Real world input volumes possible?

I manage a financial data processing team - inputting financial statement data into a platform, operating with a mix of offshore and onshore resource. I've modeled the process fairly well in Bizagi, and simulations work as expected. However, I really need more real world accuracy on the 'input' triggers (ie for new statements appearing at the front of the process). I have very accurate data of our daily volume over the course of a year - and because filing follows peaks/troughs I can't use the standard distributions. Is there anyway I can import and excel or similar set of data to use as the inputs rather than the standard distributions?

Comments (2)


Dear Chris,

Regarding your question, no, it is not possible to import such as information. You can play with a feature called What if analysis:

What if analysis is a powerful tool for improvement that evaluates how strategic, tactical or operational changes may impact the business . Through different scenarios you will be able to perform a true-to-life analysis of your processes without putting your business operation at risk.

Bizagi allows you to easily carry out what-if analysis on your processes to evaluate, understand and predict the effects of your decisions over given performance measures. You will be able to perform What if analysis in any of the simulation levels.

You will be able to answer questions like:

•How would the processing time of a case decrease if the number of available resources is doubled?

•What would be the cost/benefit rate of reducing the process time in a specified activity?

•What would be the effect of altering the working shift configuration in the operational cost and service level?

The reports generated in What if analysis will display the results of all scenarios to be easily compared.

An example of it is:



Thanks for the reply. This is a huge gap in functionality that you seriously need to address. The scenario functions (such as What-If) is not what I need here. Input trigger variation are key to many process flows, and the assumption that these are consistent, or follow a simple distribution, over time is naive.

I'd urge you to revisit this as you develop the tool. The UI is good (though I'd also like more than one trigger entry point into the flow), and output is usable. But for now I need to use CaseWise - which has a really nasty UI - simply because it allows me to build a much more true representation of input volumes over a period.