Process & Change Management

You will see how AI-based models become part of your day-to-day work on change – as a sparring partner, an analytical tool and an assistant. Classic process and change thinking is combined with data-driven methods to free up time for the decisions that really matter. The aim: to rethink processes and change and to lead change more effectively.

• Understand the role and impact of AI in process optimization and change leadership
• Use AI as a sparring partner, analytical tool and assistant in day-to-day change work
• Combine experience and process knowledge with data in a targeted way
• Redesign decision architectures for complex change questions
• Use tools for fast, robust decisions in process and change initiatives
• Clarify responsibility and transparency when using new analysis methods
• Consistently avoid misreading process and performance data
• Win back time for strategic change work

Data-driven methods change how you work with process information, weigh options and take change decisions. The seminar shows how the quality, speed and consistency of your decisions improve measurably – without losing rigor.

• Understand data-driven systems and integrate them into change processes
• Use Predictive Analytics and scenarios to spot developments earlier
• Use simulations for capacity, lead-time and resource decisions
• Separate relevant metrics from irrelevant – focus on what matters
• Prioritize change initiatives by effort, impact and risk
• Secure quality and consistency in change decisions
• Delegate to AI-based analysis tools sensibly and keep control
• Safeguard decision quality through structured reflection

Process optimization starts with solid facts, not assumptions. You learn to make workflows visible end to end, identify bottlenecks and waste, and design improvements where they pay off.

• Structure the process landscape and make it visible end to end
• Use Process Mining and process data for robust analyses
• Identify bottlenecks, system breaks, duplicated work and waste
• Improve lead times, error rates and process costs systematically
• Weigh standardization against deliberate exceptions
• Assess automation and AI potential realistically
• Reorganize the interfaces between units, systems and partners
• Put the customer perspective and value creation firmly at the center
• Embed continuous improvement in daily work instead of leaving it to projects

Every process change reaches beyond its own area – into roles, skills, costs, interfaces and culture. You learn to anticipate these effects systematically, measure them and steer them actively.

• Make impact chains visible: from the process change to the business result
• Run impact assessments for the areas, roles and interfaces affected
• Detect unwanted side effects and displacement effects early
• Avoid local optimization at the expense of the wider system
• Assess the effects on employees, skills and workload realistically
• Evaluate the effects on customers, quality and delivery capability
• Build robust cost, benefit and payback calculations
• Evidence impact with suitable KPIs and before-and-after measurement
• Organize corrective action when the expected impact fails to materialize

Change does not succeed by decree, but through participation, clarity and consistency. You learn to set up change initiatives so that they land in the organization and last.

• Make the case for change clearly and develop a convincing target picture
• Set up the change architecture, roles and responsibilities cleanly
• Turn those affected into participants and involve key people early
• Understand resistance, take it seriously and work with it constructively
• Balance pace, sequence and the organization's capacity realistically
• Use quick wins without putting long-term impact at risk
• Enable managers to act as multipliers in the change process
• Understand and shape culture as a success factor in transformation
• Move transformation from concept to consistent implementation
• Identify what makes change last and prevent a relapse into old patterns

Effective change depends on clear communication. The module covers stakeholder communication, dialogue with those affected, crisis communication and alignment between executive management, the project and the line organization.

• Sharpen messages for different stakeholders and affected groups
• Use AI to make complex process and data relationships easy to grasp
• Present the logic behind decisions transparently and comprehensibly
• Strengthen trust, credibility and clarity in change communication
• Prepare dialogue formats, town halls and feedback loops deliberately
• Communicate effectively in critical phases and after setbacks
• Ensure alignment between project, line organization and executive management
• Balance AI-supported and personal communication sensibly

You analyze project trajectories, process metrics and organizational dynamics with modern methods – and translate weak signals into effective countermeasures, resilience and stability.

• Build early-warning systems for process deviations and project progress
• Recognize weak signals of overload, lost trust and change fatigue
• Expose spurious causality, policy resistance and typical thinking traps
• Assess the risks of automation, system changes and migrations
• Make dependencies on systems, suppliers and key people visible
• Build resilience to disruptions, outages and swings in demand
• Find the balance between stability and agility
• Prepare and rehearse crisis management systematically
• Resolve conflicts between units constructively
• Adapt organizational models, responsibilities and interfaces to new dynamics

AI changes not only process decisions, but also responsibility, liability and trust.

The seminar treats AI not as uncritical hype, but as a responsible leadership instrument for lasting impact and legitimate decisions.

• Develop governance structures for process ownership and the use of AI
• Define responsibility, liability and roles clearly in automated processes
• Take account of data protection, employee representation, compliance and regulatory requirements
• Establish ethical guardrails for automation and performance data
• Build acceptance among employees, the works council and stakeholders
• Address bias and misinterpretation in process and performance data systematically
• Ensure quality assurance, documentation and auditability
• Assess and communicate the effects of automation on jobs transparently
• Judge the limits of AI in process and change initiatives realistically
• Balance human responsibility and technological possibilities sensibly

You identify the biggest levers in your own area of responsibility and develop your personal process and change playbook – strategically grounded and ready to use in your leadership practice.

• Reflect on your own process and change practice in a structured way
• Recognize strengths, gaps and untapped potential
• Identify the biggest levers for impact, speed and acceptance
• Bundle fragmented initiatives and align them for shared impact
• Derive concrete measures for your own area of responsibility
• Set implementation priorities for the next 100 days
• Develop a personal process and change playbook for everyday leadership
• Prepare the transfer into your organization, your team and everyday change work