Business Intelligence and Simulation Modeling
Author: Descreye Solutions
What is the relationship between business intelligence (BI) and discrete-event simulation modeling (DES)?
Business intelligence and discrete-event simulation are partners in providing insights into complex business processes and systems. It would probably be correct to say that DES is a subset of BI, but in practice that is rarely the case, at least organizationally. In some cases, simulation is used to forecast future performance using data that is gathered in a BI data warehouse. In that case it is the consumer of the BI data, and can provide additional insight that is difficult to obtain without knowing the limitations and dependencies of the system that are part of the simulation model. In other cases, the discrete event simulation is the provider of data that allows the BI algorithms to optimize business processes to result in better financial performance for the organization. In either case, it is sometimes valuable to create interfaces between business intelligence teams and simulation teams in an organization in order to get more valuable results.
How can business intelligence (BI) and discrete event simulation (DES) inform each other?
Often organizations have artificially siloed discrete-event simulation into manufacturing roles and business intelligence under an IT, supply chain or finance organization. This organization structure often makes it difficult for these teams to easily create interfaces that would be mutually beneficial, but the following things can help to develop those interfaces.
Training simulation modelers in business intelligence and methods of data management, gathering, and analysis can be useful in giving modelers access to data that is often already being captured within the organization. Business intelligence teams are often capable of quickly finding their way around data sets that are often not easily accessible or searchable, so sharing those techniques with simulation modelers is often beneficial. It would also be beneficial for data scientists to be trained in simulation modeling. Without a knowledge of how data will be used to make operational decisions, a business intelligence professional will waste both their time and many others time in gathering and managing less worthwhile data. In most organizations the simulation modelers in the operations space are frontline business intelligence professionals that take data and convert it into tools that can be used to make operation decisions in the various facilities in which they work. Performing cross-training between these sets of professionals would create understanding and skills that would be mutually beneficial to both groups.
Don't Equate BI with IT
Many organizations see similar skill sets in IT professionals and BI professionals and so they organizationally equate the two. While both can write and SQL query and, hopefully, know some amount of programming that is likely where the similarities should end. Business intelligence professionals should not just understand data systems. For them to be truly effective they must understand the business from a process point of view not an IT system point of view. IT systems in an organization are not BI systems, and if they are viewed that way, then the synergies between BI and DES will be very limited. However, there can be insight and worthwhile forecasts when business intelligence can take data gathered in IT systems and process it in a way that simulations can use to forecast and optimize. If DES has to go straight to IT systems for data there is an inherent data post-processing delay that makes any simulation less worthwhile, as simulations are almost always very time-sensitive.
For more information on BI and DES, google it... There are a lot interesting research papers and blog posts about how these can be used together for advanced understanding of complex systems.
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