EA038379B1 - Intelligent control system for detecting deviations in processes and displaying tasks for their elimination - Google Patents

Abstract

The disclosed technical solution known as Intelligent Control System (ICS) generally relates to computer engineering, in particular to a method and a device for detecting deviations and generating recommendations for elimination of deviations in any processes running in various types of human activities, including banking, sales of products and services, etc. The technical result achieved through the solution of said technical problem consists in the enhancement of functionality by presenting to manager the information on a deviation, employee, and task aimed at change of the deviation value of at least one stage of process based on the deviation priority in the process. The method comprises the steps of obtaining process data for at least one process; determining a type of process; comparing the process data with standard process performance rules to determine the presence of at least one deviation in the process step; identifying an employee who initiated said deviation in the process step; determining the deviation priority based on history information on deviations in said process step; determining the employee managers based on the employee's identifier; obtaining from database the information on task aimed at changing the deviation value in said process step depending on type of process and deviation priority; outputting information on the deviation, employee, and task to the manager information displaying equipment based on the deviation priority in the process.

Description

Technology area

This technical solution, called the Intelligent Control System (IMS), generally refers to the field of computer technology, and in particular to a method and device for detecting deviations and generating recommendations for eliminating deviations in any processes occurring in various spheres of human activity, including in the banking sector, sales of goods and services, etc.

State of the art

Currently, monitoring systems for process indicators are widely used in various branches of technology. Known systems provide the ability to collect indicators of the processes performed in an organization, analyze the effectiveness of the process and provide recommendations for managing the process. The closest technical solution is a system and method for optimizing one or more business processes in an organization, disclosed in the application US 2013013370 (A1), publ. 10.01.2013

This document discloses the choice, using one or more processors, at least one business process for optimization; identifying, using one or more processors, the first performance indicator associated with the selected business process; identifying, using one or more processors, the first process characteristics corresponding to at least the first performance indicator; and determining, using one or more processors, at least one transformation template corresponding to the first process characteristics, wherein the at least one transformation template is identified based on at least one predetermined criterion.

The disadvantage of the known solution is the inability to analyze the parameters of specific stages of the process, to identify deviations in the execution of the stages of the process by a person and to display data on the deviation and tasks to eliminate deviations, taking into account the priority of the deviation.

The essence of the technical solution

The technical problem or task posed in this technical solution is to create a simple and reliable method and device for processing process data, identifying deviations in the process and promptly eliminating the identified deviations.

The technical result achieved when solving the above technical problem is to expand the functionality by displaying data about the deviation, the employee and the task to the manager, aimed at changing the deviation value of at least one stage of the process, based on the priority of the deviation in the process.

The specified technical result is achieved through the implementation of a method for detecting and displaying deviations in at least one process and tasks for their elimination, performed by at least one computing device, containing the stages, which obtain data on at least one process;

determine the type of process;

comparing the process data with the rules for executing a typical process to determine the presence of at least one deviation in the process step;

identify the employee who is the initiator of the deviation at the stage of the process;

determine the priority of the deviation based on historical data on deviations in the process step;

define employee managers based on employee ID;

obtaining from the database information about the task aimed at changing the deviation value in at least one stage of the process, depending on the type of process and the priority of the deviation;

output data about the deviation, employee and task, to the means of outputting information of the manager based on the priority of the deviation in the process.

In one of the particular examples of the implementation of the method, the priority of the process is additionally determined; refining the priority of the rejection based on the priority of the process; determine the values of the capacity of the managers' working time; in this case, the aforementioned data are outputted to the manager's information output means, taking into account the value of the capacity of working time and the specified priority of the deviation in the process.

In another particular embodiment of the method, data is additionally obtained about the actions of the employee in the time interval at which the presence of a deviation is determined; specifying the priority of the deviation in the process based on the data on the employee's actions in the time interval on which the presence of the deviation is determined; in this case, the aforementioned data are output to the manager's information output means, taking into account the data on the employee's actions and the specified priority of the deviation in the process. In another particular embodiment of the method, data is additionally obtained about the actions of the manager aimed at changing the deviation value in the process; determine the value of the effectiveness of the manager's actions aimed at changing the value of the deviation in the process; correct or form and send a request for the need to adjust the rules of a typical process and a task aimed at changing the deviation value, based on the value effectively

- 1,038379 actions of the head. In another preferred embodiment of the claimed solution, a data processing device is provided for detecting and displaying deviations in at least one process and tasks for eliminating them, comprising at least one computing device and at least one memory device containing machine-readable instructions that, when execution by at least one computing device, the above method is performed.

