{"id":4662,"date":"2025-12-29T02:41:27","date_gmt":"2025-12-29T02:41:27","guid":{"rendered":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/"},"modified":"2025-12-29T02:41:27","modified_gmt":"2025-12-29T02:41:27","slug":"mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model","status":"publish","type":"post","link":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","title":{"rendered":"Die Meisterung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell"},"content":{"rendered":"<p>In der komplexen Welt der Unternehmensstrategie ist es nur die H\u00e4lfte des Kampfes, einen brillanten Plan zu haben. Die eigentliche Herausforderung liegt oft in der Umsetzung und der Ausrichtung. Organisationen sind lebendige Systeme, bei denen eine Ver\u00e4nderung in einem Bereich Wellen in anderen ausl\u00f6st. Um diese Komplexit\u00e4t zu meistern, st\u00fctzen sich F\u00fchrungskr\u00e4fte auf robuste Rahmenwerke, um sicherzustellen, dass jeder Teil ihres Unternehmens in dieselbe Richtung geht. Unter den dauerhaftesten und effektivsten dieser Werkzeuge ist das McKinsey-7S-Modell.<\/p>\n<p><img alt=\"McKinsey 7S Model layout\" decoding=\"async\" src=\"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png\"\/><\/p>\n<p>Dieser Leitfaden erkundet die Tiefen des McKinsey-7S-Frameworks, eines zentralen Bestandteils des <a href=\"https:\/\/www.archimetric.com\/comprehensive-tutorial-visual-paradigm-model-canvas-tool\/\">Ultrabusiness-Canvas-Toolkasten<\/a>. Wir werden seine zentralen Konzepte analysieren, schrittweise Anleitungen zur Umsetzung bereitstellen und zeigen, wie k\u00fcnstliche Intelligenz (KI) die Art und Weise revolutionieren kann, wie Sie Ihre Organisation analysieren und ausrichten.<\/p>\n<h2>Wichtige Konzepte: Die Entschl\u00fcsselung des 7S-Frameworks<\/h2>\n<p>Das McKinsey-7S-Modell ist ein strategisches Werkzeug, das darauf abzielt, die Wirksamkeit einer Organisation zu bewerten. Im Gegensatz zu Rahmenwerken, die ausschlie\u00dflich externe Faktoren (wie PESTLE) oder Wettbewerbsposition (wie Porters F\u00fcnf Kr\u00e4fte) betrachten, konzentriert sich das 7S-Modell auf die interne Ausrichtung. Die Grundidee ist einfach: Damit eine Organisation erfolgreich ist, m\u00fcssen sieben spezifische Elemente ausgerichtet und wechselseitig st\u00fctzend sein.<\/p>\n<p>Diese sieben Elemente werden in \u201eHarte\u201c und \u201eWeiche\u201c Elemente eingeteilt. Das Verst\u00e4ndnis des Unterschieds ist entscheidend f\u00fcr eine wirksame Analyse.<\/p>\n<h3>Die harten Elemente<\/h3>\n<p>Sie sind greifbar, leichter zu identifizieren und direkt durch Managemententscheidungen beeinflussbar.<\/p>\n<ul>\n<li><strong>Strategie:<\/strong> Der Plan, der entwickelt wurde, um einen Wettbewerbsvorteil gegen\u00fcber der Konkurrenz aufzubauen und aufrechtzuerhalten. Er beschreibt den Weg, den die Organisation verfolgen m\u00f6chte, um ihre Ziele zu erreichen.<\/li>\n<li><strong>Struktur:<\/strong> Die Art und Weise, wie die Organisation strukturiert ist und wer wem berichtet. Dazu geh\u00f6ren das Organigramm und die Hierarchie der Autorit\u00e4t.<\/li>\n<li><strong>Systeme:<\/strong> Die t\u00e4glichen Aktivit\u00e4ten und Verfahren, an denen die Mitarbeiter teilnehmen, um ihre Aufgaben zu erf\u00fcllen. Dazu geh\u00f6ren alles von IT-Systemen \u00fcber Finanzprozesse bis hin zu HR-Abl\u00e4ufen.<\/li>\n<\/ul>\n<h3>Die weichen Elemente<\/h3>\n<p>Sie sind immateriell, schwerer zu beschreiben und werden durch die Kultur beeinflusst. Sie sind jedoch oft genauso wichtig wie die harten Elemente f\u00fcr den Erfolg.<\/p>\n<ul>\n<li><strong>Geteilte Werte:<\/strong> Der Kern des Modells. Es handelt sich um die grundlegenden Werte des Unternehmens, die sich in der Unternehmenskultur und der allgemeinen Arbeitsmoral widerspiegeln. Sie verbinden jedes andere Element.<\/li>\n<li><strong>Stil:<\/strong> Der gew\u00e4hlte F\u00fchrungsstil. Dazu geh\u00f6rt der kulturelle Stil der Organisation und das Verhalten der Schl\u00fcsselmanager bei der Erreichung der Unternehmensziele.<\/li>\n<li><strong>Mitarbeiter:<\/strong> Die Mitarbeiter und ihre allgemeinen F\u00e4higkeiten. Es geht nicht nur um die Kopfzahl, sondern um die Talent-Management-Praxis und die Art und Weise, wie das Arbeitskr\u00e4ftepotenzial gef\u00f6rdert wird.<\/li>\n<li><strong>F\u00e4higkeiten:<\/strong> Die tats\u00e4chlichen F\u00e4higkeiten und Kompetenzen der Mitarbeiter des Unternehmens. Es geht um die Frage: \u201eWas k\u00f6nnen wir am besten?