Data usage effectiveness determination

Patent metadata

Field	Value
Publication number	US-10866835-B2
Application number	US-201515764326-A
Country	US
Kind code	B2
Filing date	Nov 23, 2015
Priority date	Nov 23, 2015
Publication date	Dec 15, 2020
Grant date	Dec 15, 2020

Abstract

Examples disclosed herein relate to determining data usage effectiveness. A processor may determine data usage effectiveness information related to an entity's workflow based on workflow data collected related to the entity's operations and metrics determined based on the data. The determination may be based on a comparison of the information related to the entity's workflow to target workflow information and priority information associated with the target workflow information. The processor may output information related to the determined data usage effectiveness.

First claim

The invention claimed is:

1. A computing system, comprising:
a storage to store:
a list of target workflow information; and
priority information associated with the target workflow information; and

a processor to:
compare a set of entity workflow information to the target workflow information and the priority information associated with the target workflow information to determine data usage effectiveness associated with an entity, wherein the entity workflow information comprises at least one of workflow data collected and metrics determined based on the workflow data;
output information related to the data usage effectiveness that is determined, wherein the data usage effectiveness identifies which information from the target workflow information is missing from the set of entity workflow information;
determine a type of data of the information that is missing and a piece of equipment that is to collect the information that is missing from the set of entity workflow information;
compare the data usage effectiveness that is output to settings of the piece of equipment; and
change the settings of the piece of equipment to collect the type of data of the information that is missing from the set of entity workflow information based on the data usage effectiveness that is output that is compared to the settings of the piece of equipment.

2. The computing system of claim 1 , wherein the processor is further to determine a recommendation to improve the data usage effectiveness of the entity.

3. The computing system of claim 1 , wherein the processor is further to determine relative data usage effectiveness between the entity and a second entity based on the information that is output.

4. The computing system of claim 1 , wherein the processor is further to determine the list of target workflow information based on at least one of:
workflow information associated with a second entity and workflow information associated with a simulation.

5. The computing system of claim 1 , wherein the processor is further to determine a priority associated with a piece of information in the list of target workflow information based on at least one of: a number or metrics that the piece of information is associated with, the effect on an associated metric, and a priority of an associated metric.

6. The computing system of claim 1 , wherein the processor is further to preprocess the entity workflow information to add entity workflow information determined based on the entity workflow information.

7. A method, comprising:
determining a set of entity workflow information, wherein the entity workflow information comprises at least one of workflow data collected and metrics determined based on the workflow data that is collected;
determining target workflow information and priority levels associated with the target workflow information;
determining information about data usage effectiveness of an entity based on a comparison of the set of entity workflow information to the target workflow information and the priority levels associated with the target workflow information, wherein the data usage effectiveness identifies which information from the target workflow information is missing from the set of entity workflow information;
outputting information related to the data usage effectiveness that is determined;
determining a type of data of the information that is missing and a piece of equipment that is to collect the information that is missing from the set of entity workflow information;
comparing the data usage effectiveness that is output to settings of the piece of equipment; and
changing the settings of the piece of equipment to collect the type of data of the information that is missing from the set of entity workflow information based on the comparing.

8. The method of claim 7 , further comprising determining priority information associated with data in a list of the target workflow information based on at least one of: a number of metrics to which the data contributed and priority information associated with metrics to which the data contributed.

9. The method of claim 7 , wherein determining the target workflow information comprises:
determining demand associated with the set of entity workflow information;
running a simulation based on the demand that is determined; and
determining the target workflow information based on the simulation.

10. The method of claim 7 , further comprising selecting an action to improve the data usage effectiveness based on the information that is output.

11. The method of claim 7 , wherein determining the data usage effectiveness comprises:
creating a target tree with nodes representing the target workflow information, wherein tree edges represent relationships between the target workflow information and wherein a height of the target tree indicates a priority associated with a node; and
comparing the target tree with an entity tree representative of the set of entity workflow information.

12. The method of claim 11 , wherein determining the data usage effectiveness comprises determining a data usage effectiveness score based on at least one of: a proportion of missing tree nodes in the entity tree compared to the target tree, the number of tree nodes in the target tree, and the height of the tree nodes in the target tree.

13. A machine-readable non-transitory storage medium comprising instructions executable by a processor to:
determine data usage effectiveness information related to a workflow of an entity based on workflow data collected related to operations and metrics of the entity determined based on the data usage effectiveness information, wherein the data usage effectiveness is determined based on a comparison of the workflow of the entity to target workflow information and priority information associated with the target workflow information, wherein the data usage effectiveness identifies which information from the target workflow information is missing from the workflow of the entity;
output information related to the data usage effectiveness that is determined;
determine a type of data of the information that is missing and a piece of equipment that is to collect the information that is missing from the workflow information of the entity;
compare the data usage effectiveness that is output to settings of the piece of equipment; and
change the settings of the piece of equipment to collect the type of data of the information that is missing from the set of entity workflow information based on the data usage effectiveness that is output that is compared to the settings of the piece of equipment.

14. The machine-readable non-transitory storage medium of claim 13 , further comprising instructions to:
create a representation including nodes representative of at least one of the workflow data and metrics, wherein the nodes are connected based on a relationship between information associated with the nodes; and
cause a user interface to be displayed including information related to the representation that is created.

15. The machine-readable non-transitory storage medium of claim 13 , wherein the workflow is associated with at least one of manufacturing, additive manufacturing, healthcare, and transportation.

Assignees

• Hewlett Packard Development Co

Inventors

• Kothari Sunil
• Reasoner Michael L
• Peck Thomas J
• Sexton Douglas A
• Oblea Francisco
• Zeng Jun
• Dispoto Gary J

Classifications

• G06Q10/06 Primary

  Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling · CPC title

• G16H50/50

  for simulation or modelling of medical disorders · CPC title

• G06F9/5011 Primary

  the resources being hardware resources other than CPUs, Servers and Terminals · CPC title