Brief Description of Drawings

Features and advantages of the present invention will become apparent from the following detailed description of the invention and the accompanying drawings, in which: FIG. 1 shows an example of a system for detecting and displaying deviations in at least one process;

in fig. 2 shows an example of a sequence of process steps;

in fig. 3 shows an example of a general view of a computing device.

Detailed description of the invention

Below will be described the concepts and terms necessary to understand this technical solution.

In this technical solution, the system means, including a computer system, a computer (electronic computer), CNC (numerical control), PLC (programmable logic controller), computerized control systems and any other devices capable of performing a given, well-defined sequence operations (actions, instructions).

A command processing device means an electronic unit or an integrated circuit (microprocessor) that executes machine instructions (programs).

A command processor reads and executes machine instructions (programs) from one or more storage devices. The role of data storage devices can be, but are not limited to, hard disks (HDD), flash memory, ROM (read only memory), solid state drives (SSD), optical drives.

A program is a sequence of instructions intended for execution by a computer control device or a command processing device.

As shown in FIG. 1, a system for detecting and displaying deviations in at least one process comprises at least one process data recording device 1 and at least one process data processing device 10.

The device 1 for recording process data can be made on the basis of a recording device - a device for automatically recording on a data carrier data coming from sensors or other technical means, including those made with the ability to register the values of the measured or related value and link the recorded parameter values to real time scale. Recording devices can be integral functional units of measuring instruments, installations, blocks as part of information, measuring, control systems, complexes, or independent devices.

The process data processing device 10 can be implemented on the basis of at least one computing device and at least one memory device containing machine-readable instructions, which, when executed by at least one computing device, perform a method for detecting and displaying deviations, generating tasks for their elimination in at least one process. The computing device will be disclosed in more detail in the description below.

The device 10 for processing process data may include, connected by a common data bus, a module 11 for collecting, processing and storing process data, a module 12 for analyzing process deviations, a deviation prioritization module 13, a task generating module 14, and a feedback data collection and processing module 15.

In accordance with the programmed algorithm laid down by the user, the process data recording device 1 registers incoming data for less than one process and transfers the recorded data to the process data processing device 10. For data transmission, the above-mentioned devices 1 can be equipped with wired and / or wireless communication means, providing data transmission via an internal or external computer network, for example, Intranet, Internet, LAN, etc. Such means can be used, but not limited to: Ethernet card, GSM modem, GPRS modem, LTE modem, 5G modem, satellite communication module, NFC module, Bluetooth and / or BLE module, Wi-Fi module, etc.

The process data may include a process identifier, at least one process step identifier, at least one process step indicator (for example, a metric, the execution time of a process step), at least one identifier of an employee responsible for at least one process step. Employee identifiers can be collected by data logging devices 1 by methods well known in the art, for example, by reading their identification information from special passes, or collecting their account data, or by requesting this information from employees, or employee identifiers can be introduced into said device 1 by a specially trained person.

In an alternative embodiment of the system, the identifiers of the employees responsible for the process steps are not contained in the process data, but can be stored in advance in the corresponding employee database located in the module 11 for collecting, processing and storing process data, and are associated with the corresponding identifier of the process step and at least one identifier of the manager of this employee.

Let us consider a method for registering data on the example of the process of providing services to customers using an electronic queue device in the organization Service Center (CPU), in which the process data recording devices 1 can be installed in the CPU to register the processes occurring in it. For example, the process data logger 1 may be configured to log a customer service process to provide a service of their choice.

In a particular embodiment of the claimed solution, the customer service process for providing the service of his choice in accordance with FIG. 2 can be implemented as follows.

