What is the Analytics and Data module?

These configurations pertain to custom attributes and configurations associated with EXI application filters. The primary functionality of such settings is to structure the data handling processes by defining the data model relevant to the custom attributes. This allows you to create a system that’s tailored according to your specific data management needs.

By customizing how the attributes associate with these data models, you improve the system’s ability to process, manage, and interpret data, making it more efficient. In essence, these configurations play a crucial role in streamlining your data management tasks, thus enhancing overall productivity.

Configuring Analytics and Data

Custom attributes

Documentation for Registry Registrations Fields

1. Model

   In the Registry Registrations, you’re required to select a data model. This could either be the User Data Model or the Knowledge Article Data Model.

   Example: If you want to store data related to users, you’d select the User Data Model.

   The Model field determines how your data will be structured and categorized in the system.

2. Attributes

   Custom attributes are additional parameters associated with the chosen data model.

   • Name: Enter the name of the Custom Attribute that you expect for the chosen data model. Ensure this field matches, case-sensitively, with the name in the external system.

     Example: If a user is associated with a VIP status in your system, you’d enter “is_vip” as a custom attribute.

   • Data Sensitivity Policy Policy Type: Select the type of sensitivity policy that the custom attribute should follow. The policy type option includes Customer Data.

     Example: If the custom attribute is dealing with sensitive user data, you’d select CUSTOMER_DATA_USER_DATA.

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The Registry Registrations tab allows you to register and manage data models within your system. It provides key details about chosen data models and their custom attributes, helping organize and structure your data efficiently. Importantly, it ensures data matches exactly with the information from the external system, streamlining any data-related processes you execute.

Application Config

/service-management/moveworks-setup/advanced-config-editor

Bot Insights Config

Documentation for Issue Resolution Efficiency Fields

1. Measuring Issue Resolution Efficiency within 24 Hours

   This denotes whether an issue is considered resolved if a user resets their password within 24 hours of receiving a password expiry notification.

   Example: If set to “true”, the system will include those instances where a user resets their password within 24 hours after receiving a notification about password expiry in calculating resolution efficiency.

2. Benchmark MTTR (Mean Time to Resolution)

   This represents the average time expected to resolve issues prior to the bot’s operation. This number is usually provided by the pre-sales team. The default value is 2820.

   Example: If the Benchmark MTTR is set to 2820, this means that, on average, it took 2820 minutes to resolve an issue before the bot was implemented.

3. Agent Minutes Saved per Resolution

   This shows the amount of agent time, in minutes, saved for each issue resolved by the bot. The default value is 48.

   Example: If the default value of 48 is used, with each bot resolution, you’re saving 48 minutes of an agent’s time.

4. Agent Minutes Saved per Ticket Accelerated

   This is the amount of agent time, in minutes, saved for each bot-accelerated ticket. The default value is 5.

   Example: If this field is set to 5, then for each ticket sped up by the bot, you’re saving 5 minutes of an agent’s time.

5. Agent Minutes Saved per Accurate Triage

   This represents the amount of agent time, in minutes, saved each time the bot accurately triages a ticket. The default value is 5.

   Example: If the default value of 5 is used, an accurate triage by the bot saves an agent 5 minutes.

6. Employee Productivity Factor

   This is the ratio of productive work time to total wait time for each issue resolution for each employee. The default value is 0.02.

   Example: If the default value of 0.02 is used, that means the productive work time makes up 2% of the total wait time in the resolution process per employee.

7. Interaction Resolution Acceleration Factor

   This stands for the portion of the original Time to Resolution (TTR) that becomes the new TTR because it benefits from issue acceleration and user interaction with the bot. The default value is 0.15.

   Example: If its value is set to 0.15, then 15% of the original TTR becomes the new TTR due to bot acceleration.

8. Employee Minutes Saved per Lookup

   This applies to the number of employee minutes saved per lookup operation. The default value is 1.

   Example: With the default value of 1, an employee saves one minute per lookup operation.

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Each of these fields helps ensure that the bot accelerates issue resolution and contributes towards increased agent and employee productivity by reducing resolution time and enhancing work efficiency. These factors are crucial in driving performance analytics and business outcomes.

Analytics Value Config

The Value Assumptions page lets you review and adjust the assumptions used to calculate the value your organization realizes from your Moveworks AI Assistant. Moveworks uses these assumptions to generate value reporting internally, which is then shared and reviewed with you. Adjusting them ensures that reporting reflects your organization’s actual costs and time savings.

Value Assumptions

Hourly Agent Salary

The dollar value of one hour of a service desk agent’s work. It can be derived from the annual salary of agents, or from the service desk contract value divided by the total number of service desk agents.
Example: If an agent’s yearly salary is $62,400, their hourly wage would be$30 (assuming a 40-hour week over 52 weeks).

Hourly Employee Salary

The dollar value of one hour of an employee’s productive time. It can be derived from revenue per employee or salary per employee.
Example: An employee earning an annual salary of $124,800 will have an hourly value of$60.

Additional Controls

These assumptions capture the time saved when employees and operators use your AI Assistant instead of raising or handling a ticket. All time savings in this section are measured in minutes.

Operator Time Savings

• Operator time savings for ticket information (minutes): Time saved by operators when end users retrieve ticket information through the AI Assistant.
• Operator time savings for form finding (minutes): Time saved by operators when end users find forms through the AI Assistant.
• Operator time savings for ticket interactions (minutes): Time saved by operators when end users interact with tickets through the AI Assistant.

End User Time Savings

• End user time savings for search ticket deflections (minutes): Time saved by end users when a ticket-eligible search is answered directly by the AI Assistant.
• End user time savings for ticket information (minutes): Time saved by end users when retrieving ticket information.
• End user time savings for form finding (minutes): Time saved by end users when finding forms.
• End user time savings for people and room lookups (minutes): Time saved by end users when looking up people and rooms.
• End user time savings for approval information (minutes): Time saved by end users when retrieving approval information.
• End user time savings for group information (minutes): Time saved by end users when retrieving group information.
• End user time savings for file search (minutes): Time saved by end users when searching for files.
• End user time savings for action ticket deflections (minutes): Time saved by end users when a ticket-eligible action is completed directly by the AI Assistant.
• End user time savings for ticket interactions (minutes): Time saved by end users when interacting with tickets.
• End user time savings for approvals (minutes): Time saved by end users when performing approvals.
• End user time savings for email writing (minutes): Time saved by end users when writing emails with the AI Assistant.
• End user time savings for text translation (minutes): Time saved by end users when translating text with the AI Assistant.

Agent Tickets Handled Annually

The number of tickets handled by a single service desk agent per year. Used to translate time savings into agent-capacity terms in value reporting.