Herausforderungen im Management Digitaler transformationen

Die 5 größten Herausforderungen im Management Digitaler Transformationen

Ähnelt Ihr Management der digitalen Transformation einer aneinander Reihung von IT-Projekten oder einem IT Großprojekt? Hm, falls Ja, dann sollten Sie kurz mal innehalten und die nachfolgenden Herausforderungen im Management Digitaler Transformationen sich durchlesen. Falls Nein, dann lohnt sich das Lesen trotzdem. Es gibt nämlich wesentliche Unterschiede zu beachten. Wer eine digitale Transformation steuern möchte, wie ein IT-Projekt, wird am Ende scheitern. Erfahren Sie hier die wesentlichen Unterschiede, und wie Sie als verantwortliche Führungskraft einer digitalen Transformation damit umgehen können.

Daten sind das Fundament einer jeden digitalen Transformation

Gewiss, auch in vergangenen IT-Projekten wie die Einführung einer ERP Lösung waren Daten wichtig. Aber sie standen nicht als oberste Priorität auf der Agenda des Programmverantwortlichen. Wer eine große SAP Einführung einmal mitgemacht hat, weiß aber wie sehr “saubere” Datenbestände und ein klares Datenmanagement am Ende einen erfolgreichen Rollout beeinflussen. In einer digitalen Transformation sind Daten jedoch der entscheidende Faktor. Vergleichbar einer Energiequelle für die fortlaufende Transformation im digitalen Zeitalter. Egal ob für den Einsatz künstlicher Intelligenz, Industrie 4.0, Digital Twins, IoT oder für die ersten Schritt im Metaverse … immer sind oder werden Daten die Treiber sein. Die Digitale Transformation bedeutet vor allem eine Veränderung hin zu einem daten-getriebenen Unternehmen. Ein aktueller Artikel von McKinsey (The data-driven enterprise of 2025 vom 28. Januar 2022) zeigt 7 Daten-Anforderungen auf, die es in folgender Form auch im Management einer digitalen Transformation zu berücksichtigen gilt:

  1. Daten müssen so vorliegen, dass sie in jede Entscheidung, Interaktion und jeden Prozess eingebettet werden können.
  2. Daten müssen in Echtzeit verarbeitet und abrufbar sein.
  3. Nutzung flexibler Datenspeicher für einfache Datenintegrationen in Echtzeit. 
  4. Im Datenbetriebsmodell werden Daten wie ein Produkt behandelt.
  5. Der Datenmanager steht in direkter Verbindung zur Führungsebene.
  6. Aufbau von unternehmensübergreifenden Daten-Plattformen, um die Zusammenarbeit mit Partnern bei datengesteuerten Projekten zu erleichtern.
  7. Die Datenverwaltung erfolgt weitgehend automatisiert, um Datenschutz, Sicherheit und Ausfallsicherheit zu gewährleisten.

 

“Das Ziel ist klar, nur weiß man nicht wie es konkret aussehen wird.”

Eine Digitale Transformation ähnelt einem agilen Vorgehen: das Backlog wird gefüllt, aber die Priorisierung kann sich von Zeit zu Zeit (Sprints) ändern. Das heißt konkret: die Absicht ist meist klar, nämlich möglichst viele Abläufe zu digitalisieren oder die Kundeninteraktion auf Digitale Kanäle umzustellen. Aber welche Anwendungen dafür am Ende genutzt werden, welche Abläufe wann umgesetzt sind oder wie weit und wo KI zum Einsatz kommen wird, kann nicht von Beginn an festgelegt werden. Meine praktischen Tipps hierzu:

  1. Gehen Sie iterativ bei der Digitalisierung vor und lernen Sie aus jedem Zyklus.
  2. Legen Sie zu Beginn Ihres Vorhabens die Rahmenbedingungen der Transformation in einer Digital Transformation Strategy fest.
  3. Empfehlenswert ist auch die Ausarbeitung einer Mission und Vision zur Digitalen Transformation. Dies kann jedes Unternehmen unabhängig von Beratern auf der Plattform von ConWISE (kostenlos und unverbindliche Registrierung hier) erstellen.
  4. Legen Sie besonderen Augenmerk auf das Change Management (Veränderungsmanagement) Ihrer Mitarbeiter. Denn welche Arbeitsplätze sich wann und wie verändern werden, kann zu Beginn nicht genau vorhergesehen werden. Die Verunsicherung wächst entsprechend, und sollten frühzeitig begegnet werden (auch dazu helfen die Punkte 2 und 3).

