Jadon Rosner, chief data engineer of Light-Up Electronics, is considering investing in a new state-of-the-art analytics enterprise system. If the new system achieves the full potential, Light-Up can realize an increase in profits of $250,000. If it falls short, Light-Up could lose $100,000. Being conservative, Rosner estimates a 60% chance that the new process will fail.

Jadon Rosner has an option to make a smaller investment to implement a partial system and then decide whether to invest in the full state-of-the-art analytics enterprise system at a later date. The partial system would cost $15,000 to implement. Rosner predicts a 50-50 chance that the partial system will succeed. d not fail.

If the partial system works, that would be an optimistic sign for the success of the full analytics system -- there would be a 75% chance that (if purchased) the analytics system will be successful and meet the promised potential.

If the partial system fails, there is still a 15% chance that (if purchased) the analytics system will be successful and meet the promised potential.

Rosner needs advice. Should he invest in the new state-of-the-art analytics enterprise system? Should he first invest in the partial system and then depending on outcome make a decision?

Develop a decision tree for this problem and determine the optimal decision strategy. USE THE DRAWING TOOLS IN WORD OR POWERPOINT (OR EXCEL ADD-IN TREEPLAN), CREATE AND SOLVE THE DECISION TREE. SAVE THE FILE AND UPLOAD IT HERE.