IT-Leadership                                                                                                               Vision

SIBB series "IT Leadership Vision" started on January 11, 2023 with Dr. Ralph Kleindiek CDO - Chief Digital Officer of the State of Berlin and State Secretary for Digital and Administrative Modernization.

Here you can find all videos of previous IT-Leadership Vision events in one playlist.

The next dates for SIBB IT Leadership Vision

2nd quarter 2024, tba

Our past dates in the overview

30th January 2024
Dr. Matthias Flügge, Chief Digital Officer, Digital strategy and digital transformation at Deutsche Rentenversicherung Bund
Youtube videolink

18th October 2023 
Martina Klement - Staatssekretärin für Digitalisierung und Verwaltungsmodernisierung des Landes Berlin
Youtube videolink

23th May 2023
Michael von Roeder, Group CDO 50Hertz Transmission GmbH I Elia Group
Youtube videolink

20th March 2023
Dr. Torsten Freiberger, Head of Organizational and Productivity Management at Berliner Sparkasse
Youtube videolink

11th January 2023
Dr. Ralph Kleindiek CDO - Chief Digital Officer of the State of Berlin and State Secretary for Digital and Administrative Modernization
Youtube videolink

Public Cloud (Native) First Strategy

• The focus in cloud computing is clearly no longer on the technological level, but on the business and its applications. Enterprise customers want to accelerate their digital transformation strategies, modernize their legacy environments and move to the cloud. This now includes legacy systems from the mainframe environment.

• Companies are therefore benefiting from increasingly mature migration concepts and aids. Cloud programming interfaces and analytics functions are gaining importance. Companies are also aligning their migration strategies more closely with business scenarios and looking for differentiated deployment models.

• Significant growth in demand for multi-cloud services, and this is largely independent of company size. It is true that many companies have been operating with multiple cloud solutions for some time. But most of these are still running independently of each other. Accordingly, the integration and joint management of these individual solutions is now coming into focus. The goal is to integrate the systems and their data to such an extent that their usage behavior and the associated costs can be predicted (and optimized).

AI Driven Automation & Autonomous Services

• According to ISG Research, most companies remain in the early stages of automation. Only seven percent worldwide are enriching simple Robotic Process Automation (RPA) with intelligent automation that makes use of artificial intelligence (AI), among other things. Often, the know-how to deal with unstructured data is lacking. But insufficient AI knowledge and too little internal training also hinder such projects. This is driving enterprise customers to look for transformative sourcing options that incorporate intelligent automation.

• These might include software bots that can interact with unstructured data and also bring the following capabilities: Image recognition, Natural Language Processing (NLP), cognitive capabilities, and automated (customer) dialog systems (Conversational AI). Thanks to such automation technologies and in combination with advances in process mining, for example, it is now possible to automate processes that were previously considered impossible to automate.
  
  
  

Trusted Cyber Security Mesh

• On the rise are "zero trust" architectures that follow the "trust but verify" approach. In this respect, companies no longer rely primarily on reactive but on proactive and preventive measures to protect their data assets from attackers.

• However, security frameworks are only as good as the IT staff who implement them. In addition, cybersecurity experts must be familiar with new approaches such as "cybersecurity mesh." This involves establishing mobile security zones around individual users that function outside of traditional security zones on the corporate network.

• In addition, the DataSecOps approach is becoming more widespread, with IT and data scientists collaborating from the outset to integrate security measures into the infrastructure. This ensures that applications are transparently integrated into the security network to improve the integration of all relevant systems and devices.
  
  
  

Embedded Data Science Factory & Resilience

• Data analytics is now one of the key factors that determine the competitiveness of companies. However, data science is often carried out in isolation in laboratories that deal exclusively with machine learning models instead of gaining meaningful insights for the business. This is where so-called "embedded data science factories" provide a remedy. They are embedded in the overall organization rather than isolated from it. They work with the data that their company generates every day.

• Successful embedded data science factories rest primarily on two pillars: first, they need suitable structures and a corporate culture that integrate the data factory into daily business operations. This includes training for all employees, not just data scientists. Second, all stakeholders need the right tools that can be operated by both subject matter experts and data scientists.

• Data analytics is also playing a growing role because the topic of "data resilience" is increasingly being discussed. What is meant by this is that data can "bounce back" if, for example, a cyber attack or natural disaster causes disruption and interruption. The cloud, for example, enables data resilience because data can be stored and accessed in multiple locations.

