PATENT CLAIM ANALYSIS

Application Number: 16284643
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-10
Patent Classification: ["709", "220000"]

Abstract:
A device may receive a request for a service management plan that is to be used to implement a fully-integrated enterprise resource planning (ERP) system for an organization. The device may receive organizational data associated with the organization. The device may determine, based on the organizational data, observations that serve as hypotheses for deficiencies associated with a current state of a system of the organization. The device may identify, based on the observations, priorities that define a target state for the fully-integrated ERP system that is to be generated. The device may select, based on a machine-learning-driven analysis of the observations and the priorities, a recommendation for a configuration of the fully-integrated ERP system. The device may generate, based on the recommendation, the service management plan for the organization. The device may perform a set of actions to cause the configuration to be implemented.

Claim (Index 15):
A non-transitory computer-readable medium storing instructions, the instructions comprising:\n one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to:\n receive a request for a service management plan that is to be used to implement a fully-integrated enterprise resource planning (ERP) system for an organization; \n receive organizational data associated with the organization,\n wherein the organizational data includes one or more of:\n process data that describes a set of organizational processes that are used for providing goods and/or services to customers, \n application data that is generated while the set of organizational processes are being performed, or \n performance indicator data that identifies a set of network performance metrics for measuring performance within the organization; \n \n \n determine, based on the organizational data, a set of observations that include observations describing deficiencies associated with a current state of a system of the organization; \n identify, based on the set of observations, a set of priorities that define a target state for the fully-integrated ERP system that is to be generated; \n determine, using a machine-learning-driven analysis of the set of observations and the set of priorities, a set of scores for a set of recommendations for configurations of the fully-integrated ERP system,\n wherein the set of scores indicate likelihoods of particular configurations, of the configurations, causing a state of the fully-integrated ERP system to be the target state; \n \n select a recommendation, of the set of recommendations, for a configuration, of the configurations of the fully-integrated ERP system, based on the set of scores,\n wherein the configuration identifies at least one of:\n an environment used to support the fully-integrated ERP system, \n a set of service management tools that are to be used within the environment of the fully-integrated ERP system, or \n a data fabric aggregation tool that allows the set of service management tools to access shared application data, \n wherein the shared application data is associated with other fully-integrated ERP systems; \n \n \n generate, based on the recommendation, the service management plan for the organization,\n wherein the service management plan includes a timeline that indicates when to implement one or more aspects of the configuration for the fully-integrated ERP system; and \n \n perform a set of actions over time to cause the configuration to be implemented,\n wherein implementing the configuration allows the set of service management tools to support end-to-end processes of the organization.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 2.59677
- Patent Class: 709.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['14492562', '12823389', '15380865', '15247069', '12314683']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2204861117527456
- 35 USC 102 Novelty (BERT): 0.4769078069508736
- Combined Prediction Score: 0.2461282812725584
- Mean Citation Score: 154.556274
- Max Citation Score: 160.78648
- Similarity Product: 115.26293842390058

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test