In the first step, the process data logger 1 registers the time of receipt of the service request 100 from the client CPU. The device 1 for recording process data in this example can be located in a specialized terminal of the CPU, when interacting with the graphical interface of which the client can select the type of required service, send a request (100) for the service according to the selected type and receive a paper or electronic document from the terminal, in particular coupon, with the number of the queue. The time of interaction of the client with the graphical interface for sending a request (100) for the service and the time of issuing the ticket (101) by the terminal can also be registered by the said device 1.

Accordingly, the above registered customer service process data is sent by the process data logger 1 to the process data processing apparatus 10, the process data in this case including a process ID indicating that the process is a CPU customer service process; process step identifiers, in particular the step identifier (100) of the service request and the step identifier (101) of the ticket; indicators of the stages of the process, in particular, the time it took the client to send (100) a request for a service, and the time it took to issue (101) a coupon; and the identifier of an employee, for example, who is near the terminal and assists the CPU clients with the terminal.

Also, the process data registration device 1 can be installed on an automated workstation (AWS) of a CPU employee to register the stages of the customer service process, at which the said employee calls (102) the customer according to his queue number, the choice (103) on the AWS of the service that is required provide the client, provide (104) services to the client, prepare (105) the documents necessary for the provision of the service, complete (106) the process of providing the service, transfer (107) documents to the operational accounting unit and close (108) the coupon.

Accordingly, in the above example, the process data supplied to the process data processing apparatus 10 from the data logging apparatus 1 located in the workstation of the CPU employee will include a process ID indicating that the process is a CPU customer service process;

process step identifiers 102-108;

indicators of the stages of the process, characterizing the time of execution of stages 102-108;

the identifier of the employee of the CPU - the operator of the mentioned AWP.

Information about the execution time of step 102 can be received by the data logger 1, for example, from the workstation of the employee of the CPU at the moment the employee presses the corresponding button to call the client in the graphical interface of the workstation or connected to the workstation. The data logger 1 can receive information about the execution time of step 103, for example, from the workstation of a CPU employee at the time of launching the corresponding application for selecting a service, as well as when the employee selects a specific service on the workstation. Information about the execution time of step 103 can be received by the data logging device 1, for example, from the workstation of a CPU employee after pressing the corresponding button on the graphical interface of the workstation to provide the service. Information about the execution time of step 104 can be determined by the data logger 1, for example, based on the data on the time when the button was pressed on the graphical interface of the AWP for the provision of the service and the button for printing the documents required for the provision of the service.

Information about the execution time of step 105 can be received by the data logger 1, for example, from the workstation of a CPU employee after loading a copy of the prepared documents into a specialized workstation application. Information about the execution time of step 106 can be received by the data logger 1, for example, from the workstation of the CPU employee after the said employee sends the prepared documents to the operational accounting unit. The data logger 1 can receive information about the time of execution of stage 108, for example, from the workstation of a CPU employee at the moment the employee presses the corresponding button to close the ticket in the graphical interface

AWP or an input device connected to the AWP.

The above information describing the registration method by the data device 1 of the customer service process of the CPU is given in the present application by way of example only. Data logging devices 1 can be configured to record data of any types of processes, including service processes of any equipment, processes taking place in the field of sales, maintenance processes, etc. Also, data logging devices 1 can be configured with the ability, in addition to time , also record other indicators, for example, indicators of a process stage (productivity, time, speed, satisfaction, number of defects, etc.), number of units, physical parameters, geodata or indicators disclosed in the closest analogue.

In addition, in an alternative embodiment of the declared solution, the process data can be registered by a specially trained employee at the automated workstation allocated to him. Accordingly, the process data entered by the said employee will be sent by the AWP to the process data processing device 10 at the command of the employee or in accordance with the hardware and software algorithm embedded in the AWP.

At the first stage of operation of the process data processing device 10, the received process data from at least one data recording device 1 is sent to the process data collection, processing and storage unit 11, which, based on the data of the process identifier, process step identifiers, identifiers of employees responsible for the steps process, and indicators of the stages of the process, for example, the indicator of the execution time of the stages, generates data about the process and stores them in a data library with which this module can be equipped. The process data in module 11 can be stored, for example, in the form of a time series, i. E. a set of values of process indicators for several consecutive moments or periods of time.

