Data and process modeling is based on the current data and process, which is based on the facts type of modeling whereas object-oriented modeling is based more on the objectives that one wants to achieve, thus it’s more of a predictive type of modeling.
In my opinion, data and process modeling is better because it focuses on the current process, thus allowing more improvements to be made. According to Harvard’s Business Review’s framework of ‘Commoditization of Processes’, there are 5 steps to going thru the process modeling. The first one is the initial level whereby the management tries to stabilize the environment and new ideas are tried. Next is the repeatable stage whereby it’s to develops familiarization with the process. After that, it is followed by the defined stage and the management stage. This basically highlights controlling of the variations which could be caused by the attributes or constraints of the process. Finally, at the last stage, the process reaches a state where it continuously goes thru improvement.
Thus, a better system is created as mentioned above, when evaluation of the attributes and constraints of the process allows improvement to happen on a more regular basis. Thus, the management would have to balance which is more than the other, either the attributes or the constraints faced. This allows management to implement change in a business as the above modeling process allows flexibility and saves time and money for a business. Apart from that, some management also allows feedback from their customers or employees who allow them to see things from more perspectives, thus also creating flexibility not only in the process but also in the management.