SuiteAnalytics Workbook: Building Advanced Reports in NetSuite

SuiteAnalytics Workbook is NetSuite's modern reporting and data visualization tool. It gives you a drag-and-drop interface for building datasets, pivot tables, and charts without writing a single line of code. If you have ever hit the limits of Saved Searches for complex analytics, Workbook is your next step up.

What Is SuiteAnalytics Workbook?

SuiteAnalytics Workbook is a built-in NetSuite analytics tool that sits alongside Saved Searches and SuiteAnalytics Connect. It was introduced to address the growing need for self-service business intelligence directly inside NetSuite, without requiring third-party tools.

At its core, a workbook has three components:

• Datasets -- the foundation layer where you select records, fields, joins, and filtering criteria
• Pivot tables -- summarized views of your data with rows, columns, and calculated measures
• Charts -- visual representations of your pivot table data

Think of a workbook as a structured pipeline: you define the raw data first, then slice and summarize it, then visualize the results.

Workbook vs. Saved Search: Key Differences

Before diving in, it helps to understand where Workbook fits relative to Saved Searches, since both are native reporting tools.

Capability	Saved Search	SuiteAnalytics Workbook
Record selection and filtering	Yes	Yes
Formula columns (SQL syntax)	Yes	No (uses built-in calculated measures)
Drag-and-drop pivot tables	No	Yes
Built-in charting	Limited (summary only)	Full charting engine
Conditional formatting	Row-level highlighting	Cell-level, gradient, and threshold rules
Multiple visualizations per report	No	Yes (multiple pivots and charts per workbook)
Scheduling and email delivery	Yes	Yes
Available as SuiteScript data source	Yes	No
Embedding in dashboards	Yes (portlet)	Yes (portlet)
Cross-record joins	Yes (but limited UI)	Yes (visual join builder)

The short version: Use Saved Searches for quick lists, formula-driven columns, and scripting. Use Workbook for multi-dimensional analysis, pivot tables, and visual dashboards.

Enabling SuiteAnalytics Workbook

Workbook is available in most NetSuite editions, but it must be enabled:

1. Navigate to Setup > Company > Enable Features
2. Go to the Analytics subtab
3. Check SuiteAnalytics Workbook
4. Click Save

Once enabled, you will find workbooks under Analytics > Workbook in the main navigation. If you do not see this menu item, confirm that your role has the SuiteAnalytics Workbook permission (under Reports permissions in role configuration).

Creating Your First Workbook

Let's walk through building a workbook from scratch.

Step 1: Start a New Workbook

1. Navigate to Analytics > Workbook > New Workbook
2. You will see the workbook editor with three tabs along the bottom: Data, Pivot, and Chart
3. The workbook opens on the Data tab by default

Step 2: Name Your Workbook

Click the default name at the top left (usually "Untitled Workbook") and give it a meaningful name. For this walkthrough, name it "Monthly Revenue Analysis."

Step 3: Choose Your Record Type

On the Data tab, you will see a prompt to select a record type. This is the primary record that drives your dataset.

1. Click Add record type
2. Search for and select Transaction
3. The field selector panel appears on the left

This is equivalent to choosing the search type in a Saved Search, but the Workbook interface makes it easier to explore available fields and relationships.

Building Datasets

The dataset is the foundation of every workbook. It determines which records and fields are available for analysis.

Selecting Fields

After choosing your record type, add fields to the dataset:

1. In the left panel, expand the Transaction field group
2. Click fields to add them to the dataset grid. For a revenue analysis, add:
   • Date (transaction date)
   • Type (transaction type)
   • Amount
   • Status
   • Entity (customer)
3. Each selected field appears as a column in the dataset preview

You can drag columns to reorder them, and the preview updates in real time.

Joining Related Records

One of Workbook's strengths is its visual join builder. To pull in fields from related records:

1. In the left panel, notice the relationships listed below the Transaction fields (for example, Customer, Item, Subsidiary)
2. Click a relationship such as Customer to expand it
3. Select fields from the related record, such as Category, Territory, or Sales Rep

Each relationship creates a join. You can chain joins -- for example, Transaction > Customer > Sales Rep > Department -- to reach deeply nested data. The visual layout makes it clear which record each field comes from.

