In this post
Introduction to this topic
1. Historical Foundation
What companies should permanently take away from accelerated digitalization separates the structural lessons of 2020 from short-term crisis improvisation.
The contribution shows why digital connectivity, clear responsibility, accessible knowledge, and robust processes were more sustainable than individual emergency solutions.
2. Current Maturity Check
What digital maturity truly showed in 2025 forms the core contribution of the topic area.
He explains digital maturity as controlled use of technology, knowledge, roles, and control. The contained maturity model serves as a checklist for specific use cases.
3. New Marketing Function
The new task of marketing teams: activating knowledge deals with the organizational connection of expertise, content, search, service, and AI systems.
The contribution defines Knowledge Activation as the goeke.digital organizational model and distinguishes this role from pure content production and classic document management.
Transformation is decided in regular operations
Organization and transformation are not downstream accompanying topics of digitalization. They determine whether new technologies, communication channels, and work methods actually become compatible within the company.
Digital maturity is therefore not reflected in the number of tools used. It is reflected in whether a company:
- Assigns changes to a business purpose,
- Responsibility organized accessibly and comprehensibly,
- provides reliable knowledge and data,
- Processes designed across departmental and system boundaries,
- new ways of working are controlled and transferred into operations,
- Effectiveness and risks regularly reviewed,
- learns from mistakes and changing requirements.
The topic area connects the historical experience of accelerated digitalization, the 2025 final exams, and the changed role of marketing teams in 2026.
The central problem
Many digital projects begin as technical initiatives.
A new platform is selected. An AI pilot is launched. A CRM, a website, or an automation tool is introduced. Responsibilities, knowledge, workflows, and success criteria are added later.
This sequence creates typical breaks.
Technology is available, but its use remains person-dependent
Individual employees know how a system is used effectively. This knowledge is not documented or shared. If the person is absent or changes tasks, the application loses its effectiveness.
Responsibility gets stuck between departments
The specialist department, marketing, IT, data protection, sales, and management view the same use case from different perspectives. If no binding decision-making level exists, decisions are either made too late or action is taken informally.
Processes are digitally mapped but not clarified
An unclear workflow is replicated in a new tool. Media disruptions and duplicate maintenance remain. The interface changes, the organizational logic does not.
Knowledge is stored but not activatable
Documents are stored in cloud folders, wikis, emails, and presentations. Their validity, responsibility, and relationship to each other are unclear. This leads to recurring coordination and contradictory statements.
Pilots work better than regular operations
A project team closely monitors the trial. Exceptions are resolved manually. After the expansion, time, roles, quality control, and measurable decision criteria are missing.
What digital transformation means organizationally
Digital transformation is the permanent change of value creation, communication, collaboration, and control through digital possibilities.
It is not to be equated with digitalization.
Digitalization can transfer an existing analog process into a digital form. Transformation additionally changes the way of working, responsibility, or performance logic.
A digital form is digitalization. A continuous process in which information is captured once, checked responsibly, used across systems, and evaluated for impact, has a transformative dimension.
The size of the project is not decisive. What is decisive is whether the work system changes.
The five levels of organizational connectivity
1. Purpose and priority
Every change requires a comprehensible business purpose.
This can lie in higher quality, better access, lower effort, faster response, stronger customer orientation, or reduced dependence.
Without priority, digital projects compete for time and attention. The number of initiated projects increases while the ability to implement decreases.
2. Roles and Decision
Change requires roles for:
- business purpose,
- technical quality,
- Process responsibility,
- technical implementation,
- Knowledge and data,
- Release,
- Risk and escalation,
- Measurement and further development.
In smaller companies, several functions can be held by one person. However, they must not remain invisible.
3. Knowledge and Competence
Employees need more than just operating knowledge for a tool.
You need to understand:
- why the new way of working is being introduced,
- which rules apply,
- which information is binding,
- which limits and risks exist,
- when human review is necessary,
- how errors are reported,
- who decides in uncertainty.
Competence arises from application, feedback, and clear work foundations.
