FAQs

When selecting benchmarks, you can easily view the characteristics of each member including the AWI value.   An AWI value of 1.0 is the average for the country.  A value of above 1.0 indicates you might be in a higher wage market and a value below 1.0 indicates that you might be in a lower wage market.   This may not be true for your university so we allow the AWI feature to be used or not – currently, it is the best and only proxy we are aware of that adjusts for regional wage differences in the field of higher education.

Area Wage Index (AWI) is updated yearly by the Centers for Medicare and Medicaid (CMS).  The index uses an average hourly wage for each labor market area (total wage costs divided by total hours for all hospitals in the geographic area) and a national average hourly wage (total wage costs divided by total hours for all hospitals in the nation). A labor market area’s wage index (AWI) value is the ratio of the area’s average hourly wage to the national average hourly wage.

For member universities with an associated medical center, we use the AWI for that medical center. For those member universities that not have an associated medical center, the AWI associated with the closest zip code is used.

The Area Wage Index (AWI) is designed to adjust for the difference in the cost of human capital in different geographies.  For instance, an Application Developer of the same level of skill and experience hired in the San Francisco Bay Area would be paid a higher wage than a person performing the same job in a small rural town in Alabama due to the cost of living. When comparing the cash compensation in different geographies it is useful to adjust for area wage disparities.  You will see AWI listed in the numerator as SAM Spend (AWI adjusted) or not – simply select the appropriate choice for your analysis.

Here is an explanation of how it works.

1. When AWI is used, the total cash compensation paid in the benchmarking charts is adjusted for AWI so that the total human capital investment is “apples to apples” on a relative cost basis.

2. When AWI is not used, the total paid in the benchmarking charts is not adjusted and the dollars reflected are the ACTUAL dollars paid.

What is DataFlex and what does it include?
DataFlex provides nightly updated extracts containing detailed, person-level internal data alongside aggregated external benchmark data and analysis factors. It is designed to eliminate the need for manual extract requests from HelioCampus and empower institutions to perform independent analyses and visualizations.

For legacy clients with multiple fiscal years and multiple peers, rows may be dropped from the external contract portion of the extract due to file size limitations. Excel can only handle files up to 1,048,576 rows. As external contract rows are last in the extract, those values are often dropped. HelioCampus is currently working on a solution for this.

The DataFlex extract is updated nightly to ensure users have access to the most current mappings and benchmark information. Please note that changes to the benchmark set will appear in the output file after the next refresh, typically within 24–48 hours.

To comply with data-sharing governance agreements, internal data is provided at the individual row/person level, whereas peer institution data is aggregated at the Standard School or standard division level. This prevents the potential re-identification of individuals at other institutions. 

No. We are not able to share titles or FTE information for benchmark institutions. There is a potential re-identification risk that could expose person-level compensation for titles associated with small populations. As a result, the activity-level grain is the only level of detail we can share externally, both through the platform and the DataFlex extract.

Remind members that the extract is available under Left Menu Button > Benchmarking Preferences > DataFlex > Download DataFlex Extract. If a member reports they cannot see the option, verify they have "Program Coordinator" designations, as access is restricted to this role.

You can update your peer list at any time within the platform under Settings > DataFlex > Edit DataFlex Peers. Please note that changes to the benchmark set will appear in the output file after the next refresh, typically within 24–48 hours.

Changes to the benchmark set will appear in the data file export after the next refresh, typically within 24–48 hours.

Yes. If you prefer to use a script rather than a manual download, HelioCampus can provide AWS S3 access keys please contact your Project Manager or Client Success Manager.

Universities that are part of a system can download DataFlex extracts for all institutions within that system.

Two separate extract files are available:

• University DataFlex Extract – Contains data for the individual university and its benchmark set.
• System DataFlex Extract – Contains data for all institutions within the system.

To download the System DataFlex Extract, the user must have a System Administrator account.

Exception: Users who are logged in under the system entity will only see the following download options:

• Download System DataFlex Extract
• Download Data Dictionary

Differences may occur due to rounding methodologies, decimal place cutoffs, or recent changes to internal/external data that have not yet cycled through the daily refresh. This is common when dividing very small numerators by very large denominators.

It is also important to understand the discrepancies that may arise between the visualizations within the Labor Cost Analytics platform and the raw DataFlex extracts. Specifically, the internal single-year charts are configured to exclude labor spend and FTE for individuals mapped to specific subactivities to provide a cleaner high-level view.

The Administrative Labor platform charts exclude the following subactivities from the Administrative Charts:

• Excluded
• Review Required
• Data Load
• No Artifact Found
• Unmappable
• Teaching/Research/Service
• Library Services
• Coaching/Training/Support
• Exception

It should be noted that while Teaching/Research/Service, Library Services, and Coaching/Training/Support are excluded from the administrative charts, users can view academic labor (Teaching/Research/Service and Library Services) in the Academics charts and athletic spend in the Athletics charts within the platform.