Adding Criteria (Filters)

To filter the dataset:

1. Click the Conditions area at the top of the Data tab (or the filter icon)
2. Click Add condition
3. Choose a field, an operator, and a value. For example:
   • Type is Invoice
   • Date is within This Year
   • Posting is Yes
4. You can group conditions with AND/OR logic by clicking the connector between conditions

Conditions work the same way as Saved Search criteria, but the visual builder makes complex condition groups easier to manage.

Previewing Data

The bottom half of the Data tab shows a live preview of the dataset results. You can scroll through records, sort by clicking column headers, and verify that the data looks correct before moving on to pivots and charts.

Pivot Tables

Pivot tables are where Workbook truly shines. They let you summarize, group, and cross-tabulate data without any formula syntax.

Creating a Pivot Table

1. Click the Pivot tab at the bottom of the workbook editor
2. If no pivot exists yet, click Create Pivot
3. The pivot editor appears with four drop zones: Row, Column, Measures, and Filters

Configuring Rows

Rows define how data is grouped vertically:

1. Drag a field from the field list into the Row zone. For example, drag Customer: Category to group revenue by customer segment
2. You can add multiple row fields for nested grouping. Add Customer: Name below Category to see individual customers within each segment
3. Each row field creates an expandable hierarchy in the pivot output

Configuring Columns

Columns create horizontal groupings:

1. Drag a date field like Date into the Column zone
2. Workbook automatically offers date granularity options: Year, Quarter, Month, Week, or Day
3. Select Month to see revenue broken out by month across the top of the pivot

Combining row and column fields creates a cross-tabulation. For example, Customer Category in rows and Month in columns produces a matrix showing revenue per segment per month.

Adding Measures

Measures are the numeric aggregations that fill the cells of the pivot table:

1. Drag Amount into the Measures zone
2. By default, Workbook sums numeric fields. Click the measure to change the aggregation to Count, Average, Maximum, Minimum, or Median
3. You can add multiple measures. For example, add Amount as both Sum and Count to see total revenue and transaction count side by side

Calculated Measures

For derived metrics, you can create calculated measures without writing formulas:

1. Click the + icon in the Measures zone and select Add calculated measure
2. Give it a name, such as "Average Order Value"
3. Use the expression builder to define the calculation. For example, select Sum of Amount divided by Count of Amount
4. The calculated measure appears alongside your other measures in the pivot

This is the Workbook equivalent of formula columns in Saved Searches, but done through a point-and-click interface.

Sorting and Ranking

You can sort pivot results:

1. Click any measure header in the pivot output to sort by that measure
2. For ranking, right-click a measure and choose Rank to add a rank column that shows each row's position

Chart Types and Visualization

Charts in Workbook transform your pivot data into visual form.

Creating a Chart

1. Click the Chart tab at the bottom of the workbook editor
2. Select the pivot table that should feed the chart (if you have multiple pivots)
3. Workbook renders a default chart based on your pivot structure

Available Chart Types

Workbook supports a variety of chart types. Select the chart type from the toolbar:

• Bar chart -- horizontal bars, good for comparing categories
• Column chart -- vertical bars, ideal for time-series comparisons
• Line chart -- trend lines, best for showing change over time
• Area chart -- filled line chart, useful for volume trends
• Pie / Donut chart -- proportional breakdown of a single measure
• Scatter plot -- relationship between two numeric measures
• Combo chart -- combine bars and lines in a single visualization (for example, revenue as bars and order count as a line)

Customizing Charts

Once a chart type is selected, you can adjust:

• Title and subtitle -- click the chart title area to edit
• Axis labels -- click an axis to rename or format it
• Legend position -- drag the legend or use chart settings to move it
• Colors -- click a series in the legend to change its color
• Data labels -- toggle on/off to show values directly on bars or points
• Stacking -- for bar and column charts, choose stacked or grouped layout

Multiple Charts per Workbook

A single workbook can contain multiple pivots and multiple charts. This means you can build a complete analytics dashboard inside one workbook. For example, one chart showing revenue trends and another showing customer acquisition in the same workbook.

To add another visualization, click the + icon on the Chart tab and select Add chart.

Conditional Formatting

Conditional formatting helps you spot important patterns at a glance.

