improvement 

We’re excited to introduce our new reconciliation wizard, designed to help you compare actuals and forecast data, identify conflicts, and resolve them efficiently.

What’s new?

Previously, reconciling actuals and forecast data for your headcount management was a time-consuming, manual process. Our new, user-friendly wizard guides you through the reconciliation process step by step, so you can easily resolve data conflicts with just a few clicks.

How it works

1. Import latest actuals. Manually or via autosync.
2. Open reconciliation wizard. Data conflicts are automatically detected and presented one by one for review.
3. Review conflicts. The reconciliation wizard presents possible duplicated rows, helping you decide what action to take.
4. Reconcile! Choose the appropriate action (delete/postpone/skip) and quickly resolve conflicts.

Ready to try it?

Explore reconciliation in the Abacum Academy and start streamlining your data management workflow today. To learn more and be one of the first to try out this feature, please contact your Customer Success Manager.

We’ve expanded our permissions control to streamline collaboration and resource management: Super admins can now share restricted resources — such as connections, datasets, or models — with specific admins.

What’s New?

Super admins no longer need to grant full Super admin privileges to enable admin-level access to restricted resources. Instead, they can directly share specific resources with certain admins, who can then view and edit them as needed.

To see this feature in action, check out the video below. It demonstrates the interface from both perspectives:

• Super admin view (left side): How resources are shared and permissions are configured.
• Admin view (right side): How the shared resources appear and can be managed by assigned admins.

We are excited to introduce the new OFFSET function, designed to help you dynamically shift values across periods by a specified number of months.

Formula syntax

OFFSET(variableA, variableB)

• variableA: The input variable to shift.
• variableB: The number of months to offset values (positive, negative, or zero).

Learn more in the academy: Link.

How can this formula be useful

Examples of use-cases where you could use this function:

• Cash collection models: Easily adjust collection periods from spaces and instantly see the impact on cash flow.

  Example:

  If your projected revenue for January 2025 is $50,000, and you set an offset of 2 months, this amount will shift to March 2025. This allows you to instantly see how adjustments to collection periods affect cash flow projections.

• Property launch models: Quickly test assumptions for new property launches to inform decisions.
  Example:

  A site initially planned to open in Q2 2025 has its launch delayed to Q3. Using the OFFSET function, you can shift the expected revenue from May to August 2025 directly in the model, without needing to reconfigure formulas or calculations.

• Other use-cases: Useful for sales cycle modeling, deferred revenue adjustments, and cash flow accruals.

The m parameter is now available, allowing you to reference the current cohort month directly in formulas. 

Example Usage

Here’s an example formula leveraging the m parameter:

IF m <= 12 THEN (This.m.c-3:c-1 / 3) ELSE (This.t-1)

Explanation:

• For the first 12 months of a cohort, it calculates the average value of the same month across the last 3 cohorts.
• For months beyond 12, it references the value from the previous period.

How to use it

You can use this parameter for IF-ELSE logic.m dynamically adapts to the cohort month in context to execute the correct formula. 

Learn more about cohorts functions and their structure here: Link.

The usage of MAX and MIN functions is pretty common on finance. Until today, we’ve seen a lot of usage of IF ELSE to cover these formulas (e.g. IF variableA > variableB THEN variableA ELSE variableB). However, this makes formulas less readable and clean.

What’s new?

We are now introducing two new functions into our formula library: MAX and MIN to make modeling experience quicker and cleaner.

How do they work?

• MAX formula returns the largest values in a set of variables or constants
• MIN formula returns the lowest values in a set of variables or constants

These functions can also be combined with other functions, such as IF ELSE. 

Learn more about how to use them in the academy:

• MAX: Link
• MIN: Link

FP&A teams often face the challenge of analyzing large amounts of financial data to spot outliers. Reviewing all the data manually is time-intensive and inefficient, delaying decisions that rely on accurate insights.

What’s new?

We are launching our Abacum Intelligence anomaly detection feature to empower teams like yours to automatically identify and address unusual patters in actuals data so that you can proactively explore outliers and take corrective actions if needed.

How does it work?

There are two modes of operation:

1. Automated anomaly detection: You can enable anomaly detection for specific variable so that every time this data is updated due to an actuals change anomaly detection model will be run to check if there is any outlier. You can also adjust “lookback” setting, which allows you to define how many months of historical data the AI will analyze to establish a baseline for normal behavior.
2. Ad-hoc anomaly detection: You can additionally activate initiative detection manually by selecting the “Detect data anomalies” action for specific variables.

Once anomalies have been detected, you can resolve these anomalies. The resolution workflow works like this:

• Notifications alert you when anomalies are detected.
• Review and resolve anomalies directly in the activity sidebar by marking them as resolved with a predefined reason.
• You can choose between permanent or transient resolutions, providing clarity for recurring or one-time issues.

Learn more about this in the academy: AI Anomaly Detection.

This feature is being rolled out gradually to our customers. If you don’t see it in your account yet, don’t hesitate to contact your customer success manager, and we’ll be happy to activate it for you. 

• Drag any KPI card to a new position.
• A visual cue will show the card's new placement as you drag.
• Drop the card, and it will snap into the new position, shifting other cards as needed.
• Dropping the card outside valid positions will return it to its original spot.

When duplicating a version as manual inputs, you can now customize exactly what’s included to make the process more streamlined and focused on what matters most.

How does it work?

When duplicating a version as manual inputs, you can now select the specific models, sections, or variables you want to include in the new version.

Any unselected items will not carry over values into the duplicated version.

Recommendations

• Duplicate only necessary variables and models: Avoid including test models or auxiliary variables that aren’t essential.
• Why does it matter? Selecting more variables will slow down the duplication process and impact your models performance.

Working with large models? Struggling to find specific variables, especially in summary groups? The new search bar in the model builder makes it easier than ever to navigate complex models.

Here’s how it works:

• As you type in the search bar, the model builder dynamically displays variables that match your input.
• If a variable is hidden in a collapsed section or group, it will automatically expand to reveal the matching item.

Notes:

While using the search bar, drag-and-drop actions and variable creation are temporarily disabled to ensure a smooth experience.

If you've ever used the DISTRIBUTE function, which requires two date inputs, you may be familiar with its syntax:

DISTRIBUTE (start_date, end_date, amount) FROM DATASET

Unlike DISTRIBUTE, which requires both a start and end date, DATE_SUM allows you to aggregate values with just one date parameter. This simplicity makes it especially useful for cases where a single date, such as a closing date or transaction date, determines in which time a certain amount is allocated. Additionally, DATE_SUM includes an optional "last" parameter to help you work with snapshot datasets, avoiding duplicate data entries.

This function can be used both in actuals and versions formulas.

Syntax explanation

DATE_SUM(date, measure, [criteria]) FROM DATASET

• measure: The numeric field (e.g., amount or value) you want to sum.
• date: The date field on which the allocation is based.
• criteria (optional): If "last" is added, it restricts the aggregation to only the last available data load, which is useful for snapshot datasets to avoid duplicates.

Examples:

DATE_SUM (close_date, amount) FROM DATASET

• Sums a certain amount based on close_date date, using all available data in the dataset.
• Use Case: Ideal for calculating total sales or expenses over time on a transactional dataset .

DATE_SUM (close_date, amount, last) FROM DATASET

• Sums a certain amount based on close_date date, but only uses the most recent data load.
• Use Case: Ideal for snapshot datasets (e.g., monthly or quarterly reports) where only the latest entries should be considered, avoiding potential duplicate entries from previous data loads.

Learn more about this function in this link.