do but in the end an abstract picture emerges. On the one hand, the data scientist is a scientist who solves business problems with the help of data and, on the other hand, he is a project manager who manages the database in the company.
I hope to have shed some light on the darkness with this article and I look forward to your comments on what the data scientists are doing in your environment. I have already worked with a few during my consulting time and can also see what my big data colleagues at the chair are researching. I also learned something from you and one quantitative analysis using data used in my doctorate.
Tip: Book suggestions too Big data
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Debate about agility in the context of digitization

The debate about the digitization of organizations is by no means new and does not directly address agile organizations. As early as 1985, Bair examined the changes in organizations due to the so-called personal computer (PC) and called for a debate about the digitization of organizations, which, however, only had other noteworthy publications since the turn of the millennium, and since 2012 an increasing number of publications.
There are mainly two opinions on the design of this digital organization. While experts such as Arnold (2016) and Gloger (2016) believe that greater agility in companies can drive digitization, Urbach & Ahlemann (2016) and Schrauzer (2016), among others, are of the opinion that digitization paves the way for increased Is agility in organizations. However, all debates aim at increasing the agility of the company organization.

Agility as a prerequisite for digitization

Schrauzer (2016) takes up this thesis of computerization and states that a more flexible reorganization of companies is possible through more mobile hardware and software. He concludes that the digitization of companies is a trailblazer for new and more flexible company forms. Urbach and Ahlemann (2016) put this into concrete terms and show the increasing flexibility of organizations. According to these, the reorganization of the internal IT is a prerequisite. Attached is an illustration of how such a reorganization can take place.

Mobile technology and software can enable constant reorganization, free choice of seats and concepts such as home office, remote or mobile work. Distributed teams and much freer work are also possible. Which is why a higher agility in work can be determined.

Agility as a result of digitization

In contrast to the sources currently cited, Arnold (2016) states that digitization, such as the IT reorganization required by Urbach and Ahlemann (2016), can require companies to make disruptive changes. He believes that this cannot be implemented in a classic / Taylorist organization and calls for more agile structures. He describes the example of Haufe-umantis and recommends testing this with experiments and evaluating how greater agility can be achieved. Similar to Arnold (2016), Petry (2016) also sees a paradigm shift in existing organizations as a “building block for sustainable corporate management in the digital economy”. He recommends that organizations adapt to the NewWork vision: work when, how and where you want. In this way, employees should be given maximum freedom in carrying out their work. He notes that making work more flexible depends heavily on mobile hardware and software, but the necessary restructuring should be made before it is introduced, as this makes the introduction of technology easier. The following figure shows the vision of NewWork.

It turns out that the introduction and implementation of technology is complex and that appropriate framework conditions must be created in order to realize the vision of NewWork. However, according to the authors, these are the real sticking point. So these frameworks should be created first. So says the union board in the 1st round table : “ Agility also needs guidelines in order not to end up in chaos. What this means is that we ultimately need framework conditions to shape agility. “ The marketing manager also adds that self-determination of work is an important prerequisite for successful digitization. According to the marketing manager, this self-determination enables a “ creative environment[mit] Regulations and framework conditions[geschaffen werden] that enables us to have this flexibility. “ So they have Participants in the 2nd round table presented a concept to increase agility in companies.

Conclusion

Ludwig et al. (2016) took up this debate and evaluated it. The result was that the goal of the digital organization continues to be the humanization of work and should represent a humane, flexible and meaningful way of working. However, he still sees numerous open areas of tension and no or little concrete implementation scenarios for classic SMEs, which are still predominantly in a Taylorist organization and are now faced with the decision to first increase technology or agility.
Reading tips

• What is digital transformation
• What is agility
• What is work 4.0
• NewWork

Of course, this reasoning does not have to be right for every company and every approach is justified. Of course, my round table only represents a small and selected group of entrepreneurs in Germany. So I would be interested to know what you think? Vote in the poll! Finally, with this post, I wish you a Merry Christmas and a Happy New Year and say goodbye to your vacation until January.
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What is big data