4. Process and System
A technical solution must fit into the actual workflow.
These include triggers, inputs, handovers, exceptions, checks, results, and feedback. Only when these connections are clarified can it be assessed whether a tool supports or creates additional complexity.
5. Steering and Learning
Transformation does not end with project completion.
New requirements, system changes, errors, user experiences, and business development require regular review.
A learning organization can expand, adapt, limit, or terminate a solution without having to reinvent the original decision path.
Typical misconceptions
“Employees just need to be more open to change”
Resistance can have personal reasons. However, it often arises from unclear goals, lack of participation, contradictory instructions, or additional burdens.
An organization should not automatically treat resistance as a lack of attitude. It can be a signal for real process or quality problems.
"A good tool sells itself"
A useful tool facilitates acceptance. It does not replace roles, rules, and integration.
If employees maintain data twice, approvals continue to happen outside the system, or binding information is missing, usage remains superficial.
„Transformation requires a large program“
Not every improvement requires a comprehensive transformation project.
Many advances arise from targeted clarification of a critical workflow. It is important that the change does not end as an isolated optimization but is connected with the adjacent roles, information, and systems.
“More centralization automatically creates order”
Common standards and knowledge sources are useful. However, excessive centralization can lead to a loss of proximity to the subject matter and speed.
Robust transformation combines central guardrails with decentralized specialist responsibility.
"Digital maturity can be represented by a single score"
Maturity is application-related.
A company can be highly developed in digital sales and weak in knowledge management. An overall score can provide orientation, but it must not obscure critical differences.
The transformation system
Connections to other topic areas
Digital Strategy
Strategy defines purpose, priority, and sequence. Organization decides whether these decisions can be implemented in everyday life.
Positioning and Impact
Clear positioning requires consistent statements, behavior, and evidence. Organizational contradictions will sooner or later lead to communication contradictions.
Websites and digital systems
Websites and systems map work and decision logic. Their quality depends on processes, roles, and knowledge.
Visibility and Search
Discoverability is not solely created by technical optimization. Subject matter clarity, timeliness, and responsibility must be organizationally secured.
Content and Expertise
Knowledge architecture and content governance require owners, maintenance processes, and activation channels.
Data and Control
Measurement only becomes effective when key figures are linked to decisions, accountability, and learning loops.
AI and automation
AI and automation reinforce the existing organizational foundation. Therefore, process clarity, knowledge base, human review, and governance are part of transformation capability.
Action framework for companies
1. Select a critical workflow
The introduction should not begin with a general transformation vision, but with a relevant process whose weaknesses are visible and whose impact is comprehensible.
2. Clarify purpose, roles, and knowledge before technology
Before selecting or expanding a system, the business purpose, subject matter responsibility, knowledge sources, and decision-making boundaries must be defined.
3. Design normal operation instead of demonstration
A process must function under real time, personnel, and quality conditions. Manual special support in the pilot must not be misunderstood as permanent performance.
4. Institutionalize feedback
Errors, queries, exceptions, and user experiences belong in a regulated improvement process.
5. Limit and prioritize change
Not every possible optimization is sensible at the same time. Clear priorities protect the organization from constant restructuring and divided attention.
Subject-matter connection
Connect digital change strategically and operationally
The SDC partnership and transformation support create a connecting level between management, marketing, specialist departments, and technical implementation. The focus is on prioritization, roles, knowledge and process clarity, as well as a controllable transition from pilot to operation.
Organize digital change as a coherent corporate capability
Sources and factual basis (6)
- OECD, „OECD Digital Economy Outlook 2020“, 2020. Open source
- European Commission, “2025 State of the Digital Decade package”, 2025. Open source
- European Commission, “State of the Digital Decade 2026: Closing structural gaps and mobilising investments for 2030 and beyond“, June 17, 2026. Open source
- ISO, "ISO 30401:2018 Knowledge management systems. Requirements". Open source
- NIST, „Artificial Intelligence Risk Management Framework 1.0“, 2023. Open source
- European Commission, "AI Act. Regulatory framework and application timeline". Open source

