Patent Publication Number: US-2019180206-A1

Title: Conversation-driven workflow

Description:
BACKGROUND 
     The present invention relates to workflow processes, and more specifically, to how to initiate, track and progress workflow processes and exceptions in a workflow processing system. 
     Workflow provides structure to business processes through the creation of flowcharts and rules representing the steps of the process and decision points. Individuals are then able to create and progress workflow processes by advancing, approving, rejecting, initiating exceptions, etc. While workflows enforce rules and provide structure and consistency, which are crucial to repeatable business processes, they also require users to leverage workflow tools and actions to perform user-initiated state transitions and when initiating exceptions, to manually control, modify or diverge from the workflow. This is often cumbersome, often requires additional actions to advance the flow in addition to any workflow related collaboration or conversation, and requires training of users in the particular workflow product and interface. 
     SUMMARY 
     According to one embodiment of the present invention, methods, systems and computer program products are provided for managing a workflow. A natural language classification engine collets a first set of natural language data that indicates a workflow process. Based on the first set of natural language data, a workflow process action is identified. A second set of natural language data that indicates a workflow process action response is collected. Based on the workflow process action response, a workflow progression operation is determined. The workflow progression operation is executed to progress the workflow process. 
     The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features and advantages of the invention will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows an example of a basic workflow  100  in accordance with one embodiment. 
         FIG. 2  shows a schematic block diagram of a system  200  in accordance with one embodiment. 
         FIG. 3  shows an exemplary configuration of a computer  1900  in accordance with one embodiment. 
     
    
    
     Like reference symbols in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
     The various embodiments of the invention pertain to techniques for initiating, tracking and progressing workflow processes and exceptions, by using natural language and human conversation to eliminate the need for most users to interact with the underlying workflow process and workflow tooling. The actual workflow process is still created and advanced to ensure that business rules and tracking are enforced, but this is done implicitly based on natural language that represents common workflow actions (and that can also be extended with specific domain or other language to expand beyond just universal workflow-related terminology). 
     As a high-level example, in a discussion channel where a conference of interest is being discussed, a user saying “I&#39;d like to go to this conference” could initiate a travel approval workflow, bringing in that user&#39;s appropriate approvers—but by bringing them into the conversation (whether the core conversation or a side branch) where they can then converse in natural language with the requester while that language is used to advance through travel approval steps. On approval (also natural language, such as the approver indicating “yes, I think you should go”), the workflow engine can then post in the conversational interface any necessary workflow approval information, and the users have had no interaction with the workflow system. 
     In some embodiments, this system can be extended to handle workflow exceptions as well by either capturing language specific to exceptions (e.g.—“I&#39;ll need additional data to handle this”) or by having workflow limits trigger actions in the conversation space (e.g. —exceeding a cost limit automatically brings in a higher-level approver to the conversation stream with the workflow agent/bot posting an explanation in the conversation such as “John has been added because the cost exceeds the $100K threshold, requiring VP approval”). 
     When needed, the workflow can be halted until the conversation indicates that the exception has been handled. Since the workflow is still being tracked under the covers/hidden from the users, all rules are still enforced and results are tracked in normal business systems. As appropriate, the workflow agent could optionally interject explanations or guidance, but this is done while still avoiding user interaction with the workflow system itself, within the conversation flow. 
     Workflows consist of states, state transitions, rules and user actions. All of these have corresponding natural language, which can be implemented in a classifier to capture text (or speech) that maps to a common set of actions and questions. This begins with a set of basic workflow actions and the language commonly used to indicate (1) a request/task initiation, approval, rejection, completion, (2) common questions that map to data or content related to the workflow, and (3) phrasing which represents initiation and handling of exceptions. 
     This allows the system to identify workflow transitions and actions which can then be mapped to state transitions. The initiation of a specific workflow can either be done through language indicating that workflow or by having a particular conversation channel mapped to a particular process. An example of the latter would be a support channel where new entries/requests create a problem ticket or support flow that can subsequently be progressed. An example of the former would add appropriate phrasing to workflows to help the system identify the appropriate flow to initiate (e.g.—for travel approval, phrasing referring to “attend a conference”, “visit a customer”, etc.) which could then be implemented in multiple channels. This is then implemented through standard natural language classifiers to identify appropriate processes. 
     Various embodiments will now be described by way of example and with reference to the figures.  FIG. 1  shows an example of a basic workflow  100  for requesting a new laptop. As can be seen in  FIG. 1 , the workflow  100  starts by an employee initiating a request, step  102 . It is then determined if the laptop is more than two years old, step  104 . If the laptop is more than two years old, a request is sent to the employee&#39;s manager for approval, step  106 . If the manager approves the request, requisition of a new laptop is initiated, step  108 , and the requisition process ends. If the manager does not approve the requisition in step  106 , the process ends. 
     If it is determined in step  104  that the laptop is less than two years old, approval is also needed from a second level manager. Therefore, a request is first sent to the employee&#39;s manager for approval, step  110 . If the manager does not approve the request, the process  100  ends. If the manager approves the request in step  110 , the request is forwarded to the second level manager, step  112 . If the second level manager also approves the request, the request is initiated, step  108 , and the process  100  ends. However, if the second level manager does not approve the request, the process  100  ends. 
     The conversation stream corresponding to the workflow process of  FIG. 1  might look as follows in a channel in which the employee (Joe) and his manager (Sue) are in:
         Joe: “Sue, I need to get a new laptop, mine is too slow.”   Sue: “OK—I approve that.”   &lt;workflow system&gt;: “Joe&#39;s laptop is less than 2 years old. Adding second line manager Fred for review.”   Fred: “Joe, why do you need a new laptop when yours is not that old?”   Joe: “New project requires a more powerful system than I have.”   Fred: “OK—I agree.”       

