{"id":3041,"date":"2025-06-16T17:04:28","date_gmt":"2025-06-16T15:04:28","guid":{"rendered":"https:\/\/tenglerconsulting.com\/?p=3041"},"modified":"2026-04-21T11:25:05","modified_gmt":"2026-04-21T09:25:05","slug":"ai-driven-portfolio-optimization","status":"publish","type":"post","link":"https:\/\/tenglerconsulting.com\/en\/ai-driven-portfolio-optimization\/","title":{"rendered":"Using AI to optimize product variety: How companies can intelligently manage their portfolio"},"content":{"rendered":"

[vc_row section_type=”fullwidth” height_ratio=”60″ padding_top_multiplier=”” padding_bottom_multiplier=”” rc_bg_type=”image” rc_bg_image=”3047″ columns_gap=”none”][vc_column][\/vc_column][\/vc_row][vc_row section_type=”fullwidth” padding_top_multiplier=”3x” padding_bottom_multiplier=”4x” columns_gap=”60″][vc_column width=”2\/3″]

Using AI to optimize product variety: How companies can intelligently manage their portfolio<\/span><\/h1>
<\/div>[\/vc_column][vc_column width=”1\/3″][\/vc_column][\/vc_row][vc_row section_type=”fullwidth” padding_top_multiplier=”” padding_bottom_multiplier=”” columns_gap=”60″][vc_column]
<\/span><\/div>[\/vc_column][\/vc_row][vc_row section_type=”fullwidth” padding_top_multiplier=”3x” padding_bottom_multiplier=”2x” columns_gap=”60″][vc_column width=”1\/3″][vc_column_text css=”” text_style=”small-text”]01<\/span>[\/vc_column_text]

Portfolio under control<\/span><\/h3>[\/vc_column][vc_column width=”2\/3″][vc_column_text css=””]Modern companies face the challenge of managing their product or service portfolios in a way that maximizes customer value and profitability, while minimizing complexity and costs within the supply chain. A key factor in this equation is the breadth of the product portfolio. The larger and less structured the assortment, the greater the effort, cost, and complexity typically involved. Companies that don\u2019t let their portfolios grow unchecked, but instead manage and streamline them actively, lay the foundation for efficient operations and avoid unnecessary burdens.<\/p>\n

Portfolio management in the supply chain context means designing the assortment in a targeted manner: Which products and variants stay in the offering? Which are reduced or removed? The goal is to provide the right products in the right quantities to meet market demand without wasting resources. Decision-making is based on both market and demand data, as well as cost, production, and logistics information.<\/p>\n

The Association for Supply Chain Management (ASCM)<\/strong> emphasizes that holistic product portfolio management is a crucial lever for building a more resilient and agile supply chain especially when new technologies such as artificial intelligence (AI) are applied strategically. AI can not only automate data processing but also support decision-making through pattern recognition and scenario analysis.[1][\/vc_column_text][\/vc_column][\/vc_row][vc_row section_type=”fullwidth” padding_bottom_multiplier=”2x” columns_gap=”60″][vc_column width=”1\/3″][vc_column_text css=”” text_style=”small-text”]02<\/span>[\/vc_column_text]

The limits of traditional approaches<\/span><\/h3>[\/vc_column][vc_column width=”2\/3″][vc_column_text css=””]Many companies still rely on traditional portfolio management methods such as manual assortment reviews, ABC analyses, or basic rules of thumb. But these approaches quickly hit their limits when product variety and market volatility increase. In practice, we often see an \u201coversupply\u201d of products: too many variants in the system, many of which generate little to no revenue.<\/p>\n

Years ago, a McKinsey study already pointed out the risks of having too few offerings for customers, while an oversupply of the \u201cwrong\u201d products leads to unnecessary costs and lost revenue opportunities. Traditional methods also tend to be retrospective, isolate product performance, and underestimate their full impact on the supply chain. Too many low-performing stock keeping units (SKUs) result in high inventory and setup costs, planning inefficiencies, and resource waste.[2]<\/p>\n

Portfolio decisions are often made in silos – e.g., by product management or sales without input from production, logistics, or supply chain management. The result: poor responsiveness, inefficient inventory levels, and internal cannibalization effects within the portfolio.[\/vc_column_text][\/vc_column][\/vc_row][vc_row section_type=”fullwidth” padding_bottom_multiplier=”2x” columns_gap=”60″][vc_column width=”1\/3″][vc_column_text css=”” text_style=”small-text”]03<\/span>[\/vc_column_text]

Vision for AI-driven portfolio optimization<\/span><\/h3>[\/vc_column][vc_column width=”2\/3″][vc_column_text css=””]<\/p>\n