---
title: "Overview - Price new jobs"
description: "Price New Jobs"
canonical_url: "https://support.pave.com/articles/overview-price-new-jobs-XCeXK8JUZz"
md_url: "https://support.pave.com/articles/overview-price-new-jobs-XCeXK8JUZz.md"
---
# Price New Jobs

Pricing new jobs is an end-to-end workflow that takes you from adding jobs to your band set through configuring market data mappings, applying data rules, and finalizing benchmark values.


---

## Table of Contents


1. Overview
2. The Complete Workflow
3. Step 1: Add Jobs to Band Set
4. Step 2: Configure Market Data Mappings
5. Step 3: Apply Data Rules
6. Step 4: Review and Finalize Benchmarks
7. Common Use Cases
8. Best Practices
9. Related Articles


---

## Overview

By the end of this workflow, your new jobs will have:

* ✅ Bands created in the band set (rows added)
* ✅ Market data mappings configured (job family → survey families)
* ✅ Data rules applied (how to calculate benchmarks)
* ✅ Benchmark values loaded (ready to inform compensation ranges)


---

## The Complete Workflow

**Full end-to-end flow:**


1. **Add jobs** → Create bands for new jobs in selected pay zones
2. **Configure mappings** → Map to survey job families and locations
3. **Apply data rules** → Set up benchmark calculation rules
4. **Review benchmarks** → Validate market data loaded correctly
5. **Set band ranges** → Use benchmarks to price the jobs (see **Edit Bands** articles)

This guide covers steps 1-4. After completing these steps, you'll be ready to set compensation ranges based on your benchmark data.


---

## Step 1: Add Jobs to Band Set

First, add the jobs you want to price to your band set. You can create jobs directly in the app or upload.

### Create New Ladder In-App

**When to use:** Adding a brand new job ladder that doesn't exist yet (e.g., expanding to a new function or creating a new family).

**From Job Manager:**


1. Navigate to **Jobs** tab (Job Manager)
2. Click **Create Job**
3. Enter the pay zone and ladder details:

* **Function** - Department (e.g., Engineering, Sales)
* **Family** - Specialization (e.g., Backend Engineering, Field Sales)
* **HRIS Matcher (based on your matchers)**


4. **Pave pre-populates levels based on standard job architecture structure**

* Typically creates P1, P2, P3, P4, P5, etc.
* You can edit, add, or remove levels on this page


5. For each level, configure:

* **Display title** (optional)
* **HRIS matchers** (HRIS level, HRIS title, HRIS job code)
* **Display levels and ranks**

**Example:**

```
Creating Finance > AI > IC ladder:
1. Function: Finance
2. Family: AI
3. Track: IC
4. Pave pre-populates: P1, P2, P3, P4, P5
5. Select pay zones: Brazil, San Francisco
Result: 10 new bands (5 jobs × 2 pay zones) ready for pricing
```

See **Add Bands** article for details on the pre-populate workflow.


---

## Step 2: Configure Market Data Mappings

After adding jobs, map them to survey data sources so Pave knows the survey job codes to pull benchmarks.

### Navigate to Mappings

From your band set:


1. Click the breadcrumb or navigate to **Mappings** tab
2. Click **Ladders** in the left sidebar

### Accessing Mappings from Job Creation Flow

After creating jobs in-app or activating a ladder, you can move directly into mapping:


1. **From Add Job flow** - After creating the ladder, select "Move to benchmarking"
2. **From the band set** - Click **Add Mapping** button which directs you to the specific ladder that needs the mapping added

Map each ladder:


1. Find your ladder in the list
2. For each survey source (Mercer, Pave, etc.):

* Click the **Label** field
* Select the matching survey job family
* Set the **Weight** (typically 1)


3. Repeat for all survey sources
4. Click **Save and regenerate benchmarks**

### Mapping Levels

After mapping ladders, map levels:


1. Click **Levels** in the left sidebar
2. Map your job levels/ranks to survey seniority levels
3. Save

### Mapping Pay Zones

Map your pay zones to survey geographies:


1. Click **Pay Zones** in the left sidebar
2. For each pay zone, map to survey location cuts
3. Example: San Francisco → "San Francisco Bay Area", "United States - West Coast"
4. Save

See **Job Mapping** article for detailed mapping instructions.


