Customer service staffing plan generation based on forecasted demand and service goals

1 . A method for forecasting with anonymized benchmarks, the method comprising:

receiving, by an interface component of an intelligent forecaster implemented by a processing system, a customer-defined service goal and a demand forecast for a customer;

generating, by a planner component of the intelligent forecaster, an entity plan for achieving the customer-defined service goal based on the demand forecast, wherein the entity plan comprises at least one of a staffing plan, resource allocation plan, or hiring plan for predicted future operations of the customer;

mining, by a first application programming interface (API) of the intelligent forecaster, interaction data from a plurality of other organizations operating across one or more private environments, wherein the first API is configured to interface with the one or more private cloud environments to receive operation and service data from the plurality of other organizations executing services with the one or more private cloud environments;

anonymizing, by the first API, the mined interaction data;

generating, by the first API, a plurality of benchmark categories by categorizing the mined interaction data by at least one of an industry and one or more additional metrics, wherein each benchmark category of the plurality of benchmark categories has a minimum number of different organizations contributing data to the benchmark category;

selecting, by the first API, a benchmark category from the plurality of benchmark categories based on a parameter defining the customer;

determining, by a second API of the intelligent forecaster, one or more benchmark service goals based on the benchmark category, wherein the second API is configured to interface with the one or more private cloud environments and the planner component to identify the benchmark category from the plurality of benchmark categories based at least on an industry associated with the customer;

generating, by the planner component, one or more benchmark-plans based on the one or more benchmark service goals for the demand forecast for the customer;

identifying, by a comparison component of the intelligent forecaster, a change from the customer-defined service goal to one of the one or more benchmark service goals that improves an operation or service metric through one or more comparison operations based on the entity plan and the one or more benchmark-plans; and

outputting, by the interface component of the intelligent forecaster and for display to the customer, the entity plan, the one or more benchmark-plans, and the change from the customer-defined service goal to the one or more benchmark service goals that improves the operation or service metric, wherein the one or more benchmark-plans are different from the entity plan.

2 . The method of claim 1 , further comprising:

determining, by the comparison component, a subset of the one or more benchmark-plans that provide an estimated amount of resource savings based on the one or more comparison operations between the entity plan and the one or more benchmark-plans; and

providing, by the interface component, a recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

3 . The method of claim 2 , wherein the recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals is provided when the estimated amount of resource savings is greater than a predefined amount.

4 . The method of claim 1 , further comprising:

determining, by the comparison component, a subset of the one or more benchmark-plans that provide an estimated amount of resource savings and an estimated satisfaction score greater than a predefined score based on the one or more comparison operations between the entity plan and the one or more benchmark-plans; and

providing, by the interface component, a recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

5 . The method of claim 4 , wherein providing the recommendation further includes displaying the estimated amount of resource savings and the estimated satisfaction score for each of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

6 . The method of claim 1 , wherein the one or more additional metrics comprise task or organization focused operating and service metrics defining data to be collected from operational data of the plurality of other organizations deploying their services within the one or more private cloud environments.

7 . The method of claim 1 , wherein selecting the benchmark category comprises matching the parameter defining the customer to one or more parameters defining organizations of the benchmark category.

8 . The method of claim 1 , further comprising scoring a relatedness of the benchmark category to the customer based on a comparison of the parameter defining the customer and one or more parameters defining organizations of the benchmark category.

9 . A computer-implemented system for forecasting with anonymized benchmarks, the computer-implemented system comprising:

a processor and a non-transitory computer-readable medium storing computer readable instructions that, when executed by the processor, cause the computer-implemented system to:

receive, by an interface component of an intelligent forecaster, a customer-defined service goal and a demand forecast for a customer;

generate, by a planner component of the intelligent forecaster, an entity plan for achieving the customer-defined service goal based on the demand forecast, wherein the entity plan comprises at least one of a staffing plan, resource allocation plan, or hiring plan for predicted future operations of the customer;

mine, by a first application programming interface (API) of the intelligent forecaster, interaction data from a plurality of other organizations operating across one or more private cloud environments, wherein the first API is configured to interface with the one or more private cloud environments to receive operation and service data from the plurality of other organizations executing services with the one or more private cloud environments;

anonymize, by the first API, the mined interaction data;

generate, by the first API, a plurality of benchmark categories by categorizing the mined interaction data by at least one of an industry and one or more additional metrics, wherein each benchmark category of the plurality of benchmark categories has a minimum number of different organizations contributing data to the benchmark category;

select, by the first API, a benchmark category from the plurality of benchmark categories based on a parameter defining the customer;

determine, by a second API of the intelligent forecaster, one or more benchmark service goals based on the benchmark category, wherein the second API is configured to interface with the one or more private cloud environments and the planner component to identify the benchmark category from the plurality of benchmark categories based at least on an industry associated with the customer;

generate, by the planner component, one or more benchmark-plans based on the one or more benchmark service goals for the demand forecast for the customer;

identify, by a comparison component of the intelligent forecaster, a change from the customer-defined service goal to one of the one or more benchmark service goals that improves an operation or service metric through one or more comparison operations based on the entity plan and the one or more benchmark-plans; and

output, by the interface component of the intelligent forecaster and for display to the customer, the entity plan, the one or more benchmark-plans, and the change from the customer-defined service goal to the one or more benchmark service goals that improves the operation or service metric, wherein the one or more benchmark-plans are different from the entity plan.

