Does data analysis reduce business risk?
In the world of design, and more generally, in the construction sector, these two statements can always be considered true:
- If a project is perfectly completed, it delivers a profit ranging between 0 and 20 %;
- If a project goes wrong, losses can potentially be very high;
So perhaps we should spend more time reading and understanding data, to better identify risk factors and improvement opportunities regarding profit margins.
We must abandon the idea that BIM is only just a better way of producing tables and drawings, with a pinch of data related to objects, clash detection and the possibility of delivering 4D, 5D, 6D or 7D projects.
The next goal to hit, and the real advantage offered by adopting this data-driven method when completing a project, will be minimizing as much as possible all risk factors. This is made possible through data mining and analysis applied on data generated by models, operations, resources and tools. All this data, if well interpreted, can lead to great margin and profit opportunities.
For several years now, here at La SIA, we have been working on “BIM oriented” projects and orders, that are evolving on digital management and coordination processes. For this reason, we produce and analyse on a daily basis a considerable amount of data, thanks the high number of resources employed and located in 9 different corporate office locations.
Interpreting data to improve decision-making phases
If we could find a way to effectively link all data related to all the models we produce, in a single macro-database, instead of querying files individually and separately, maybe we could start noticing interesting patterns.
In fact, by querying this macro-database, we could be able to predict how much a project is going to cost and what tools and resources will be necessary to complete it.
Today, this analysis is performed by professionals on the basis of their past experience. However, it is evident that performing this type of analysis with a data-driven approach can deliver conclusions that are much more objective and measurable. Therefore, by combining experience on one hand and substantial data mining on the other, undoubtedly allows us to improve quality of the choices we are called to make during the development of every project.
The implementation test
In the last few years, in La SIA, we started experimenting this data-driven approach allowing us to generate results that are increasibly precise and reliable. One of our most important projects, in terms of duration and resources employed, is the digitization of the entire infrastructure of one of the most important telecommunications companies.
Since the initial development phases of this job, we started collecting a lot of data, like for example start and completion dates of models, resources employed, tools used and tool use frequency as well as other data.
Subsequently we began to analyze this data, trying to identify the patterns mentioned above. Over the weeks, the quantity of data mined has grown considerably and has led us to an improved understanding of operations, to the addition of an extra check-point for model validation and control and to improved management and planning of future activities.
These first results, in addition to improving our team’s workflow, have brought many advantages to our client that can now plan any activity on the basis of reliable and verified data.