Siemens – Siemens enters next stage of growth with its ONE Tech Company program

EMR Analysis

More information on Siemens AG: See full profile on EMR Executive Services

More information on Dr. Roland Busch (President and Chief Executive Officer, Siemens AG): See full profile on EMR Executive Services

More information on Prof. Dr. Ralf P. Thomas (Member of the Managing Board and Chief Financial Officer, Siemens AG till 2026 + Chairman of the Supervisory Board, Siemens Healthineers AG, Siemens AG): See full profile on EMR Executive Services

More information on Veronika Bienert (Member of the Managing Board and Chief Executive Officer, Siemens Financial Services (SFS) with responsibility for the service portfolio of Siemens Real Estate and Global Business Services, Siemens AG till January 1, 2026 + Member of the Managing Board and Chief Financial Officer, Siemens AG in the course of fiscal 2026): See full profile on EMR Executive Services

More information on “ONE Tech Company” Program by Siemens AG: See full profile on EMR Executive Services

 

More information on Siemens Healthineers AG by Siemens AG: https://www.siemens-healthineers.com/ + Siemens Healthineers pioneers breakthroughs in healthcare. For everyone. Everywhere. Sustainably. The company is a global provider of healthcare equipment, solutions and services, with activities in more than 180 countries and direct representation in more than 70. The group comprises Siemens Healthineers AG, listed as SHL in Frankfurt, Germany, and its subsidiaries. As a leading medical technology company, Siemens Healthineers is committed to improving access to healthcare for underserved communities worldwide and is striving to overcome the most threatening diseases. The company is principally active in the areas of imaging, diagnostics, cancer care and minimally invasive therapies, augmented by digital technology and artificial intelligence. In fiscal 2024, which ended on September 30, 2024, Siemens Healthineers had approximately 72,000 employees worldwide and generated revenue of around €22.4 billion.

Siemens AG owns currently circa 67 percent stake in Siemens Healthineers.

More information on Dr. Bernd Montag (Chief Executive Officer, Siemens Healthineers AG, Siemens AG): See the full profile on EMR Executive Services

 

More information on Altair Engineering Inc. by Siemens AG: https://altair.com/ + When data science meets rocket science, incredible things happen. The innovation our world-changing technology enables may feel like magic to users, but it’s the time-tested result of the rigorous application of science, math, and Altair.

Our comprehensive, open-architecture simulation, artificial intelligence (AI), high-performance computing (HPC), and data analytics solutions empower organizations to build better, more efficient, more sustainable products and processes that will usher in the breakthroughs of tomorrow’s world. Welcome to the cutting edge of computational intelligence – no magic necessary.

More information on James R. Scapa (Founder, Chairman and Chief Executive Officer, Altair, Siemens AG): See full profile on EMR Executive Services

 

More information on Dotmatics by Siemens AG: https://www.dotmatics.com/ + Harmonizing Science & Data to Create a Better Future, Together.

From developing new personalized and preventive patient treatment solutions to revising climate change – Dotmatics solutions are at the core of scientific innovation.

Dotmatics is a leader in R&D scientific software connecting science, data, and decision-making. Its enterprise R&D platform and applications, including GraphPad Prism, SnapGene and Geneious, drive efficiency and accelerate innovation. More than 2 million scientists and 14,000 customers trust Dotmatics to help them create a healthier, cleaner, safer world. Dotmatics is a global team of more than 800 people dedicated to supporting its customers in over 180 countries. The company is headquartered in Boston, with 14 offices and R&D teams located around the world.

More information on Thomas Swalla (Chief Executive Officer, Dotmatics, Siemens AG): See full profile on EMR Executive Services

 

 

 

More information on Innomotics (previously Siemens Large Drives Applications) by KPS Capital Partners: https://www.innomotics.com/hub/en/ + Innomotics GmbH is a globally leading provider of electric motors and large drive systems that combines deep technical expertise and leading innovation in electrical solutions across industries and regions. With its more than 150 years of experience in developing electric motors, the company is the backbone for reliable drive technology in industry and infrastructure worldwide. Innomotics is a thought leader in the areas of industrial efficiency, electrification, sustainability, and digitalization. The company is headquartered in Nuremberg (Germany) and employs around 15,000 people worldwide. Annual revenue exceeds 3 billion euros. With 17 production sites and a comprehensive sales and service network in 49 countries, Innomotics has a wellbalanced global presence in a growing market.