\u201c<\/li>\n<\/ul>\n<h2>Anleitungen: Umsetzung der McKinsey-7S-Analyse<\/h2>\n<p>Die Anwendung des McKinsey-7S-Modells erfordert einen strukturierten Ansatz. Egal ob Sie ein Gr\u00fcndungsf\u00fchrer sind, der den Business-Canvas-Toolkasten nutzt, oder ein Unternehmensstratege \u2013 folgen Sie diesen Anleitungen, um eine gr\u00fcndliche Analyse sicherzustellen.<\/p>\n<h3>Schritt 1: Bewertung des aktuellen Zustands<\/h3>\n<p>Beginnen Sie damit, wie Ihre Organisation derzeit in allen sieben Dimensionen funktioniert, aufzuzeichnen. Seien Sie ehrlich und kritisch. Sind Ihre Systeme veraltet? Hemmt Ihre Struktur Ihre Strategie?<\/p>\n<ul>\n<li><strong><a href=\"https:\/\/circle.visual-paradigm.com\/docs\/impact-analysis\/analysis-diagram\/how-to-use-analysis-diagram-to-visualize-dependencies-between-elements\/\">\u00dcberpr\u00fcfung von Abh\u00e4ngigkeiten<\/a>:<\/strong>Suchen Sie nach L\u00fccken. Zum Beispiel, passt Ihre <em>Struktur<\/em> (hierarchisch) mit Ihrer <em>Strategie<\/em> (agile Innovation)?<\/li>\n<li><strong>Daten sammeln:<\/strong>Verwenden Sie Umfragen, Interviews und Beobachtungen, um die \u201eweichen\u201c Elemente wie Stil und geteilte Werte zu bewerten.<\/li>\n<\/ul>\n<h3>Schritt 2: Definieren des zuk\u00fcnftigen Zustands<\/h3>\n<p>Ermitteln Sie, wo sich die Organisation befinden muss. Wenn Sie ein neues Produkt lancieren oder in einen neuen Markt eintreten, wie m\u00fcssen die sieben Elemente sich \u00e4ndern, um dieses Ziel zu unterst\u00fctzen?<\/p>\n<h3><a href=\"https:\/\/www.visual-paradigm.com\/guide\/bpmn\/business-procses-modeling-and-gap-analysis\/\">Schritt 3: Analyse der L\u00fccken<\/a><\/h3>\n<p>Vergleichen Sie Ihren aktuellen Zustand mit Ihrem gew\u00fcnschten zuk\u00fcnftigen Zustand. Die Abweichungen zeigen die Bereiche auf, die einer Intervention bed\u00fcrfen.<\/p>\n<h3>Schritt 4: Entwicklung eines Aktionsplans<\/h3>\n<p>Erstellen Sie einen Fahrplan, um die L\u00fccken zu schlie\u00dfen. Denken Sie daran, dass die \u00c4nderung eines Elements <a href=\"https:\/\/www.visual-paradigm.com\/features\/impact-analysis-tools\/\">andere beeinflusst<\/a>. Wenn Sie neue <em>Systeme<\/em> (z.\u202fB. ein neues CRM), m\u00fcssen Sie m\u00f6glicherweise <em>F\u00e4higkeiten<\/em> (Ausbildung) und anpassen <em>Struktur<\/em> (IT-Support-Rollen).<\/p>\n<h2>VP AI: Wie Visual Paradigm AI die strategische Analyse verbessert<\/h2>\n<p>Traditionelle strategische Analyse kann zeitaufwendig und anf\u00e4llig f\u00fcr Verzerrungen sein.<a href=\"https:\/\/www.archimetric.com\/what-is-the-business-model-canvas-why-use-visual-paradigms-ai-bmc-tool\/\">Das von KI gest\u00fctzte Canvas-Tool von Visual Paradigm<\/a>wandelt das McKinsey 7S-Modell von einer statischen Darstellung in einen dynamischen, intelligenten Arbeitsbereich um.<\/p>\n<p><img alt=\"\" decoding=\"async\" src=\"data:image\/png;base64,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\"\/><\/p>\n<h3>Automatisierte Canvas-Erstellung<\/h3>\n<p>Von einer leeren Seite auszugehen, ist oft der schwierigste Teil der strategischen Planung. Mit Visual Paradigm AI k\u00f6nnen Sie einen kompletten 7S-Canvas aus einem einzigen Prompt generieren. Wenn Sie beispielsweise \u201eMcKinsey 7S-Analyse f\u00fcr moderne Live-Unterhaltung\u201c eingeben, erstellt die KI sofort alle sieben Elemente basierend auf Branchenstandards und spart so Stunden an Anfangsarbeit.<\/p>\n<h3>KI-unterst\u00fctzte Ideenfindung und Erkenntnisse<\/h3>\n<p>Blockaden der Kreativit\u00e4t k\u00f6nnen die Analyse verlangsamen. Wenn Sie unsicher sind, wie Sie \u201eGeteilte Werte\u201c definieren oder kritische \u201eF\u00e4higkeiten\u201c f\u00fcr eine Nischenbranche identifizieren sollen, k\u00f6nnen die KI-Funktionen unterst\u00fctzen. Durch die \u00dcberpr\u00fcfung des organisatorischen Kontexts und Branchenmuster liefert die KI handlungsorientierte Vorschl\u00e4ge \u00fcber alle sieben Dimensionen, wodurch sichergestellt wird, dass Ihr Modell umfassend ist.<\/p>\n<h3>Tiefe strategische Analyse und Empfehlungen<\/h3>\n<p><a href=\"https:\/\/www.visual-paradigm.com\/features\/visual-modeling-tool\/\">Visual Paradigms Werkzeuge<\/a> gehen \u00fcber einfache Abbildungen hinaus. Das System kann eine tiefe Analyse durchf\u00fchren, um m\u00f6gliche Missst\u00e4nde zu erkennen und Empfehlungen zu geben. Es k\u00f6nnte darauf hinweisen, dass Ihre derzeitige<em>Personal<\/em> Kapazit\u00e4t f\u00fcr Ihre aggressive<em>Strategie<\/em>, was es Ihnen erm\u00f6glicht, Risiken proaktiv anzugehen.