     In this example, the workflow process was initiated and followed but from the users&#39; perspective, they simply had a conversation. By the system understanding phrases like “get a new laptop,” “I approve,” and “I agree,” there was no need to interact with the workflow process or tooling, but its rules and process were fully implemented. In addition, since this occurs in a conversation stream, it is much faster and efficient compared to using a separate tool and also (when appropriate) more broadly visible. 
     To continue the above example, the workflow system may then continue the dialog with Joe and potentially other users to fulfill the request for the laptop, for example, as follows:
         &lt;workflow system&gt;: “Joe, your laptop request has been approved. We&#39;ve engaged Tom from procurement to assist with that. Tom will reach out to you for details.”   Tom: “Joe, based on our systems it looks like you qualify for one of the following systems: A, B, C. Let me know which one you prefer.”   Joe: “Tom, I&#39;d like to have system A. Thanks.”       

     It should be noted that while the process  100  has been described as a “single pass” process, typically this process would be running continuously during ongoing conversations and would continuously keep identifying workflow related topics and implement them. For example, there could be five approvals, 10 rules/triggers, two exceptions, etc. in a single conversation and several workflow processes could be initiated by the conversation. 
     Regarding exception handling, a simple example extending from the example above can be as follows, where exception language triggers such as “before proceeding” and “first check” trigger an exception which halts the workflow until the exception is resolved, and at which point it continues. An additional benefit of this handling is that the handling of the exception is documented in the conversation even though it is outside the normal processing of the workflow process (and would not have been maintained in that process without explicitly entering it in the workflow system, something that&#39;s unlikely to happen). For example, in the above example, assume Fred did not say “Ok—I agree,” But instead that the dialog would continue as follows:
         Fred: “Before proceeding we&#39;ve been asked by leadership to first check whether reclaimed/recycled hardware can fulfill new requests. Joe—please check that out. If not then I approve”   &lt;workflow system&gt;: “Placing ordering process on hold for exception: check whether reclaimed/recycled hardware can fulfill new requests”   Joe: “I&#39;ve checked and there isn&#39;t anything that meets my needs.”   &lt;workflow system&gt;: “Exception closed. Proceeding with order”       