Applying Conditional Formatting to Pivots

1. In the Pivot tab, right-click a measure column header
2. Select Conditional Formatting
3. Choose a formatting type:
   • Threshold -- define ranges with colors (for example, red below $10,000, yellow between $10,000 and $50,000, green above $50,000)
   • Gradient -- apply a color scale from low to high values
   • Icon set -- show arrows, flags, or traffic lights based on value ranges

Highlighting Rules

You can set up multiple rules on the same measure. For example:

• Revenue cells below target: red background
• Revenue cells at or above target: green background
• Zero-value cells: gray text

Conditional formatting updates automatically as the underlying data changes, making it useful for dashboards that are viewed regularly.

Practical Examples

Example 1: Revenue by Customer Segment with Trend Analysis

Goal: Analyze monthly revenue by customer segment to identify trends and top-performing segments.

Dataset setup:

1. Record type: Transaction
2. Fields: Date, Amount, Type, Customer: Category, Customer: Name
3. Conditions: Type is Invoice, Date is within Last 12 Months, Posting is Yes

Pivot configuration:

1. Rows: Customer: Category
2. Columns: Date (set to Month granularity)
3. Measures: Sum of Amount

Chart configuration:

1. Chart type: Line chart
2. Each customer category becomes a separate line
3. The X-axis shows months, the Y-axis shows revenue
4. Enable data labels on the final data point of each line to show the latest month's figure

What to look for: Identify segments with upward or downward trends. Segments with declining lines may need attention from your sales team. Segments with consistent growth validate your go-to-market strategy.

Example 2: Inventory Aging Report with Pivot Breakdown

Goal: Understand how long inventory has been sitting on the shelf, broken down by item category and location.

Dataset setup:

1. Record type: Item
2. Fields: Name, Display Name, Type, Item: Category, Location, Quantity On Hand, Last Purchase Date
3. Conditions: Quantity On Hand is greater than 0, Type is Inventory Item

Pivot configuration:

1. Rows: Item: Category, then Item: Name (nested)
2. Columns: Create a calculated field or use a date-based grouping to bucket items into aging ranges (0-30 days, 31-60 days, 61-90 days, 90+ days since last purchase)
3. Measures: Sum of Quantity On Hand, Count of Items

Chart configuration:

1. Chart type: Stacked bar chart
2. Each bar represents an item category
3. Segments within each bar represent aging buckets
4. Color code: green for 0-30 days, yellow for 31-60, orange for 61-90, red for 90+

What to look for: Categories with a high proportion of red (90+ days) segments indicate slow-moving inventory that may need markdowns or promotions. This report helps procurement teams adjust reorder points and purchasing decisions.

Example 3: Sales Pipeline Visualization

Goal: Visualize the sales pipeline by stage, showing deal count and total value.

Dataset setup:

1. Record type: Opportunity
2. Fields: Title, Entity (Customer), Sales Rep, Status, Probability, Projected Total, Expected Close Date
3. Conditions: Status is not Closed Lost, Expected Close Date is within Next 90 Days

Pivot configuration:

1. Rows: Status (pipeline stage)
2. Measures: Sum of Projected Total, Count of Opportunities, Average Probability

Chart configuration:

1. Chart type: Combo chart
2. Bars represent Sum of Projected Total per stage
3. A line overlays the Average Probability per stage
4. Sort stages in pipeline order (Qualification > Proposal > Negotiation > Closed Won)

What to look for: A healthy pipeline should have more value in early stages than late stages (the funnel shape). If your Negotiation stage has more value than Qualification, you may have a prospecting problem. The probability line should trend upward from left to right.

Sharing Workbooks

Workbooks support granular sharing controls.

Sharing with Roles

1. Open the workbook and click the Share button (or the sharing icon in the toolbar)
2. In the sharing dialog, click Add Role
3. Select the role(s) that should have access
4. Set the permission level:
   • View -- can see the workbook but not edit it
   • Edit -- can modify the workbook structure and layout
5. Click Save

Sharing with Individual Users

1. In the same sharing dialog, click Add User
2. Search for and select specific users
3. Set View or Edit permissions
4. Click Save

Audience Restrictions

When you share a workbook, the data each user sees is still governed by their NetSuite role permissions. If a user does not have access to certain subsidiaries or transaction types, those records are automatically excluded from their view of the workbook. You do not need to build separate workbooks for different roles -- NetSuite handles data-level security automatically.

