USAGE FOR PACKAGE ORDERS IN ANALYTICS

Bridgett Bonar

Acquisitions Data Specialist

Dartmouth Libraries

ENUG 2025

DESCRIPTION

As COUNTER reports do not include any acquisition information, one of the major problems with the increase in package ordering is dynamically summarizing the usage data, without having to create and manage individual reports for each package.

Many of our institutions have created Usage Dashboards in Alma Analytics to display our COUNTER usage data in a way that is adaptable to the user’s needs. I created such a dashboard for Dartmouth Libraries in 2022 (following two wonderful presentations here at ENUG), which relied solely on the Usage Data (COUNTER) subject area. This is sufficient for individual orders or packages that include all of our holdings on a platform, but it is not built to summarize the information in a meaningful way.

As packages are among our higher ticket items, determining the total usage is important for justifying our continued expenditure. Therefore, I have created a page that summarizes and displays usage based on portfolios under a collection with a PO Line.

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AGENDA

Introduction

Institutional Context

The Problem

My Solution

Caveats and Exceptions

Final Takeaways

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AGENDA

Introduction

INSTITUTIONAL CONTEXT

The Problem

My Solution

Caveats and Exceptions

Final Takeaways

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INSTITUTIONAL CONTEXT

WHY NOW?

At Dartmouth Libraries, we have so far been very lucky in terms of current budget constraints, but we are trying to be prepared in case we need to make some cuts in our next budget.

We are working to establish infrastructure that enables us to make data-informed arguments and decisions.

BUDGET

• Dartmouth Libraries Acquisitions and Collection Development Department manages a total budget of ~$14 million.
• Most of our collections budget comes from central (Arts & Sciences) funding, but we also receive support from our three professional schools.

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PACKAGE TITLES

In FY25, we spent $6.1 million (approx. 45% of our total collections budget) on 237 PO Lines attached to collections with portfolios in Alma.

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RENEWAL PROCESS

At Dartmouth, purchasing decisions are made by the liaison librarians.

We manage our renewal decisions and workflow tracking through three Airtable databases, which provide information about the term, price history, and usage.

This allows us to calculate figures like projected prices and cost per use.

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AGENDA

Introduction

Institutional Context

THE PROBLEM

My solution

Caveats and exceptions

Final Takeaways

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THE PROBLEM

COUNTER API REPORTS

• Limited to Usage and Identifier data
• Lack of alignment between access data and paid resources

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COUNTER API & THE USAGE DATA SUBJECT AREA

• Limited to Usage and Identifier data of the individual resource.
• Does not share a dimension with other subject areas; where package information is maintained.
• Fields such as publisher, platform, and title are formatted differently by (and sometimes within) each provider

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OUR USAGE DASHBOARD

I created a usage dashboard for Dartmouth Libraries in 2022, which relies solely on the Usage Data (COUNTER) subject area.

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Organized based on the COUNTER report structure.

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Not built to summarize the information in a meaningful way, nor easily pull usage for sets of titles.

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This is sufficient for individual title subscriptions or packages that include all of our holdings on a platform.

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WHAT ABOUT COST USAGE?

Discovering why the usage may have decimal points in the cost per use

“The usage (in this case, the “Usage JR1” column) is proportionally split according to the price of the resource in each electronic collection.”

Determining the price for cost per use for a portfolio which is part of a collection which has a POL of type Continuous

“In this case Alma takes the total cost of the Electronic Collection and divides it by the number of portfolios in the collection and the result is “cost per portfolio”.

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AGENDA

Introduction

Institutional Context

The problem

MY SOLUTION

Caveats and exceptions

Final Takeaways

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MY SOLUTION

COMPILING DATA ACROSS SUBJECT AREAS

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REPORTS STRUCTURE

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Funds Expenditure

E-Inventory

Usage Data

PO Line Reference

PO Line Title

Status = Active

Continuity = Continuous

Collection PO Line Reference

Encumbrance & Expenditure

Fund Code

Renewal Date

Matching ISSN

Lifecycle = In Repository

Material Type

No. of Available Portfolio

E Collection Interface Name

Matching ISSN

Title

TR_J3 Unique Item Requests

Access Type

Usage Date Year > 2019

Platform

Material Type Indicator

MATCHING ISSN

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MATCHING ISSN

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LIVE DEMO

IN ANALYTICS

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DASHBOARD PAGE

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Descriptions and definitions

Dashboard prompts

Fund Expenditure

COUNTER report

Fund Expenditure Report

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Electronic Inventory Report

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Visualization

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Visualization

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Count of Titles

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Usage by title

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Summary by year

Usage Data (COUNTER) report

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AGENDA

Introduction

Institutional Context

The problem

My solution

CAVEATS AND EXCEPTIONS

Final Takeaways

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CAVEATS AND EXCEPTIONS

PACKAGE MANAGEMENT IN ALMA

This analysis:

• relies on POLs being connected to the correct inventory at the correct level.
• assumes one collection will correspond to only one order.

HOLDINGS ON MULTIPLE PLATFORMS

We have holdings for many titles on multiple platforms, and analytics does not allow for more than one cross-report filter, so in collections with a lot of holdings that are also on other platforms, this filter needs to be added manually.

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MATCHING

Due to this analysis’ reliance on ISSNs, many things can prevent complete matching, including:

1. The COUNTER API report is dropping the identifiers
2. The matching ISSNs are pulling the opposite ISSN
3. The CZ record’s ISSN is missing or incorrect

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CALCULATIONS

Analytics reports can only perform calculations internally, and Dashboards cannot pull datapoints from multiple reports and perform calculations.

Therefore, even when this page gives you all the information to calculate cost-per-use, you still need to do the calculations manually.

AGENDA

Introduction

Institutional Context

The problem

My solution

Caveats and exceptions

FINAL TAKEAWAYS

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FINAL TAKEAWAYS

DATA VISUALIZATION

Using similar principles and data manipulations, I was able to create a DV workbook where the ‘Is based on the results of another analysis’ filter is replaced by an inner join, but currently, the data being pulled does not match the analytics dashboard.

FINAL TAKEAWAYS

• As we try to make data-informed decisions, it often benefits us to try to bridge the divide between invoice line costs and the usage in COUNTER reports, but the way analytics is designed makes this difficult
• Using analytics alone as a tool, there are many opportunities for data to be mismatched
• As we increase our holdings beyond non-traditional access types, including open access in our reports becomes more vital.

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QUESTIONS?

Bridgett Bonar

Acquisitions Data Specialist | Dartmouth Libraries

bridgett.e.bonar@dartmouth.edu

Shared- Community- Reports- Institutions- Dartmouth College- Usage Dashboard- Package Usage Page- PackageUsageENUG2025