Who doesn’t know this pattern?<\/p>\n\n
One important decision meeting follows the next. The same question is discussed again and again – only with slightly different participants, new slides and a fresh data point here and there. <\/p>\n\n
It is agreed that no agreement can be reached yet.<\/p>\n\n
So the circle is extended. Then it is reduced again. New perspectives are invited, old ones discarded. In the meantime, the mood shifts: sometimes option A seems sensible, then option B again. <\/p>\n\n
The management looks at the discussion and sees one thing above all: uncertainty.<\/p>\n\n
The consequences are not clear. The arguments contradict each other. Every decision seems risky. <\/p>\n\n
In the end, what happens in many organizations happens at some point:<\/p>\n\n
A word of power.<\/p>\n\n
The decision is formally made – but not in practice.
What goes wrong here is rarely a lack of data or expertise.<\/p>\n\n
The problem is more subtle:
For some, the issue is a technical risk.
And because these models are never made explicit, they appear to be discussing the same issue – but are actually discussing completely different realities.<\/p>\n\n
This is exactly where the endless loop arises.<\/p>\n\n
The discussion does not move forward because it has no common subject matter. It revolves around opinions, assumptions and gut feelings without these being able to be clearly located, verified or weighted. <\/p>\n\n
Before you can have a meaningful discussion, you need a common thinking space.<\/p>\n\n
Bowtie analysis is an amazingly effective tool for this.<\/p>\n\n
Originating from risk management, Bowtie forces a group to visualize a risk in a structured way.<\/p>\n\n
In the middle is the central risk, for example:<\/p>\n\n
“We are making the wrong release decision.”<\/strong><\/p>\n\n To the left are possible causes:<\/p>\n\n To the right are possible consequences:<\/p>\n\n In between are barriers – in other words, everything that prevents or mitigates the risk:<\/p>\n\n The effect is immediate:<\/p>\n\n Suddenly everyone is talking about the same picture.<\/p>\n\n No longer via diffuse opinions, but via an explicit system of causes, risks, consequences and countermeasures.<\/p>\n\n This is the first big step out of the endless loop.<\/p>\n\n However, a model alone does not solve a problem. A clean form of discussion is needed to turn visibility into a viable decision.<\/p>\n\n This is where J\u00fcrgen Habermas becomes interesting.<\/p>\n\n Habermas’ theory of communicative action describes communication not simply as an exchange of opinions, but as a process in which statements have to be justified, tested and understood.<\/p>\n\n Applied to decision-making meetings, this means<\/p>\n\n A statement must not simply remain in space. It must be connectable. <\/p>\n\n When someone says:<\/p>\n\n “That’s a big risk.”<\/strong><\/p>\n\n Then that’s no longer enough.<\/p>\n\n The appropriate question is:<\/p>\n\n “Where exactly in the model do you locate this risk?”<\/strong><\/p>\n\n Is it a cause? And even more important:<\/p>\n\n Why?<\/strong><\/p>\n\n This fundamentally changes the quality of the discussion.<\/p>\n\n Before that, a typical contribution might sound like this:<\/p>\n\n “I don’t think we should release.”<\/em><\/p>\n<\/blockquote>\n\n This is understandable, but difficult to work with.<\/p>\n\n After Bowtie and deliberative structure, the same contribution sounds different:<\/p>\n\n “I see a cause in the Bowtie here: the load tests are incomplete. My assumption is that the system becomes unstable under peak load. The consequence would be a loss of production. In my opinion, the current barrier is not sufficient because it has only been tested functionally, but not under real load.”<\/em><\/p>\n<\/blockquote>\n\n Now you can work concretely.<\/p>\n\n Is the assumption correct? The discussion becomes connectable.<\/p>\n\n Not because everyone is suddenly of the same opinion. The interaction is crucial:<\/p>\n\n Bowtie creates a common understanding of the problem.<\/strong> Without Bowtie, the discussion remains abstract. Something else is created together:<\/p>\n\n A space in which decisions can be made at all.<\/p>\n\n Not every uncertainty disappears. That is the difference between a discussion that goes round in circles and a discussion that converges to a decision.<\/p>\n\n In practice, this approach is surprisingly unspectacular – and that is precisely its strength.<\/p>\n\n First, the decision question is specified.<\/p>\n\n Not:<\/p>\n\n “What do we do now?”<\/strong><\/p>\n\n But clearly delineated:<\/p>\n\n “Can we release Release X under the current technical, functional and operational conditions?”<\/strong><\/p>\n\n The team then builds a bowtie model together.<\/p>\n\n What is the key risk? This step often only takes a few minutes, but is the most important part of the meeting.<\/p>\n\n This is followed by a discussion – but no longer free-floating.<\/p>\n\n It must be possible to assign each statement to a cause, a consequence, a barrier or an assumption.<\/p>\n\n The moderator takes on a new role.<\/p>\n\n He not only moderates parts of speech. He asks questions when statements remain unclear. The result is no longer a “perceived” decision, but a deducible one.<\/p>\n\n A decision based on a common understanding.<\/p>\n\n The bottleneck is rarely the method.<\/p>\n\n The bottleneck is often the organization itself.<\/p>\n\n Because this type of discussion has side effects:<\/p>\n\n Hierarchies lose influence in the short term. That is uncomfortable.<\/p>\n\n But it is precisely this discomfort that is necessary to get out of endless loops.