This post returns back to the discussion on data warehouse starting with the cost justification and return on investment for a data warehouse. We look at the macro level for cost justification before we compare the micro level. The first refers to a discussion at a high level such as what were the increase in profits or stock price. However macro level is affected by many factors and not just by improvements in warehouse. So specific association may have to be determined.
For the micro level cost justification, each data pull from operational systems and integration is compared against the ease of use from a data warehouse. Information from the legacy environment is hard to obtain where data may not be proper, undocumented APIs may be involved, guesses have to be made, and the process in general is very convoluted. Even when it isn't, there's still integration involved.  Further, the data may not all be available at the same time.  A staging area may also be required. and finally, a report might be published.
The difference in the cost of information with or without a data warehouse is the basis for its cost justification.
When we look at the steps involved in building a warehouse, they are similar to what's been just described above, with the difference that there are far less redundancies and more efficiency. Hence the cost of building a warehouse should be lesser than the same opeartions without it. Further this cost of building a warehouse is one time but the operations may need to be performed every now and then in its absence.
There is also very little time required for getting information from the data warehouse. This savings in time also translate to savings in cost.
Also the speed of information is also appreciated for decision support. Sometimes this is critical for new business. There is a time up to which the information may be very valuable and a point of time after it which it may even be worthless. This is called the time value of information and is also helpful in recognizing the significance of the warehouse albeit difficult to quantify.
Integrated information is best available from the warehouse.  For example, customer centric data may be very helpful in exploring new opportunities.
The historical data is also a real value. It becomes another dimension in the usefulness of a data warehouse.
Thus we see that a better way to proceed with a cost-justification is at a micro level
The data warehouse doesn't provide real time information but something near that can be provided by an operational data store. The data flows between the ODS and the warehouse in a bidirectional manner. Profile records are often created and placed in the ODS.