ORGANIZATIONS ARE INCREAS-ingly turning to sophisticated data analytics algorithms to support realtime decision-making in dynamic environments. However, these organizational efforts often fail-sometimes with spectacular consequences.
In 2018, real estate marketplace Zillow launched Zillow Offers, an "instant buyer" arm of the business. It leveraged a proprietary algorithm called Zestimate, which calculates how much a given residential property can be expected to sell for. Based on these calculations, Zillow Offers planned to purchase, renovate, and resell properties for a profit.¹ While it had some success for the first few years, the model failed to adjust to the new dynamics of a more volatile market in 2021. Zillow lost an average of $25,000 on every home it sold in the fourth quarter that year - resulting in a write-down of $881 million.²
This is an example of what we call algorithmic inertia: when organizations use algorithmic models to take environmental changes into account but fail to keep pace with those changes. In this article, we explain algorithmic inertia, identify its sources, and suggest practices organizations can implement to overcome it.
A Credit-Rating Catastrophe
To understand the phenomenon of algorithmic inertia, we conducted an in-depth study of another organization that failed to respond to changes in the environment: Moody's, a financial research firm that provides credit ratings for bonds and complex financial instruments such as residential mortgage-backed securities (RMBSs). These securities aggregated bundles of individual mortgages into distinct tranches with unique characteristics during the period leading up to the global financial crisis of 2008.³
この記事は MIT Sloan Management Review の Summer 2023 版に掲載されています。
7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。
すでに購読者です ? サインイン
この記事は MIT Sloan Management Review の Summer 2023 版に掲載されています。
7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。
すでに購読者です? サインイン
Ask Sanyin: How Do You Build for an Unpredictable Future?
While the pandemic was a wild ride of uncertainty for me and many of my peers in leadership, it feels like we never regained our footing.
What You Still Can't Say at Work
Most people know what can’t be said in their organization. But leaders can apply these techniques to break through the unwritten rules that make people self-censor.
Make Character Count in Hiring and Promoting
Most managers focus on competencies when evaluating candidates but it’s character that will transform the DNA of the organization. Here’s how to assess it.
Why Influence Is a Two-Way Street
Managers achieve better outcomes when they prioritize collaborative decision-making over powers of persuasion.
Know Your Data to Harness Federated Machine Learning
A collaborative approach to training AI models can yield better results, but it requires finding partners with data that complements your own.
How Integrating DEI Into Strategy Lifts Performance
Incorporating diversity, equity, and inclusion practices into core business planning can provide a competitive edge.
The Myth of the Sustainable Consumer
Companies that understand the different kinds of consumers for sustainable products can market to them more effectively.
A Practical Guide to Gaining Value From LLMs
Getting a return from generative AI investments requires a systematic approach to analyzing appropriate use cases.
Improve Workflows by Managing Bottlenecks
Understand whether process or resource constraints are stalling work.
Craft Schedules That Work for Everyone
Business leaders can improve retention and business performance with schedules that make sense for workers’ lives.
