Rushing in with tech is a crisis waiting to happen—just ask the National Eating Disorder Association and its rogue chatbot, Tessa. Earlier this year, NEDA informed its helpline staff that they would be disbanding the group and replacing them with Tessa. Unfortunately, days before the switch, it was discovered that Tessa was encouraging people with eating disorders to restrict calories, set weight loss goals and have frequent weigh-ins—all of which are disordered eating behaviors. So, instead of guiding innovative transformation, NEDA subverted its mission, demoralized its workforce, damaged its reputation and exposed itself to legal risks. This is a prime example of why tech comes last.
A “tech comes last” approach highlights the importance of prioritizing strategy, people and processes. While technology plays a crucial role in digital transformation, it’s an enabler, not the sole focus. Healthcare executives should first define a responsible strategy aligned with their organizational goals and stakeholder needs, and then identify the tech that supports their objectives. By prioritizing strategy, people and processes, they’ll ensure that tech investments are purposeful and effective.
To navigate the complexities and avoid the pitfalls of digital transformation, it’s essential for executives to become what I call “computational leaders,” who blend computational thinking and technology with a science-driven understanding of human behavior to drive innovation, make data-informed decisions and address complex problems in a digital world.
For example, computational leaders can direct cross-functional teams that harness the power of artificial intelligence and data analytics to personalize patient interventions based on a deep understanding of a patient’s unique motivational triggers, behaviors, preferences and medical history. Such teams can also be reconfigured to identify early warning signs of employee burnout, enabling proactive interventions including personalized workload adjustments and workflow automation to reduce stress. These cross-functional teams, led by healthcare executives, possess unique skills that allow them to simultaneously understand the end user and the technology. They’re also better at understanding technological limitations to avoid problems such as Tessa’s bad advice and to iterate better solutions quickly.
Building such teams and guiding digital transformation requires a structured process. Healthcare leaders need to identify systemic tensions in their organization, such as quantity vs. quality or profit vs. people, to provide the rationale and context for transformation, and to create awareness of the issues that need to be addressed. Healthcare leaders also need to define clear and actionable goals to alleviate systemic tensions. Defining goals makes the tension concrete, focuses transformation efforts and sets targets for successful change.
Another critical, though often overlooked, aspect of digital transformation is identifying critical factors to achieve goals – the psychological science behind stress and burnout, for example. Identifying science-driven factors related to underlying tensions enables a deeper understanding of the root causes of problems, informing the collection of relevant data and guiding subsequent transformation plans. Effective leaders are also skilled at determining data requirements to capture critical factors. This ensures the collection of meaningful data to guide evidence-based decision-making.
Finally, disciplined leaders select relevant tech to analyze and leverage data. Knowing what tech to use and when to use it enhances the analysis and interpretation of data, enabling experimentation and real-time insights for addressing the needs of your organization and stakeholders.
To put this “tech comes last” mindset into context, healthcare executives can, for example, take a multifaceted approach to addressing burnout. They can collaborate with senior leadership to prioritize the tension between patient volume and doctors feeling overwhelmed. Working with HR professionals and front-line managers, executives can set achievable targets to reduce turnover and boost job satisfaction without compromising care. Support from organizational psychologists can help leaders identify burnout factors like job demands and limited autonomy. Data scientists can help with analyzing workload data and absenteeism rates to pinpoint high-stress periods and behavioral patterns indicative of burnout. And by leveraging IT specialists, executives can use AI to generate real-time, personalized interventions to mitigate burnout effectively.
A “tech comes last” approach to digital transformation sets the foundation for robust change. By harnessing cross-functional talent—from front-line managers to organizational psychologists—and prioritizing strategy, people and processes, computational leaders pave the way for successful transformation. They unlock the true potential of technology and create a future in which healthcare is driven by purpose, empathy and meaningful impact for all stakeholders.
Brian R. Spisak, PhD, is an independent consultant and a research associate, National Preparedness Leadership Initiative, Harvard T.H. Chan School of Public Health, Harvard University. He can be reached at bspisak@hsph.harvard.edu.