Dad needs a coronary bypass operation—and you’re helping him choose between two local hospitals. You discover both have about the same history of patient deaths per 100 procedures performed. You further learn that, at Hospital A, most recent bypass-related deaths were performed by a few apparently sub-par surgeons. You’re comforted they’ve been asked to leave the hospital.
Hospital B shows a different pattern of surgical outcomes. Patient deaths there were not concentrated among any group of surgeons. Negative incidents were more widely distributed in the general rotation, with no discernible clustering of failure. Hospital B did not systematically dismiss “the few erring cardiologists,” but instead pursued a broader practice improvement program to enhance evidence-based protocols, training, and multi-disciplinary quality committees.
So Where Do You Send Dad For His Operation?
First take, you might choose Hospital A: decisive leadership identified the physicians responsible and moved them out. And who knows about Hospital B? Mistakes were more random there–how can you be sure that Dad won’t just be unlucky and be some doctor’s next operation mistake?
Oddly, Hospital B may be the better bet. Thus argues a new research study by Vinit Desai, an associate professor of management at the University of Colorado Denver (available in the current Academy of Management Journal) .
Desai studied patient death rates and data for cardiac bypass surgery in some 115 California hospitals—and found that in most of the hospitals, the departure of physicians performing the failed operations did not significantly diminish the rate of future patient deaths. In contrast, hospitals that improved most in overall organizational performance (i.e. reduction of coronary patient deaths) were those where the failures were widely dispersed across all operating surgeons.
Concentrated Failure, Clouded Judgment
Why would that be? It seems related to how hospital leadership tried to improve the patient survival rate. Desai’s research suggests that “concentrated failures prompt narrower attributions of responsibility which, whether accurate or not, ultimately lead to less thorough investigations and fewer of the system-wide changes that are typically required to address organizational performance problems.”
Stated simply, hospitals that most improved went beyond simply firing the sub-par performers. Instead of blame they reframed: analyzed and tackled the problem in broader, interconnected dimensions, focusing on structural solutions and coronary bypass procedures. They made more efforts to understand and address systemic issues (e.g. operating room protocols, post-op care, inconsistent organizational practice, etc.) that, taken together, were more significant in causing performance to lag.
Desai hypothesized that intensive focus on individual actors can actually obscure the deeper performance problems of any organization seeking to improve itself.
Fixing The Problem, Missing The Solution
Desai’s research rings true for anyone who’s ever been scapegoated. We all know how convenient—and often ineffectual—it is for the boss to simply blame “the poor performers.” Miss a number for Wall Street, bungle a new product rollout—the “bold leader” moves swiftly to find the guilty parties and then “solve the problem” by firing them. It’s the zero-sum game of hierarchical accountability, played the old fashioned way. Identify the cancer eating performance, and cut it out.
But so often the real problem is not just a few malignant cells, but sub-surface, interrelated causes, or wider issues of culture—mindsets, behaviors, attitudes and processes. It’s harder for a leader to work on those, but that’s often what differentiates good from poor performance.
Now think about the networked world. The frequency and cost of rush-to-judgment leadership action—blame instead of reframe—will increase as traditional organizations become more interconnected and distributed. When products are co-created across crowds and networks of customers, when competitors thrive not on the basis of their own businesses but rather the strength and reinforcing strategies of broader ecosystems, when talent is being mobilized from beyond traditional boundaries and organizational units—what leader can easily and quickly identify “just a few guilty parties” when a problem arises? What’s the right way to learn and improve from mistakes or shortfalls of performance, when results are the collective work and innovation of more and more hands?
Managing Performance In The Networked World
Welcome to the new world of networked and collaborative accountability. Tomorrow’s leaders cannot abandon focus on individual contributions, good or bad. But they also can’t just blame everyone when something goes wrong, nor celebrate “the entire crowd” when success is achieved. Leaders now have to identify individual contributions and also understand the deeper and systemic attributes of performance—culture, processes, and habits of thought. And they have to be willing to invest the time and trouble to look across boundaries, beyond organizational units, and understand more informal communities of collaboration which produce today’s best products and services. Developing in tandem individual practitioners but also the broader networks in which they operate is the new imperative. It’s yet another dimension of the “both/and” thinking that today’s network leaders must adopt.
Leadership Lessons
What broader lessons about managing performance might network leaders take—or extend– from Desai’s new research?
- Make Performance Transparent. Desai’s inquiry began with the availability of rich and comparable data about coronary bypass outcomes across a large sample of hospitals (required by California law). But you don’t have to be writing a research paper to “make data matter.” Avoid the pitfalls of “judgment by the gut” by clarifying—and making clear for all to see—what success looks like for any product/service/process you are seeking to improve. Be consistent in using that data for evaluating and managing performance.
- Build Performance Metrics Collaboratively. Measurement of excellence must not only be clear to all, it must also be agreed by all. In evaluating hospital performance and medical procedure success, patient survivability rates are relatively unambiguous. The best way to ensure metrics that are transparent and owned by a community is to create them collaboratively—not imposing upon but rather engaging the members of the community who are delivering a product or service to define the desired outcomes.
- Don’t Rush To Judge, Even If Problems Crop Up In One Place. Beware the misleading signals of “concentrated failure.” Even if one unit or a small group of contributors seems to be where performance goes bad, look for deeper, more systemic problems that could be critical factors—or even the most important source—of trouble. Engage the community to understand those, as part of the problem-solving process.
- Build A Culture Of Continuous Improvement, Governed By The Community. Desai argues that “top-down punctuated remediation”—simply removing poor performers—is often less effective than making broader cultural changes to support the best practice and quality of a service delivery. A culture of continuous improvement does not ignore individual accountability; it combines it with contextual and organizational factors, to strengthen “whole system” performance. Such a culture typically embraces open organizational values such as meritocracy, open dissent and debate, and learning from failure. In the best cases such values are co-developed with members of the performance community itself.
Originally published on Forbes.com