1. A method for migrating a world wide name from a first host bus adaptor to a second host bus adaptor comprising:
said first host bus adaptor receiving IO operations from a host computer by a SCSI command and transferring the command to a storage controller coupled to a storage device, said first host bus adaptor associated with said world wide name and a MAC address;
relocating said world wide name from said first host bus adaptor to said second host bus adaptor;
determining whether or not said MAC address associated with said first host bus adaptor can be relocated to said second host bus adaptor in response to said relocating of said world wide name;
relocating said MAC address from said first host bus adaptor to said second host bus adaptor if said determining is positive; and
said second host bus adaptor receiving IO operations from a host computer by a SCSI command and transferring the command to a storage controller coupled to a storage device, after said second host bus adaptor is associated with said world wide name and said MAC address.
2. The method according to claim 1,
wherein said determining is performed by whether said MAC address is shared by other services.
3. The method according to claim 1,
wherein said determining is performed by referring to a table including an information of whether the MAC address is included in a consistency group.
4. The method according to claim 1, further comprising:
establishing MAC layer connection after said relocating said MAC address from said first host bus adaptor to said second host bus adaptor;
wherein said determining is performed by whether said MAC address is shared by other services.
5. The method according to claim 4, wherein said storage devices are Hard Disk Drives and said storage controller configures said storage devices in a RAID array.
6. The method according to claim 2, wherein said world wide name and said MAC address are both unique identifiers.
7. The method according to claim 6, wherein said first and second host bus adaptor handles network operations performed under Fibre Channel protocol and Ethernet protocol, and said relocating of said world wide name is performed by NPIV technology.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computerized method for customer relationship capacity planning by a financial services entity, the method comprising:
receiving, by a computing device, (i) financial plan attribute data associated with a financial plan of each of a plurality of potential customers and a plurality of newly-acquired customers, wherein the financial plan attribute data relates to scope of assets and feature set of the financial plan, and (ii) personality characteristic data associated with the customer, wherein the personality characteristic data relates to a level of interaction requested by the customer and a structure of the customer’s employees;
aggregating, by the computing device, the financial plan attribute data for the plurality of potential customers and the plurality of newly-acquired customers into a binned memory structure comprising a plurality of bin storage locations, wherein the plurality of potential customers and the plurality of newly-acquired customers are grouped by at least a financial plan asset value before being allocated to a bin storage location and wherein each bin storage location contains data for customers with similar financial plan asset values;
assigning, by the computing device, an average number of hours spent in a previous time period to service existing customers having similar financial plan attribute data to the financial plan attribute data for the customers in the binned memory structure;
determining, by the computing device, a relationship complexity score associated with each of the potential customers and the plurality of newly-acquired customers based upon the financial plan attribute data, the personality characteristic data for each customer, and the average number of hours assigned to the customer’s bin storage location;
determining, by the computing device, a current workload value for a customer service manager of the financial services entity based upon the relationship complexity scores for each of a plurality of existing customers already allocated to the customer service manager, the current workload value representing a level of effort from the customer service manager to provide service to the plurality of existing customers already allocated to the customer service manager;
determining, by the computing device, a target workload value for the customer service manager based upon relationship complexity scores for each of the existing customers of the financial services entity and a past number of relationship service hours spent in a previous time period to service each of the existing customers;
allocating, by the computing device, a portion of the potential customers and the newly-acquired customers to the customer service manager based upon the current workload value and the target workload value for the customer service manager, including
determining, by the computing device, a customer satisfaction value for each existing customer already assigned to the customer service manager,
aggregating, by the computing device, the customer satisfaction value for each existing customer into a customer satisfaction score for the customer service manager,
displaying, by the computing device, a graph of a comparison between current workload values for a plurality of customer service managers and customer satisfaction scores for the plurality of customer service managers including placing one or more visual indicators on the graph to isolate data points corresponding to one or more customer service managers that have a customer satisfaction score greater than a predetermined threshold and a current workload value that is less than or equal to the target workload value, and
allocating, by the computing device, the portion of the potential customers and the newly-acquired customers to the customer service manager if the data point corresponding to the customer service manager is within one of the visual indicators on the graph; and
updating, by the computing device, an allocation table that contains information relating to the allocation of customers to customer service managers.
