Over the years I have worked with and for a great number of large engineering and design companies operating globally. The secret towards successfully managing these companies evolves largely about strategies to accurately manage knowledge. As my colleague and good friend Amy Javernick-Will wrote, this knowledge can be categorized along two main lines: local market knowledge and global technical engineering knowledge (Javernick-Will and Scott 2010). I feel that most large design and engineering organizations have a good handle on managing the local knowledge by creating decentralized organizational structures and by having an extensive merger and acquisition strategy. However, I also feel that most of the companies I worked for still struggle to a certain extent with managing their global technical expertise. Maybe these struggles are most visible in the efforts to establish central knowledge management systems and trying to convince the majority of the workforce to use this systems to post knowledge, best practice studies, and establish global discussion networks around central technical topics of importance.
The main problem with these traditional platforms is that it requires extra efforts of employees to post, maintain entries, and to discuss. In a business that is still mainly oriented on billing hours to clients this is a difficult problem, as most employees are mainly concerned with selling their valuable work hours. This of course in particular holds for the experienced and knowledgeable people that hardly ever find time to support knowledge management tasks. At the same time, however, the large design and engineering organizations sit on a large gold mine of information that could be leveraged for establishing central knowledge management systems: Reports, Project Reviews, Internal Memos, and all type of other textual data. In recent years many studies have also shown the feasibility of automatically text mining these documents to establish automated knowledge categories, dedicated search engines, and knowledge networks that link important concepts. One of my most notable colleagues in this area is for example Nora El-Gohary that has shown the potential in a myriad of different studies. In some of our recent work we also have shown the potential for renovation projects. Commercially some early start-ups are also trying to leverage this idea, such as, for example the Berlin based Architrave. However, I believe that the true potential to leverage the power of automated text mining lies with the large design and engineering companies. The methods and algorithms exist, however, the key to successful implementations lies with the availability of large textual databases that only exist at these multi-national large scale corporations.
Design optimization tools become readily available and easy to use (see for example Karamba or Dynamo. It is not surprising that studies exploring these tools are exploding. Many examples exist that illustrate how to design optimization models and execute optimizations. Often, however, these studies fail to provide the true impact that was expected in terms of improving the (simulated) performance of the engineering design. Showing that the deflection of a structure could be reduce by a centimeter or the material utilization used for the structure was reduced by some percent remains of course an academic exercise that can provide little evidence on the engineering impact of optimization technologies.
As we move forward in this field of research, we need to develop more studies that move away from simply showing the feasibility to apply relatively mature optimization methods towards formalizing optimization problems that matter. Finding such problems is not easy as we cannot truly estimate the outcomes of mathematical optimizations upfront. Whether a specific impact can be achieved can only be determined through experimentation – a long, labor extensive and hard process.
Even worse, identifying relevant optimization problems through a discussion with experts is difficult. The outcomes of each design optimization needs to be compared with the solution an expert designer would have developed using his intuition and a traditional design process. Hence, working with expert designers to identify problems might be tricky. After all they are experts and probably already can come up with pretty good solutions. It seems as one would rather need to identify problems that are less well understood, but still relevant. These problems might also be scarce as relevant problems are of course much more widely researched.
In the end, I think we need to set us up towards a humble and slow approach. An approach that is time consuming, that will require large scale cooperation, and needs to face many set-back in terms of providing an impact that truly matters. Maybe this is also the reason why a disruption of design practice is not yet visible. Until we will be able to truly understand how we can impact design practice with optimization we will still need to rely on human creativity and expertise for some time to come. (not saying that we should stop our efforts.
I was just working on an initial business plan for a consultancy business for Architects to support and manage renovation planning and execution. The consultancy service is targeted towards local districts and assumes that the service providers are able to build a strong network with the local property owners in this district. I envisioned a number of services that could be provided that follow the 4M process we designed during our P2Endure project:
- providing a service for an initial evaluation for the feasibility of a renovation (Mapping)
- supporting the detailed planning of the renovation with energy simulation, engineering the renovation, and managing the supply chain for executing the renovation work (Modeling and Making)
- setting up continuous monitoring to be able to assess renovation possibilities on a continuous basis throughout the life-cycle of a building (Monitoring)
I conducted an initial financial assessment for a district of roughly 100 privately owned properties and roughly 20% of owners who are interested in upgrading the properties. The assessment resulted in a sound business for an office with two partners. Such businesses could significantly improved the renovation rate of the building stock in Europe and, in turn, make a large contribution to the reduction of CO2. All in all a true green deal business deal. We will discuss this business mode now internally within the P2Endure project, but once the model is formally published I will provide an update. Stay tuned!
In the last years I was working with a lot of organizations, trying to explore how to better integrate advanced building performance simulation into the design and engineering processes for buildings. The struggle often is to figure out in what detail simulations are helpful during different stages of design. I have been working with companies that targeted very early decision making to support real estate developers all the way to companies that provide sophisticated consultancy in very detailed design phases. For me results are not conclusive and I really would like to do much more detailed and structured research. The farthest we are coming with our insights is in the area of supporting the renovation of buildings in two large EU funded research projects (P2Endure and BIM-Speed). Here we suggest that detailed building performance models of the existing buildings need to serve as a first step in the design process. These behavioral digital twin can then form a baseline to explore different building renovation options. A key within these efforts is to generate a baseline of the building behavior that normalized factors that are out of the control of the design, such as, weather or occupancy behavior, that cannot be statistically modeled to allow for fair comparision. From the technology development aspect at our firm Contecht we probably came furthest in setting up parametric modeling tools that allow for early simulations and host these tools through dedicated APIs that we developed in web-based design tools.
Upgrading the European building stock is still painstaking slow. Only around 2% of the buildings are renovated yearly, while a large part of the building stock still originates from the 60s. So why is up-scaling so hard, when we have also very positive cases, such as for example, the Berlin housing corporations who renovated large parts of their building stock already a decade ago? In our EU funded research project P2Endure we found that one inherent problem is that renovation approaches are very dependent on the local typology of buildings and the social fabric of their inhabitants. Therefore, renovation approaches cannot be scaled on a large scale. The alternative are local entrepreneurs, architects and engineers that are willing to develop businesses around developing renovation solutions for specific districts, the type of buildings in this district, and can get in close contact with the locals.
More information about the P2Endure project.
Report: Technical and alliance plan for temporary local renovation factory at a district level