If you enter the search term on Google, you will find the following definition of ReserachEnterpriseSoftware : Big data is a general term used to describe the large amounts of unstructured and semi-structured data that companies produce on a daily basis. This data takes a lot of time and money to load into a relational database for analysis.
That too Gabler Business Lexicon provides a definition: “Big Data” refers to large amounts of data from areas such as the Internet and mobile communications, the financial industry, energy industry, health care and transport and from sources such as intelligent agents, social media, credit and customer cards, and smart metering -Systems, assistance devices, surveillance cameras as well as aircraft and vehicles originate and which are stored, processed and evaluated with special solutions.
A great explanation can also be found at chip :

• A large amount of data is referred to as big data if the volume is too large or too complex is to process them by hand. This is especially true for data that is constantly changing.
• Big data can be harmless data from climate research. However, data about people are also collected: communication behavior, consumer behavior or surfing behavior of Internet users. You can see the effects of big data analysis every day on the Internet . A typical example is personalized advertising.

In conclusion, one can say that big data is initially large amounts of data that are unstructured and cannot be evaluated by hand.

Big data – pros and cons

Large amounts of data offer our society a number of new possibilities, at least if we are able to evaluate them. So I have at dice found some great examples which I would like to show.
Crimes can also be fought better on the one hand. As Dice says, it may not be quite like the movie Minority Report, which shows a society where police officers successfully arrest individuals for crimes they did not commit. But in fact, massive amounts of data are already helping regional and local authorities identify difficulties before they can become a major problem.
Furthermore, diseases can be predicted. As dice says: Predicting events based on existing data could offer individual medical care for each patient. By analyzing digitally recorded medical data and similar disease courses from patients, personal disease risk profiles can be created. Doctors could then prescribe preventative treatments or review related symptoms.
Another great example is Netflix. At dice, for example, the following can be found: For Netflix, the visualization of data is of the utmost importance in order to be able to continue its success story. Netflix can use data calculations to determine what viewers want to see and how they would like the content to be presented.
So there are numerous great examples. For more you can just click dice Continue reading. In the following, however, big data may not always be a success factor, which is why I would also like to present the downsides.
So says the magazine CIO, the criticism of big data “is probably due to the “algorithm weakness” widespread among machines, i.e. the inability to draw the right conclusions from a lot of collected information. That being said, there are two main reasons why companies do not benefit, or not enough, from big data. The first: With the help of data analysis, you will come to results that you could have had with less big data. “
The second: Big Data produces results and ideas that, for whatever reason, cannot be implemented in practice. A large US retailer had found in a model test that sales increase if you put a special offer product on the shelves a while before it is cheaper and leave it there when the offer price is no longer valid ( CIO ).
In this paragraph we have now seen some good examples of big data, but also some that may not be quite as meaningful. So, as always, it is up to us that we use big data correctly and not just do it because it is just hype.

AI, deep learning and machine learning

One potential that the mastery of large amounts of data brings with it is the ability to give machines an intelligence, i.e. artificial intelligence. A machine could evaluate the controlling report itself and initiate measures, right?
On the one hand, you can find the term artificial intelligence. So says t3n : All technologies used in connection with the provision of intelligence services that were previously reserved for humans can be found under the generic term AI.
There is also the possibility of machine learning: machine learning describes mathematical techniques that enable a system, i.e. a machine, to independently generate knowledge from experience ( t3n ). However, deep learning goes one step further: “Deep Learning” with artificial neural networks is a particularly efficient method of permanent machine learning based on statistical analysis of large amounts of data (big data) and the most important future technology within AI ( t3n ).

Conclusion: what is big data?

Big data is a lot of unstructured data that we cannot evaluate by hand. Mastering such amounts of data can lead to great potential, but it can also “backfire”. The potential of this data mastery are new methods such as artificial intelligence, which can offer an enormous market advantage. I hope to have given an insight into the topic with this article and I am looking forward to my first article on this topic myself.

LEARN MORE ABOUT: What is Big Data

If you would like to find out more about the question: What is Big Data, please contact the Round tables participate and discuss relevant topics with myself and other experts. Or write in the comments how you are dealing with this trend. Also read my article to big data.
Tip: Book suggestions too Big data
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