Welcome to the first article in a series of five where I will share how to use ServiceNow’s Predictive Intelligence (PI) to improve the employee-agent HR experience. Predictive Intelligence is an in-platform machine learning capability that can drive following outcomes: reduce case hop by predicting the right place to send work, recommend solutions to help agents solve cases faster, find patterns that may be impacting your process, identify gaps in your knowledge base, and prevent profanity in our agent-requestor interactions.

In the five articles I’ll show you how to configure, train, use, and troubleshoot some of the most common Predictive Intelligence use cases for HR. Each article contains a mini lab with steps that you should be able to use in your San Diego instance.

Article 1 - Auto determination of HR Assignment Group

Article 2 - Use similarity to help agents solve issues faster

Article 3 - Find patterns using clustering

Article 4 - Use Knowledge Demand Insights to find gaps in your knowledge base

Article 5 – Watch agent language with Profanity filtering

Article 6- Tuning Predictive Intelligence Models (part 5) – Regression

DISCLAIMER - This article series is ambitious as I would have preferred to use a controlled Knowledge lab as a teaching platform. In a lab environment all my screen shots would correspond to your results. Because you are using your instance, your results will vary because your data is different than my data. My hope is that you’ll be able to follow along with your instance and replicate these results. If you run into issues, you can (1) post them here (2) open a support case (3) reach out to your ServiceNow HR sales team for assistance.

These articles are not exhaustive. For an overview of Predictive Intelligence for HR please see this video. For additional instructions on other HR PI uses cases please see the San Diego Predictive Intelligence for HR documentation.

REFERENCE - These labs are meant to get you results quickly, so I don’t go into detail explaining each step in the labs. I’ve skipped explaining each step because cover those details in other Knowledge Courses and articles. For example, if you would like to understand what a word corpus is or how clustering works you’ll want to head over to the below NowLearning courses that I’ve listed and invest some time there.

NowLearning Courses:

K21 Accelerate Incident Resolution for Agents using AI/ML and Flow Designer

Predictive Intelligence Advanced Topics

K20 Accelerate Incident Resolution with Predictive Intelligence and Agent Workspace

Before you can get started.

1. The lab assumes you are using a sub-prod San Diego instance cloned from production and you have basic experience using HR Case Management on ServiceNow.2. Your user id needs to be assigned the hr_admin & ml_admin roles in your sub-prod instance. Ask you administrator to confirm that you have these roles.3. You need to have a minimum of 10k cases in your sn_hr_core_case table. You can check if you meet this requirement by going to all > application filter > sn_hr_core_case.list

4. The following plugins should be installed by your admin:

• Human Resources Scoped App: Core
• Predictive Intelligence
• Predictive Intelligence Workbench
• Predictive Intelligence Workbench HRSD Content
• Predictive Intelligence for Contextual Search
• Predictive Intelligence for Knowledge Management
• Predictive Intelligence for Universal Request

5. Your admin should set the below system properties to true. These properties enable the Auto Determination HR capabilities. If these properties do not exist create them.

• sn_hr_core.case_auto_assignment set to true
• glide.platform_ml.auto_training.enabled set to true

Lab 1 - Auto determine the HR Assignment group in HR Agent Workspace

We will use Predictive Intelligence to auto determine (aka predict) the assignment group from a case after the employee enters a short description. Predictive Intelligence “learns” from past cases to predict how to route future cases. Using machine learning in this way is useful to reduce the dependency on assignment rules and to reduce the amount of case hop due to sending work to the wrong team (for example a payroll issue getting sent to benefits).

Configure & Train Auto determination

1. All > Predictive Intelligence Homepage2. Expand the Classification carrot3. Scroll down to Auto assignment group for HR Cases

4. Click Train

5. Your PI solution may take up to 30minutes to train depending on the size of your data. When the PI solution is finished training it will have a [Version: #] next to it.

See Auto Determination in Action in HR Agent Workspace

1. Impersonate a HR user (preferably a HR agent). In my instance I impersonate Harry Taylor.2. Go to All > Agent Workspace for HR Case Management3. Under All HR Cases click assigned to me.

4. Create a new case, by clicking New

5. Select a new employee, in my case this is Abel Tuter.

6. Click Next

7. Populate the case details with valid information relevant to YOUR SYSTEM. In my instance I use COE = HRIT Total Rewards Case HR Service = Dental Benefits Inquiry

Work Notes = I have a question about my dental benefits

8. Click Create Case

9. If PI was able to make a prediction with high confidence a blue box with the assignment group prediction will show on the case form. At this point the agent can decide if they want to go with the prediction from Predictive Intelligence or stay with the default prediction.

10. In this case let’s change the assignment group and use the prediction. Click into the Assignment group field and change from HR Tier 1 to HR Benefits and hit Save.

Congrats you’ve finished learning about how use machine learning to route work to the right place!

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