---

## Step 3: Apply Data Rules

Data rules control how benchmark data is calculated from your survey sources. Associate your new jobs with data rules.

### Navigate to Benchmarking Tab


1. Go to **Benchmarking** tab in your band set
2. Navigate to the new jobs you just added
3. Click **Apply data rules** button in the toolbar

### Choose Data Rule Option

**Option 1: Add to existing rule** (Recommended)

If you already have a data rule for similar jobs:


1. Select **Add to existing rule**
2. Choose the rule from the list (e.g., "Data Rule 3")
3. Click **Apply**

The new jobs will use the same benchmarking configuration as other jobs in that rule.

**Option 2: Create new rule**

For jobs that need different benchmark logic:


1. Select **Create new rule**
2. Configure:

* **Name the rule:** e.g., "Account Management - Brazil"
* **Select survey sources:** Choose which surveys to use
* **Choose percentile targets:** P25, P50, P75, or custom
* **Configure fallbacks:** What to do when survey data is missing


3. Click **Apply**

**Option 3: Duplicate existing rule**

Copy an existing rule's configuration and modify:


1. Select **Duplicate existing rule**
2. Choose which rule to copy
3. Modify any surveys or percentiles
4. Click **Apply**

See **Data Rules** article for detailed configuration options.

### Regenerate Benchmarks for New Jobs Only

This feature allows you to regenerate matches only for added/updated jobs, so you don't lose previous benchmark edits.

**From the Benchmarking tab:**


1. After adding new jobs and configuring mappings/data rules
2. Click **Regenerate benchmarks**
3. Choose regeneration scope:

* **Only for updated jobs** (recommended) - Preserves existing benchmark edits
* **All jobs** - Full refresh

This prevents accidentally overwriting manual benchmark adjustments you've made to existing jobs while ensuring new jobs get the latest data.


---

## Step 4: Review and Finalize Benchmarks

After applying data rules, review the benchmark values to ensure they're correct.

### Check Benchmark Status

In the Benchmarking tab, look for status indicators:

**✅ Has Benchmark (Green)**

* Benchmark loaded successfully
* Shows benchmark value (e.g., R$227,949.95)
* Shows progression percentage (e.g., 14%, 33%)

**⚠️ No Data (Red/Gray)**

* Survey doesn't have data for this job
* Need to adjust mapping or use different survey

**⚠️ Missing Mapping**

* Job family mapping incomplete
* Go back to Step 2 and complete mappings

**⚠️ Missing Data Rule**

* Data rule not applied
* Go back to Step 3 and apply data rule

### Use the Benchmarking Sidepeek

Click any job to open the sidepeek and review:

**Benchmark value:**

* The composite benchmark (weighted average)
* Visual range showing P25/P50/P75

**Contributing data sources:**

* Each survey source with its value
* Sample size for each
* Weight applied
* How the composite is calculated

**Auto-smoothing indicator:**

* If auto-smoothed, shows "Auto-smoothed" badge
* Link to "Revert this job to Composite to adjust weighting"

**Quality checks:**

* Are sample sizes adequate? (>20 is good, <20 is questionable)
* Are values consistent across surveys?
* Does the benchmark make sense for this role?

### Fill Data Gaps (If Needed)

See **Auto-Smoothing** and **Benchmarks Edits** articles for details.

## What's Next?

After pricing new jobs with benchmark data, you're ready to:


1. **Set band ranges** - Use benchmarks to define min/mid/max compensation (see **Edit Bands** articles)
2. **Assign to grades** - If using grades, slot jobs into your grade structure (see **Edit Bands & Assign Jobs to Grades**)
3. **Review impact** - See how many employees fall within the new bands
4. **Publish** - Push bands live or to a merit cycle (see **Publish** articles)


---