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| Section | Weight | Objectives |
|---|---|---|
| Business Process Modeling | 20% | - Appian Process Concepts
|
| Appian Software Development Lifecycle (SDLC) | 22% | - Agile & Delivery Practices
|
| Requirements Gathering | 20% | - Documentation
|
| Introduction to the Appian Platform | 24% | - Platform Usage and Resources
|
| User Story Creation | 14% | - Agile Story Writing
|
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NEW QUESTION # 26
The Human Resources (HR) department is responsible for managing all job postings, and coordinating the onboarding and offboarding of team members. When a new hire joins the organization, they are asked to complete a number of documents by hand on their first day. These documents are then processed to ensure the employee is enrolled in benefits, has their paychecks set up, and has the needed hardware provided to them to complete their day-to-day activities. Currently, the process can take multiple days.
Which option illustrates the best opportunity for automation within the outlined process?
Answer: A
Explanation:
The best automation opportunity is C because it removes manual paper handling, starts the process before the employee's first day, captures information digitally once, and orchestrates downstream work across departments. Appian's delivery methodology emphasizes reviewing the current state to identify pain points and then defining application behavior that improves how users perform work; this scenario's pain points are handwritten forms, first-day delays, manual routing, and multi-day departmental processing.
Option C aligns with Appian process automation patterns: a secure digital form captures structured data, and submission initiates process tasks for HR, benefits, payroll, and IT. Appian tasks are used for users to input information into a running process, and process tasks can include deadlines so work can be tracked and prioritized. Follow-up reminders are also consistent with Appian escalation/notification behavior, where an action can occur when a task is not completed before a configured trigger.
Options A , B , and D digitize fragments but preserve manual coordination, rekeying, or delayed initiation.
Relevant topics: Process Automation Opportunities, Current-State Analysis, Future-State Design, User Input Forms, Task Assignment, SLAs, Escalations, and Appian Workflow Orchestration .
NEW QUESTION # 27
The order management team receives orders via different channels, including email. Emails are accompanied by attachments containing the details of the order information. The team reviews the emails and attachments for clarity. Then, they extract the order specifics to create a customer record in their Customer Relationship Management (CRM) platform and an order in their Order Management System (OMS).
What is the most effective form of automation to help increase fulfillment efficiency in this process?
Answer: B
Explanation:
The most effective form of automation to increase fulfillment efficiency in this process is using trained artificial intelligence (AI) to extract order data information from the emails and attachments. AI can be trained to recognize and extract key details such as customer names, order numbers, and product information directly from the content of the emails and attachments. This automation significantly reduces the manual effort required to review and input data, thereby speeding up the order processing time and reducing the chance of errors.
Reference: Appian Documentation - AI and Automation Capabilities
Note: The other options (B, C, D) provide minimal automation and would still require significant manual intervention, which does not effectively enhance fulfillment efficiency.
NEW QUESTION # 28
A partially created user story for an approval task has been added to the Product Backlog and you have been asked to review it.
So far, the user story includes acceptance criteria stating:
" Verify that the user can select approve or deny. "
" Verify that the user can enter an approval comment. "
What are two examples of additional content that need to be added to the user story before it can be considered complete?
Answer: A,D
Explanation:
User Story Description (B): A complete user story should include a detailed description that outlines the context, goals, and specific actions the user can perform. This helps in setting a clear understanding of what needs to be developed and why. The description provides the foundation for the user story and ensures that all stakeholders have a shared understanding of the requirement.
Reference: Appian Documentation - Writing User Stories
Condition upon Selecting Either " Deny " or " Approve " (A): To ensure that the user story is complete, you must specify what happens when the user selects " deny " or " approve. " This could include conditions such as sending notifications, triggering workflows, or updating statuses. Clearly defining these conditions ensures that the development team knows exactly what to implement and how the system should behave in different scenarios. Reference: Appian Documentation - Acceptance Criteria Examples
NEW QUESTION # 29
An organization wants to automate identification of its dissatisfied customers based on the ticket description and assign the appropriate team to provide a quick resolution.
What is the best way to auto-classify the dissatisfied customers as part of processing?
Answer: B
Explanation:
The organization aims to automate the identification of dissatisfied customers based on the ticket description.
To achieve this, leveraging natural language processing (NLP) capabilities is the most efficient method.
Appian provides connected systems that allow integration with external NLP services. These services can analyze text data (such as ticket descriptions) to determine the sentiment or classify the text into predefined categories (like "dissatisfied customer").
* Natural Language Connected System:
* Appian can integrate with third-party NLP platforms such as Google Cloud Natural Language, AWS Comprehend, or Azure Text Analytics via connected systems.
* These services analyze the text provided in the ticket description to detect sentiment, keywords, or specific categories indicating dissatisfaction.
* Based on the analysis, the system can automatically assign the appropriate team to handle the case.
* Why Not Other Options?:
* B. Decision Table: While decision tables are useful for rule-based decisions, they are not suitable for interpreting unstructured text like ticket descriptions.
* C. Image Analysis Connected System: This option is irrelevant as the task involves text processing, not image analysis.
* D. SAIL Form: SAIL forms are primarily used for user interface creation and are not intended for text analysis or classification.
* Implementation in Appian:
* Create a connected system to integrate with the chosen NLP service.
* Configure the NLP service to analyze the text data and return the sentiment or classification results.
* Based on the results, use process models to route the ticket to the appropriate team for resolution.
* References:
* Appian Documentation on Connected Systems: Appian Connected Systems
* Appian Community Success Guide:Appian Delivery Methodology
* Third-Party NLP Services Integration: Google Cloud NLP Documentation
NEW QUESTION # 30
During the development phase, a feature was identified that was not initially part of the project scope but is now considered crucial.
What should the Appian Analyst do?
Answer: B
Explanation:
Explanation:
NEW QUESTION # 31
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