A leading hospital was facing major challenges. Despite high patient volumes and strong utilisation, it was struggling with long waiting times and rising costs. Doctors and nursing staff were buried in administrative tasks and runaway internal and external coordination. These inefficiencies caused significant time loss, duplicated work and many iterative process loops. Internal surveys showed clear dissatisfaction across the workforce, reflected in rising sick leave and higher turnover. Doubts about the credibility of the administrative leadership were getting louder: “You keep saying it will get better soon, but nothing is happening!” That is when hospital management decided to act.
A comprehensive analysis — including multi-moment analysis (MMA), work-pressure analysis (WPA), calendar analysis and other methods — uncovered the root causes of these inefficiencies. The most pressing problems sat in the high planning effort, the administrative tasks and the many alignment meetings, which were eating up most of the time of expensive medical resources. That dramatically reduced the time available for value-adding patient care. Facility management and kitchen processes were analysed too, since these areas were also driving substantial delays and inefficiencies.
The multi-moment analysis (MMA) records and analyses how working time is spent. Using a sampling method, random pre-defined points in time are picked at regular intervals to record what activity each member of staff is performing. Alongside the activity, waste is also noted — for example IT problems, waiting times, or rework. About 10–15 sample points per day are recorded, and the survey typically runs for two weeks. For the individual staff member this means no more than 10 minutes of additional effort per day. The data is anonymised and aggregated centrally to give a precise picture of how time is spent across the hospital. The results provide concrete pointers for where to focus optimisation.
The work-pressure analysis (WPA) assesses daily workload and staff satisfaction. At the end of each day staff record whether it was a successful working day or whether their productivity was disrupted by various factors. Data on working hours, overtime and subjective workload are collected and analysed to identify overload and dissatisfaction. The method makes it possible to develop targeted measures to improve working conditions and reduce stress factors.
In shadowing, an observer accompanies a member of staff through their working day to gain a deep understanding of the actual workflows and challenges. The method gives practical insight into daily activities and identifies potential improvement opportunities directly on site.
With many interviews and shadowing across all departments and hierarchies, the experts built a deep understanding of daily operations and challenges. From there, targeted process-optimisation measures were developed and prioritised — including substantial simplification of communication processes and formats, and the introduction of new lean and digital processes.
By implementing these measures, the hospital was able to lift its efficiency considerably. Reducing administrative effort and optimising communication processes cut waiting times by 20% and reduced working hours by 15%. Facility management and the hospital kitchen processes were significantly improved as well, leading to faster and more efficient patient care. Overall, the various approaches doubled value creation in operational patient care. With higher schedule reliability and better quality of care, patient satisfaction rose markedly.
To sum up: a mix of analysis methods reliably identifies inefficient processes and ways of working, providing a basis to define improvement measures. The anonymised approach encourages openness from every stakeholder group during the workload and efficiency analysis, and supports the implementation of the measures. The individual analysis of working patterns lets participants achieve significant improvements often on their own.