Artificial Intelligence (AI) has emerged as one of the central topics in business and technology over recent years. Its applications range from automating simple processes to supporting complex strategic decisions. In product portfolio management, AI is also proving to be a game-changer. Generative AI (GenAI) offers businesses entirely new ways to analyze data, find answers faster, and make well-informed decisions.
Particularly in a field as data-intensive and strategically critical as product portfolio management, AI unleashes tremendous potential. It not only saves time but also enables businesses to address complex questions through simple prompting and supports intricate analyses.
This article aims to highlight how Generative AI (GenAI) can assist companies in managing their product portfolios. The focus is not solely on the technology itself but also on the interplay of various components. After all, it is not a single artificial intelligence that resolves all challenges, but rather the intelligent integration of multiple AI assistants and strategies into existing processes that makes a lasting difference.
A company’s product portfolio includes all its products and their strategic alignment to balance revenue, costs, and market demands with corporate objectives. However, the complexity of portfolio management has increased significantly in recent years.
Managing an extensive portfolio has become more challenging because businesses often need to offer numerous product variants to meet diverse customer needs. This variety leads to high complexity costs, such as additional production and logistics efforts, which can impact efficiency. On top of this, companies must quickly adapt to changing market demands, requiring further adjustments and resources.
A common issue is that while companies may generate higher revenue, their EBIT often declines because management costs eat into the additional income. High product complexity frequently burdens profitability, making it necessary to reduce complexity to cut costs and improve efficiency. The challenge lies in finding the right balance - meeting market demands without allowing complexity to compromise financial performance. Achieving this balance is no small feat, as multiple perspectives within the company must be factored into the decision-making process.
Given the growing complexity of managing product portfolios, Generative AI (GenAI) offers a promising solution to enhance efficiency and competitiveness. One of AI's primary advantages lies in its ability to analyze multidimensional perspectives. It can process data from various sources (such as ERP, CRM, PIM, CPQ) simultaneously, identifying patterns and dependencies that are often invisible to the human eye.
Additionally, AI enables the automated processing of large datasets. This not only accelerates portfolio analysis but also uncovers hidden opportunities and risks. The ability to deliver data-driven insights in real-time is a critical advantage in a business environment that demands swift decision-making.
AI serves as an excellent assistant to support human decision-making. Its recommendations in product portfolio management can be business-critical and offer valuable insights. However, the final decision should always rest with humans, as strategic thinking, experience, and alignment with corporate goals remain indispensable.
To fully harness AI's potential, the necessary IT infrastructure must be in place. High-quality data and the right technical foundation are essential for GenAI to deliver precise and actionable recommendations.
Despite its capabilities, AI is not a standalone solution for the challenges of product portfolio management. The true value lies in combining AI with sound strategy, aligned processes, and robust data management.
Product portfolio management involves complex trade-offs where strategic thinking, analytical approaches, and experience are critical. While GenAI can analyze data and provide recommendations, the final decisions must always be made within the context of the company’s goals. Moreover, every business has unique requirements and data structures that must be considered.
Success, therefore, depends on the interplay of multiple factors. AI needs to be seamlessly integrated into existing processes - from data collection and analysis to decision-making. It can automate numerous small tasks, reducing workload and freeing up resources for higher-value activities. However, without well-coordinated workflows and confidence in the data, its potential remains limited.
In portfolio management, product management plays a central role in this task. It must regularly analyze the portfolio and manage it strategically to meet market demands and ensure profitability. This is where the high value of generative AI becomes evident in various activities that ease and improve everyday work:
Overall, the practical benefits of AI are evident in multiple areas. Product management is equipped with a range of assistants that help with specific tasks - from data analysis and market opportunity identification to scenario simulation. But not only product management benefits from AI-powered assistants; surrounding stakeholders from procurement, sales, controlling and management can also access specialized assistants to support them in their specific tasks.
Especially at the interfaces between departments, GenAI plays an important role. This is where AI assistants come into play, acting as data analysts and providing the product management team with relevant information from procurement or sales - without the need for direct communication or waiting for departments. The analyses are carried out by the AI assistants through prompting and deliver the required data at the push of a button. However, a prerequisite for this efficiency is a clean data foundation and a linked data structure that allows information to be retrieved from a "Single Source of Truth". This not only saves time but also valuable resources and enhances overall efficiency in product portfolio management.
Reading recommendation: The importance of data integration in product portfolio management for a holistic view
The application of artificial intelligence in product portfolio management is particularly evident in the concept of Product Mining (German). This process involves identifying optimization potential from product-centric data and already employs various AI-powered assistants to support the process. A key prerequisite for success is a well-structured platform that consolidates different information systems and data sources. This structure is crucial to ensure that relevant data is processed efficiently and high data quality is maintained. Only with a solid foundation can the assistants provide informed and meaningful suggestions.
The basic steps of Product Mining - Discovery, Optimize and Impact - provide the framework in which GenAI plays a central role. It supports the entire process, from data integration and product portfolio analysis to specific optimization recommendations. One of GenAI's particular strengths lies in its ability to interpret data and identify patterns that would be difficult for humans to grasp. This allows risks and opportunities to be identified in real-time. AI is especially valuable as a decision-making aid, providing data-driven recommendations and evaluating various scenarios to present optimal action options.
An important factor in harnessing the full potential of AI is its specialization. While general AI models like ChatGPT can cover a wide range of tasks, customized AI solutions are significantly more effective for product portfolio management. This is where we at MYNR come into play: We develop specialized applications that are precisely tailored to the needs and requirements of businesses. These solutions integrate all necessary components, including GenAI, to make product portfolio management more efficient and targeted.
The combination of artificial intelligence and data-driven management is transforming product portfolio management sustainably. AI creates transparency, identifies opportunities and risks, and supports data-based strategic decisions. However, despite these advancements, human involvement remains essential to make meaningful use of AI's recommendations. Only through the collaboration of humans and technology can companies fully leverage the value of their product portfolios. The rapid development of AI makes it necessary to implement modern software solutions to remain competitive and minimize costs and risks.
Ready for the next step? Visit the product page of the MYNR APP and discover how you can optimize your product portfolio with AI and secure long-term competitive advantages.
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