<\/p>\n<h3>Professionelle Berichterstattung<\/h3>\n<p>Sobald die Analyse abgeschlossen ist, erleichtert das Werkzeug die Kommunikation. Sie k\u00f6nnen Ihre Leinwand und die von der KI generierten Erkenntnisse in professionelle Formate wie PDF oder Word exportieren. Dies ist entscheidend f\u00fcr die Ausrichtung der Stakeholder, um sicherzustellen, dass die gewonnenen Erkenntnisse klar an die F\u00fchrungsebene kommuniziert werden.<\/p>\n<h2>Tipps und Tricks f\u00fcr den Erfolg<\/h2>\n<p>Um das Maximum aus dem McKinsey-7S-Modell und dem<a href=\"https:\/\/online.visual-paradigm.com\/knowledge\/business-model-canvas\/business-model-canvas-guide-with-examples\/\">Business-Canvas-Toolkit<\/a>zu erhalten, sollten Sie diese praktischen Tipps ber\u00fccksichtigen:<\/p>\n<ul>\n<li><strong>Beginnen Sie mit geteilten Werten:<\/strong> Da sie im Zentrum des Modells stehen, beeinflussen geteilte Werte jedes andere Element. Wenn sie unklar sind, wird der Rest des Modells Schwierigkeiten haben, sich auszurichten.<\/li>\n<li><strong>Untersch\u00e4tzen Sie die \u201eweichen S\u201c nicht:<\/strong> Es ist leicht, sich auf Strategie und Struktur zu konzentrieren, da diese greifbar sind. Doch die meisten Ver\u00e4nderungsinitiativen scheitern aufgrund von Stil, Personal, F\u00e4higkeiten oder Werten.<\/li>\n<li><strong>Nutzen Sie mehrere Ansichten:<\/strong> Wenn Sie digitale Werkzeuge verwenden, wechseln Sie zwischen einer ganzheitlichen Leinwandansicht, um das Gesamtbild zu sehen, und einer fokussierten Ansicht, um ohne Ablenkung bestimmte Abschnitte (wie Systeme) detailliert zu untersuchen.<\/li>\n<li><strong>Iterieren Sie regelm\u00e4\u00dfig:<\/strong> Das 7S-Modell stellt einen Momentaufnahme dar. Wenn sich der Markt ver\u00e4ndert (externe Faktoren), muss Ihre interne Ausrichtung sich ebenfalls weiterentwickeln. Behandeln Sie dies als lebendiges Dokument, kein einmaliges Training.<\/li>\n<li><strong>Nutzen Sie das gesamte Werkzeugset:<\/strong> Das McKinsey-7S ist m\u00e4chtig, funktioniert aber am besten, wenn es mit anderen Werkzeugen kombiniert wird. Verwenden Sie eine<em>SWOT-Analyse-Leinwand<\/em> um die externe Umgebung zu verstehen, bevor Sie 7S nutzen, um Ihre internen Ressourcen auf diese Herausforderungen auszurichten.<\/li>\n<\/ul>\n<div>\n<div class=\"cl-preview-section\" style='color: rgba(0, 0, 0, 0.75); font-family: Lato, \"Helvetica Neue\", Helvetica, sans-serif; font-size: 18px; font-variant-ligatures: common-ligatures; background-color: rgb(243, 243, 243);'>\n<h2 id=\"resource\" style=\"margin-top: 0px; margin-bottom: 1.8em; line-height: 1.33;\">Ressource<\/h2>\n<\/div>\n<div class=\"cl-preview-section\" style='color: rgba(0, 0, 0, 0.75); font-family: Lato, \"Helvetica Neue\", Helvetica, sans-serif; font-size: 18px; font-variant-ligatures: common-ligatures; background-color: rgb(243, 243, 243);'>\n<ul style=\"margin-top: 1.2em; margin-bottom: 1.2em; margin-left: 0px;\">\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.archimetric.com\/what-is-the-business-model-canvas-why-use-visual-paradigms-ai-bmc-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Was ist die Business Model Canvas? Warum Visual Paradigmen und KI-Tools nutzen?<\/a>: Dieser umfassende Leitfaden erkl\u00e4rt die Business Model Canvas, ihre Kernkomponenten und wie visuelle Paradigmen und KI-gest\u00fctzte Werkzeuge die strategische Planung und Unternehmensinnovation verbessern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/business-model-canvas-builder\/editor\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">KI-gest\u00fctzter Business Model Canvas-Baukasten \u2013 Sofortige Strategiegestaltung<\/a>: Ein k\u00fcnstlich-intelligente Werkzeug, das die Erstellung von Gesch\u00e4ftsmodell-Rahmen automatisiert und intelligente Vorschl\u00e4ge sowie Echtzeit-Einblicke bietet, um das Gesch\u00e4ftsplanen zu beschleunigen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai-toolbox.visual-paradigm.com\/app\/canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Tool \u2013 Intelligente Gestaltung f\u00fcr Gesch\u00e4ftsrahmen<\/a>: Eine k\u00fcnstlich-intelligente Canvas-Anwendung, die Nutzern hilft, Gesch\u00e4ftsmodelle, Wertversprechen und Strategierahmen mit intelligenten Vorschl\u00e4gen