Customer satisfaction is the ultimate goal of the supply chain.  At the same time, business success relies on the income made from offering service. With increasing competition, complexity, higher variety and advancing technology; supply chain management SCM is becoming challenging. Many tools have been commercialised to assist in the analysis, design, management, and evaluation of supply chains (SC). Simulation software is one of common manager's aids that facilitates the modelling and calculation of more complicated situations. Firstly, demand have been defined based on the literature to develop an appropriate concept. Complex elements of external and internal variables affect the SC performance especially at service level. The purpose of this research is to analyse different aspects of demand then to develop a demand agent that is able to simulate a wide range of real life demand cases within the context of supply. It has been utilized as a development and modelling environment for several reasons. In addition to its 3D GUI, it offers powerful development and customizations by its features. Moreover, it can be a promising tool if combined with the numerical based applications in order to transform supply chain performance to a next level by adopting the white-box examining method and value streaming. Agent based demand have been developed using the provided C++ programming facilities of the chosen simulation software application.  Virtually, demand object can be used as a powerful option in SC or production network simulation as well. In addition, it can be used in both pull and push production strategies instead of just a “sink" within the environment. An experiment has been carried out to examine the effect of different distribution patterns. Four pattern have been tested for both supply and demand: uniform, normal, triangular, and exponential. A supply object is used to represent the product end line. It has been observed that proposed demand object behaved according to the design input. Result shows that distribution type at the same frequency have different effect on service level.  It also suggests that waiting variable can significantly affect the service level.