ESD.71 Nestor Quispez-Asin - 1 - Real Options for a Computer Wholesaler Distribution Center Expansion Strategy Nestor Quispez-Asin ESD. 71 December 5, 2006ESD.71 Nestor Quispez-Asin - 2 - Table of Contents Abstract..........................................................................................3 System Background……………………………………………...3 System Uncertainties…………………………………………... 4 Basic Data………………………………………………............ 5 Fixed Design………………………………………………….... 6 Flexible Design……………………………………………….... 7 Two-Stage Decision Analysis…………………………………. 7 Lattice Analysis of Uncertainty………………………………... 11 Lattice Valuation of Option……………………………………. 12 Conclusion……………………………………………………... 16ESD.71 Nestor Quispez-Asin - 3 - Abstract In this paper, the expansion of a distribution chain of a computer wholesale company into a specific region of Peru is analyzed using real options analysis. The driving force behind the expansion of distribution centers (DC’s) is that clients in the region will no longer have to assume transportation risks and costs and as a result demand will increase from the region for each DC established. A fixed design of establishing just one large DC is explained. Then it is contrasted with a flexible design that has the one time option each year to add just one other DC that will increase demand in the region by a certain percentage. The option is thus similar to a European call option that seeks to take advantage of potential upsides in uncertainty. The main uncertainty across which the designs are contrasted is demand. First, a two stage decision analysis is carried out where demand uncertainty is modeled with uniform random distributions, and the value of the option is assessed. Second, the demand is modeled by lattice analysis which uses a lognormal binomial distribution for demand, and the value of the option is calculated in this scenario. Results suggest that while real options has clear potential to exploit upsides of uncertainty in this case, the model used to describe the demand uncertainty and the values of the fixed parameters used greatly determine the value of the option. The results of the analysis in the paper reveal new areas and issues for future productive investigation of the system. System Background The system analyzed in this paper entails the distribution chain of a computer wholesale company in Peru in a specific region of the country in its interior, Huancayo. The system to be deployed and analyzed is establishing new distribution centers (DC’s) in that region where none exists, and these new locales would in theory help increase profit from the region and grow the information technology market there as well. As it stands, the region currently gets its distribution from the central warehouse in Lima, and the costs and risks of shipment are incurred by the clients in Huancayo. However, under the system to be analyzed, the company would assume these costs and risks, but would be able to sell at a higher price in the region as well as increase demand there since potential customers would no longer have to assume the previous risks. Also, the DC’s would not carry inventory, but simply be regional outposts where the pre-ordered merchandise could be picked up by the customers when the merchandise is shipped every month. This eliminates complications caused by overstock and computer depreciation. The system analysis presented in this paper contrasts a fixed and flexible strategy of establishing DC’s in the region. The fixed strategy consists of establishing one large DC in the region. Adding to the fixed strategy the option of adding a second, smaller DC that would increase demand by a certain percentage is the option in the flexible strategy.ESD.71 Nestor Quispez-Asin - 4 - It is important to note that the system includes only the segment of the client region in Huancayo and excludes all other regional markets. Also, the merchandise being analyzed will be looked on as computers as predetermined whole units, rather than parts, which would complicate the analysis by fragmentizing it per part and brand. Given the nature of the system, the time frame of the analysis will be over 3 to 5 years, as it would be too uncertain to forecast demand beyond this time frame in a region that is fairly susceptible to national and market issues, as the next section addresses. System Uncertainties In practice, there are various factors that could affect the system. The political situation can deteriorate the market for computers in the Huancayo region, for example. Various climate issues, such as with El Nino, can complicate travel to this region which is relatively hard to access. Peru is very subject to these types of logistical disruptions, and so customers tend to lose faith in the DC approach and often prefer to buy directly from Lima, if at all. However, though important, these issues are very difficult to model and speculate as to their future. Thus, for the purposes of this system model, it is necessary to neglect side issues and concentrate on market forces. Such market forces include the effect of competition causing sales to fall, and then the profitability of having a local DC would be heavily compromised. Another relevant market force although exogenous is the overall economic situation of Peru which would influence buying power of clients and the industry as a whole. All of these market uncertainties are reflected in demand (and therefore sales). It is clear then that the main uncertainty applying to the system is demand, and it is influenced positively and negatively by different factors. One factor that increases demand stems from the general underlying driver in having a DC in the region. The idea is that customers do not have to assume the costs and risks of transporting merchandise themselves. As a result, demand is expected to increase from year to year in the region as clients gain confidence in the established, reliable system. The particular increase in demand can vary within a certain range. However, this projected demand can also be less than a projected value due to market competition, low service