 

Kein ‘One solution fits all’

Die Digitalisierung ist nicht geprägt von einem einzelnen Big Player. Auch gibt es keine integrierte Lösung wie SAP oder Salesforce. Und falls Ihnen das angeboten wird, dann seien Sie misstrauisch. Die aktuelle Phase der Digitalisierung ist geprägt von einer unzähligen Vielfalt an Lösungen. Täglich kommen Startups auf dem Markt, die neue Innovationen bieten. Tech-Giganten wie Microsoft, Google oder Meta (Facebook) versuchen aus Eigeninteresse möglichst vieles unter einem Hut zu bringen. Interessant ist aber zu beobachten, dass dies meist durch offene Schnittstellen (API’s) geschieht. Und genau darauf sollten Unternehmen achten, dass die Lösungen flexibel eingebunden werden können und entsprechende Schnittstellen bieten.

Sie sollten auch die Möglichkeiten von Cloud-Lösungen nutzen. Damit bleiben Sie flexibel in der Einbindung neuer Applikationen. Die oben genannten Hinweise gelten entsprechend auch für Eigenentwicklungen. Falls Sie dazu externe Partner engagieren wollen, so setzen Sie auf Mikroprojekte, also kleine Projektausschreibungen, die von Zeit zu Zeit verlängert oder erweitert werden. Eigene Lösungen sollten dabei auch nach der Minimum Viable Product (MVP) Philosophie entstehen. Das heißt, primär geht es darum möglichst schnell ein lauffähiges Produkt auf die Beine zu stellen, das dann in Iterationen weiterentwickelt wird.

 

Neue Anforderungen an Release-Management, Rollouts und DevOps 

Die bisher genannten Herausforderungen im Management Digitaler Transformationen führen gleichzeitig zu gravierenden Veränderungen an organisatorischen Abläufen:

  • Release-Management: die Ausrichtung nach MVPs verkürzt einerseits die Release-Zyklen und steigert andererseits die Anzahl neuer Releases. Gerade bei innovativen Lösungen von Startups kommt es teilweise zu wöchentlichen oder monatlichen Updates. Grundsätzlich können sich diese auch auf andere Lösungen in Ihrem Unternehmen auswirken. Ein flexibles Testkonzept mit einer möglichst hohen Testautomatisierung ist deshalb unausweichlich. Dabei muss vor allem das Thema Datensicherheit und -integrität hohe Priorität eingeräumt werden. 
  • Rollout Management: in einer digitalen Transformation finden Rollouts ständig statt. Es fällt somit eine explizite Rollout-Phase weg. Bei Einführung von KI-Lösungen beispielsweise, wird die Skalierbarkeit auf andere Prozesse im Unternehmen ein entscheidendes Erfolgskriterium im Wettlauf der Digitalisierung sein. Dies liegt daran, dass es sinnvoll ist neue KI-Lösungen erst an einem “Prototyp”-Geschäftsprozess anzuwenden. Sobald dies erfolgreich war, kommt der Wunsch nach Ausweitung auf andere Prozesse unmittelbar auf.
  • DevOps: Die Definition von DevOps geht auf die Einheiten Development und IT Operations (Betrieb) zurück (Quelle: Wikipedia). Während vergangene IT Projekte entlang eines Wasserfall-Modell die explizite Übergabe von Entwicklung zum Betrieb vorsah, ändert sich dies mit DevOps hin zu einer aktiven Zusammenarbeit während des gesamten Vorhabens. Der Betrieb sollte bereits in die Erstellung der Anforderungen eingebunden sein.

 

Disruptive Solutions oder der Umgang mit neuen Technologien

Disruptive Solutions stehen im Zusammenhang mit digitalen Transformationen für technologische Lösungen, die das Zeug haben, die Transformation eine neue Richtung zu geben und so Prioritäten und Roadmaps durcheinander wirbeln. Problem ist nur, dass der disruptive Charakter dieser Trends zu Beginn Ihres Aufkommens schwer einschätzbar ist. Aktuelle Beispiele dafür sind Web3 und Metaverse. Beide Technologien wirken sich gravierend auf die Geschäftsprozesse oder gar auf das Geschäftsmodell aus. Mein Tipp: wenn man nicht gerade an der Spitze der Digitalisierung stehen möchte, reicht es ruhig zu bleiben und die Entwicklungen zu beobachten. Je besser Sie die Herausforderungen im Management Digitaler Transformationen kennen und entsprechend agieren, desto schneller sind Sie auch bei der Berücksichtigung möglicher disruptiver Technologien. Dies gilt besonders für hier als erstes beschriebene Herausforderung ein daten-orientiertes Unternehmen zu werden. Ist erst das Datenmanagement optimiert, kann man innerhalb kurzer Zeit auf Entwicklungen im digitalen Zeitalter reagieren ohne Wettbewerbsnachteile zu erleiden.

 

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Projektmanagement von IT Großprojekten

New approaches in the project management of large-scale IT projects

Every IT executive struggles with the implementation of large-scale IT projects. Studies consistently show that two out of three large programmes regularly fail to meet the original budget, miss the schedule and fall short of user goals and expectations after a long period of implementation. Often by a multiple.

