Idee

Finding the true cost of portfolio complexity

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McKinsey Quarterly

Fabian Bannasch, Florian Bouché

A fine-grained allocation of costs can help companies weed out “freeloader” products and improve performance.



Portfolio complexity is swamping many businesses. In the wake of globalization, some manufacturers have launched large and unwieldy numbers of country-specific models to suit particular markets: one vehicle manufacturer that had 30 models in the 1990s, for example, now has more than 300, and other companies have responded to the growing demands of customers for more customized—and sophisticated—offerings. From our work in the truck-manufacturing industry, meanwhile, we also see local product managers pushing variation to meet sales goals in the tough postcrisis economic environment.

Rooting out unnecessary—and costly—complexity is made more difficult in many cases by the lack of accounting transparency around niche offerings and products that sell in small quantities. Typically, costs are allocated by share of revenues. But since many specialized models have higher true costs arising from customization and lower production runs, they effectively freeload off more profitable lines. They often require more investment in R&D, tooling, testing, marketing, purchasing, and certification. Moreover, smaller batch sizes, lower levels of automation, longer assembly set-up times, and higher-cost technologies located further down the S-curves (for example customized, small-run technology for a new truck axle) will likely incur additional (and not always visible) expenses. Such distortions can lead to poor decisions. One truck executive we know argued for, and won, investment in a new, smaller engine to match a competitor, claiming it cost 10 percent less to manufacture than the company’s standard engine. In fact, with costs fairly allocated, it cost 20 percent more.

To identify hidden complexity costs, companies must dive deep into the data, applying granular assessments to individual components so as to understand the impact of customization or scale on the cost profiles of each model. Exhibit 1 shows the true contribution to profitability of one manufacturing portfolio, and the amount of cost concealed by traditional accounting practices.

Exhibit 1

qweb portfolio complexity ex

Executives should be prepared to take strong action to eliminate “hopeless cases”—products that sharply diminish margins—by moving up and left of the profit curve as shown in Exhibit 2. They can then further improve margins by recouping scale losses through greater standardization. In our experience, this healing process can reduce costs by up to 7 percent.

Exhibit 2

qweb portfolio complexity ex

About the author(s)

Fabian Bannasch is a senior expert in McKinsey’s Munich office, where Florian Bouché is a consultant.