In this short session, we will familiarize your managers with the format, purpose, learning objectives, requirements and framework, and establish the common ground rules for the upcoming learning journey.

We begin by deconstructing the global and digital developments of our time and exploring how they affect you as a leader and your company – today and in the future:

• What is Data Leadership and why do we need it?
• How well prepared are you as a company and as a leader for the changes and challenges of the digital age?
• What are the most important digital topics and trends of our time, what strategies do the best technology companies use, and how can you use them too?
• What other megatrends are influencing companies in the 21st century – and which are most relevant to your company?
• How do you make effective data-based decisions in a volatile, uncertain, complex, and ambiguous economic environment?
• How can you sharpen your data awareness to effectively incorporate data insight into your decision-making?
• What new skills do you need as an individual and as an organization to make the best possible use of the potential of new technologies?

To work effectively with data analytics and insights, we need to develop a basic understanding (“how-to”) of the function and value of data:

• Why are data, data analytics, and business intelligence so valuable to companies – what is the “value of data driven”?
• What is the ABCs of data and how do (A) AI (Artificial Intelligence), (B) Big Data, and (C) Cloud technologies work?
• What are the characteristics of Big Data and how can information derived from it best be used to solve complex business problems?
• What is the CRISP model and how can it serve as a guide on your path to becoming a data-driven company?
• How do you develop business hypotheses that can be tested and resolved through data analysis?
• What are the characteristics of structured, semi-structured, and unstructured data – and when should you use which system?
• What data analysis methods are available – and when is each one helpful?
• How can you test and validate data using modeling?
• What roles and responsibilities do managers and IT experts have in AI-driven projects?
• How do they communicate effectively with data scientists?
• How do you correctly evaluate and measure the results of a data analysis – and what steps are necessary to implement the new insights?
• How can Agile, Design, and Lean Thinking improve your work with data?
• How do you translate data insights into a business context to derive concrete action steps for yourself and your teams?

In addition to building data knowledge, leaders must also learn new leadership principles, skills, practices, and systems to support their teams in understanding and working with data and new technologies:

• How can data-driven leaders provide meaning and guidance for employees during their digital business transformation?
• How do you integrate established and new leadership approaches to create synergy between old and new ways of thinking and behaving?
• What is a data-driven mindset – and how do you develop it (lead with data)?
• What are the unique potentials of people and technologies – and how can you combine both to your advantage?
• How can you spark curiosity and motivation for data projects and create innovation?
• How do you prevent cognitive bias and instead develop an objective and holistic view of your projects, your company, and the economic environment in order to make decisions with clarity and foresight?
• How do you feel about data in general, and how do you deal with your thoughts and emotions in connection with specific data projects or analyses – especially when the results do not meet your original expectations or wishes?
• How do you cultivate “Diversity of Thought” within yourself, your teams, and the entire company to foster (technological) innovation?
• What is “systems thinking”, why is it an essential leadership skill in the digital age, and how can you harness its power?
• How do you make adaptability one of your core personal and organizational competencies, enabling you to change direction quickly, flexibly, and almost effortlessly when needed?

Having developed a theoretical understanding of data and its use in businesses, we will now examine how its potential can be used practically in everyday business:

• What data sets already exist in your company and how do you determine what information still needs to be acquired in order to reduce costs, increase revenue, improve products/services or promote innovation?
• What specific methods can be used to make money with data, and when should you apply which monetization strategy?
• Which data analysis methods does your company currently use most frequently, and are these methods suitable for overcoming current challenges?
• How can you use “digital storytelling” to communicate data projects and results to different stakeholders in a simpler and more engaging way?

In this module, we will further deepen your understanding of data and broaden your perspective on the use of technology in general:

• What are the 5 principles of digital ethics, and why are they so important for future business success?
• What moral obligations exist in the collection, protection, and use of data, as well as in the application of artificial intelligence?
• What is the difference between supervised, unsupervised, semi-supervised, and augmented learning in the context of machine learning (ML)? What are the characteristics of each of these learning types, and which is best suited to improving processes in your team/department/company?
• How do you distinguish between correlation and causation – and why is this important for your decision-making?
• How do you assess the potential of exponential technologies? Which ones should be integrated, and which ones are better left out?
• What are the unique capabilities of humans compared to machines? How can we integrate the diverse potential of algorithms and so-called “androrithms” to create synergy?
• What can you do to develop your human potential and use it as a unique selling point in a machine-dominated world?
• In which areas will humanity be most relevant in the future?