2. The method of claim 1, wherein the step of determining a relationship complexity score further comprises assigning, by the computing device, the customer to a cluster based upon the financial plan attribute data including the scope of assets and the feature set of the financial plan.
3. The method of claim 2, further comprising analyzing, by the computing device, the financial plan attribute data associated with each of the customers in the cluster to identify similarities among the customers.
4. The method of claim 1, wherein the step of determining a relationship complexity score further comprises assigning, by the computing device, a weight value to each of the financial plan attribute data and the personality characteristic data.
5. The method of claim 1, wherein the past number of relationship service hours is associated with a predetermined service period.
6-7. (canceled)
8. The method of claim 1, further comprising:
determining, by the computing device, a tolerance associated with the target workload value; and
allocating, by the computing device, the portion of the potential customers and the newly-acquired customers to the customer service manager if (i) the relationship complexity scores for the portion of the potential customers and the newly-acquired customers are greater than the difference between the current workload value for the customer service manager and the target workload value for the customer service manager and (ii) the difference between the current workload value for the customer service manager and the target workload value for the customer service manager is less than or equal to the tolerance.
9. (canceled)
10. The method of claim 1, further comprising determining, by the computing device, a manager performance metric based upon the customer satisfaction score for the customer service manager, the target workload value for the customer service manager, and the current workload value for the customer service manager.
11. The method of claim 1, wherein the personality characteristic data is based upon survey responses from the customer.
12. A system for customer relationship capacity planning by a financial services entity, the system comprising a computing device configured to:
receive (i) financial plan attributes associated with a financial plan of each of a plurality of potential customers and a plurality of newly-acquired customers, wherein the financial plan attributes relate to scope of assets and feature set of the financial plan, and (ii) personality characteristics associated with the customer, wherein the personality characteristics relate to a level of interaction requested by the customer and a structure of the customer’s employees;
aggregate the financial plan attribute data for the plurality of potential customers and the plurality of newly-acquired customers into a binned memory structure comprising a plurality of bin storage locations, wherein the plurality of potential customers and the plurality of newly-acquired customers are grouped by at least a financial plan asset value before being allocated to a bin storage location and wherein each bin storage location contains data for customers with similar financial plan asset values;
assign an average number of hours spent in a previous time period to service existing customers having similar financial plan attribute data to the financial plan attribute data for the customers in the binned memory structure;
determine a relationship complexity score associated with each of the potential customers and the plurality of newly-acquired customers based upon the financial plan attribute data, the personality characteristic data for each customer, and the average number of hours assigned to the customer’s bin storage location;
determine a current workload value for a customer service manager of the financial services entity based upon the relationship complexity scores for each of a plurality of existing customers already allocated to the customer service manager, the current workload value representing a level of effort from the customer service manager to provide service to the plurality of existing customers already allocated to the customer service manager;
determine a target workload value for the customer service manager based upon relationship complexity scores for each of the existing customers of the financial services entity and a past number of relationship service hours spent in a previous time period to service each of the existing customers;
allocate a portion of the potential customers and the newly-acquired customers to the customer service manager based upon the current workload value and the target workload value for the customer service manager, including
determining a customer satisfaction value for each existing customer already assigned to the customer service manager,
aggregating the customer satisfaction value for each existing customer into a customer satisfaction score for the customer service manager,
displaying a graph of a comparison between current workload values for a plurality of customer service managers and customer satisfaction scores for the plurality of customer service managers including placing one or more visual indicators on the graph to isolate data points corresponding to one or more customer service managers that have a customer satisfaction score greater than a predetermined threshold and a current workload value that is less than or equal to the target workload value, and
allocating the portion of the potential customers and the newly-acquired customers to the customer service manager if the data point corresponding to the customer service manager is within one of the visual indicators on the graph; and
update an allocation table that contains information relating to the allocation of customers to customer service managers.