Scheduling and Exporting

Scheduling Workbook Delivery

You can schedule workbooks to be emailed on a recurring basis:

1. Open the workbook
2. Click Schedule in the toolbar
3. Configure the schedule:
   • Frequency: Daily, Weekly, Monthly, or a custom schedule
   • Recipients: Select roles, users, or enter email addresses
   • Format: PDF or Excel
   • Time: Choose when the report should be generated and sent
4. Click Save Schedule

Scheduled workbooks run with the permissions of the user who created the schedule, so make sure that user has access to the relevant data.

Exporting on Demand

For one-time exports:

1. Open the workbook
2. Navigate to the Pivot or Data tab (depending on what you want to export)
3. Click the Export icon in the toolbar
4. Choose your format:
   • CSV -- raw data, useful for importing into other tools
   • Excel -- formatted spreadsheet with pivot structure preserved
   • PDF -- print-ready format, good for sharing with stakeholders who do not have NetSuite access

Tips for Performance with Large Datasets

Workbook performance depends on the size of your dataset and the complexity of your pivots. Follow these guidelines to keep things running smoothly.

Limit Your Dataset Early

• Apply conditions (filters) on the Data tab to reduce the number of records before they reach the pivot. Filtering after the fact is slower because Workbook must process the full dataset first.
• Use date range filters aggressively. Instead of loading all transactions ever, limit to the relevant period (last 12 months, current fiscal year, etc.).

Be Selective with Fields

• Only include fields you actually need in the dataset. Every additional field increases the amount of data Workbook must process.
• Avoid adding fields "just in case." You can always go back to the Data tab and add more fields later.

Optimize Joins

• Each join adds processing time. If you only need the customer name, join to Customer but do not also join to Customer > Sales Rep > Department unless you need those fields.
• Keep join chains short. Three levels deep is usually fine; five or more may cause timeouts on large datasets.

Pivot Carefully

• Avoid putting high-cardinality fields in both rows and columns simultaneously. For example, putting Customer Name in rows and Item Name in columns on a dataset with 10,000 customers and 5,000 items creates a 50-million-cell matrix.
• Use hierarchical rows instead: put Category in the first row level and Name in the second, so users can expand only the categories they care about.

Use Summary Record Types When Available

• For financial reporting, consider using Transaction Summary or Accounting Period record types instead of individual transactions. These pre-aggregated record types load faster.
• Check if NetSuite offers a summary record for your use case before building a dataset from granular records.

Monitor Workbook Load Times

• If a workbook takes more than 15 seconds to load, review your dataset for optimization opportunities.
• Large workbooks can impact other users on the same account. Be considerate with scheduled workbooks that run during business hours.

Workbook vs. Saved Search: When to Use Which

Here is a decision framework to help you choose the right tool:

Use a Saved Search when you need to:

• Create a quick list of records with filters
• Use formula columns with Oracle SQL syntax
• Feed data to a SuiteScript or workflow
• Display results in a record-context portlet
• Set up email alerts based on search criteria
• Build KPI scorecards with a single metric

Use a Workbook when you need to:

• Build multi-dimensional pivot tables
• Create charts and visual dashboards
• Analyze data across multiple record types with complex joins
• Apply conditional formatting with gradients and thresholds
• Build a self-service report that non-technical users can interact with
• Combine multiple visualizations in a single report

Use both together when:

• You need a Saved Search as a data source for scripts AND a Workbook for visual analysis of the same data
• Your reporting needs span both operational lists (Saved Search) and strategic analytics (Workbook)

The two tools are complementary, not competitive. Many NetSuite teams use Saved Searches for day-to-day operational reporting and Workbooks for monthly or quarterly business reviews.

Next Steps

Now that you have a solid foundation in SuiteAnalytics Workbook, explore these related tutorials:

• Saved Search Formulas for formula-driven reports using Oracle SQL syntax
• Scheduled Search Exports for automated report delivery via email and FTP
• Search API in SuiteScript for programmatic reporting and data access in custom scripts

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Need help building custom reports and dashboards? Contact us for a NetSuite analytics consultation.