BUS606: Operations and Supply Chain Management

Whether it concerns a high-level procedural model or a detailed analytical model, for a process modelling initiative to impact beyond a few specialists, the models should be easy to understand and deliver clear benefit. Even if practitioners might in principle derive benefits from models and modelling, in an industry context, there are many pressures competing for time and attention. During product development, modelling and improving processes are often seen as non-critical activities and delivery of the next program often takes priority. Process improvement and its related modelling activities are seen by many design personnel as tasks that can be left for later lifecycle phases, for example for improving production processes when ramping up production. Another issue is that development projects can often seem quite ad-hoc, with much attention devoted to chasing for information and attention, and addressing issues and problems as they emerge. Thus, from a practitioner's perspective, many DDP models can seem idealised and sterile and not relevant to the day-to-day activities of the design engineers who must participate in developing or implementing them. Due to the difficulties of bringing such personnel on board and the limited available time, modellers may often choose the ‘low-hanging fruit' and focus their efforts on support processes such as engineering change management which have a more repeatable nature and often involve administrative instead of technical issues.

Another issue of great importance to practitioners is the availability of tools for modelling. Large companies often prescribe tools and process modelling notations to standardise the information that is generated. The benefits of this approach include facilitating training, understanding, and curation of models - but it also forces modellers to work within a particular tool and notation that may not be suitable for every purpose. The approach that is chosen is often one of the main task precedence representations such as BPMN or EPC which are mainly oriented towards business process modelling and, arguably, are not ideal for the DDP context due to its iteration, novelty, and complexity. Many research approaches that might better address these issues are not implemented in deployable tools at all, and those that are both implemented and available for download or purchase must compete against the offerings of large established software suppliers. Finally, DDP modelling and improvement requires an understanding of engineering issues alongside skills such as workshop facilitation and change management. This is challenging work, but it is often perceived in companies as non-critical, so it may be difficult to attract and retain personnel with the ideal skill set.