The Appian UX Design Guide is the appropriate resource to consult when making decisions about

layout choices like side-by-side versus column layouts. This guide provides best practices for

designing user interfaces in Appian applications, ensuring that the UI is intuitive, responsive, and

consistent with Appian's design principles. Referring to the UX Design Guide helps in making

informed

design

decisions

that

enhance

user

experience.

Reference: Appian UX Design Guide

Note: While other resources like Appian Tutorials, Discussion Boards, and SAIL Recipes are useful for

specific cases, the UX Design Guide is the primary reference for best practices in UI design.

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.

The status of the user story is Pending because it does not yet meet the team's Definition of Ready

(DoR). The filter criteria, which are critical to the functionality described in the user story, have not

been fully determined. Until this information is clarified, the story cannot be considered ready for

development

or

any

subsequent

phases

like

QA.

Reference: Appian Documentation - User Stories and Definitions of Ready

Note: The user story cannot be marked as Done (A), Ready for Development (B), or Ready for QA (D)

because it lacks critical details needed for development to proceed.

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.

Appian Documentation on Connected Systems: Appian Connected Systems

Appian Community Success Guide: Appian Delivery Methodology

Third-Party NLP Services Integration: Google Cloud NLP Documentation

Connecting to Database Management Systems (C): One of Appian's core capabilities is its ability to

connect with various database management systems. This allows for seamless data integration,

retrieval, and management, enabling applications to interact with databases like Oracle, MySQL, and

Microsoft

SQL

Server,

among

others.

Reference: Appian Documentation - Database Connections

Designing Effective User Interfaces by Combining Available UI Components (D): Appian provides a

wide range of UI components that can be combined to design effective and user-friendly interfaces.

This capability allows developers to create intuitive and interactive applications that meet user

requirements.

Reference: Appian Documentation - User Interface Design

Automating Business Processes with Complex Workflow (E): Appian excels in automating business

processes, especially those that involve complex workflows. Its workflow automation capabilities

allow for the orchestration of tasks, approvals, and other process activities, making it a powerful tool

for

process-driven

applications.

Reference: Appian Documentation - Workflow Automation

Note: Building highly-interactive reporting or data exploration applications (A) is possible in Appian,

but it's not the platform's primary focus. Accommodating applications that need to run completely

offline (B) is not one of Appian's core capabilities, as it is primarily designed for online, connected

applications.

For intelligent and automated routing of complex case types based on free text descriptions,

integrating with a Natural Language Processing (NLP) system is the most effective solution. NLP can

analyze the free text, understand the context, and categorize the cases based on the content,

enabling automated and accurate routing.

NLP System Integration Overview:

NLP systems can process and understand human language in text form, identifying key phrases,

sentiments, and categories.

By integrating with an NLP service, Appian can automatically route cases to the appropriate

department or user based on the analysis of the text provided by external users.

This approach reduces the need for manual review and ensures that cases are handled efficiently and

accurately.

Why Not Other Options?:

A . Manual Review Task: This does not automate the process and relies on human intervention,

which can be time-consuming and prone to error.

B . Find Functions for Keyword Search: This approach is limited to exact matches and lacks the

sophistication needed to understand complex language and context.

C . Translation Service Integration: While useful for language translation, it does not offer the

categorization and routing capabilities needed for this use case.

Appian Documentation on NLP Integration: NLP in Appian

Integrating an NLP system with Appian ensures that complex cases are categorized and routed with

high accuracy, improving the efficiency and effectiveness of case management.

The best opportunity for automation in the manual process described is to leverage Optical

Character Recognition (OCR) and workflow tools. OCR can automatically extract data from the

invoices received via email, and the workflow tools can automate the review process, checking the

data for accuracy, processing payments, and prompting employees only when exceptions are found.

OCR and Workflow Tools Overview:

OCR technology converts the text in scanned documents or images into machine-readable data,

which can be automatically processed.

Workflow tools in Appian can then route the extracted data through a series of steps, automating

tasks like data entry, validation, and payment processing.

Automating these steps reduces manual effort, minimizes errors, and ensures that invoices are

processed more efficiently.

Why Not Other Options?:

A . Robotic Process Automation (RPA) for thank you messages: This is a less critical part of the

process and does not significantly reduce manual work.

B . Creating a task for manual input: This still involves manual data entry, which does not fully utilize

automation potential.

C . Macro in the shared spreadsheet: This provides minimal automation and doesn't address the root

of the problem, which is manual data entry.

Appian Documentation on OCR Integration: OCR in Appian

Appian Workflow Automation Guide: Automating Processes in Appian

By using OCR and workflow tools, the organization can significantly reduce manual processing time

and increase the accuracy of invoice handling.

:

The "Start Process Link" in Appian is used to initiate a process directly from a site page. In this case,

when users press the link on the homepage, it should navigate them through the request forms

within the site. The Start Process Link is designed for scenarios where a new process instance needs

to be started, such as submitting a Statement of Work (SOW) request.

Start Process Link Overview:

This link type allows users to start a new process directly, leading them into the forms or steps

defined in the process model.

It is ideal for initiating workflows, such as submitting new requests or forms within an application.

Why Not Other Options?:

A . Authorization Link: Typically used for authorization or access control, not for starting a new

process.

B . Submit Link: Used for submitting forms within a process, not for starting a new process.

C . Dynamic Link: Provides general navigation or actions within an interface but does not start a

process.

Appian Documentation on Links: Using Links in Appian

The Start Process Link is the appropriate choice to navigate users through the request submission

forms in the application.

As an Appian Analyst, collaborating with a Product Owner during the creation of process models is

considered best practice. The Product Owner is responsible for defining the requirements and

ensuring that the process models align with the business goals and needs. The Product Owner has a

deep understanding of the product vision and user stories, which are crucial during the requirements

gathering phase.

Role of Product Owner:

The Product Owner provides detailed requirements and prioritizes them based on business needs.

They ensure that the process models being developed accurately reflect the intended business

processes and user stories.

Close collaboration with the Product Owner ensures that the process models are aligned with both

the technical and business aspects of the project.

Why Not Other Options?:

A . Product Manager: Typically focuses on the overall product strategy and market alignment rather

than detailed process modeling.

C . Architect: While architects provide valuable input on the system's design and architecture, they

are not primarily responsible for requirements gathering.

D . Scrum Master: The Scrum Master facilitates the Agile process but does not directly contribute to

defining or modeling business processes.

Appian Community Success Guide: The Role of Product Owner in Appian Projects