Introduction
This interactive tool is based upon “The Total Economic Impact™ Of HPE Compute Ops Management,” a commissioned study conducted by Forrester Consulting on behalf of HPE in September 2026.
Forrester interviewed six representatives of six organizations using Compute Ops Management to identify and quantify potential key benefits of investing in the platform.
Use the inputs on the left to customize the analysis and estimate the potential impact that an investment in HPE Compute Ops Management can bring to your organization.
Inputs
You provided the following information about your organization’s environment.
Name of your organization
Location (country)
Annual revenue
Total servers (including both remote servers and/or data center servers)
Remote servers
Remote server locations
Current annual cost of server management tools
Results for:
Benefits (Three-Year)
Financial Summary
Consolidated Three-Year, Risk-Adjusted Metrics for
Return on investment (ROI)
Benefits PV
Net present value (NPV)
Payback
Cash Flow Chart (Risk-Adjusted)
Cash Flow Analysis (Risk-Adjusted)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | $0 | $0 | $0 | $0 | $0 | $0 |
| Total benefits | $0 | $0 | $0 | $0 | $0 | $0 |
| Net benefits | $0 | $0 | $0 | $0 | $0 | $0 |
| ROI | ||||||
| Payback |
Quantified benefit data as applied to
Total Benefits
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Avoided server downtime | $0 | $0 | $0 | $0 | $0 |
| Btr | Server management time savings | $0 | $0 | $0 | $0 | $0 |
| Ctr | Improved server visibility and decision support | $0 | $0 | $0 | $0 | $0 |
| Dtr | Decommissioning other server management tools | $0 | $0 | $0 | $0 | $0 |
| Etr | Edge-location travel cost savings | $0 | $0 | $0 | $0 | $0 |
| Total benefits (risk-adjusted) | $0 | $0 | $0 | $0 | $0 |
Avoided Server Downtime
HPE Compute Ops Management includes AI-driven analytics, predictive maintenance insights, and intelligent alerting that could help teams identify potential server issues earlier and take corrective actions. This could reduce planned and unplanned server downtime.
Avoided Server Downtime
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Servers managed with Compute Ops management | 0 | 0 | 0 | ||
| A2 | Planned downtime per server before Compute Ops Management (hours) | Interviews | 0 | 0 | 0 | |
| A3 | Reduction in planned downtime with Compute Ops management | Interviews | 0% | 0% | 0% | |
| A4 | Avoided planned downtime (hours) | A1*A2*A3 | 0 | 0 | 0 | |
| A5 | Percent of servers with unplanned downtime | Interviews | 0% | 0% | 0% | |
| A6 | Unplanned downtime per unplanned incident before Compute Ops Management (hours) | Interviews | 0 | 0 | 0 | |
| A7 | Reduction in unplanned downtime with Compute Ops management | Interviews | 0% | 0% | 0% | |
| A8 | Avoided unplanned downtime (hours) | A1*A5*A6*A7 | 0 | 0 | 0 | |
| A9 | Total avoided downtime (hours) | A4+A8 | 0 | 0 | 0 | |
| A10 | Avoided downtime per server (hours) | A9/A1 | 0 | 0 | 0 | |
| A11 | Cost per hour of downtime | Scaled for | $0 | $0 | $0 | |
| At | Avoided server downtime | A9*A11 | $0 | $0 | $0 | |
| Risk adjustment | ↓5% | |||||
| Atr | Avoided server downtime (risk-adjusted) | $0 | $0 | $0 | ||
| Three-year total: $0 | Three-year present value: $0 | |||||
Server Management Time Savings
HPE Compute Ops Management could help server management teams save time when making firmware and BIOS updates and patches.