These lapses are particularly detrimental to companies, as large programmes are usually of critical importance. Whether it is a global consolidation of ERP systems, the system-wide harmonisation of operational processes, or the merging of financial data across locations.

A number of new methodologies and tools that have emerged in recent years can significantly improve the implementation of large programmes. Combined with disciplined and experienced project management, the success rates of complex large-scale technology projects can be significantly increased.

We’ll show you how.

We show you below how programme management can be supported with the help of modern and partly digital applications. 

Using agile methods

Even companies that are committed to agile development often resist using agile methods for large programmes. This is not about black and white thinking, either agile or not, but rather using the advantageous components of agile management for themselves. From our experience, these are:

  1. Clear product responsibility
  2. .

  3. Prioritised product backlog
  4. Roadmaps based on sprints
  5. .

  6. Small cross-functional teams
  7. Iterative releases with timebox sprints
  8. Modular architecture
  9. Use of Objectives and Key Results (OKRs)
  10. Minimal Viable Products (MVP) as the first major milestone
  11. .

An agile mindset also encourages project staff to work more closely together, to break down possible silo thinking, to react more quickly to change, and to keep testing and learning.

The use of agile methods in large-scale projects also brings some advantages. The conversion of programmes that have already been running for some time to agile development also pays off – despite the late timing of the conversion:

  • Faster to visible results
  • .

  • Lower frustration among users
  • .

  • Fewer errors in the system
  • .

  • Better collaboration between different providers
  • .

  • Inclusion of smaller development companies instead of a large system integrator
  • .

  • Increased productivity
  • Higher delivery speeds

Using design thinking

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Many large programmes meet functional requirements but not the true needs of users. To meet the users’ requirements, design thinking comes into play. This is a method of problem solving that helps deliver products and features that users want and need and are therefore more likely to use. Another benefit is savings, as teams only develop the features that are really needed.

For large programmes, design thinking starts with identifying user requirements, through a mix of quantitative survey and qualitative research. This gives a clear picture of how users want to use the product, what their experience has been so far and what needs have not been met so far. It would be a mistake in a long-running programme to see this as a one-off. Rather, it needs regular and intensive user involvement throughout the programme’s life, for example in the creation of prototypes and in user tests. The comparison with the traditional approach should make clear how design thinking can work.

In the traditional approach, the user would be involved in the design process.

In the traditional approach, one would start with the collection of requirements from R&D, production, sales and customer service. This collection is often done in isolation from each other and then recorded in a requirements and specifications document. This is usually so complex that a review by the technical department more or less follows.

In contrast, within the framework of design thinking principles, cross-functional workshops and interviews take place to collect current problems and requirements together. Today, the use of a “digital twin” (Digital Twins) can be helpful. This is a digital simulation of a process on the computer. This makes it easier for those involved to identify problems and necessary interactions. This leads to an early exchange of information between the departments concerned, users, suppliers, providers and developers. On the one hand, an understanding of the true requirements is created for all, and on the other hand, the basis is laid for close and successful further cooperation during the course of the programme. This approach also speeds up the release of functions and facilitates the prioritisation of requirements in the product backlog by the product owner.

Cloud-based services

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Many executives tend to reduce the benefits of the cloud to efficiencies in infrastructure management. However, the possibilities inherent in cloud services can also be seen when applied to complex large-scale projects. The features offered by many cloud service providers give programme managers flexibility in deploying different environments. Cloud solutions make it possible to scale development environments within a short period of time, allowing prototyping or testing of novel solutions in a short period of time. The creation of project reports, which is usually resource- and time-intensive, can also be done much faster with the help of the cloud.

On the software development side, using a Platform-as-a-Service (PaaS) solution can significantly increase productivity and provide access to thousands of innovative services.

But it is not only during project realisation that the cloud can be used sensibly; even when determining the basic solution architecture, numerous cloud services now open up new options. Opting for a software-as-a-service (SaaS) solution, for example, can avoid the effort of custom development and lead to an equivalent solution that is also easier to maintain.

More flexible through microservices and modular components

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Many companies are moving to more modular, flexible architectures that allow for the inclusion of microservices, for example. This move allows companies to rely on multiple vendors in a programme, reducing dependence on just one major implementation partner. This also solves one of the biggest problems in managing large programmes: with single-vendor solutions, it is almost impossible to exert constant cost pressure, as fixed-price contracts often include a significant risk premium and change orders are common. On the other hand, time-and-material contracts create incentives for providers to extend or expand programmes and thus increase their revenue streams.

Modular architectures, on the one hand, allow clients to collaborate with multiple providers as mentioned, and on the other hand, individual providers can be replaced as needed. If several development companies work together in the programme, they can either compete against each other in each project phase or each receive smaller work packages (microservices), e.g. front-end designs or development and testing services. As the programme progresses, the best-performing providers – who bring in consistently competent staff at a reasonable cost – can then win the contract for a larger portion of the work.