und Automatisierung zu erstellen und zu verfeinern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.visual-paradigm.com\/solution\/ai-business-model-canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Gesch\u00e4ftsmodell-Canvas-Tool \u2013 Intelligente Strategieentwicklung<\/a>: Eine umfassende, k\u00fcnstlich-intelligente erweiterte L\u00f6sung zum Aufbau und zur Verfeinerung von Gesch\u00e4ftsmodellen mit intelligenten Erkenntnissen, Echtzeit-Feedback und kooperativen Funktionen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/updates.visual-paradigm.com\/releases\/ai-canvas-editor\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Editor-Release-Update<\/a>: Einf\u00fchrung eines k\u00fcnstlich-intelligenten Canvas-Editors, der die Diagrammerstellung durch intelligente Vorschl\u00e4ge und automatisierte Layout-Optimierung verbessert.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/guides.visual-paradigm.com\/ai-powered-business-model-canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Leitfaden zum k\u00fcnstlich-intelligenten Gesch\u00e4ftsmodell-Canvas-Tool<\/a>: Ein Schritt-f\u00fcr-Schritt-Leitfaden zur Verwendung eines k\u00fcnstlich-intelligenten Tools zur Erstellung und Verfeinerung von Gesch\u00e4ftsmodell-Canvas mit intelligentem Eingabeverfahren und Echtzeit-Empfehlungen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/mission-model-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Mission-Modell-Canvas | K\u00fcnstlich-intelligentes Strategietool von VP<\/a>: 28. Oktober 2025 \u2013 Koordinieren Sie Live-Sitzungen mit Ihrem Team mithilfe des integrierten Timers und exportieren Sie Ihren endg\u00fcltigen Canvas oder Berichte in professionelle Formate wie Word, Markdown oder CSV. \u2026 Der Mission-Modell-Canvas ist speziell f\u00fcr Nicht-Profits, Beh\u00f6rden, soziale Unternehmen und alle Organisationen konzipiert, deren prim\u00e4res Ziel die Erreichung der Mission ist, anstatt Gewinn zu erzielen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.cybermedian.com\/comprehensive-tutorial-ai-powered-business-canvas-toolkit-with-visual-paradigm\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Umfassender Leitfaden: K\u00fcnstlich-intelligentes Business-Canvas-Toolkit mit Visual Paradigm<\/a>: Diese Seite bietet einen detaillierten Leitfaden zur Verwendung eines k\u00fcnstlich-intelligenten Business-Model-Canvas-Tools, das mit Visual Paradigm integriert ist, um die automatisierte Entwicklung von Gesch\u00e4ftsstrategien zu erm\u00f6glichen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/tool\/canvas-tool\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">AI-Canvas-Tool \u2013 Visual Paradigm<\/a>: Ein k\u00fcnstlich-intelligentes Werkzeug innerhalb von Visual Paradigm, das Nutzern erm\u00f6glicht, Gesch\u00e4fts-Canvas durch intelligente Automatisierung und Eingabe in nat\u00fcrlicher Sprache zu erstellen und zu verfeinern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/www.diagrams-ai.com\/blog\/mastering-the-business-model-canvas-with-ai-a-step-by-step-guide-using-visual-paradigm\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Beherrschen des Gesch\u00e4ftsmodell-Canvas mit KI: Schritt-f\u00fcr-Schritt-Anleitung mit Visual Paradigm<\/a>: Dieser Blogbeitrag bietet eine strukturierte Anleitung zur Nutzung der KI-Funktionen in Visual Paradigm, um Business-Model-Canvases effizient zu erstellen, anzupassen und zu optimieren.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/ai.visual-paradigm.com\/tool\/business-model-canvas-builder\/how-it-works\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">So funktioniert der KI-gest\u00fctzte Gesch\u00e4ftsmodell-Canvas-Baukasten \u2013 Visual Paradigm<\/a>: Diese Seite erl\u00e4utert die Funktionalit\u00e4t des k\u00fcnstlich-intelligenten Business-Model-Canvas-Baukastens und zeigt auf, wie maschinelles Lernen die Erstellung von Canvas und die Generierung strategischer Erkenntnisse automatisiert.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/online.visual-paradigm.com\/diagrams\/templates\/analysis-canvas\/strategy-tools\/deep-learning-ai-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Deep-Learning-KI-Canvas | Vorlage f\u00fcr Analyse-Canvas mit Strategietools<\/a>: Bearbeiten Sie die lokalisierte Version: Tiefes Lernen AI-Canvas (TW) | Tiefes Lernen AI-Canvas (CN) Diese Seite anzeigen in: EN TW CN \u00b7 Visual Paradigm Online (VP Online) ist eine Online-Diagramm-Software, die Analyse-Canvas, verschiedene Diagramme, UML, Flussdiagramme, Rack-Diagramme, Organigramme, Stammb\u00e4ume, ERD, Grundrisse usw. unterst\u00fctzt.