10 . The computer-implemented system of claim 9 , further comprising computer readable instructions that, when executed by the processor, cause the computer-implemented system to:

determine, by the comparison component, a subset of the one or more benchmark-plans that provide an estimated amount of resource savings based on the one or more comparison operations between the entity plan and the one or more benchmark-plans; and

provide, by the interface component, a recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

11 . The computer-implemented system of claim 10 , wherein the recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals is provided when the estimated amount of resource savings is greater than a predefined amount.

12 . The computer-implemented system of claim 9 , further comprising computer readable instructions that, when executed by the processor, cause the computer-implemented system to:

determine, by the comparison component, a subset of the one or more benchmark-plans that provide an estimated amount of resource savings and an estimated satisfaction score greater than a predefined score based on the one or more comparison operations between the entity plan and the one or more benchmark-plans; and

provide, by the interface component, a recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

13 . The computer-implemented system of claim 12 , wherein providing the recommendation further includes causing the processor to display the estimated amount of resource savings and the estimated satisfaction score for each of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

14 . The computer-implemented system of claim 9 , wherein the one or more additional metrics comprise task or organization focused operating and service metrics defining data to be collected from operational data of the plurality of other organizations deploying their services within the one or more private cloud environments.

15 . The computer-implemented system of claim 9 , further comprising computer readable instructions that, when executed by the processor, cause the computer-implemented system to select the benchmark category matching the parameter defining the customer to one or more parameters defining organizations of the benchmark category.

16 . The computer-implemented system of claim 9 , further comprising computer readable instructions that, when executed by the processor, cause the computer-implemented system to score a relatedness of the benchmark category to the customer based on a comparison of the parameter defining the customer and one or more parameters defining organizations of the benchmark category.

17 . A computer-implemented system for forecasting with anonymized benchmarks, the computer-implemented system comprising:

a computing device communicatively coupled to one or more cloud-based servers, the computing device configured to:

receive, by an interface component of an intelligent forecaster implemented by the computing device, input from a user comprising a customer-defined service goal;

receive, from one of the one or more cloud-based servers, a demand forecast for a customer;

receive, by a planner component of the intelligent forecaster, an entity plan for achieving the customer-defined service goal based on the demand forecast, wherein the entity plan comprises at least one of a staffing plan, resource allocation plan, or hiring plan for predicted future operations of the customer;

mine, by a first application programming interface (API) of the intelligent forecaster, interaction data from a plurality of other organizations operating across one or more private cloud environments, wherein the first API is configured to interface with the one or more private cloud environments to receive operation and service data from the plurality of other organizations executing services with the one or more private cloud environments;

anonymize, by the first API, the mined interaction data;

generate, by the first API, a plurality of benchmark categories by categorizing the mined interaction data by at least one of an industry and one or more additional metrics, wherein each benchmark category of the plurality of benchmark categories has a minimum number of different organizations contributing data to the benchmark category;

select, by the first API, a benchmark category from the plurality of benchmark categories based on a parameter defining the customer;

determine, by a second API of the intelligent forecaster, one or more benchmark service goals based on the benchmark category, wherein the second API is configured to interface with the one or more private cloud environments and the planner component to identify the benchmark category from the plurality of benchmark categories based at least on an industry associated with the customer;

generate, by the planner component, one or more benchmark-plans based on the one or more benchmark service goals for the demand forecast for the customer;

identify, by a comparison component of the intelligent forecaster, a change from the customer-defined service goal to one of the one or more benchmark service goals that improves an operation or service metric through one or more comparison operations based on the entity plan and the one or more benchmark-plans; and

output, by the interface component of the intelligent forecaster and for display to the customer, the entity plan, the one or more benchmark-plans, and the change from the customer-defined service goal to the one or more benchmark service goals that improves the operation or service metric, wherein the one or more benchmark-plans are different from the entity plan.

18 . The computer-implemented system of claim 17 , wherein the computing device is further configured to:

determine, by the comparison component, a subset of the one or more benchmark-plans that provide an estimated amount of resource savings based on the one or more comparison operations between the entity plan and the one or more benchmark-plans; and

provide, by the interface component, a recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals corresponding to the subset of the one or more benchmark-plans.

19 . The computer-implemented system of claim 18 , wherein the recommendation to change the customer-defined service goal to the one of the one or more benchmark service goals is provided when the estimated amount of resource savings is greater than a predefined amount.

20 . The method of claim 1 , wherein the parameter defining the customer comprises at least one of an industry of the customer, size of the customer, or location of the customer.