Smart Strategies Require Smarter KPIs
KPIs are becoming more versatile and valuable for securing strategic advantage.
Digital processes, platforms, and predictive algorithms transform the strategic role and purpose of key performance indicators. KPIs are becoming measurably smarter, more dynamic, and more adaptive. This makes them more versatile and valuable for securing strategic advantage. For data-driven disruptors like Alibaba, Amazon, Airbnb, and Uber, KPIs don’t simply monitor enterprise success; they proactively drive it. This shift creates innovative opportunities for ambitious leadership.
To reap the benefits of these next-generation metrics, a new level of top management insight and oversight is required. This article identifies a virtuous cycle of critical success factors that determine effective KPI leadership.
Our research shows digitally sophisticated organizations have flipped traditional KPI purpose and processes inside out. Instead of seeing KPIs primarily as analytic outputs for humans, leading organizations increasingly use them as inputs for machines. That is, management relies on KPIs to train, tune, and optimize their machine learning models for business impact.
The organizational, operational, and cultural implications of this big flip are enormous. Smart KPIs literally learn to improve their performance and the performance of the organization. This emergent capability creates novel value-added relationships between management, metrics, and machines.
The most important insight: KPIs ― both individually and collectively ― become central organizing principles for leadership investment in data and decision-making. People, process, and technology are radically reorganized around metrics. Data and analytic priorities, as well as decision-making authority, are redefined and determined by smarter KPIs. As we concluded in a recent MIT Sloan Management Review article, your KPIs are your strategy; your strategy is your KPIs. For top-tier transformers, KPIs explicitly shape the strategic leadership dialogue and debate.
Customer churn offers the canonical KPI example of how virtual interdependencies between data and decision-making coevolve. According to Harvard Business Review, the cost of acquiring new customers can prove to be five to 25 times more expensive than keeping existing ones. Customer retention is key to sustaining cash flow and profitability. This holds particularly true for subscription businesses, notably software, financial services, and mobile telephony.
For these industries, reducing churn ― the KPI that tracks customers ending their relationship with a company over a particular time period ― is a strategic priority. Even determining that period ― a week, month, quarter, or year ― is itself a strategic choice. Almost without exception, significant changes in churn rates command immediate top management attention.