Finally, we will develop approaches for how you can further integrate your new data know-how into your company:

• What is the Dialogical Process and how can it help business leaders have deeper and more valuable conversations about data, technology, and business decisions?
• In your opinion, what are the key skills that ‘data-driven leaders’ need to successfully lead themselves, others, and their company through the digital age?
• What are the 4 digital mindsets, how do you cultivate them alone and in your teams, and why are they relevant for improving data-driven decision-making?
• What do you need to do differently, what should you avoid, and what can be improved on a personal and organizational level to leverage data and new technologies? What actions can you take in the next 72 hours to kick-start your digital transformation?
• How can you drive positive change in your company and in society as a whole by using technology and data “for good”?

Data-driven leadership ensures that every leader becomes a driving force for change through data and AI – and doesn’t unknowingly hinder it. Change often requires new skills and competencies from the people affected. In our training, we impart these skills and tailor them to your specific needs. This ensures that your leaders master precisely the principles, competencies, and tools that are essential for your company.

The advantage of a data-driven approach is faster, better, and more transparent decisions. Leaders make many decisions quickly. These decisions are often based on experience, intuition, or feelings—and can be influenced by unconscious bias. Data-driven decision-making means that leaders and teams use existing or new data sources to inform their decision-making, leading to better decisions. These decisions are transparent and supported by evidence.

Key competencies for data-driven leadership include a fundamental understanding of data sources and structures, analytics methods, and technological concepts (data literacy). Another important competency is the ability to embrace new perspectives. Data-driven decisions can differ from conventional ones, and new and more diverse viewpoints are integrated. Data-driven leadership also represents a cultural shift and influences collaboration, co-creation, and decision-making.

Almost every leadership situation can be supported by data-driven strategies. Depending on the field of activity, function, situation, or problem, data can be used to improve the quality of decisions. Data-driven leadership is becoming a deeply ingrained leadership competency.

This question is difficult to answer, as there are thousands of trainers and even more training options available. Generally speaking, we stand for New Leadership, meaning we don’t rehash theories from the 80s and 90s. We don’t just impart knowledge with PowerPoint – there’s often no shortage of that – but focus on application, experience, reflection, and collaborative learning. And we don’t offer standard formats; instead, we tailor each training program specifically to your requirements and needs.

Many of our leadership training programs fundamentally support a cultural shift, going beyond simply imparting skills. In this way, leadership training becomes a foundation for your organizational development.

The Data Driven Leadership training is designed as a 4-day event or as a learning journey over several weeks. Depending on your requirements or those of the participants, we can conduct it as a single event or in several sessions.

If we choose the Learning Journey format, participants deepen their knowledge through independent work (also in groups) and learning on the job.

Ideally, every employee in a leadership role should participate. Data-driven leadership is new for everyone, so we don’t impose any restrictions. The mix of first-line managers, middle and senior executives often creates an interesting dynamic and a fruitful exchange.

Each training or program is developed to meet the specific requirements of your company. This begins with a co-creation, concept phase, iterative improvements and a roll-out. We don’t do anything “off the shelf”, but immerse ourselves deeply in your culture and structure. In this way, our work becomes part of your organizational development.

Admittedly, this is a challenge. How do you combine universal New Leadership principles and new leadership skills with very specific, strategic topics such as digitalization, AI or sustainability?

And how do you adapt this to your company? We master this through our community of trainers from different disciplines, who are integrated into the development process from the outset and “speak the same language”. This means we cover a diverse range of topics, but work together with the same spirit.

All of the trainers in our community have their own leadership experience, have all completed in-depth external coaching and/or trainer education and have also taken part in our internal train-the-trainer programs.