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/product-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Produkt-Canvas | K\u00fcnstlich-intelligentes Strategietool von VP<\/a>: Erstellen Sie Produkte, die Menschen lieben. Kombinieren Sie Strategie, Design und Feedback in einem visuellen Raum mit unserem k\u00fcnstlich-intelligenten Produkt-Canvas, um Ideen schneller auf den Markt zu bringen.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/lean-ux-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Lean-UX-Canvas | K\u00fcnstlich-intelligentes Strategietool von VP<\/a>: 28. Oktober 2025 \u2013 Erstellen Sie innerhalb von Momenten einen vollst\u00e4ndigen Strategierahmen. Beschreiben Sie einfach Ihre Vision, und der KI-Canvas-Generator verwandelt sie in einen strukturierten, erkenntnisreichen Canvas, der Ihnen hilft, Ihre n\u00e4chste gro\u00dfe Idee zu visualisieren, zu planen und zu verfeinern.<\/p>\n<\/li>\n<li>\n<p style=\"margin-top: 1.2em; margin-bottom: 1.2em;\"><a href=\"https:\/\/canvas.visual-paradigm.com\/lean-canvas\/\" style=\"background-color: transparent; color: rgb(12, 147, 228);\">Lean-Canvas \u2013 Visual Paradigm<\/a>: 28. Oktober 2025 \u2013 Unsere Anwendung ist als Ihr strategischer Partner konzipiert und bietet intelligente Werkzeuge, um jeden Schritt Ihres Planungsprozesses f\u00fcr den Gesch\u00e4ftsmodell-Canvas zu verbessern. \u2026 Haben Sie eine Startup-Idee? Geben Sie einfach \u201eeine Mobile-App f\u00fcr die Lieferung von hausgemachten Mahlzeiten vor Ort\u201c ein und lassen Sie unsere KI einen vollst\u00e4ndigen Lean-Canvas erstellen, der das Problem, die L\u00f6sung und die wichtigsten Kennzahlen darstellt.<\/p>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>In der komplexen Welt der Unternehmensstrategie ist es nur die H\u00e4lfte des Kampfes, einen brillanten Plan zu haben. Die eigentliche Herausforderung liegt oft in der Umsetzung und der Ausrichtung. Organisationen sind lebendige Systeme, bei denen eine Ver\u00e4nderung in einem Bereich Wellen in anderen ausl\u00f6st. Um diese Komplexit\u00e4t zu meistern, st\u00fctzen sich F\u00fchrungskr\u00e4fte auf robuste Rahmenwerke, um sicherzustellen, dass jeder Teil ihres Unternehmens in dieselbe Richtung geht. Unter den dauerhaftesten und effektivsten dieser Werkzeuge ist das McKinsey-7S-Modell. Dieser Leitfaden erkundet die Tiefen des McKinsey-7S-Frameworks, eines zentralen Bestandteils des Ultrabusiness-Canvas-Toolkasten. Wir werden seine zentralen Konzepte analysieren, schrittweise Anleitungen zur Umsetzung bereitstellen und zeigen, wie k\u00fcnstliche Intelligenz (KI) die Art und Weise revolutionieren kann, wie Sie Ihre Organisation analysieren und ausrichten. Wichtige Konzepte: Die Entschl\u00fcsselung des 7S-Frameworks Das McKinsey-7S-Modell ist ein strategisches Werkzeug, das darauf abzielt, die Wirksamkeit einer Organisation zu bewerten. Im Gegensatz zu Rahmenwerken, die ausschlie\u00dflich externe Faktoren (wie PESTLE) oder Wettbewerbsposition (wie Porters F\u00fcnf Kr\u00e4fte) betrachten, konzentriert sich das 7S-Modell auf die interne Ausrichtung. Die Grundidee ist einfach: Damit eine Organisation erfolgreich ist, m\u00fcssen sieben spezifische Elemente ausgerichtet und wechselseitig st\u00fctzend sein. Diese sieben Elemente werden in \u201eHarte\u201c und \u201eWeiche\u201c Elemente eingeteilt. Das Verst\u00e4ndnis des Unterschieds ist entscheidend f\u00fcr eine wirksame Analyse. Die harten Elemente Sie sind greifbar, leichter zu identifizieren und direkt durch Managemententscheidungen beeinflussbar. Strategie: Der Plan, der entwickelt wurde, um einen Wettbewerbsvorteil gegen\u00fcber der Konkurrenz aufzubauen und aufrechtzuerhalten. Er beschreibt den Weg, den die Organisation verfolgen m\u00f6chte, um ihre Ziele zu erreichen. Struktur: Die Art und Weise, wie die Organisation strukturiert ist und wer wem berichtet. Dazu geh\u00f6ren das Organigramm und die Hierarchie der Autorit\u00e4t. Systeme: Die t\u00e4glichen Aktivit\u00e4ten und Verfahren, an denen die Mitarbeiter teilnehmen, um ihre Aufgaben zu erf\u00fcllen. Dazu geh\u00f6ren alles von IT-Systemen \u00fcber Finanzprozesse bis hin zu HR-Abl\u00e4ufen. Die