The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance.,The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size.,Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation).,The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio.,The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

中文翻译：

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产品级盈利能力

本文的目的是分析当前的挑战，并阐明基于商业和技术产品结构，关键业务流程，公司业务IT和公司数据资产的，数据驱动的，基于事实的产品组合管理（PPM）的前提条件。这里，从（产品/客户/供应商）主数据，交易数据和物联网数据的角度从PPM角度对数据资产进行了分类。该研究还探讨了公司级数据治理的支持作用。该研究结合了文献综述和对从八家大小不同的国际公司收集的经验数据进行定性分析。公司目前无法基于现有数据有效地分析产品奇怪。本调查结果确定了数据驱动的基于事实的PPM的许多前提条件，包括对公司产品的相互了解（以建立一致的商业和技术产品结构），将产品分类为战略，支持或非战略性（以将商业和技术产品结构与产品战略联系起来）以及针对整个公司的数据模型调整公司的业务IT（以支持产品组合可视化）。这些发现为基于事实的产品水平的产品盈利能力分析和产品生命周期内的产品组合分析提供了逻辑和经验基础，从而支持以下数据：驱动的方法来优化商业和技术产品结构，业务IT系统和公司产品策略。作为现实的虚拟表示，公司数据模型有助于产品可视化。