     Architecturally, the above process can be implemented in a variety of systems that include some kind of collaboration tools. A schematic example of a system  200  in which the above techniques can be implemented is shown in  FIG. 2 . As can be seen in  FIG. 2 , the system  200  includes a conversation stream module  202 , a natural language classifier  204 , a general workflow classifier  206 , a domain-specific workflow classifier  208 , a workflow engine  214 , an internal services module  210  and an external services module  212 . It should be noted that while the components of the system  200  are shown as individual units, they may be combined in various ways and implement the same functionality that was described above with respect to the process  100  of  FIG. 1 . 
     The conversation stream module  202  is where the participants discuss in natural language and are being added as needed to route/approve requests, provide expertise, etc., as described above. The conversation stream module  202  effectively works as the “user interface” to the workflow process and may implement functionality similar to what is available in products such as Watson Workspaces or Slack. Watson Workspaces is available from International Business Machines Corporation (IBM) of Armonk, N.Y., and Slack is available from Slack Technologies Inc., of Vancouver, BC, Canada. In some embodiments, the workflow system is also enhanced to participate in the conversation when needed by mapping appropriate rules and actions in the workflow into actions in the conversation stream—such as adding an approver and notifying them, or noting decision criteria. 
     The natural language classifier  204  identifies intents and actions from human natural language in the conversation stream module  202 , as described above. The natural language classifier  204  is configured to capture and classify common workflow-related actions. Such classifiers can be built and implemented, for example, through a system such as Watson Natural Language Classifier, also available from IBM. This allows the system to map the workflow-related actions to workflow state transitions. In  FIG. 2 , there are two general types of classifiers; a general workflow classifier  206  and a domain-specific workflow classifier  208 . The general workflow classifier  206  captures terminology relating to general workflows, such as “flow,” “approval,” etc. The domain-specific workflow classifier  208  captures terminology relating to domain-specific workflow language, such as (in the case of auto insurance, for example) “getting repair estimates,” “extending car rental,” “retrieving police reports,” etc. As the skilled person realizes, in some cases, such requests are easy to map to content, but in various domain-specific processes, additional classifiers are needed to map common requests, and such classifiers can be implemented as needed. 
     The system  200  can communicate with various internal services  210  and external services  212  through a workflow engine  214  to obtain data that is needed to implement the workflow. For example, the internal services  210  can include claims forms, policies, etc., and the external services  212  can include medical information, police reports, email communications, etc. As the skilled person realizes, there is virtually an unlimited amount of internal and external services that can be connected to the workflow management system  200 . The workflow engine  214  accesses the internal services  210  and the external services  212  as needed to obtain the necessary data and to progress the workflow as needed. 
       FIG. 3  shows an exemplary configuration of a computer  1900  in accordance with one embodiment. The computer  1900  according to the present embodiment includes a CPU  2000 , a RAM  2020 , a graphics controller  2075 , and a display apparatus  2080  which are mutually connected by a host controller  2082 . The computer  1900  also includes input/output units such as a communication interface  2030 , a hard disk drive  2040 , and a DVD-ROM drive  2060  which are connected to the host controller  2082  via an input/output controller  2084 . The computer also includes legacy input/output units such as a ROM  2010  and a keyboard  2050  which are connected to the input/output controller  2084  through an input/output chip  2070 . 
     The host controller  2082  connects the RAM  2020  with the CPU  2000  and the graphics controller  2075  which access the RAM  2020  at a high transfer rate. The CPU  2000  operates according to programs stored in the ROM  2010  and the RAM  2020 , thereby controlling each unit. The graphics controller  2075  obtains image data generated by the CPU  2000  on a frame buffer or the like provided in the RAM  2020 , and causes the image data to be displayed on the display apparatus  2080 . Alternatively, the graphics controller  2075  may contain therein a frame buffer or the like for storing image data generated by the CPU  2000 . 
     The input/output controller  2084  connects the host controller  2082  with the communication interface  2030 , the hard disk drive  2040 , and the DVD-ROM drive  2060 , which are relatively high-speed input/output units. The communication interface  2030  communicates with other electronic devices via a network. The hard disk drive  2040  stores programs and data used by the CPU  2000  within the computer  1900 . The DVD-ROM drive  2060  reads the programs or the data from the DVD-ROM  2095 , and provides the hard disk drive  2040  with the programs or the data via the RAM  2020 . 