More information on Michael Reichle (Chief Executive Officer, Innomotics, KPS Capital Partners): https://www.innomotics.com/hub/en/company/about-innomotics + https://www.linkedin.com/in/michael-reichle/ 

 

 

 

 

 

 

 

 

 

 

 

EMR Additional Notes:

• Earning Per Share (EPS):
  • Company’s net income subtracted by preferred dividends and then divided by the average number of common shares outstanding. The resulting number serves as an indicator of a company’s profitability. It is common for a company to report EPS that is adjusted for extraordinary items and potential share dilution.
  • The higher a company’s EPS, the more profitable it is considered to be.
  • Earnings per share value is calculated as net income (also known as profits or earnings) divided by available shares. A more refined calculation adjusts the numerator and denominator for shares that could be created through options, convertible debt, or warrants. The numerator of the equation is also more relevant if it is adjusted for continuing operations.
• Earning Per Share (EPS) per Purchase Price Allocation (PPA):
  • PPA (Purchase Price Allocation) happens after a company acquires another — it’s the accounting process of allocating the purchase price of the acquired business to its identifiable assets and liabilities (like revaluing assets, recognizing goodwill, etc.).
  • EPS pre PPA means the company’s earnings per share calculated before taking into account the accounting effects of purchase price allocation from acquisitions.
  • In other words, it’s a “clean” or adjusted EPS showing the company’s underlying profitability without acquisition-related accounting distortions (like amortization of intangible assets or revaluation effects).

 

 