Additionally, the module 11 for collecting, processing and storing process data can be equipped with a database on the actions of employees, which records information about the actions of employees on a time interval at the time of registration of process data by devices 1. Information about the actions of employees can indicate, for example, that the employee responsible for the stage of the process is at the workplace during the time interval or is absent from the workplace due to being on sick leave or on vacation, was engaged in another process. This information can be collected by methods known from the prior art or entered into the module 11 by the user of the device 10.

Further, at the command of the user of the device 10 or in accordance with the firmware algorithm embedded in the device 10, the said device 10 proceeds to the step of determining the presence of at least one deviation in the process, in particular in the process of serving the client. At this stage, the module 11 for collecting, processing and storing process data extracts data from the data library of at least one process and sends them to the module 12 for analyzing deviations in the process.

To determine deviations, the deviation analysis module 12 determines the type of process and extracts from the data library of the module 11 the model of typical processes, in which the mentioned models can be stored in advance. Models of typical processes characterize the rules for the execution of typical processes and include reference data on typical processes, in particular a list of stages of typical processes and the range of acceptable indicators of stages of typical processes. Models of typical processes can be generated by users of the process data processing device 10 based on the rules in accordance with which these processes must be performed to ensure the required performance indicators of the process.

For example, with respect to the CPU customer service process, the desired performance metric might be to reduce the CPU customer service time to 15 minutes, which would be determined, for example, based on the time the service request 100 was received and the time the ticket was closed 108. Also, the required performance indicator can be an indicator of the execution time of a specific stage, for example, the time to provide 104 services, etc. Reference data on typical processes, in particular a list of stages of typical processes and the range of acceptable indicators of stages of typical processes, can be generated by users of the device 10 based on the analysis historical data of process data indicators that can be collected by methods well known in the art. Also, when forming models of typical processes, the number of employees, their length of service, labor productivity, place of work, work schedule and breaks, number of customers, errors and defects, etc. can be taken into account.

Upon receipt of process data, module 12 extracts the process identifier and, based on this identifier, determines the type of process. Accordingly, when receiving data about the process according to the above example, the module 12 extracts the process identifier, compares it with the previously stored identifiers in the database, for example, located in the module 11, and, based on the results of the match, determines the process type, in particular, that the process type is a service process. client CPU. Additionally, module 12, based on the process ID, can determine that

- 4 038379 this type of CPU customer service process is carried out using an electronic queue or a live queue.

After determining the type of process, the module 12 extracts from the database a model of a typical process, in particular a model of a process for servicing a CPU client, and compares the process data with typical process data characterizing the rules for executing this typical process to determine the presence of at least one deviation in the process step. ... Module 12 may determine a variance in the sequence of at least one process step or in terms of a process step by comparing them to a range of acceptable performance for a typical process step. Also, the module 12, on the basis of the above-mentioned comparison, determines the deviation value of the process step, which characterizes the amount of deviation of the process step from the typical process step.

For example, in the process of servicing a CPU client using an electronic queue, based on the comparison results, module 12 may determine that the received process data is missing information about steps 100-102, which indicates that the CPU employee responsible for step 103 has started providing a service to a CPA client out of turn.

Accordingly, the information about the deviation value of each step 100-102 of the process in this example will indicate that there is no information about these steps. Alternatively, it can be determined by the module 12 that the execution time of step 102, which characterizes the waiting time of the CPU client in the queue after the ticket 101 has been issued, exceeds the set waiting time, i. E. above the specified range of acceptable times for this stage 102 of the typical process. Accordingly, the information about the deviation value of step 102 will indicate the amount of deviation of the time indicator of step 102 from the predetermined range of allowable indicators of the execution time of this step.

After determining at least one deviation in the process, module 12 generates a rejection notification, which includes information about the process identifier and data about the deviation in the process, including information: the identifier of the process step, the identifier of the employee responsible for the process step, the deviation value of the process step.

For example, in the above example, when a deviation is detected in steps 100-102 when these steps are not present, module 12 generates a notification that includes an identifier indicating that the process is a CPU client service process; process deviation data including process step identifiers 100-102, at least one employee identifier responsible for steps 100-102, and process step deviation values indicating that there is no information about these steps.