In contrast, the DataFlex extract includes labor spend and FTE for all subactivities, including those listed above. This comprehensive inclusion is what typically drives the difference in values between the platform and the extract. When performing checks and balances to reconcile these figures, creating a pivot table from the DataFlex data is a highly effective starting point.

To facilitate a more effective investigation by our development team, please download and provide your Project Manager both the current and the previous files to help pinpoint specific differences. 

We recommend including System Labor data for a complete view of total labor effort and accurate comparison against benchmarks. System Labor with detail includes individual employee-level data from the Data File, while System Labor without detail is an aggregate of that employee data. When conducting your analysis, please use only one of the two datasets, as including both would result in double-counting your System Labor spend.

While member-provided SCH is collected for Academic (Teaching/Research/Service) Analyses within the platform, DataFlex pulls the Total Student Credit Hours from IPEDS. We utilize the IPEDS value for benchmark consistency to support aggregated peer comparisons, as required by our data privacy sharing agreements.

Discrepancies or empty fields within analysis factors typically occur when the specific metric has not yet been provided by the client or is unavailable from external third-party sources such as IPEDS. In such instances, the system will populate the extract using the most recent data available, spanning a maximum look-back period of two fiscal years.

The IPEDS number was added to the DataFlex-peers file to help you more easily join additional IPEDS information to the DataFlex extracts for their own analyses.

The DataFlex-funding file was added to support an optional field that some clients send us. If your institution does not provide a funding source code in the Data File, you can disregard this file, and it will be labeled as "n/a" or blank. If you are interested in adding the funding source field to your data file, please contact your Project Manager.

Differences may occur due to filters, rounding, or recent data changes. To replicate platform totals, ensure you are applying the correct filters and mappings, such as including specific auxiliaries (e.g., Aux - Dining and University Wide) when calculating totals like University External Labor.

The total is not at the bottom of the internal single-year chart unless System Labor was entered as External Labor. Instead, view the External Single Year Chart and toggle to System Labor; this chart combines any Data File System Labor with any External System Labor to show the full value.

-Excluded: This category includes any institutional activities that have not been classified within the HelioCampus Standard Activity Model.

-Unmappable: This status is assigned to job titles when neither the Source Analysis nor discussions with Program Coordinators provide enough information to determine a specific mapping.

-Data Load: This represents an inherited mapping based on a subgroup average. When an individual row lacks a direct mapping, the system applies the average mapping of their respective Sub Group. For instance, if two of three employees in a subgroup are researched and mapped, the third individual will automatically inherit that same mapping. HelioCampus uses their expertise to leverage sampling.

-Under Review: This status indicates that our Implementation Team is actively evaluating the current classification to verify it precisely aligns with the employee's daily operational duties.

-No Artifact Found: This status indicates that the Implementation Team lacks sufficient documentation to validate the current classification, necessitating a consultation with the Program Coordinator to determine the precise mapping.

Detailed descriptions for all DataFlex columns and data fields are available directly within the Labor Cost Analytics platform on the DataFlex settings page. Users may also download a local copy of the Data Dictionary for offline reference.

To help us troubleshoot this access issue, please provide the following details:

• The specific bucket you are trying to access (individual institution or the Illinois System bucket).
• The credentials you are currently using.
• Screenshots of any error messages you receive.

Our Development Team also suggests a preliminary test: please try connecting using a tool like Cloudberry or a comparable application. This will help us isolate the problem:

• If successful: The issue is likely within Denodo (or the software being utilized).

If unsuccessful: The issue may be related to security settings on the HelioCampus side. 

Yes. HelioCampus offers technical support for configuring Tableau and Power BI Dashboards that connect directly to your DataFlex extract. This service is intended to expand your institutional capacity for custom internal visualizations and autonomous data analysis initiatives.

A starting point for self-service or provisioned analysis and dashboarding, including:

• Activity-based analysis and benchmarking of FTE and Labor Spend
• Trended FTE/Labor Spend normalized using parameterizable allocation bases
• Compensation Variance Analysis
• Decentralized Activity Locator

Why are they important?

• Offers a new flexible method to engage with client data outside of traditional platform or curated insights
• Showcases our strength in delivering managed data services and dashboarding
• Possible upsell opportunities stemming from extant, available Helio data served in Tableau Cloud/ Power BI

Many of our member universities have contracted various business processes within the university in areas such as dining services, information technology, and bookstore management. To provide a true “apples to apples” comparison, the consortium asks members to include External Labor contracts that materially impact the institution’s benchmarking graphs to ensure that we are capturing all human capital investment in support of university operations across all member campuses.

