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Making decisions in the digital age

, by Arnaldo Camuffo e Alfonso Gambardella, full professors at Department of Management and Technology
Higher operational performance is the most obvious, but not the most important, consequence of digital transformation. In fact, by automating highfrequency but lowimpact decisions, managers can better focus on strategic decisions, while new managerial job profiles are being born

Why do superstar firms characterized by hyper-growth emerge in the digital era? Why are public, managerial corporations eclipsing in favor of concentrated ownership, agentic investors and high financial leverage? Why do owners/entrepreneurs remain at the helm of firms and keep running them even if they become complex and large? Why do firms increasingly rely on M&As and external growth flexibly, reconfiguring their knowledge base and assets? Why do firms become increasingly customer-centric and tend to experiment more?
These apparently unrelated trends have instead common grounds in the effects of the digital revolution on the functioning of firms. Digitalization changes the nature of firms, radically transforming strategic decision-making and strategic management.
As highlighted by a recent Strategic Management Review article and a recent CEPR discussion paper, superior operational performance is the most apparent but not the most important consequence of digitalization. It becomes a major source of competitive advantage when complemented with the ability to better explore markets, profile customers, tap into their needs and design products and services accordingly. There are three complementary conditions that can produce superior performance out of management cognitive time and effort spent on low-frequency/high-impact decisions: a) the adoption of a "scientific approach" to decision-making under uncertainty; b) the embracement of uncertainty as the ultimate source of economic growth; and c) the redefinition of business owners' role as strategists.

Digitalization and algorithms flatten organizational structures, shorten business process cycles, modularize and externalize activity sets and units, replace or at least change operational and managerial jobs, and modify the correspondent skill requirements. As data, algorithms, AI and machine learning allow to digitalize high-frequency/low-impact decisions, managers can dedicate more time and attention to strategic, low-frequency/high-impact decisions. Differences in the amount and quality of managerial time and attention available for strategy, along with differences in the effectiveness of strategies, represents a major source of variation in firm performance.
So, from the managerial standpoint, the automation of high frequency/low impact/low uncertainty decisions has two potential implications. First, other things equal, it frees-up cognitive resources that can be dedicated to making low frequency/high uncertainty/ high impact decisions. Second, as it hollows out traditional managerial jobs which are no longer needed to make high-frequency/low-uncertainty decisions, it also generates new managerial jobs needed to support the digitalization/automation process and to make low-frequency/high-impact/high-uncertainty decisions.