• AI – Artificial Intelligence:
  • Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.
  • As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but several, including Python, R and Java, are popular.
  • In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. In this way, a chatbot that is fed examples of text chats can learn to produce lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples.
  • AI programming focuses on three cognitive skills: learning, reasoning and self-correction.
  • The 4 types of artificial intelligence?
    • Type 1: Reactive machines. These AI systems have no memory and are task specific. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future ones.
    • Type 2: Limited memory. These AI systems have memory, so they can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way.
    • Type 3: Theory of mind. Theory of mind is a psychology term. When applied to AI, it means that the system would have the social intelligence to understand emotions. This type of AI will be able to infer human intentions and predict behavior, a necessary skill for AI systems to become integral members of human teams.
    • Type 4: Self-awareness. In this category, AI systems have a sense of self, which gives them consciousness. Machines with self-awareness understand their own current state. This type of AI does not yet exist.
  • Machine Learning (ML):
    • Developed to mimic human intelligence, it lets the machines learn independently by ingesting vast amounts of data, statistics formulas and detecting patterns.
    • ML allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.
    • ML algorithms use historical data as input to predict new output values.
    • Recommendation engines are a common use case for ML. Other uses include fraud detection, spam filtering, business process automation (BPA) and predictive maintenance.
    • Classical ML is often categorized by how an algorithm learns to become more accurate in its predictions. There are four basic approaches: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.
  • Deep Learning (DL):
    • Subset of machine learning, Deep Learning enabled much smarter results than were originally possible with ML. Face recognition is a good example.
    • DL makes use of layers of information processing, each gradually learning more and more complex representations of data. The early layers may learn about colors, the next ones about shapes, the following about combinations of those shapes, and finally actual objects. DL demonstrated a breakthrough in object recognition.
    • DL is currently the most sophisticated AI architecture we have developed.
  • Generative AI (GenAI):
    • Generative AI technology generates outputs based on some kind of input – often a prompt supplied by a person. Some GenAI tools work in one medium, such as turning text inputs into text outputs, for example. With the public release of ChatGPT in late November 2022, the world at large was introduced to an AI app capable of creating text that sounded more authentic and less artificial than any previous generation of computer-crafted text.
  • Small Language Models (SLM) and Large Language Models (LLM):
    • Small Language Models (SLMs) are artificial intelligence (AI) models capable of processing, understanding and generating natural language content. As their name implies, SLMs are smaller in scale and scope than large language models (LLMs).
    • LLM means Large Language Models — a type of machine learning/deep learning model that can perform a variety of natural language processing (NLP) and analysis tasks, including translating, classifying, and generating text; answering questions in a conversational manner; and identifying data patterns.
    • For example, virtual assistants like Siri, Alexa, or Google Assistant use LLMs to process natural language queries and provide useful information or execute tasks such as setting reminders or controlling smart home devices.
  • Computer Vision (CV) / Vision AI & Machine Vision (MV):
    • Field of AI that enables computers to interpret and act on visual data (images, videos). It works by using deep learning models trained on large datasets to recognize patterns, objects, and context.
    • The most well-known case of this today is Google’s Translate, which can take an image of anything — from menus to signboards — and convert it into text that the program then translates into the user’s native language.
    • Machine Vision (MV) :
      • Specific application for industrial settings, relying on cameras to analyze tasks in manufacturing, quality control, and worker safety. The key difference is that CV is a broader field for extracting information from various visual inputs, while MV is more focused on specific industrial tasks.
      • Machine Vision is the ability of a computer to see; it employs one or more video cameras, analog-to-digital conversion and digital signal processing. The resulting data goes to a computer or robot controller. Machine Vision is similar in complexity to Voice Recognition.
      • MV uses the latest AI technologies to give industrial equipment the ability to see and analyze tasks in smart manufacturing, quality control, and worker safety.
  • Multimodal Intelligence and Agents:
    • Subset of artificial intelligence that integrates information from various modalities, such as text, images, audio, and video, to build more accurate and comprehensive AI models.
    • Multimodal capabilities allows AI to interact with users in a more natural and intuitive way. It can see, hear and speak, which means that users can provide input and receive responses in a variety of ways.
    • An AI agent is a computational entity designed to act independently. It performs specific tasks autonomously by making decisions based on its environment, inputs, and a predefined goal. What separates an AI agent from an AI model is the ability to act. There are many different kinds of agents such as reactive agents and proactive agents. Agents can also act in fixed and dynamic environments. Additionally, more sophisticated applications of agents involve utilizing agents to handle data in various formats, known as multimodal agents and deploying multiple agents to tackle complex problems.
  • Agentic AI:
    • Agentic AI is an artificial intelligence system that can accomplish a specific goal with limited supervision. It consists of AI agents—machine learning models that mimic human decision-making to solve problems in real time. In a multiagent system, each agent performs a specific subtask required to reach the goal and their efforts are coordinated through AI orchestration.
    • Unlike traditional AI models, which operate within predefined constraints and require human intervention, agentic AI exhibits autonomy, goal-driven behavior and adaptability. The term “agentic” refers to these models’ agency, or, their capacity to act independently and purposefully.
    • Agentic AI builds on generative AI (gen AI) techniques by using large language models (LLMs) to function in dynamic environments. While generative models focus on creating content based on learned patterns, agentic AI extends this capability by applying generative outputs toward specific goals.
  • Edge AI Technology:
    • Edge artificial intelligence refers to the deployment of AI algorithms and AI models directly on local edge devices such as sensors or Internet of Things (IoT) devices, which enables real-time data processing and analysis without constant reliance on cloud infrastructure.
    • Simply stated, edge AI, or “AI on the edge“, refers to the combination of edge computing and artificial intelligence to execute machine learning tasks directly on interconnected edge devices. Edge computing allows for data to be stored close to the device location, and AI algorithms enable the data to be processed right on the network edge, with or without an internet connection. This facilitates the processing of data within milliseconds, providing real-time feedback.
    • Self-driving cars, wearable devices, security cameras, and smart home appliances are among the technologies that leverage edge AI capabilities to promptly deliver users with real-time information when it is most essential.
  • High-Density AI: 
    • High-density AI refers to the concentration of AI computing power and storage within a compact physical space, often found in specialized data centers. This approach allows for increased computational capacity, faster training times, and the ability to handle complex simulations that would be impossible with traditional infrastructure.
  • Explainable AI (XAI) and Human-Centered Explainable AI (HCXAI): 
    • Explainable AI (XAI) refers to methods for making AI model decisions understandable to humans, focusing on how the AI works, whereas Human-Centered Explainable AI (HCXAI) goes further by contextualizing those explanations to a user’s specific task and understanding needs. While XAI aims for technical transparency of the model, HCXAI emphasizes the human context, emphasizing user relevance, and the broader implications of explanations, including fairness, trust, and ethical considerations.
  • Physical AI & Embodied AI: 
    • Physical AI refers to a branch of artificial intelligence that enables machines to perceive, understand, and interact with the physical world by directly processing data from a variety of sensors and actuators.
    • Physical AI provides the overarching framework for creating autonomous systems that act intelligently in real-world settings. Embodied AI, as a subset, focuses on the sensory, decision-making, and interaction capabilities that enable these systems to function effectively in dynamic and unpredictable environments.

 

 

• Spin-Off:
  • To “spin-off” a company means a parent company creates a new, independent company by separating one of its business units, often distributing the new company’s shares to the parent company’s existing shareholders. This process allows the spun-off division to focus on its own strategy and allows parent company management to concentrate on their core business, potentially increasing the overall value for both entities.