If module 12 detects a deviation in the metric of the process step, in particular in the metric of the execution time of the process step 102, then the module 12 generates a deviation notification, which includes an identifier indicating that the process is a CPU client service process; and rejection data in the process, including the process ID 102, the ID of the employee in charge of the process 102, and the rejection value of the process step 102, i. the amount of deviation of the indicator of the execution time of stage 102 of the process from a predetermined range of allowable indicators of the execution time of the typical stage of the process.

The generated notification by the module 12 is sent to the deviation prioritization module 13, which is connected to the historical data base on deviations in at least one process located in the previously mentioned module 11. The historical data on deviations in at least one process may include identifiers of employees responsible for process steps, and previously recorded information about the deviation of at least one indicator of the process step, about the number of deviations of the said indicator, the history of the deviations of the said indicator, and how long ago the deviation occurred in the process. Module 13, based on the process identifier, employee identifier and deviation data in the process step, searches for historical data on deviations in this process step for this employee, which could previously have been recorded in a time range predefined by the user in the device 10, and based on the previously registered The deviation information at this stage of the process determines the priority level for this deviation. Based on the priority level, in the future, the manager or other responsible person will be determined to whom the data on the deviation will be sent. For example, the first priority level might indicate that the deviation should be forwarded to the manager responsible for the employee whose ID is in the deviation data, the second priority level might indicate that the deviation should be forwarded to an upstream manager, who might be , for example, the leader of a process or stage of a process. Information about the managers of employees and their priority levels can be pre-entered into module 11 by the user of the device 10.

In a particular embodiment of the claimed solution, if the module 13, based on the information on the deviation value of the process step, determined that the deviation in the process steps is due to the absence of steps 101 and 102, while there is no information about the deviation in steps 101 and 102 in the historical database ( i.e. the variance associated with steps 101 and 102 is determined in the first

- 5,038379 times), then the deviation prioritization module 13 assigns, by the module 12, the deviation characterizing the deviations in process steps 101 and 102, the first priority level. Likewise, the module prioritizes a deviation associated with a deviation of a process step metric, in particular a client wait time between steps 101 and 102, if there is no information about this deviation in the historical database.

If module 13 finds information in the history database about a deviation in the process associated with the absence of steps 101 and 102, then module 13 assigns a higher priority level depending on the historical data of this deviation.

For example, if module 13 determines that the historical deviation data contains information about this deviation associated with the absence of steps 101 and 102 for a given period of time, then module 13 assigns the deviation, for example, a second, third or other priority level, depending on the magnitude of the deviation. a process step metric, the number of deviations in a process step metric, and data indicating how long ago the deviation was last detected. Likewise, module 13 operates to determine if there is a process deviation associated with a process step metric, such as a client wait time between steps 101 and 102.

Additionally, the module 13 can be configured to refine the level of priority of the deviation in the process based on the data on the actions of the employee in the time interval in which the presence of the deviation is determined. To provide this possibility, module 13 refers to module 11, extracts from the data library information about the time interval when a deviation was registered in the process step, and based on the employee identifier, searches the database for information about the employee's actions in this time interval. After that, module 13, based on information about the employee's actions in this time interval, specifies the priority level of deviations in the process.

For example, if the information about the employee's actions indicates that the employee responsible for the stage of the process is absent from the workplace at this time interval, for example, due to being on sick leave or on vacation, then module 13 lowers the rejection priority level. For example, a process variance can be assigned the lowest priority level due to the absence of an employee at the workplace, according to which the data on this variance will not be displayed to the manager, and this variance in the process will not be considered by module 13 as a variance. If the information about the employee's actions indicates that the employee responsible for the stage of the process was at the workplace, then the rejection priority level does not change.

Also, the deviation priority level can be refined by the module 13 based on the process priority level, which can also be set by the device user. For example, said user in the database of unit 13 can set a priority level for each process, and a maximum priority level can be set for the CPU client service process. Thus, module 13 may refine the rejection priority level based on the process priority level, for example, increase the rejection priority level due to the absence of steps 101 and 102 or the deviation of the client timeout value by the process priority level.

Also, in addition, module 13 can be configured to identify the employee responsible for the process, if the data about the deviation received by the module 13 in the process does not contain information about the employee's identifier. To determine the employee responsible for the process step, module 13 sends the process step identifier to the process data collection, processing and storage module 11, which automatically extracts the identifier of the employee responsible for the process step and sends it to module 13. The received employee identifier module 13 associates with the received data deviations in the process step, thus identifying the employee who is the initiator of the deviation in the process step.

