The plan allows future users to know what will happen and when they should expect certain changes, which avoids unnecessary uncertainties and therefore creates a better working atmosphere.
The plan also makes clear when the real adoption takes place and gives the future users the opportunity to get ready for this change.
[1] If the data is not valid, the management need to determine the changes again and the organisation will have to prepare a different way of executing the Big bang adoption.
The model above shows what activities need to be executed (in the grey box) by the system controller, to get the outcomes that lead to the released parts.
Poor training can have bad outcomes for an organization, as the FoxMeyer case illustrates (Scott, Vessey, 2000).
This company used the big bang method to implement an enterprise resource planning (ERP) system.
Regatta (Koop, Rooimans and de Theye, 2003) is for example a method which is developed to implements systems.
The organization might not be ready yet for this, an incorrect dataset might be used, or the information system can get stuck, because of a lack of experience and start up problems.
Also an incapable fall-back method can be a risk in implementing a system using the Big Bang (Koop, Rooimans and de Theye, 2003).
The 1986 the London Stock Exchange closed on Friday night and the computers were all switched on the following Monday morning.
The company was prepared for the adoption and first conducted three pilot implementations, before using the new system across the global organization.
(Scott, Vessy, 2000) Dow Corning monitored the progress constantly and made decisions to make sure that the deadlines would be met.
They instead tried to minimize problems by ignoring them, and gave discouraging criticism, which resulted in ambiguous feedback.
So bad communication and ambiguous feedback are also risks when adopting a system with the big bang (Scott, Vessey, 2000).