weichen Elemente Sie sind immateriell, schwerer zu beschreiben und werden durch die Kultur beeinflusst. Sie sind jedoch oft genauso wichtig wie die harten Elemente f\u00fcr den Erfolg. Geteilte Werte: Der Kern des Modells. Es handelt sich um die grundlegenden Werte des Unternehmens, die sich in der Unternehmenskultur und der allgemeinen Arbeitsmoral widerspiegeln. Sie verbinden jedes andere Element. Stil: Der gew\u00e4hlte F\u00fchrungsstil. Dazu geh\u00f6rt der kulturelle Stil der Organisation und das Verhalten der Schl\u00fcsselmanager bei der Erreichung der Unternehmensziele. Mitarbeiter: Die Mitarbeiter und ihre allgemeinen F\u00e4higkeiten. Es geht nicht nur um die Kopfzahl, sondern um die Talent-Management-Praxis und die Art und Weise, wie das Arbeitskr\u00e4ftepotenzial gef\u00f6rdert wird. F\u00e4higkeiten: Die tats\u00e4chlichen F\u00e4higkeiten und Kompetenzen der Mitarbeiter des Unternehmens. Es geht um die Frage: \u201eWas k\u00f6nnen wir am besten?\u201c Anleitungen: Umsetzung der McKinsey-7S-Analyse Die Anwendung des McKinsey-7S-Modells erfordert einen strukturierten Ansatz. Egal ob Sie ein Gr\u00fcndungsf\u00fchrer sind, der den Business-Canvas-Toolkasten nutzt, oder ein Unternehmensstratege \u2013 folgen Sie diesen Anleitungen, um eine gr\u00fcndliche Analyse sicherzustellen. Schritt 1: Bewertung des aktuellen Zustands Beginnen Sie damit, wie Ihre Organisation derzeit in allen sieben Dimensionen funktioniert, aufzuzeichnen. Seien Sie ehrlich und kritisch. Sind Ihre Systeme veraltet? Hemmt Ihre Struktur Ihre Strategie? \u00dcberpr\u00fcfung von Abh\u00e4ngigkeiten:Suchen Sie nach L\u00fccken. Zum Beispiel, passt Ihre Struktur (hierarchisch) mit Ihrer Strategie (agile Innovation)? Daten sammeln:Verwenden Sie Umfragen, Interviews und Beobachtungen, um die \u201eweichen\u201c Elemente wie Stil und geteilte Werte zu bewerten. Schritt 2: Definieren des zuk\u00fcnftigen Zustands Ermitteln Sie, wo sich die Organisation befinden muss. Wenn Sie ein neues Produkt lancieren oder in einen neuen Markt eintreten, wie m\u00fcssen die sieben Elemente sich \u00e4ndern, um dieses Ziel zu unterst\u00fctzen? Schritt 3: Analyse der L\u00fccken Vergleichen Sie Ihren aktuellen Zustand mit Ihrem gew\u00fcnschten zuk\u00fcnftigen Zustand. Die Abweichungen zeigen die Bereiche auf, die einer Intervention bed\u00fcrfen. Schritt 4: Entwicklung eines Aktionsplans Erstellen Sie einen Fahrplan, um die L\u00fccken zu schlie\u00dfen. Denken Sie daran, dass die \u00c4nderung eines Elements andere beeinflusst. Wenn Sie neue Systeme (z.\u202fB. ein neues CRM), m\u00fcssen Sie m\u00f6glicherweise F\u00e4higkeiten (Ausbildung) und anpassen Struktur (IT-Support-Rollen). VP AI: Wie Visual Paradigm AI die strategische Analyse verbessert Traditionelle strategische Analyse kann zeitaufwendig und anf\u00e4llig f\u00fcr Verzerrungen sein.Das von KI gest\u00fctzte Canvas-Tool von Visual Paradigmwandelt das McKinsey 7S-Modell von einer statischen Darstellung in einen dynamischen, intelligenten Arbeitsbereich um. Automatisierte Canvas-Erstellung Von einer leeren Seite auszugehen, ist oft der schwierigste Teil der strategischen Planung. Mit Visual Paradigm AI k\u00f6nnen Sie einen kompletten 7S-Canvas aus einem einzigen Prompt generieren. Wenn Sie beispielsweise \u201eMcKinsey 7S-Analyse f\u00fcr moderne Live-Unterhaltung\u201c eingeben, erstellt die KI sofort alle sieben Elemente basierend auf Branchenstandards und spart so Stunden an Anfangsarbeit. KI-unterst\u00fctzte Ideenfindung und Erkenntnisse Blockaden der Kreativit\u00e4t k\u00f6nnen die Analyse verlangsamen. Wenn Sie unsicher sind, wie Sie \u201eGeteilte Werte\u201c definieren oder kritische \u201eF\u00e4higkeiten\u201c f\u00fcr eine Nischenbranche identifizieren sollen, k\u00f6nnen die KI-Funktionen unterst\u00fctzen. Durch die \u00dcberpr\u00fcfung des organisatorischen Kontexts und Branchenmuster liefert die KI handlungsorientierte Vorschl\u00e4ge \u00fcber alle sieben Dimensionen, wodurch sichergestellt wird, dass Ihr Modell umfassend ist. Tiefe strategische Analyse und Empfehlungen Visual Paradigms Werkzeuge gehen \u00fcber einfache Abbildungen hinaus. Das System kann eine tiefe Analyse durchf\u00fchren, um m\u00f6gliche Missst\u00e4nde zu erkennen und Empfehlungen zu geben. Es k\u00f6nnte darauf hinweisen, dass Ihre derzeitigePersonal Kapazit\u00e4t f\u00fcr Ihre aggressiveStrategie, was es