13. The system of claim 12, wherein the step of determining a relationship complexity score further comprises assigning the customer to a cluster based upon the financial plan attribute data including the scope of assets and the feature set of the financial plan.
14. The system of claim 13, further comprising analyzing the financial plan attribute data associated with each of the customers in the cluster to identify similarities among the customers.
15. The system of claim 12, wherein the step of determining a relationship complexity score further comprises assigning a weight value to each of the financial plan attribute data and the personality characteristic data.
16. The system of claim 12, wherein the past number of relationship service hours is associated with a predetermined service period.
17-18. (canceled)
19. The system of claim 12, further comprising:
determining a tolerance associated with the target workload value; and
allocating the portion of the potential customers and the newly-acquired customers to the customer service manager if (i) the relationship complexity scores for the portion of the potential customers and the newly-acquired customers are greater than the difference between the current workload value for the customer service manager and the target workload value for the customer service manager and (ii) the difference between the current workload value for the customer service manager and the target workload value for the customer service manager is less than or equal to the tolerance.
20. (canceled)
21. The system of claim 12, further comprising determining a manager performance metric based upon the customer satisfaction score for the customer service manager, the target workload value for the customer service manager, and the current workload value for the customer service manager.
22. The system of claim 12, wherein the personality characteristic data is based upon survey responses from the customer.
23. A computer program product, tangibly embodied in a non-transitory computer readable storage medium, for customer relationship capacity planning by a financial services entity, the computer program product including instructions that, when executed by a processor of a computing device, cause the computing device to:
receive (i) financial plan attributes associated with a financial plan of each of a plurality of potential customers and a plurality of newly-acquired customers, wherein the financial plan attributes relate to scope of assets and feature set of the financial plan, and (ii) personality characteristics associated with the customer, wherein the personality characteristics relate to a level of interaction requested by the customer and a structure of the customer’s employees;
aggregate the financial plan attribute data for the plurality of potential customers and the plurality of newly-acquired customers into a binned memory structure comprising a plurality of bin storage locations, wherein the plurality of potential customers and the plurality of newly-acquired customers are grouped by at least a financial plan asset value before being allocated to a bin storage location and wherein each bin storage location contains data for customers with similar financial plan asset values;
assign an average number of hours spent in a previous time period to service existing customers having similar financial plan attribute data to the financial plan attribute data for the customers in the binned memory structure;
determine a relationship complexity score associated with each of the potential customers and the plurality of newly-acquired customers based upon the financial plan attribute data, the personality characteristic data for each customer, and the average number of hours assigned to the customer’s bin storage location;
determine a current workload value for a customer service manager of the financial services entity based upon the relationship complexity scores for each of a plurality of existing customers already allocated to the customer service manager, the current workload value representing a level of effort from the customer service manager to provide service to the plurality of existing customers already allocated to the customer service manager;
determine a target workload value for the customer service manager based upon relationship complexity scores for each of the existing customers of the financial services entity and a past number of relationship service hours spent in a previous time period to service each of the existing customers;
allocate a portion of the potential customers and the newly-acquired customers to the customer service manager based upon the current workload value and the target workload value for the customer service manager, including
determining a customer satisfaction value for each existing customer already assigned to the customer service manager,
aggregating the customer satisfaction value for each existing customer into a customer satisfaction score for the customer service manager,
displaying a graph of a comparison between current workload values for a plurality of customer service managers and customer satisfaction scores for the plurality of customer service managers including placing one or more visual indicators on the graph to isolate data points corresponding to one or more customer service managers that have a customer satisfaction score greater than a predetermined threshold and a current workload value that is less than or equal to the target workload value, and
allocating the portion of the potential customers and the newly-acquired customers to the customer service manager if the data point corresponding to the customer service manager is within one of the visual indicators on the graph; and
update an allocation table that contains information relating to the allocation of customers to customer service managers.