The process of transitioning new environmental satellite products and algorithms into operations is a challenging task. Within NOAA's Office of Research and Applications, this transition process is evolving to satisfy the more stringent algorithm requirements for the next generation of satellite users. Taking algorithm research into operations means modifying old processes to suit users' increased need for more accurate, reliable and timely remotely sensed products. At the same time, the entire end-to-end process must support the processing of more complex data, higher data volumes due to increased spatial resolution and improved monitoring latencies, increased satellite coverage, increased spectral bands, and multi-disciplinary products. The products and data also need meta-data about instrument status, shifts in product accuracy, and other information that affect product quality for today's increasingly sophisticated user. These needs are stretching traditional scientific research skills into multi-disciplinary tasks that require an understanding of processes not usually equated with scientific algorithm development and include instrument operation, systems engineering, information technology approaches, data fusion, data assimilation, and related capabilities. These added capabilities require new approaches, and skills, for dealing with this multifaceted problem. Steps for improving algorithm research to operations processes will be identified, discussed and compared to past methods.