At the next stage of the operation of the process data processing device 10, the said module 13 for prioritizing deviations based on the employee ID and priority determines the identifiers of the managers responsible for the employee, and sends to the task generating module 14 information about the identifiers of the leaders, the process identifier, the information about the priority of the deviation and the data about deviation in the process. Upon receipt of said information, the task generating unit 14 requests information from the task generating unit 11 about the task aimed at changing the deviation value in at least one process step, depending on the process type, which is determined based on the process ID and the rejection priority level.

For example, if the process is a customer service process, and the deviation in the process is the lack of information about steps 100-102, which indicates that the CPU employee responsible for step 103 has started providing the service to the CPU customer out of turn, then module 14 generating jobs based on the process identifier determines that the process is a CPU customer service process, determines the priority of the deviation based on the priority level value and retrieves from the database of module 11 a job corresponding to the CPU customer service process aimed at eliminating the deviation associated with the lack of information about the stages 100102, according to the first priority level. The task for the first priority level can be, for example, an indication of the need to work with the employee on the implementation of the rule for working with an electronic queue: Serving only 1 customer for 1 coupon and make sure that the employee understands this rule. For the second level of priority, for example, an assignment may be received indicating the need to develop the manager's skills in working with employees. Accordingly, for other priority levels, other tasks can be generated in the database of the module 11.

If, in the process of serving a customer, a deviation in the process is, for example, a process indicator - the time of customer service from the moment the customer's call 102 was selected until the ticket was closed 108, then the task may indicate to the manager the need to perform the following steps:

1. Find out from the employee the reasons for the long-term performance of operations.

2. Check the knowledge of the performance of operations by the employee.

3. Teach the employee, send him to training.

4. Practice the skill of performing operations.

5. Monitor the implementation in the future.

6. In case the employee performs the correct actions, the reason for the deviations in the process problems, escalate the problem to the owner of the process.

Further, the module 14 for generating tasks based on the data on the priority of the deviation in the process determines the corresponding to the priority level of the leader and outputs the data on the deviation of the process, the employee and the mentioned task to the means for outputting the information of the manager, thus providing the output of the mentioned data based on the priority of the deviation in the process.

In an alternative embodiment of the claimed solution, the task generation module 14 can generate a list of deviations in the work of employees, in processes. The list of deviations can be sent to the manager's information output means and updated in real time. Module 14 for generating tasks can be equipped directly with means for outputting information or connected to said means. The output means can be, for example, a display (monitor), a touch screen, a touch panel, augmented reality, a voice interface, a tablet, indicator lights, a projector, etc.

Additionally, in an alternative embodiment of the claimed solution, module 14 can be configured to determine the value of the capacity of the managers' working time. The value of the working time capacity by the module 14 can be determined on the basis of the data of the manager's schedule and the data of the tasks assigned to him, information about which can be pre-entered into the data library of the module 11 directly by the manager, to which the said module 14 refers. When determining the value of the capacity of working time, module 14 can also take into account the historical data on the manager's schedule and the tasks performed by him. Accordingly, the information about the process identifier, the data on the deviation in the process and the mentioned task are output by the module 14 to the manager whose working time capacity value is the smallest. If the priority of the deviation in the process was previously specified, for example, based on the priority of the process or on the basis of data on the employee's actions in the time interval at which the presence of a deviation was determined, then respectively the mentioned data is output to the manager's information output means taking into account the value of the working time capacity and the adjusted the priority of the deviation in the process or taking into account the data on the employee's actions and the refined priority of the deviation in the process.

Also, the task generation module 14 displays information about the time at which the task is to be completed (for example, information about the time interval in which the task is executed). Information about the due dates of tasks is also indicated by the user of the device 10 in the data library along with the task and is displayed upon request by the module 14. In this case, the module 14 can analyze the data on the manager's working time occupancy stored in the module 11, and if the time interval during which the manager is busy, falls on the time interval in which the task is executed, then the task execution time can be increased by module 14, for example, by the value of the time interval during which the manager is busy.

