Why do heuristic functions only approximate the real value of the cost?
If you create a heuristic that returns the exact cost for each node in the search tree, you can find the optimal solution easily: Start at the initial state and generate all successor states. Take the state with the best heuristic value and repeat, until you find the goal state. Because the estimated cost (from the heuristic) for each node in the search tree is equal to the actual cost, you never make a wrong decision.

Unfortunately for most problems constructing such a heuristic would mean that for each node to evaluate you calculate the solution and then return the cost of the solution. Thus you already solve your problem inside the heuristic function.