Performance, Attention, and Authority: Rethinking AI-Enabled Enterprise Performance Management

Abstract

The way enterprises manage performance has changed, moving on from static and periodic reports to a more continuous form of real-time monitoring. But for the finance leader this shift has not been a panacea; an overabundance of data has yet to yield decisions that are any faster or more firmly in hand. We contend in this article that what is now holding back modern enterprise performance management is not a lack of information so much as it is the paucity of managerial attention and ambiguity around who has the authority to decide. In putting forward a three-layer architecture of performance, attention and authority, we make use of the latest thinking in financial planning and analysis, human-AI collaboration and the problem of information overload. To help executives determine which signals merit their time, we introduce a five-dimension Management Attention Test (covering materiality, persistence, confidence, decision ability and ownership). The piece also makes the case for separating analytical from decision authority and lays out the governance needed for the responsible application of AI in finance, along with a sensible path to implementation. Our conclusion is that an organisation will be better served by a disciplined approach to filtering and assigning accountability than by rolling out more AI dashboards. In short, artificial intelligence should be viewed as an analytical partner in the finance function, not a stand-in for making the call.