 

 

• Hardware vs. Software vs. Firmware: 
  • Hardware is physical: It’s “real,” sometimes breaks, and eventually wears out.
    • Since hardware is part of the “real” world, it all eventually wears out. Being a physical thing, it’s also possible to break it, drown it, overheat it, and otherwise expose it to the elements.
    • Here are some examples of hardware:
      • Smartphone
      • Tablet
      • Laptop
      • Desktop computer
      • Printer
      • Flash drive
      • Router
  • Software is virtual: It can be copied, changed, and destroyed.
    • Software is everything about your computer that isn’t hardware.
    • Here are some examples of software:
      • Operating systems like Windows 11 or iOS
      • Web browsers
      • Antivirus tools
      • Adobe Photoshop
      • Mobile apps
  • Firmware is virtual: It’s software specifically designed for a piece of hardware
    • While not as common a term as hardware or software, firmware is everywhere—on your smartphone, your PC’s motherboard, your camera, your headphones, and even your TV remote control.
    • Firmware is just a special kind of software that serves a very narrow purpose for a piece of hardware. While you might install and uninstall software on your computer or smartphone on a regular basis, you might only rarely, if ever, update the firmware on a device, and you’d probably only do so if asked by the manufacturer, probably to fix a problem.

 

 

• SaaS (Software as a Service):
  • Cloud-based service where instead of downloading software your desktop PC or business network to run and update, you instead access an application via an internet browser. The software application could be anything from office software to unified communications among a wide range of other business apps that are available.
  • This offers a variety of advantages and disadvantages. Key advantages of SaaS includes accessibility, compatibility, and operational management. Additionally, SaaS models offer lower upfront costs than traditional software download and installation, making them more available to a wider range of businesses, making it easier for smaller companies to disrupt existing markets while empowering suppliers.
  • The major disadvantage of SaaS applications is that they ordinarily require an internet connection to function. However, the increasing wide availability of broadband deals and high-speed phone networks such as 5G makes this less of an issue. Additionally, some SaaS applications have an offline mode that allows basic functionality.

 

 

• CAGR (Compound Annual Growth Rate):
  • The Compound Annual Growth Rate is the rate of return that would be required for an investment to grow from its beginning balance to its ending balance, assuming the profits were reinvested at the end of each period of the investment’s life span.
  • To calculate the CAGR of an investment:
    • Divide the value of an investment at the end of the period by its value at the beginning of that period.
    • Raise the result to an exponent of one divided by the number of years.
    • Subtract one from the subsequent result.
    • Multiply by 100 to convert the answer into a percentage.

 

 

• Grid, Microgrids, DERs and DERM’s:
  • Grid / Power Grid:
    • The power grid is a network for delivering electricity to consumers. The power grid includes generator stations, transmission lines and towers, and individual consumer distribution lines.
      • The grid constantly balances the supply and demand for the energy that powers everything from industry to household appliances.
      • Electric grids perform three major functions: power generation, transmission, and distribution.
  • Microgrid:
    • Small-scale power grid that can operate independently or collaboratively with other small power grids. The practice of using microgrids is known as distributed, dispersed, decentralized, district or embedded energy production.
  • Smart Grid:
    • Any electrical grid + IT at all levels.
  • Micro Grid:
    • Group of interconnected loads and DERs (Distributed Energy Resources) within a clearly defined electrical and geographical boundaries witch acts as a single controllable entity with respect to the main grid.
  • Distributed Energy Resources (DERs): 
    • Small-scale electricity supply (typically in the range of 3 kW to 50 MW) or demand resources that are interconnected to the electric grid. They are power generation resources and are usually located close to load centers, and can be used individually or in aggregate to provide value to the grid.
      • Common examples of DERs include rooftop solar PV units, natural gas turbines, microturbines, wind turbines, biomass generators, fuel cells, tri-generation units, battery storage, electric vehicles (EV) and EV chargers, and demand response applications.
  • Distributed Energy Resources Management Systems (DERMS):
    • Platforms which helps mostly distribution system operators (DSO) manage their grids that are mainly based on distributed energy resources (DER).
      • DERMS are used by utilities and other energy companies to aggregate a large energy load for participation in the demand response market. DERMS can be defined in many ways, depending on the use case and underlying energy asset.