     The ROM  2010  and the keyboard  2050  and the input/output chip  2070 , which are relatively low-speed input/output units, are connected to the input/output controller  2084 . The ROM  2010  stores therein a boot program or the like executed by the computer  1900  at the time of activation, a program depending on the hardware of the computer  1900 . The keyboard  2050  inputs text data or commands from a user, and may provide the hard disk drive  2040  with the text data or the commands via the RAM  2020 . The input/output chip  2070  connects a keyboard  2050  to an input/output controller  2084 , and may connect various input/output units via a parallel port, a serial port, a keyboard port, a mouse port, and the like to the input/output controller  2084 . 
     A program to be stored on the hard disk drive  2040  via the RAM  2020  is provided by a recording medium as the DVD-ROM  2095 , and an IC card. The program is read from the recording medium, installed into the hard disk drive  2040  within the computer  1900  via the RAM  2020 , and executed in the CPU  2000 . 
     A program that is installed in the computer  1900  and causes the computer  1900  to function as an apparatus implementing the process  100  of  FIG. 1 , includes a natural language processing module. The program or module acts on the CPU  2000 , to cause the computer  1900  to function as one or more sections, components, or elements of the system  100  of  FIG. 2 . 
     The information processing described in these programs is read into the computer  1900 , to function as the determining section, which is the result of cooperation between the program or module and the above-mentioned various types of hardware resources. Moreover, the apparatus is constituted by realizing the operation or processing of information in accordance with the usage of the computer  1900 . 
     For example, when communication is performed between the computer  1900  and an external device, the CPU  2000  may execute a communication program loaded onto the RAM  2020 , to instruct communication processing to a communication interface  2030 , based on the processing described in the communication program. The communication interface  2030 , under control of the CPU  2000 , reads the transmission data stored on the transmission buffering region provided in the recording medium, such as a RAM  2020 , a hard disk drive  2040 , or a DVD-ROM  2095 , and transmits the read transmission data to a network, or writes reception data received from a network to a reception buffering region or the like provided on the recording medium. In this way, the communication interface  2030  may exchange transmission/reception data with the recording medium by a DMA (direct memory access) method, or by a configuration that the CPU  2000  reads the data from the recording medium or the communication interface  2030  of a transfer destination, to write the data into the communication interface  2030  or the recording medium of the transfer destination, so as to transfer the transmission/reception data. 
     In addition, the CPU  2000  may cause all or a necessary portion of the file of the database to be read into the RAM  2020 , such as by DMA transfer, the file or the database having been stored in an external recording medium such as the hard disk drive  2040 , the DVD-ROM drive  2060  (DVD-ROM  2095 ) to perform various types of processing onto the data on the RAM  2020 . The CPU  2000  may then write back the processed data to the external recording medium by means of a DMA transfer method or the like. In such processing, the RAM  2020  can be considered to temporarily store the contents of the external recording medium, and so the RAM  2020 , the external recording apparatus, and the like are collectively referred to as a memory, a storage section, a recording medium, a computer readable medium, etc. Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording apparatus, to undergo information processing. Note that the CPU  2000  may also use a part of the RAM  2020  to perform reading/writing thereto on the cache memory. In such an embodiment, the cache is considered to be contained in the RAM  2020 , the memory, and/or the recording medium unless noted otherwise, since the cache memory performs part of the function of the RAM  2020 . 
     The CPU  2000  may perform various types of processing, onto the data read from the RAM  2020 , which includes various types of operations, processing of information, condition judging, search/replace of information, etc., as described in the present embodiment and designated by an instruction sequence of programs, and writes the result back to the RAM  2020 . For example, when performing condition judging, the CPU  2000  may judge whether each type of variable shown in the present embodiment is larger, smaller, no smaller than, no greater than, or equal to the other variable or constant, and when the condition judging results in the affirmative (or in the negative), the process branches to a different instruction sequence, or calls a sub routine. 
     In addition, the CPU  2000  may search for information in a file, a database, etc., in the recording medium. For example, when a plurality of entries, each having an attribute value of a first attribute is associated with an attribute value of a second attribute, are stored in a recording apparatus, the CPU  2000  may search for an entry matching the condition whose attribute value of the first attribute is designated, from among the plurality of entries stored in the recording medium, and reads the attribute value of the second attribute stored in the entry, thereby obtaining the attribute value of the second attribute associated with the first attribute satisfying the predetermined condition. 
     The above-explained program or module may be stored in an external recording medium. Exemplary recording mediums include a DVD-ROM  2095 , as well as an optical recording medium such as a Blu-ray Disk or a CD, a magneto-optic recording medium such as a MO, a tape medium, and a semiconductor memory such as an IC card. In addition, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a recording medium, thereby providing the program to the computer  1900  via the network. 
     The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.