Ihnen erm\u00f6glicht, Risiken proaktiv anzugehen. Professionelle Berichterstattung Sobald die Analyse abgeschlossen ist, erleichtert das Werkzeug die Kommunikation. Sie k\u00f6nnen Ihre Leinwand und die von der KI generierten Erkenntnisse in professionelle Formate wie PDF oder Word exportieren. Dies ist entscheidend f\u00fcr die Ausrichtung der Stakeholder, um sicherzustellen, dass die gewonnenen Erkenntnisse klar an die F\u00fchrungsebene kommuniziert werden. Tipps und Tricks f\u00fcr den Erfolg Um das Maximum aus dem McKinsey-7S-Modell und demBusiness-Canvas-Toolkitzu erhalten, sollten Sie diese praktischen Tipps ber\u00fccksichtigen: Beginnen Sie mit geteilten Werten: Da sie im Zentrum des Modells stehen, beeinflussen geteilte Werte jedes andere Element. Wenn sie unklar sind, wird der Rest des Modells Schwierigkeiten haben, sich auszurichten. Untersch\u00e4tzen Sie die \u201eweichen S\u201c nicht: Es ist leicht, sich auf Strategie und Struktur zu konzentrieren, da diese greifbar sind. Doch die meisten Ver\u00e4nderungsinitiativen scheitern aufgrund von Stil, Personal, F\u00e4higkeiten oder Werten. Nutzen Sie mehrere Ansichten: Wenn Sie digitale Werkzeuge verwenden, wechseln Sie zwischen einer ganzheitlichen Leinwandansicht, um das Gesamtbild zu sehen, und einer fokussierten Ansicht, um ohne Ablenkung bestimmte Abschnitte (wie Systeme) detailliert zu untersuchen. Iterieren Sie regelm\u00e4\u00dfig:<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4662","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm<\/title>\n<meta name=\"description\" content=\"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm\" \/>\n<meta property=\"og:description\" content=\"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/\" \/>\n<meta property=\"og:site_name\" content=\"Diagrams AI German\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-29T02:41:27+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png\" \/>\n<meta name=\"author\" content=\"vpadmin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Verfasst von\" \/>\n\t<meta name=\"twitter:data1\" content=\"vpadmin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Gesch\u00e4tzte Lesezeit\" \/>\n\t<meta name=\"twitter:data2\" content=\"9\u00a0Minuten\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/\"},\"author\":{\"name\":\"vpadmin\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/#\\\/schema\\\/person\\\/ecc36153eaeb4aeaf895589c93d5de12\"},\"headline\":\"Die Meisterung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell\",\"datePublished\":\"2025-12-29T02:41:27+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/\"},\"wordCount\":1741,\"image\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/canvas.visual-paradigm.com\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/McKinsey-7S-Model-layout-1024x574.png\",\"articleSection\":[\"Uncategorized\"],\"inLanguage\":\"de\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/\",\"url\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/\",\"name\":\"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/canvas.visual-paradigm.com\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/McKinsey-7S-Model-layout-1024x574.png\",\"datePublished\":\"2025-12-29T02:41:27+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/#\\\/schema\\\/person\\\/ecc36153eaeb4aeaf895589c93d5de12\"},\"description\":\"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#breadcrumb\"},\"inLanguage\":\"de\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#primaryimage\",\"url\":\"https:\\\/\\\/canvas.visual-paradigm.com\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/McKinsey-7S-Model-layout-1024x574.png\",\"contentUrl\":\"https:\\\/\\\/canvas.visual-paradigm.com\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/McKinsey-7S-Model-layout-1024x574.png\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Die Meisterung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/#website\",\"url\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/\",\"name\":\"Diagrams AI