Additionally, the module 11 for collecting, processing and storing process data can be configured to register the reason for not submitting the task to the manager for the detected deviation. In case of non-submission of the task, the module 11 generates in the data library a mark about the reason for not submitting the task, and the mark may include the following text: the task is not exposed; the task is not set, the employee is dismissed or absent (vacation, sick leave); the task is not set, tk. the period of execution of the previous assignment has not ended; the task is not set, tk. the limit of the permissible number of tasks for the head has been exceeded; the task is not set, tk. found recipient position is not occupied (vacancy), etc.

After the manager has completed the task, he sends to module 14 by means of information input data about the actions he performed and a command, according to which module 14 transmits information about the process ID, manager ID, data on deviation in the process and data on the actions performed by the manager. to the module 15 for collecting feedback data. The received data module 15 enters into the database of historical data on deviations located in module 11.

- 7 038379

Thus, when module 12 receives new data about this process and detects an illogical deviation in a process step, module 12 will send a new notification to module 13, which includes information about the process identifier and data about a new deviation in the process. Accordingly, when accessing the historical database, module 13 will find information about a previously determined deviation in this process, as well as about the actions performed by the manager, in connection with which module 13 will assign a higher priority level, for example, the second priority level, for sending data about new deviation and actions taken by the manager.

Further, module 13 refers to the database stored in module 11, determines the higher-level managers of the employee and sends information about the process identifier, data about the process priority, data about the deviation in the process and the actions of the manager to the task generation module 14. The display of deviation and task data for a superior manager based on the priority of deviation in the process and the collection of the actions performed by him can be carried out by the device 10 in the previously described manner in accordance with the above functions of modules 14 and 15. In particular, module 14 requests information about a task for a superior manager, aimed at changing the deviation value of at least one stage of the process, depending on the type of process and the priority of the deviation, and outputs data about the deviation of the process, the employee and the task aimed at changing the deviation value in the process, to the information output of the superior manager , thus ensuring that said information is output based on the priority level of the deviation in the process.

Additionally, the module 15 for collecting feedback data can be configured to determine the value of the effectiveness of the actions of the manager, aimed at changing the value of the deviation in the process. To do this, module 15 refers to the deviation analysis module 12 to obtain new deviation data in this process after the task has been completed by the supervisor. If new deviation data in the process is received from module 12, then module 15 assigns the manager's actions a low level of efficiency, and the mentioned value is calculated by comparing the new value of the process step indicator with the value of the process step indicator, information about which is contained in the deviation data received from the module 14 formation of tasks. When determining a low level of efficiency, module 15 can be configured to generate a request for the need to adjust the rules of a typical process and a task aimed at changing the deviation value. The request by the module 15 can be output to the information display means of the device 10.

If no deviations are found in the process, then module 15 assigns a high level of managerial effectiveness. When determining a high level of efficiency of actions, module 15 in the automated mode adjusts the rules of the typical process and the task aimed at changing the deviation value, for example, by adjusting the range of acceptable indicators of the typical process in accordance with the new value of the process indicator or adjusting the task by entering data on the actions taken by the manager ...

Thus, the achievement of the specified technical result is ensured, which consists in expanding the functionality, in particular, by displaying data on the deviation, the employee and the task to the manager, aimed at changing the deviation value of at least one stage of the process, based on the priority of the deviation in the process. In general form (see Fig. 3), the process data processing device 10 contains one or more processors (201) united by a common data exchange bus, memory means such as RAM (202) and ROM (203), input / output interfaces (204 ), input / output devices (205), and a device for networking (206).

The processor (201) (or multiple processors, multi-core processor, etc.) can be selected from a range of devices that are currently widely used, for example, such manufacturers as: Intel ™, AMD ™, Apple ™, Samsung Exynos ™, MediaTEK ™, Qualcomm Snapdragon ™, etc. Under the processor or one of the processors used in the device (200), it is also necessary to take into account a graphics processor, for example, NVIDIA GPU or Graphcore, the type of which is also suitable for full or partial execution of the method, and can also be used for training and applying machine learning models in various information systems.