Conclusion

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Large-scale IT projects continue to pose immense challenges to corporate executives. Their implementation has a significant impact on company operations. Not least, such programmes require massive budgets over several years, tie up a large number of employees in the company and are crucial for the careers of many executives involved in the project. Whether such programmes are successful certainly depends to a large extent on the leadership qualities of the people involved. In recent years, however, new approaches have been developed and technical possibilities have been added that project managers can access. Those who use these possibilities and apply them to their programme significantly increase the likelihood of success of complex projects. The best thing to do is to discuss with the project managers at Arentzen & Partner the extent to which the approaches presented could also benefit you and your project. Contact us!

Images used:

Computer photo created by standret – www.freepik.com

Dare to have lean project structures – build on your team

** Dear reader, this is an automated translation of the German blog post for your convenience. Please switch language to German to see the original contents. **
One of the strengths of established companies is that experience and knowledge gathered over the years have been poured into processes and Group-wide guidelines clarify many issues without the need for separate decisions. This ensures efficiency and uniform quality in the processes. It is precisely this supposed strength, however, that often changes into a obstacle for digitization projects.

In the case of these projects, the nature of the case is that the target state can not be completely defined in advance. (This was also the case with many previous projects for the automation case, if one allows an honest consideration.) Nevertheless, still today many projects are managed according to classic waterfall models.

The supposedly safe feeling

Although the classic waterfall method has not given many companies a good success in the implementation of projects in the past, they seem to give the participants a structure and a secure feeling. Finally, a plan can be drawn up, which lists all processes up to the finished project result and gives the project workers a guideline which is to be done in the near future. Thus, deadlines are foreseeable and in the ideal case also the required budget is transparent. At the very least, this is the illusion, which one is only willing to give.

The good feeling is supported by extensive project methods, which have been developed over the years and often provide a rigid framework for projects. There are process definitions, tools, templates and predefined stage gates, which should regulate the daily business in the project. These projects also take place in a corporate environment, which is governed by directives which have become complex through the years of experience. With these tight conditions, many established companies are trying to minimize the internal centrifugal forces and to ensure that all employees comply with the corporate orientation.

And now comes a digitization project

In hardly a larger project, the entire complexity can be viewed in advance and planned with the accuracy desired by the management. This is especially true for digitalization projects. With the help of agile approaches nowadays attempts are being made to take account of this and to lead projects iteratively to the goal. In each individual iteration, the knowledge gained in the previous iteration can be constructed. The subject is gradually opened up, and difficulties become more apparent, as it becomes clear within the short iterations whether or not they are solved.

However, since, for the reasons already mentioned, a classical waterfall model (without hybrid constructions) is often used, it is all the more important to maintain a certain flexibility in the sequences. No process, however well defined, will cover all possible scenarios, so that improvisation is inevitably necessary. In such situations, we often have a reputation for more structure and more process in order to manage the chaotic project.

The team decides

However, this should be done with an eye. In our experience, something else is of decisive importance in such an environment: the personal coordination of project staff among themselves. The personal (face to face) collaboration of teams and team members affected by a problem is THE key to success. It is not without reason that modern enterprises create flexible workspaces, which allow a situational collaboration of employees of different teams. And the more direct communication is, the better. Avoid trying to solve problems by mail ping pong. Encourage your employees to talk to each other personally.

In the case of locally distributed teams, select the best possible communication type that can be made available. If, for example, a trip to a common location is not possible, a video conference should be given preference over a pure telephone call or the exchange via e-mail.

You will experience it: If the employees in the project communicate well, many problems are easier to solve. However, this does not mean countless meetings, but the situational meeting in order to solve defined problems. However, it is also necessary for the employees to be given the corresponding responsibility and the trust that they can solve the task. Furthermore, it should be encouraged (and encouraged) to actively approach colleagues. Otherwise there is a risk that the employees will retreat to the defined process and find reasons why someone else is responsible for the next step…

Recommendations for the project management method

  1. If you do not want to (or can not) change to agile methods at the same time, check which flexibility allows the existing project method. Assume that, to the best of your knowledge, you are not able to plan everything in advance, and you are deliberately planning checkpoints, in which you can consciously review and adjust the existing planning. Be sure to be honest with yourself. Shifting problems into later phases brings the anger later, but you have less possibilities to react.
  2. Check what you can remove from your project methods. Do not always add rules. (“Perfection is not achieved when nothing can be added, but nothing can be left out,” Antoine de Saint-Exupéry
  3. Set the focus on open and direct communication. Your process will never cover all eventualities. But especially in unforeseen situations, people can find creative solutions through direct exchange. And if this is still difficult at first, a moderator or facilitator can help.