 

 

• Semiconductor:
  • Solid substance that has a conductivity between that of an insulator and that of most metals, either due to the addition of an impurity or because of temperature effects. Devices made of semiconductors, notably silicon, are essential components of most electronic circuits. Some examples of semiconductors are silicon, germanium, gallium arsenide, and elements near the so-called “metalloid staircase” on the periodic table. … Silicon is a critical element for fabricating most electronic circuits.
• Semiconductor Wafer:
  • A semiconductor wafer is a thin, circular slice of a semiconductor material, most commonly silicon, that serves as the foundation for creating integrated circuits and other microelectronic devices. These wafers are made from highly pure, single-crystal material and undergo numerous processing steps to build the complex circuitry of chips.
• SiC Semi-Conductor Technology:
  • Silicon carbide (SiC), a semiconductor compound consisting of silicon (Si) and carbon (C), belongs to the wide bandgap (WBG) family of materials. Its physical bond is very strong, giving the semiconductor a high mechanical, chemical and thermal stability.
  • Silicon carbide, exceedingly hard, synthetically produced crystalline compound of silicon and carbon. Its chemical formula is SiC. Since the late 19th century silicon carbide has been an important material for sandpapers, grinding wheels, and cutting tools.
  • Since there is less energy to dissipate, an SiC device can switch at higher frequencies and improve efficiency. The higher efficiency, smaller size and lower weight of SiC can create a higher-rated solution or a smaller design with reduced cooling requirements.

 

 

• Free Cash Flow (FCF):
  • Free cash flow (FCF) is a company’s available cash repaid to creditors and as dividends and interest to investors. Management and investors use free cash flow as a measure of a company’s financial health. FCF reconciles net income by adjusting for non-cash expenses, changes in working capital, and capital expenditures. Free cash flow can reveal problems in the financial fundamentals before they become apparent on a company’s income statement. A positive free cash flow doesn’t always indicate a strong stock trend. FCF is money that is on hand and free to use to settle liabilities or obligations.

 

 

• GDP (Gross Domestic Product):
  • GDP measures the monetary value of final goods and services—that is, those that are bought by the final user—produced in a country in a given period of time (say a quarter or a year). It counts all of the output generated within the borders of a country.
  • Standard measure of the value added created through the production of goods and services in a country during a certain period. As such, it also measures the income earned from that production, or the total amount spent on final goods and services (less imports).
  • GDP is defined by the following formula: GDP = Consumption + Investment + Government Spending + Net Exports or more succinctly as GDP = C + I + G + NX where consumption (C) represents private-consumption expenditures by households and nonprofit organizations, investment (I) refers to business expenditures by businesses and home purchases by households, government spending (G) denotes expenditures on goods and services by the government, and net exports (NX) represents a nation’s exports minus its imports.

 

 

 

 

 

 

 

 

 

 

 

EMR Additional Financial Notes: 

• Major financial KPI’s since 2017 are available on EMR Executive Services under “Financial Results” and comparison with peers under “Market Positioning”
• Companies’ full profile on EMR Executive Services are based on their official press releases, quarterly financial reports, annual reports and other official documents like the Universal Registration Document.
• All members of the Executive Committee and of the Board have their full profile on EMR Executive Services
• Siemens Q4 FY 2025 Earnings Release and Financial Results can be found here: https://assets.new.siemens.com/siemens/assets/api/uuid:3948cdd4-35e0-4c1d-8412-9aed4097b3d0/HQCOPR202511117277EN.pdf 
• Siemens Record Results for 2025 Presentation can be found here: https://assets.new.siemens.com/siemens/assets/api/uuid:7fe2d062-c9a2-4468-98bf-06015dcf2fad/2025-q4-presentation-en.pdf 
• Siemens Annual Report 2024 can be found here: https://www.siemens.com/global/en/company/investor-relations/events-publications-ad-hoc/annualreports.html
• Siemens Q4 FY 2024 Earnings Release and Financial Results can be found here: https://assets.new.siemens.com/siemens/assets/api/uuid:7c6b9d32-94a1-450d-a921-ce8c09544ad9/2024-q4-earnings-release-en.pdf
• Siemens Q4 FY 2024 Presentation can be found here: https://assets.new.siemens.com/siemens/assets/api/uuid:8a7337e7-d3db-42bb-851e-3d649a19747b/2024-q4-presentation-en.pdf
• Siemens Annual Report 2023 can be found here: https://www.siemens.com/global/en/company/investor-relations/events-publications-ad-hoc/annualreports.html
• Siemens Annual Report 2022 can be found here: https://www.siemens.com/applications/b09c49eb-3a14-73b3-9f71-e30e3c2dfdbd/s3_assets/pdfs/en/Siemens_Report_FY2022.pdf?ste_sid=4e3952fc97563bcdbc8b2c7599f83d74
• Siemens Annual Report 2021 can be found here: https://new.siemens.com/content/dam/internet/siemens-com/global/company/investor-relations/application-pages/report/report4you_en/assets/pdfs/Siemens_Report_FY2021.pdf