The common driver is to improve efficiency and quality while “perhaps” also reducing costs. The motivation to outsource functions vary but the primary benefits include cost savings, budgetary constraints, desire to improve quality of service, access to talent.

The university’s Project Coordinator (PC) will talk to all relevant points of contact at the university to gather the information related to the university’s contracts. This information will be provided to the assigned CSM who will then enter the relevant contract information into our benchmarking platform.

The following resources have been proven to be helpful in gathering External Labor data for our member universities:

Accounts Payable:  Since this office is responsible for processing invoices for payment to vendors, they may have information pertaining to specific dollar amounts allocated to the human capital that we would like to capture.

Procurement Office: The procurement services office may also serve as an important point of contact. Procurement offices are responsible for purchasing goods and services for the university and managing financial stewardship of all payments to external vendors of services. In charge of purchasing, procurement offices would have the knowledge and the ability to interpret different contracts.

Other Resources: Additionally, some colleges and universities may devote a full-time position to managing a specific contract and the areas managed under the contract. If your university has such a position, contacting the employee hired for this function will help in obtaining further information about the contract. Some universities may also have an office of contract administration that would be an additional resource for information. Finally, the controller can serve as a reference and may be able to put the Project Coordinator in contact with other offices across the campus.

The list below highlights the initial areas of focus for FY14 – FY17.  The ABC Insights team, with support from our members, may add additional focus areas in the future.

Anything excluded in our Standard Activity Model (SAM) is also excluded from External Labor analysis.  Please contact your Client Services Manager (CSM) for the most recent list of all excluded areas of our Standard Activity Model.

Full-time equivalent (FTE) is the budgetary equivalent of one position, continuously filled full-time for the entire fiscal year and which may be comprised of any combination of part-time and full-time positions. During the implementation process, we determine FTE on a per unique role basis by dividing the amount an individual was paid in the fiscal year by what they were contracted to make for that role if they worked a full year (annualized rate). If a university cannot provide an annualized or contracted rate then we will work with the member university to include a reasonable estimate to ensure they are not under-reported in the area of FTE. 

FTE is important in a variety of areas in addition to annual budget construction. It is used for university reporting and in the accreditation process. It is also important for university statistics and funding discussions, as well as in comparisons with benchmarks.

HelioCampus has worked closely with its members to develop standard FTE rules for each classification of employee. For more information about those standard classifications and FTE calculations please contact your Client Services Manager (CSM) or Project Manager (PM).

A core part of our mapping process includes a sampling of titles and performing research on individuals to determine exactly what they are doing.  This research includes online resources to provide clues that can inform more accurate activity descriptions than a standard job description in some cases.  Names are used to help research the activities for job titles that are difficult to identify otherwise.

The HelioCampus team has passed rigorous security audits to securely transfer, process and store sensitive information.  To gain more specific information in this area please contact your Client Services Manager (CSM) to receive a copy of our information security policies and procedures.

The Program Coordinator (PC) is our single point of contact for the implementation of each member.  He or she is critical to ensuring that the implementation remains on schedule and that the data is reviewed and reasonably accurate to provide decision support.  The PC is expected to spend up to 1 hour per week for a standing check-in meeting. The time is less in the early stages of the project and can be more during the final phases of the project when more precise reviews are required.

A first-year implementation for a new member university is estimated to take 4-5 months from the time a validated payroll file is imported into the HelioCampus platform.  The basic phases and time to complete are outlined below:

• Kick-Off Meeting – typically 2 weeks from signed Letter of Agreement

• Payroll File Meeting – typically 2 weeks from Kick-Off Meeting

• Payroll File Received – typically 4 weeks from Payroll File Meeting

• Payroll File Imported – typically 1 week from Payroll File received

• 90-Day Business Officer Check-In Meeting – scheduled 90 days from Kick-Off meeting

• Insights Meeting Conducted – typically 4 months from Payroll File Imported

• Final Benchmarkable – typically 2 weeks from Insights Meeting

The mapping process is guided by the consistent application of rules developed to inform what activities certain job roles are performing on campus.  Some of these decisions are clear based on title and dept. combinations and some are more complex and require deeper analysis as shown in the flow-chart below.

Once the previous fiscal year of data is marked as benchmarkable in the platform the following process kicks off.

• Payroll File Migrated – typically 4 weeks from previous year becoming benchmarkable with timely receipt of the payroll file

• Insights Meeting Conducted – typically 3 months from Payroll File migration

• Final Benchmarkable – typically 2 weeks from Insights Meeting

The process that the HelioCampus team uses to determine job role activities is much broader than an analysis of the title itself.  University members provide us with a detailed payroll file that provides supporting columns of information that provide valuable clues into the job activities measured in our standard activity model (SAM).  In addition, we perform research on a sample of individuals that perform each job role to provide additional clues/support that assist with the accuracy of the activity mappings.   The results of this process ensure that the activity mappings are reasonably accurate and beneficial for decision making.  In cases, when our research analyst team has insufficient evidence to support a mapping we will request position description information/guidance from our assigned university Program Coordinator (PC) to inform the mapping.

