Digital Twins of Organizations – the new normal

When competition suddenly draws closer 

Imagine Chinese providers pushing into your market over the next few years. Perhaps you don't even have to imagine it. In the automotive industry, mechanical engineering, or solar technology, this shift has long been visible. 

You will notice that your company is exposed to a pressure that it did not know in this form before. The new competitor is often cheaper. Wages and energy costs, two of the major cost drivers for many companies, are far below the German level elsewhere in the world. Added to this are larger home markets, a high speed of scaling, and an industrial policy that can be debated, but whose impact is difficult to argue away. 

To continue competing in the future, you basically have exactly two levers. 

The first is called product differentiation. If your product is significantly better than that of the competitor, you can charge a higher price. Perhaps it offers better quality, more sophisticated features, stronger design, easier use, or more security. Those who have a real head start need to fear pure price comparison less. 

If this strategy works for you, it is an extremely luxurious situation. And one that fewer and fewer companies can rely on in the long run. The learning curves of the competition are getting steeper. Globally available technologies, purchased expertise, and AI ensure that knowledge travels faster. A lead that used to last ten years can be exhausted after three years today. The German automotive industry is currently demonstrating quite clearly how a differentiation strategy is reaching its limits. 

This leaves the second lever: productivity. You have to manage to generate more output with the same input, or the same output with less input. This reduces the relative costs per produced good. Your unit labor costs decline, and the gap to the cheaper competition becomes smaller. 

So far, this is banal. Of course, every company wants to become more productive. The term only has one decisive disadvantage: it is cloudy enough so that everyone agrees and no one knows exactly what should run differently on Monday. 

A rallying cry will not solve your problem 

I'm probably not leaning out of the window too far when I assert: in your company, quite a lot of people are already in constant stress. Calendars are full, inboxes are fuller, and someone always has an urgent, high-priority question. 

Do you want to make a rallying cry now and explain to your employees that they should work faster and more? 

No. That would not be an increase in productivity. It would merely be an increase in pressure. 

Anyone who accelerates a poor workflow produces questions, loops, and errors faster. More speed does not clarify responsibilities. And the third hour of overtime does not transform a superfluous task into value-creating activities. 

Real productivity increase is unsexy. It is operational. It lies in handovers, approvals, search times, system disruptions, and responsibilities. There you have to find out why three departments maintain the same data, why a report is created that no one reads, and why a process needs five signatures even though two of the signees have long forgotten what they are actually liable for. 

The devil is in the details here too. 

Effectiveness comes before efficiency 

When thinking about productivity, companies quickly ask the question: How can we improve our processes? This question is important. It probably already determines a significant part of the work in your management levels today. 

Before that, however, another question belongs on the table: Are we doing the right thing? 

Business administration distinguishes here between effectiveness and efficiency. Effectiveness means doing the right things. Efficiency means doing these things right. The order is crucial. Otherwise, you might optimize a process whose existence no one can justify anymore. 

You can build the most efficient bread baking machine in the country, complete with a fully automatic vending machine and a supply chain that brings tears to any management consultant's eyes. If your business model consists of selling cars, you'd better turn the apparatus off. 

The bread machines of everyday office life are harder to recognize. They are called monthly reporting, grown approval cascades, or special solutions for a customer who already canceled in 2019. Because these processes work, hardly anyone questions their existence. You shorten the throughput time, automate individual steps, and rejoice over green metrics. This makes the ineffectiveness cheaper. It doesn't make the process right. 

Why process management alone is not enough 

At this point, a justified objection usually arises: We are already doing process management. We have documented our processes, use specialized software, and model according to BPMN 2.0. Why do we additionally need a digital twin of the organization? 

Process management is excellent at taking a close look at a single workflow. A BPMN model can show where a process begins, what steps are taken, who is involved, and at which point a decision is made. This allows weaknesses to be found, throughput times to be shortened, and processes to be prepared for full automation. 

This answers the question about the efficiency of this process. 

For the question of its effectiveness, the organizational context is missing. Does the process still fit the business model? Does the company have the appropriate capabilities and resources? What systems, roles, and documents depend on it? Who uses the output? Is it processed further in another process? Does the same work exist elsewhere, just under a different name? 

These questions can hardly be answered from the isolated analysis of a single process. Even a hundred cleanly modeled processes do not yield a complete picture of the organization if they lie side by side in folders.  

This is exactly the difference between pure process management and a Digital Twin of an Organization. 

The DTO connects the individual snippets 

A Digital Twin of an Organization, or DTO, represents the organization as an interconnected system. It links processes with roles, responsibilities, systems, documents, resources, and handovers. From many individual models, a digital operational picture emerges. 

Suddenly, you see more than the process itself. You recognize where processes depend on one another, which people hold critical knowledge, and which systems are actually needed for value creation. You see whether a result is processed further somewhere or ends in organizational nowhere. Duplication of work and missing responsibilities become visible, as do departments working on the same goal without knowing about each other. 

This allows you to ask the questions in the correct order. First: Does this process make sense for our business model and our value creation? After that: How can it be improved? 

The DTO also provides a reality check for change projects. During a reorganization, it becomes visible which handovers and responsibilities are affected. Before an ERP migration, you recognize which processes depend on certain systems. During an AI implementation, you can check where automation makes functional sense, what data is available, and who is responsible for the process. 

This allows a transformation to be discussed based on the real organization. This is significantly more helpful than the version of the company that was projected onto the wall at the last board retreat. 

How BLIKS IO impacts this 

BLIKS IO builds such an organizational twin from the bottom up. The platform starts with the people who actually know the processes. Employees describe their process steps, the systems and documents used, the resources required, and the handover to the next participant. AI helps to structure this information. The expert employees review and confirm the result. 

This approach is important because the operational reality is rarely fully contained in process manuals or system logs. Frequently, it sits with the colleague who knows why the official route doesn't work on Wednesdays. Or with the employee who has been maintaining an Excel list for years, without which a supposedly automated process would grind to a halt. 

Step by step, the recorded information is linked together. BLIKS IO thereby shows the process in connection with its organization. An output without a recipient stands out. Duplications can be recognized. Critical knowledge held by individual persons becomes visible. It also shows which software is actually used in which processes and where automation or AI offers reliable leverage. 

BLIKS IO therefore does not replace process management. The platform expands its view. Individual processes remain modelable and optimizable. Added to this is the level on which it is possible to assess what contribution a process makes to value creation and what consequences its change triggers in the rest of the company. 

Companies need both: good processes and a clear picture of how these processes work together. Only then does efficiency turn into productivity. The most efficient detour remains, after all, a detour.