German\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"de\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/#\\\/schema\\\/person\\\/ecc36153eaeb4aeaf895589c93d5de12\",\"name\":\"vpadmin\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g\",\"caption\":\"vpadmin\"},\"sameAs\":[\"https:\\\/\\\/www.diagrams-ai.com\"],\"url\":\"https:\\\/\\\/www.diagrams-ai.com\\\/de\\\/author\\\/vpadmin\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm","description":"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","og_locale":"de_DE","og_type":"article","og_title":"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm","og_description":"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.","og_url":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","og_site_name":"Diagrams AI German","article_published_time":"2025-12-29T02:41:27+00:00","og_image":[{"url":"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png","type":"","width":"","height":""}],"author":"vpadmin","twitter_card":"summary_large_image","twitter_misc":{"Verfasst von":"vpadmin","Gesch\u00e4tzte Lesezeit":"9\u00a0Minuten"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#article","isPartOf":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/"},"author":{"name":"vpadmin","@id":"https:\/\/www.diagrams-ai.com\/de\/#\/schema\/person\/ecc36153eaeb4aeaf895589c93d5de12"},"headline":"Die Meisterung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell","datePublished":"2025-12-29T02:41:27+00:00","mainEntityOfPage":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/"},"wordCount":1741,"image":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#primaryimage"},"thumbnailUrl":"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png","articleSection":["Uncategorized"],"inLanguage":"de"},{"@type":"WebPage","@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","url":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/","name":"Der ultimative Leitfaden zur McKinsey-7S-Modell-Analyse | Visual Paradigm","isPartOf":{"@id":"https:\/\/www.diagrams-ai.com\/de\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#primaryimage"},"image":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#primaryimage"},"thumbnailUrl":"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png","datePublished":"2025-12-29T02:41:27+00:00","author":{"@id":"https:\/\/www.diagrams-ai.com\/de\/#\/schema\/person\/ecc36153eaeb4aeaf895589c93d5de12"},"description":"Beherrschen Sie die organisatorische Ausrichtung mit dem McKinsey-7S-Modell. Lernen Sie die zentralen Konzepte, schrittweisen Anleitungen und die Nutzung von Visual Paradigm AI f\u00fcr strategische Analysen.","breadcrumb":{"@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#breadcrumb"},"inLanguage":"de","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/"]}]},{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#primaryimage","url":"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png","contentUrl":"https:\/\/canvas.visual-paradigm.com\/wp-content\/uploads\/2025\/12\/McKinsey-7S-Model-layout-1024x574.png"},{"@type":"BreadcrumbList","@id":"https:\/\/www.diagrams-ai.com\/de\/mastering-organizational-alignment-a-comprehensive-guide-to-the-mckinsey-7s-model\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.diagrams-ai.com\/de\/"},{"@type":"ListItem","position":2,"name":"Die Meisterung der organisatorischen Ausrichtung: Ein umfassender Leitfaden zum McKinsey-7S-Modell"}]},{"@type":"WebSite","@id":"https:\/\/www.diagrams-ai.com\/de\/#website","url":"https:\/\/www.diagrams-ai.com\/de\/","name":"Diagrams AI German","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.diagrams-ai.com\/de\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"de"},{"@type":"Person","@id":"https:\/\/www.diagrams-ai.com\/de\/#\/schema\/person\/ecc36153eaeb4aeaf895589c93d5de12","name":"vpadmin","image":{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/secure.gravatar.com\/avatar\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/56e0eb902506d9cea7c7e209205383146b8e81c0ef2eff693d9d5e0276b3d7e3?s=96&d=mm&r=g","caption":"vpadmin"},"sameAs":["https:\/\/www.diagrams-ai.com"],"url":"https:\/\/www.diagrams-ai.com\/de\/author\/vpadmin\/"}]}},"_links":{"self":[{"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/posts\/4662","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/comments?post=4662"}],"version-history":[{"count":0,"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/posts\/4662\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/media?parent=4662"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/categories?post=4662"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.diagrams-ai.com\/de\/wp-json\/wp\/v2\/tags?post=4662"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}