Server Management Time Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| B1 | IT FTEs on the server management team before Compute Ops Management | Scaled for | 0 | 0 | 0 | |
| B2 | Percent of time the server management team spent on server management before Compute Ops Management | TEI case study | 0% | 0% | 0% | |
| B3 | Server-management time reduction with Compute Ops Management | Interviews | 0% | 0% | 0% | |
| B4 | Fully burdened annual salary for an IT FTE on the server management team | TEI case study | $0 | $0 | $0 | |
| B5 | Productivity recapture | TEI methodology | 0% | 0% | 0% | |
| Bt | Server management time savings | B1*B2*B3*B4*B5 | $0 | $0 | $0 | |
| Risk adjustment | ↓5% | |||||
| Btr | Server management time savings (risk-adjusted) | $0 | $0 | $0 | ||
| Three-year total: $0 | Three-year present value: $0 | |||||
Improved Server Visibility And Decision Support
HPE Compute Ops Management includes dashboards, analytics, AI-assisted reporting, and HPE Compute Copilot. These features could improve visibility into server performance data, help server management teams and executives make more informed operational decisions, and reduce difficulty complying with audit requests.
Improved Server Visibility And Decision Support
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| C1 | IT FTEs on the server management team | B1 | 0 | 0 | 0 | |
| C2 | Percent of time spent on server monitoring and data analysis before Compute Ops Management | TEI case study | 0% | 0% | 0% | |
| C3 | Time savings for server monitoring and analysis with Compute Ops Management | Interviews | 0% | 0% | 0% | |
| C4 | Server monitoring effort saved with Compute Ops Management (FTEs) | C1*C2*C3 | 0 | 0 | 0 | |
| C5 | Audits | TEI case study | 0 | 0 | 0 | |
| C6 | Time required per audit before Compute Ops Management (hours) | Interviews | 0 | 0 | 0 | |
| C7 | Compliance audit-preparation time reduction | Interviews | 0% | 0% | 0% | |
| C8 | Time savings for compliance audit preparation (hours) | C5*C6*C7 | 0 | 0 | 0 | |
| C9 | Fully burdened annual salary for an IT FTE on the server management team | B4 | $0 | $0 | $0 | |
| C10 | Productivity recapture | TEI methodology | 0% | 0% | 0% | |
| Ct | Improved server visibility and decision support | ((C4*C9)+(C8*C9/2,080))*C10 | $0 | $0 | $0 | |
| Risk adjustment | ↓5% | |||||
| Ctr | Improved server visibility and decision support (risk-adjusted) | $0 | $0 | $0 | ||
| Three-year total: $0 | Three-year present value: $0 | |||||
Decommissioning Other Server Management Tools
Organizations may be able to decommission other server monitoring and management tools after deploying HPE Compute Ops Management.
Decommissioning Other Server Management Tools
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| D1 | Cost of other server management tools before Compute Ops Management | $0 | $0 | $0 | ||
| D2 | Percent of other server management tools decommissioned | Interviews | 0% | 0% | 0% | |
| Dt | Decommissioning other server management tools | D1*D2 | $0 | $0 | $0 | |
| Risk adjustment | ↓5% | |||||
| Dtr | Decommissioning other server management tools (risk-adjusted) | $0 | $0 | $0 | ||
| Three-year total: $0 | Three-year present value: $0 | |||||
Edge-Location Travel Cost Savings
Resolving server issues remotely could reduce time and costs associated with server management teams traveling to edge server locations.
Edge-location Travel Cost Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| E1 | Remote servers | 0 | 0 | 0 | ||
| E2 | Remote servers per edge location | E1/E3 | 0 | 0 | 0 | |
| E3 | Edge locations | 0 | 0 | 0 | ||
| E4 | Percent of edge locations that required a trip before Compute Ops Management | Interviews | 0% | 0% | 0% | |
| E5 | Trips to edge locations before HPE Compute Ops Management | E3*E4 | 0 | 0 | 0 | |
| E6 | Percent of trips avoided with Compute Ops Management | Interviews | 0% | 0% | 0% | |
| E7 | Travel costs per trip | Interviews | $0 | $0 | $0 | |
| E8 | Edge-location travel cost savings | E5*E6*E7 | $0 | $0 | $0 | |
| E9 | Travel time per trip (hours) | Interviews | 0 | 0 | 0 | |
| E10 | Fully burdened hourly salary for an IT FTE on the server management team (rounded) | TEI case study | $0 | $0 | $0 | |
| E11 | Edge-location travel time savings | E5*E6*E9*E10 | $0 | $0 | $0 | |
| Et | Edge-location travel cost savings | E8+E11 | $0 | $0 | $0 | |
| Risk adjustment | ↓5% | |||||
| Etr | Edge-location travel cost savings (risk-adjusted) | $0 | $0 | $0 | ||
| Three-year total: $0 | Three-year present value: $0 | |||||
Quantified cost data as applied to
Total Costs
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Ftr | License fees | $0 | $0 | $0 | $0 | $0 | $0 |
| Gtr | Implementation and maintenance costs | $0 | $0 | $0 | $0 | $0 | $0 |
| Htr | Training costs | $0 | $0 | $0 | $0 | $0 | $0 |
| Total costs (risk-adjusted) | $0 | $0 | $0 | $0 | $0 | $0 |
License Fees
Organizations pay license fees to HPE based on the number of ProLiant servers managed with HPE Compute Ops Management.