<\/p>\n\n Up to this point, everything sounds methodical.<\/p>\n\n And this is precisely the error in thinking that we see in many organizations:<\/p>\n\n The problem is not just the discussion.<\/strong> In theory, deliberative communication needs good arguments.<\/p>\n\n In practice, good arguments need an observable reality.<\/p>\n\n And this is exactly where it often fails.<\/p>\n\n Data does not exist. The result:<\/p>\n\n Meetings become a substitute for the lack of observability.<\/p>\n\n You don’t discuss because there are so many options. When we get into projects, we rarely see “too few meetings”.<\/p>\n\n We see something else:<\/p>\n\n Systems without meaningful metrics. And that is precisely why endless loops are created.<\/p>\n\n Not because people make bad decisions. We don’t go into organizations and say:<\/p>\n\n “You simply have to moderate better.”<\/strong><\/p>\n\n That would be too short-sighted.<\/p>\n\n We start earlier.<\/p>\n\n We are building the foundation so that deliberative communication can function at all.<\/p>\n\n Because good decisions are not only made through better meetings. A common reflex is:<\/p>\n\n “Then we’ll just build a big data platform.”<\/strong><\/p>\n\n A data warehouse. That sounds professional, but it often is:<\/p>\n\n too slow, Our approach is more pragmatic:<\/p>\n\n Which one metric really decides this specific question?<\/strong> Small technical interventions are often enough:<\/p>\n\n an additional counter, No months-long platform projects. But targeted visibility exactly where decisions are made.<\/p>\n\n A Bowtie Analysis is only valuable if it doesn’t end in a PowerPoint.<\/p>\n\n We help to anchor the elements technically.<\/p>\n\n Causes become visible as measurable events or states. For example:<\/p>\n\n Feature toggles. This becomes:<\/p>\n\n “That could be a risk.”<\/strong><\/p>\n\n a verifiable system:<\/p>\n\n “If event X happens and barrier Y is missing, we see effect Z.”<\/strong><\/p>\n\n This is the moment when a discussion tips over.<\/p>\n\n From opinion to verifiable reality.<\/p>\n\n Most architectures do not answer any questions. That’s enough for operations, but not for good decisions.<\/p>\n\n We deliberately turn this around:<\/p>\n\n Good architecture must be capable of making decisions.<\/strong><\/p>\n\n This means:<\/p>\n\n Services provide targeted, decision-relevant information. The goal is not observability as a buzzword.<\/p>\n\n The goal is more concrete:<\/p>\n\n An architecture that can be argued.<\/strong><\/p>\n\n An architecture in which you not only see that something is happening, but also understand why it is happening, what it means and what decision can be derived from it.<\/p>\n\n Another problem:<\/p>\n\n Even if data exists, it often arrives too late.<\/p>\n\n Three weeks later in reporting. Then they are interesting, but no longer effective in making decisions.<\/p>\n\n That’s why we rely on short, direct feedback loops:<\/p>\n\n small releases instead of large big-bang deployments, The important thing is:<\/p>\n\n Do not scale to the maximum. Perhaps the greatest effect is not a technical one, but a cultural one.<\/p>\n\n When systems become more transparent, communication changes.<\/p>\n\n Opinions lose weight. This drastically reduces political discussions.<\/p>\n\n Not because politics is banned. If a system shows what is happening, there is less need for speculation.<\/p>\n\n If this approach is pursued consistently, the role of meetings will change.<\/p>\n\n Meetings are no longer held to generate clarity. The dynamic is changing:<\/p>\n\n Before:<\/strong> After:<\/strong> That is a fundamental difference.<\/p>\n\n Because an organization that can observe its reality has to guess less. The combination of Bowtie Analysis and J\u00fcrgen Habermas provides a strong methodological basis:<\/p>\n\n A common model. But without a technical basis, this remains theory.<\/p>\n\n Our experience at ONLU is clear:<\/p>\n\n The real problem is not that there is too little data. That’s why our focus is not on making meetings look better.<\/p>\n\n Our focus is:<\/p>\n\n Building systems so that meetings make sense again.<\/p>\n\n Or even more directly:<\/p>\n\n No deliberative communication without observable reality.<\/strong> How to break the deadlock in decision-making meetings – with J\u00fcrgen Habermas, Bowtie Analysis and decision-capable system architecture<\/p>\n","protected":false},"author":15,"featured_media":5591,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-7320","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-nicht-kategorisiert"],"yoast_head":"\n\n
\n
\n
Step 2: Structuring discussions – with Habermas<\/h2>\n\n
From gut feeling to verifiable argumentation<\/h2>\n\n
\n
\n
The decisive effect: convergence instead of circular motion<\/h2>\n\n
A practical process for real meetings<\/h2>\n\n
Why this still fails in many organizations<\/h2>\n\n
How we help at ONLU: Making deliberation possible in the first place<\/h1>\n\n
The real bottleneck: No reality capable of making decisions<\/h2>\n\n
Our approach at ONLU: Creating decisiveness – not optimizing meetings<\/h2>\n\n
1. minimally invasive measurability instead of big data dreams<\/h2>\n\n
2. operationalize Bowtie: Making risks measurable<\/h2>\n\n
3. build architecture in such a way that it answers questions<\/h2>\n\n
4. shorten feedback loops without infrastructure overkill<\/h2>\n\n
5. depoliticize communication through visibility<\/h2>\n\n
What this changes in concrete terms<\/h2>\n\n
Conclusion: Deliberation needs reality<\/h1>\n\n