Since our consortium database contains over 50,000 unique university titles we have created a robust mapping index through analysis of roles/activities at other member universities.  This proprietary mapping index provides valuable information to support the mapping process.

The combination of all of these research sources is what we call our “All Source Analysis” ASA mapping process.  This process results in an “apples-to-apples” comparison of job activities across our membership.   The lessons learned during our implementation process can be very helpful in directing your focus to obtain improved title clarity and we see many members using our services to inform the pace and urgency of their internal job title improvement efforts.

Effective benchmark selection is largely based on what questions you are trying to ask.  In general, HelioCampus will use the following benchmark selection criteria when preparing for a general Insights Meeting.  We look at benchmarks that are similar in the following areas:

1. Total Operating Expense
2. Carnegie Classification ($ size of Research expenses)
3. Total Students and Employees (IPEDS)
4. Region of the Country

The Employee (IPEDS) number is a “snapshot” of the employees in the university on the exact date IPEDS requested the information.  As a result, it does not provide a complete picture of how many FTE the university served in any given Fiscal Year. The FTE Employees (HelioCampus) captures is inclusive of the entire fiscal year and as a result is a more accurate count to use for analysis.

We find the dividing the Total Standard Activity Model (SAM) Spend on your campus using the following Analysis Factors is a good comparison of over or underperformance in a particular activity.  The following are the most logical comparisons to use for normalization.  Note – it is best to use Total SAM Spend AWI adjusted since this adjusts the labor dollars nationally for a better comparison of wage-adjusted dollars.

• Facilities divided by Acres Maintained
• Student Services divided by Students (IPEDS)
• IT divided by Employees + Students (IPEDS)
• Finance divided by Employees + Students (IPEDS)
• Communications divided by Funds Raised
• Development divided by Funds Raised
• Human Resources divided by Employees (ABC)
• Research Administration divided by Awards

Note – US News and World Report publishes a list of the most efficient universities in the US annually.  Their study uses total students (IPEDS) as a common efficiency ranking for spending across the categories in their study.

We provide descriptive information at the top of the chart / heading and we also provide more detailed information at the bottom left of any of the reports that says Chart Notes.  If you click on Chart Notes you will see valuable information about the selections made to generate the chart. Since the charts are dynamically generated this can be very helpful if you are taking a screenshot of the results.  As you can see at the bottom of the screen, the Chart Notes include detailed information regarding:

1. Peer Information (who was included and their status)
2. Selected Standard Schools / Divisions (what was included)
3. Data View (Organizational Classification or Employee Classification)

Yes.  We allow our members to click on the icon that says Select Divisions.  Once clicked, the platform will show all of your Divisions (and/or Schools) that have been mapped into our Standard Organizational Model™ (SOM).  For instance, you may want to compare human capital investment between your School of Business and that of a benchmark university. To do so, simply de-select all and then select just the areas of the SOM you wish to compare.  Note – if your university has no clear Division / School that maps into our SOM then you will see a * next to that Standard Division / School name.

The platform is a decision support tool for university leaders.  The platform enables members to examine the relative intensity of staffing costs and compare those costs to benchmarks using an activity-based costing methodology.

Member institutions provide a payroll file for each fiscal year. Files include several variables for each person who received pay during a given fiscal year. Typical columns include name, division, department, job title, and salary.  In addition, member universities provide relevant information about external labor contacts to measure human capital investment and FTE that are not included in their payroll file. Finally, our members provide a set of Analysis Factors that allow data to be normalized and effectively compared across institutions.  For instance, universities provide Analysis Factors for Total Acres or Development Funds Raised to determine their spending/unit relative to benchmarks.

The platform provides a variety of flexible views of the data based on feedback from our consortium members.  If you need alternate views or raw data to support decision making then please contact your Client Services Manager (CSM) to determine an appropriate solution.

The team at HelioCampus follows stringent security protocols to ensure the data is secured and protected.  For more information about our security processes please contact your Client Services Manager (CSM).

Marketing and Communications

The creation and management of internal and external communications.  This includes online marketing and engagement (web pages and social media) for both external and internal audiences.

Public Affairs

Managing communications and relationships with external stakeholders, including the media, government entities (including governing boards), and the local community.

Other
Includes Communications sub-activities not separately identified at this time. Examples include, but are not limited to, TV/radio broadcasting, production, and technical support; graphic design services; printing services; photography and videography; and document/publishing services.