License Fees
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| F1 | ProLiant servers managed with HPE Compute Ops Management | 0 | 0 | 0 | ||
| F2 | Annual HPE Compute Ops Management cost per server | TEI case study | $0 | $0 | $0 | |
| Ft | License fees | F1*F2 | $0 | $0 | $0 | $0 |
| Risk adjustment | ↑5% | |||||
| Ftr | License fees (risk-adjusted) | $0 | $0 | $0 | $0 | |
| Three-year total: $0 | Three-year present value: $0 | |||||
Implementation And Maintenance Costs
Organizations typically incur internal costs to pilot, deploy, and maintain HPE Compute Ops Management.
Implementation And Maintenance Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| G1 | Implementation effort (FTE) | Scaled for | 0 | |||
| G2 | Maintenance effort (FTE) | Scaled for | 0 | 0 | 0 | |
| G3 | Fully burdened annual salary for a server management team member | TEI case study | $0 | $0 | $0 | $0 |
| Gt | Implementation and maintenance costs | (G1+G2)*G3 | $0 | $0 | $0 | $0 |
| Risk adjustment | ↑5% | |||||
| Gtr | Implementation and maintenance costs (risk-adjusted) | $0 | $0 | $0 | $0 | |
| Three-year total: $0 | Three-year present value: $0 | |||||
Training Costs
Organizations might need to dedicate time to train server management teams on HPE Compute Ops Management.
Training Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| H1 | FTEs on the server management team | Scaled for | 0 | 0 | 0 | 0 |
| H2 | Training time per FTE (hours) | Interviews | 0 | 0 | 0 | 0 |
| H3 | Fully burdened hourly salary for a server management team FTE | TEI case study | $0 | $0 | $0 | $0 |
| Ht | Training costs | H1*H2*H3 | $0 | $0 | $0 | $0 |
| Risk adjustment | ↑5% | |||||
| Htr | Training costs (risk-adjusted) | $0 | $0 | $0 | $0 | |
| Three-year total: $0 | Three-year present value: $0 | |||||
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in HPE Compute Ops Management.
The objective of the framework is to identify the cost, benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that HPE Compute Ops Management can have on an organization.
Due Diligence
Interviewed HPE stakeholders and Forrester analysts to gather data relative to HPE Compute Ops Management.
Interviews
Interviewed six representatives at organizations using HPE Compute Ops Management to obtain data about costs, benefits, and risks.
Financial Model Framework
Constructed a financial model representative of the interviews using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewees.
ROI Calculator
Constructed a calculator based on the model in the associated study and in accordance with Forrester and TEI standards. Forrester’s aim is to clearly show all calculations and assumptions used in the analysis.
Disclosures
Readers should be aware of the following:
This study is commissioned by HPE and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.
Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the study to determine the appropriateness of an investment in HPE Compute Ops Management. For any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect's business. Forrester believes that this analysis is representative of what companies may achieve with HPE Compute Ops Management based on the inputs provided and any assumptions made. Forrester does not endorse HPE or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, HPE and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein. The interactive tool is provided ‘AS IS,’ and Forrester and HPE make no warranties of any kind.
HPE reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.
HPE provided the customer names for the interviews but did not participate in the interviews.
Consulting Team:
Jennifer Adams
Published
September 2026
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