Low-Code/No-Code Strategy

• Low-code is much more than just a new tool for citizen developers and does not stand for a comeback of uncoordinated shadow IT. Low-code stands for a fundamental paradigm shift, and is just as suitable for professional software developers as for so-called 'business developers', but above all also for mixed low-code developer teams consisting of business and IT experts.

• Low-code and no-code stand less for a concrete technology than for a different approach. There are many quite different approaches to solutions, each optimized for specific types of tasks. Therefore, it is not a matter of deciding on exactly one low-code platform, but rather of initiating a change in thinking throughout the entire company. The goal must be to implement a wide range of digitization options with low code, using the most suitable platforms for the various purposes.

• Low-code is also an answer to the shortage of skilled workers: both through much greater efficiency and through a much broader developer base. No one can get around low-code and no-code anymore, because there aren't nearly as many programmers as would otherwise be needed.

Decentralized & Hybrid Enterprise

• Technologies that enable workplaces beyond the traditional office have become commonplace at the latest with the COVID pandemic. In this context, ISG also speaks of the hybrid workplace, where technology appears to be less problematic than the provision of adequate and thus digital training offerings in the context of a change management program for employees.

• The next step is now to use these technologies for further analysis and to use them to tap new business potential. For example, it may be a matter of identifying digital burnouts and other signs of fatigue in the workforce at an early stage. Another focus is on "immersive learning," where employees are trained with the help of augmented and virtual realities.

• It is now also up to employees themselves to decide which devices, apps or artificial intelligence they want to use and possibly optimize through in-house developments using low code/no code solutions. This democratization of job design and equipment must be able to map the technology both in the hybrid workplace and throughout the company.

Sustainability & Decarbonization

• Digitization is leaving an ever-increasing technological and infrastructural footprint. IT is therefore a central building block when it comes to the sustainability and CO2 neutrality of companies. Particularly since these characteristics are also increasingly decisive for business success. After all, those who continue to follow non-sustainable business models will find it increasingly difficult to find business partners or end customers and, in particular, the already scarce skilled workers who are increasingly guided by sustainability criteria when choosing a job.

• As a result, a separate market for sustainability and decarbonization services has emerged in the IT industry. The declared goal: net-zero emissions and the use of 100 percent renewable energy. The service providers primarily advise public cloud, data center and hardware providers on how they can achieve their sustainability goals and drive digital transformation at the same time.

X-Reality & Converged Experience

• While some companies have recently shifted customer contact to online channels, others are already a step further and are using their online channels for entirely new services. So-called X-Reality technologies are blurring the boundaries between the real and digital or virtual worlds. This trend is changing the way companies develop products or organize marketing, sales, delivery and post-sales processes.

• In any case, augmented reality (AR) will bring back much of the context and trust in product purchasing that was lost in part with the pandemic and lockdown-induced closure of already struggling retailers. Examples include indoor navigation or interactive price tags to avatars.

• In addition, in the context of e-commerce or the trend toward the distance economy, digitally advertised products can be better assessed, which can also reduce the rate of returns. One of the strengths of AR is its ability to present products in larger dimensions. In addition, product attributes can be presented more convincingly through 3D and AR interfaces than through conventional 2D images in classic e-commerce.

Digital Supply Chain Transformation & Management

• Supply chains, or the disruption of them, are currently making headlines on an almost daily basis. Technologies such as IoT, machine learning, artificial intelligence (AI) and the predictive analytics they enable can help make the supply chain more flexible, efficient and resilient through digitization.

• For one, a digitized supply chain transforms a company's ability to proactively assess and then serve customer needs. On the other hand, predictive maintenance & production creates further optimization of processes beyond the boundaries of the company. In addition to cost savings, the goal here is to create a predictive, self-optimizing supply chain and thus generate further competitive advantages.

• To provide such capabilities, sensors, predictive analytics, digital twins, blockchain, machine learning, and AI are being used to create the most end-to-end real-time visibility possible. Most recently, the COVID-19 pandemic significantly accelerated the shift to digital supply chains in enterprises. In times of volatility in financial markets and raw material availability, it is more important than ever to track individual components, their delivery status, or even specific conditions (for example, in the food industry) down to the last detail.