IT Capital BudgettingIndiana University of PennsylvaniaDr. James RodgerFall 2010 Ankur DhakalJustin JosephSeok Joo Kim Introduction What is the smart data? (Ankur) What is the Capital budgeting? (Justin) What is the difference between IT and traditional capital budgeting? (Kim) Can you tell us something about Situational Model? (Ankur) Would you explain about the overall structure and results of experiments? (Kim) Tell us something more precisely about 4 methods?(Ankur) Would you tell me about the Simulation results of 4 Methods?(Justin) Do you think there is any potential improvements and extensions of thisresearch?(Kim) Do you think there is any potential improvements and extensions of thisresearch?(Ankur) Tell the audience something about our conclusion?(Justin) What is the smart data?(Kim ask)Ankur answerSmart data is the comprehensive concept to use data smartly to manage the organization more efficientlyIn relation to the MIS, the use of smart data concept can bea great tool for solving the organization problem becausemaking data smart enables the organization to have certainsuperior characteristicsBy smart data, the data are interoperable and readilyexchangeable among qualified members of an enterpriseAnd it also contributes to optimizing enterprise performanceby providing a strategy that will vastly improve enterprisedata resource managementSo, we will use this smart data concept to select theeffective methods to solve the ITCB problem What is the Capital budgeting ?(Ankur ask)Justin answerThe capital budgeting problem is the problem of selecting a set of capital expenditures thatsatisfy certain financial and resourceconstraintsAnd, the type of capital budgeting problemconsidered in our research is sometimescalled a hard capital rationing problemBecause a decision-maker has to select thebest project mix among several competingprojects under the budget constraint such as What is the difference between IT and traditionalcapital budgeting?(Justin ask)Kim answerCapital budgeting in IT is slightly different from the traditional capital budgeting problemBecause a certain investments are mandatory, theinvestments size is large and only certain investmentscan be depreciatedAbout the depreciation issue, IRS provides amaximum upper limit on the IT depreciation expensedeductionSo, in this study, we will consider these constraintsabout finding the optimal solution of the ITCB problem Can you tell us something about SituationalModel? (Kim ask)Ankur answerThis method used e-based antilogarithm transformation of revenue and IT budgeting variable to compute theactual values of revenue and IT budget for analysisA general ITCB problem can be mathematicallyrepresented as the binary variable knapsackoptimization problemwhere objective function is a non-linear function thatmaximizes certain managerial criterion such as after-taxprofit of a set of IT investments Would you explain about the overall structureand results of experiments? (Justin ask)Kim answerUsing several simulations, this research empirically compared the performance of two SA heuristicprocedures with the performance of two well-knowntraditional ranking methods for capital budgetingFor the purpose of benchmarking, this researchused two simple ranking methods that can be usedto solve the ITCB problemAccording to the experiment result, the heuristicapproaches was best suited for solving the ITCBproblem Tell us something more precisely about 4methods?(Kim ask)Ankur answer4 Different approches were used A Rank D Rank FRSA (Feasibility Restoring Stimulate Annealing) SSA (Simple Stimulate Annealing) CONTINUED Projects ranked in the acending order of theirinvestment value ,before their selection usingthe budget constrai, then the ranking is calledA-RANK.Projects ranked in the decending order oftheir investment value ,before their selectionusing the budget constrai, then the ranking iscalled D-RANK. CONTINUEDAnd, we developed two simulated annealing (SA) procedures for solving the ITCB problemOur first SA procedure(FRSA) utilizes a feasibilityrestoration component. The feasibility restoration alwaysmaintains a feasible solutionIn our second procedure(SSA), we eliminate the“feasibility restoration” step from the first SA procedure.In the event when a solution is not feasible, failure occursin our second SA procedure and annealing schedule isomittedThis simulated annealing can deal with arbitrary systemsand cost functions and statistically guarantees finding anoptimal solution. This method is relatively easy to code,even for complex problems Would you tell me about the Simulation results of 4Methods?(Ankur ask)Justin answerAbout the After-Tax Profit, FRSA, SSA outperformed A-Rank, D-Rank in the maximization of after-taxprofit. But, difference of profits was not significantbetween A-Rank and D-Rank because of t he existence of common projects And, the difference of profits was not significant between FRSA and SSA. It resulted from the weak effects of “feasibility restoration” continuedAbout the Number of Projects selected, Ranking methods selected more projects than2 SA methods. It was caused by the Rankingmethods are biased toward smaller or largerprojects. But, SA methods have preference forthe projects which increase the after-tax profitAnd, about the pairwise differences in meanscomparison, we couldn’t find no significantdifference in FRSA and SSA, but, found thesignificant difference in A-Rank and D-Rank Would you make the summary of simmulationresults then?(Justin ask)Kim answerConclusively, Two Smart Data SA heuristic methods(FRSA, SSA) outperformed traditionalmethods(A,D-rank) Given that 0-1 knapsack optimization problem is NPhard, Simulation model for 500 companies provedthese factsAnd, we can argue that this research contribute theoptimization of IT capital budgeting Because the use of corporate taxation anddepreciation for selecting the profitable IT investmentscan improve the organizational profitability Do you think there is any potential improvementsand extensions of this research?(Kim ask)Ankur answerFirst, The objective function can be changed into the maximization of NPV if the management don’twant the tax-induced interactionSecond, other heuristic methods such as GeneticAlgorithm and Tabu Search can be used becausesingle investment budgeting period is not realisticAnd, finally, for more practical application, futureresearch is needed for solving the multi-periodITCB problem Tell the audience something about our conclusion?(Ankur ask)Justin answerThis case showed that how Smart Data approach could improve the efficiency andeffectiveness of capital budgeting in ITindustryThe utilization of smart data AI methods suchas SSA and FRSA could outperform thetraditional capital budgeting methods such asA-Rank and D-Rank methodsConclusively, the organization can select theIT projects which lead to the highest after-taxprofits and optimizing enterprise performance,by applying the Smart Data approach
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