Context: When in need for a software solution, companies of all sizes prefer buying an existing commercial-off-the-shelf (COTS) product rather than investing the time and effort on developing and maintaining their own. However, purchasing the wrong COTS solution can lead to a painful and company-critical process as well. Problem: Within this context, the absence of a both repeatable as well as pragmatic approach for the selection of a suitable third-party tool remains a common problem at various companies, including Munich Re. Approach: To this end, this work combines and extends established methodologies aiming for an efficient and effective requirements engineering approach. To validate feasibility of the approach, we furthermore report on a case study at Munich Re, in which we exemplarily apply the process in-vivo for selecting a requirements modeling tool suggested to be used across all
development teams of the whole organization. Results: The application at Munich Re indicates the feasibility of the approach for the selection of a medium sized software solution. Impact: We encourage practitioners to extend the presented method and incorporate it into their own decision-making process for third-party tools, with the aim to making buy-decisions more objective and more efficient in the future.

Context: When in need for a software solution, companies of all sizes prefer buying an existing commercial-off-the-shelf (COTS) product rather than investing the time and effort on developing and maintaining their own. However, purchasing the wrong COTS solution can lead to a painful and company-critical process as well. Problem: Within this context, the absence of a both repeatable as well as pragmatic approach for the selection of a suitable third-party tool remains a common problem at various companies, including Munich Re. Approach: To this end, this work combines and extends established methodologies aiming for an efficient and effective requirements engineering approach. To validate feasibility of the approach, we furthermore report on a case study at Munich Re, in which we exemplarily apply the process in-vivo for selecting a requirements modeling tool suggested to be used across all
development teams of the whole organization. Results: The application at Munich Re indicates the feasibility of the approach for the selection of a medium sized software solution. Impact: We encourage practitioners to extend the presented method and incorporate it into their own decision-making process for third-party tools, with the aim to making buy-decisions more objective and more efficient in the future.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.