Cushion consultancy is a growing privately owned firm which is specialized in business process management. Our business model is based on providing solutions to companies depending heavily on laboratory practice and related manufacturing operations.
Cushion consultancy is a growing privately owned firm which is specialized in business process management. Our business model is based on providing solutions to companies depending heavily on laboratory practice and related manufacturing operations. Across industries many of those have been facing challenges in data management, system replacement, content management and enterprise integration. We help companies transforming their business and enhancing performance. Cushion consultancy is very familiar with the domains of Laboratory Work, Information Systems, and Business Control. We are also extensively experienced in transferring knowledge across functional disciplines. Our qualities fit well with current trends to replacing lab information systems and transforming laboratories holistically. Lab practices are increasingly becoming integrated into end-to-end business practices. Organizational silo’s need to collaborate more than ever before. Also, competition becomes increasingly time based. At the same time scientists seek more time for conducting research and wish for learning efficiently. In line with these challenges, most of our current projects are related to consolidating and simplifying lab processes and making them more agile and adaptive. From a holistic point of view.
Cushion consultancy offers clients an end-to-end process management services. Consultancy, interim management and training sessions in the following areas:
- Mapping, simplification, integration and standardization of laboratory work processes.
- Processes Alignment to governance, reporting and quality regulations.
- IT systems replacement.
- Transition from paper to automated work practice.
- Improvement of internal controls within laboratories.
- Enhancement of research documentation and learning from past research.
- Improvement of product cycle times.
- Risk management.
- Cross functional collaboration amongst scientist and professionals.
- Learning from other industries.
- Business case development.