Patent ID: 8515796
Filing Date: 2013-08-20
Classification: G06Q

Abstract:
1. A method comprising: receiving, by a computer processor of a computing system from a plurality of service centers servicing accounts, operational metrics and data values associated with said operational metrics; aggregating, by said computer processor, said data values; removing, by said computer processor, noisy data from said operational metrics, said noisy data consisting of corrupt data, unstructured data, and unreadable data; calculating, by said computer processor, statistical averages associated with a performance of said accounts during a specified time period; modeling, by said computer processor, each account of said accounts as a collection of operational performance variables and key performance indicators (KPI), wherein an account (i)={Op generating, by said computer processor, a ranking list (R) comprising a ranking of said accounts within said operational parameter space (Op) using a pair-wise similarity measure; calculating, by said computer processor, a minimum number of independent operational parameters necessary (D) for representing a group of accounts of said accounts in a reduced operational space {P} of dimension D; representing, by said computer processor, said accounts as points in said reduced operational space {P}; calculating, by said computer processor, pairwise ranks {r} of said group of accounts within said reduced operational space {P}; updating, by said computer processor, x_i->x_i+a*sum_{i,j} (R_ij−r_ij)(x_i−x_j)/|x_i−x_j|, wherein x_i comprises a position of account (i) within said reduced operational space {P}, wherein x_j comprises a position of account (j) within said reduced operational parameters space {P}, and wherein (a) comprises a relaxation parameter; selecting, by said computer processor, values associated with a tolerance limit epsilon; determining, by said computer processor, if sum_{i,j} (R_ij−r_ij)^2 is less than said tolerance limit epsilon then presenting, by said computer processor, updated coordinates within said group of accounts within said reduced operation space {P}, otherwise, if sum_{i,j} (R_ij−r_ij)^2 is greater than said tolerance limit epsilon, repeating said calculating pairwise ranks and said updating until said sum_{i,j} (R_ij−r_ij)^2 is less than said tolerance limit epsilon; plotting, by said computer processor, a trajectory for each account of said group of accounts within said reduced operational space {P}, wherein each said trajectory is associated with a specified time period associated with a specified time resolution, and wherein each said trajectory corresponds to a specific type of customer satisfaction rating; calculating, by said computer processor, aggregates for overall account health of each said account of said group of accounts, wherein said calculating said aggregates is based on annual customer surveys and account manager ratings associated with an overall customer satisfaction corresponding to an account at regular time intervals; and mining, by said computer processor, each said trajectory for scores corresponding to financial health and business health based on benchmarking against project management reports in place of said annual customer surveys.