RAM (202) is a random access memory and is intended for storing machine-readable instructions executed by the processor (201) for performing the necessary operations for logical data processing. RAM (202), as a rule, contains executable instructions of the operating system and corresponding software components (applications, software modules, etc.). In this case, the available memory of the graphics card or graphics processor can act as RAM (202).

ROM (203) is one or more persistent storage devices such as hard disk drive (HDD), solid state data storage device (SSD), flash memory (EEPROM, NAND, etc.), optical storage media (CD-R / RW, DVD-R / RW, BlueRay Disc, MD), etc.

Various types of I / O interfaces (204) are used to organize the operation of device components (200) and to organize the operation of external connected devices. The choice of the appropriate interfaces depends on the specific version of the computing device, which can be, but are not limited to: PCI, AGP, PS / 2, IrDa, FireWire, LPT, COM, SATA, IDE, Lightning, USB (2.0, 3.0,

3.1, micro, mini, type C), TRS / Audio jack (2.5, 3.5, 6.35), HDMI, DVI, VGA, Display Port, RJ45, RS232, etc.

To ensure user interaction with the device (200), various means (205) of I / O information are used, for example, a keyboard, display (monitor), touch display, touch pad, joystick, mouse manipulator, light pen, stylus, touch panel, trackball , speakers, microphone, augmented reality, optical sensors, tablet, light indicators, projector, camera, biometric identification (retina scanner, fingerprint scanner, voice recognition module), etc.

The means of networking (206) provides data transmission via an internal or external computer network, for example, Intranet, Internet, LAN, etc. One or more means (206) may be used, but not limited to: Ethernet card, GSM modem, GPRS modem, LTE modem, 5G modem, satellite communication module, NFC module, Bluetooth and / or BLE module, Wi-Fi module, and dr.

Additionally, satellite navigation aids can also be used as part of the system (200), for example, GPS, GLONASS, BeiDou, Galileo. The specific choice of elements of the device (200) for the implementation of various software and hardware architectural solutions can vary while maintaining the required functionality provided.

Modifications and improvements to the above described embodiments of the present technical solution will be apparent to those skilled in the art. The foregoing description is provided by way of example only and is not intended to be limiting in any way. Thus, the scope of the present technical solution is limited only by the scope of the attached claims.

Claims (5)

CLAIM 1. A method for detecting and displaying deviations in data about at least one process from data characterizing the rules for executing a typical process, and tasks for their elimination, performed by at least one computing device, containing stages at which data about at least one process; determine the type of process; comparing the data on the process with data characterizing the rules of the typical process to determine the presence of at least one deviation in the process step; identify the employee who is the initiator of the deviation at the stage of the process; determine the priority of the deviation based on historical data on deviations in the process step; define employee managers based on employee ID; obtaining from the database information about the task aimed at changing the deviation value in at least one stage of the process, depending on the type of process and the priority of the deviation; output the data about the deviation, the employee and the task to the means of outputting information of the manager based on the priority of the deviation in the process. 2. The method according to claim 1, characterized in that it further comprises stages, which determine the priority of the process; refining the priority of the rejection based on the priority of the process; determine the values of the capacity of the managers' working time; in this case, the aforementioned data are outputted to the manager's information output means, taking into account the value of the capacity of working time and the specified priority of the deviation in the process. 3. The method according to claim 1, characterized in that it further comprises the stages, which receive data on the actions of the employee in the time interval at which the presence of a deviation is determined; specifying the priority of the deviation in the process based on the data on the employee's actions in the time interval on which the presence of the deviation is determined; in this case, the aforementioned data are output to the manager's information output means, taking into account the data on the employee's actions and the specified priority of the deviation in the process. 4. The method according to claim 1, characterized in that it further comprises the stages at which data is obtained on the actions of the manager aimed at changing the value of the deviation in the process; determine the value of the effectiveness of the manager's actions aimed at changing the value of the deviation in the process; they correct or form and send a request for the need to adjust the rules of a typical process and a task aimed at changing the value of the deviation in the process, based on the value of the effectiveness of the leader's actions. - 9 038379 5. A data processing device for detecting and displaying deviations in the data of at least one process from the data characterizing the rules for performing a typical process, and tasks for their elimination, containing at least one computing device and at least one memory device containing machine-readable instructions which, when executed by at least one computing device, execute the method according to any one of claims 1 to 4.