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Total Economic Impact
Cost Savings And Business Benefits Enabled By The Cognite Industrial AI And Data Platform
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Cognite, January 2026
Total Economic Impact
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Cognite, January 2026
The industrial sector faces a growing challenge: Operational data amassed over decades is scattered across multiple operational technology (OT), IT, and engineering systems, making it difficult to access, integrate, and use effectively. The complexity of data integration slows decision-making, limits innovation, and increases operational costs. To stay competitive, companies in asset-intensive industries like oil and gas, chemicals, and manufacturing need solutions that can unify and contextualize their data, turning it into actionable insights.
Cognite provides an industrial AI and data platform that integrates and contextualizes data from IT, OT, and engineering systems into a unified, accessible source. It transforms raw, siloed data into actionable insights, enabling advanced analytics and AI applications for smarter, more efficient operations.
Cognite commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Cognite solutions.1 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Cognite on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed seven decision-makers at four organizations with experience using Cognite. For the purposes of this study, Forrester aggregated the experiences of the interviewees and combined the results into a single composite organization that is operating in an asset-intensive industry, generating $5 billion in revenue across 10 sites.
Interviewees said that prior to using Cognite, their organizations struggled to access and leverage data from siloed, outdated industrial systems — a significant barrier in their digital transformation journey. While they made attempts to digitalize their industrial operations, interviewees invariably found that their organizations were not equipped to tackle the complexity and scale of the project alone. They recognized the necessity of advanced technologies like AI and ML in such transformation projects.
With the investment in Cognite, interviewees found that their organizations were able to implement and scale their projects much quicker than before. The improvement in data access, coupled with AI that assisted with analytics, gave them better oversight of asset performance, allowing them to optimize production and operations (e.g., maintenance).
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
Incremental profit from production optimization. With improved access to critical operational data like sensor readings, equipment performance metrics, and maintenance logs, the composite organization can better monitor asset health and maintenance needs to adjust production and maintenance parameters in real time. The resulting 1% to 2% improvement in production throughput attributed to Cognite results in $10.7 million in incremental profit for the composite organization.
Improved onsite staff efficiency. With Cognite’s unified platform, engineers, technicians, and even data analysts can easily retrieve contextualized information linked to specific assets or processes instead of spending time manually searching through multiple IT, OT, and engineering systems and sources for sensor readings, maintenance records, or equipment documentation, etc. The instant, remote access to data reduces time spent searching for information and traveling to onsite locations, enabling them to focus on data analysis and problem-solving instead. Overall, the improved efficiency saves the composite organization $10.5 million.
Reduction in unplanned downtime. Another key benefit of a unified data platform is that the composite organization now has more useable, accessible data for analysis. Combined with Cognite’s AI agents, the improved data access — and ease of access — to a wider group of users speeds up root cause analysis by up to 60%. This minimized downtime by quickly identifying and resolving issues before they escalate, keeping production running smoothly. For the composite organization, using Cognite to help with root cause analysis leads to reduction in downtime worth $14.5 million.
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
The transition toward more autonomously run plants. To overcome slowly rising labor shortages, the composite organization plans to build (or retrofit existing plants to become) digitalized and autonomized “plants of the future” within the next five to 10 years. The establishment of a data operations platform like Cognite is a crucial first step toward further digital transformation efforts for the composite.
Better, faster business decision-making through data democratization and improved collaboration. Cognite expands the number of employees at the composite that now have easy, shared access to accurate, contextualized data. This improves collaboration between engineering and data teams that are typically located offsite and onsite operational teams.
The reduction of health and safety risks. By minimizing the time that employees spend onsite — especially field visits for general inspections — the composite organization not only saves on travel time and costs but also reduces employees’ exposure to health and safety risks in hazardous areas.
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
Cognite subscription fees of $2.9 million. Subscription fees for Cognite depend on the number of equipment items across different sites and the number of user licenses needed.
Implementation and project management fees of $3.4 million. This includes the deployment of six FTEs toward the project implementation and four toward the ongoing management of the Cognite platform, as well as professional service fees to further help with data integration.
The financial analysis that is based on the interviews found that a composite organization experiences benefits of $35.7 million over three years versus costs of $6.3 million, adding up to a net present value (NPV) of $29.4 million and an ROI of 465%.
Return on investment (ROI)
Benefits PV
Net present value (NPV)
Payback
| Role | Industry | Region | Number Of Sites/Facilities |
|---|---|---|---|
| Chief digital officer | Oil and gas | Europe | 6 offshore sites |
| • Chief digital officer • Maintenance strategy and asset performance management manager |
Energy | Asia Pacific | 3 refinery sites |
| Senior manager, technology | Oil and gas | North America | 3 production sites |
| • Senior director, manufacturing services • Senior director, digital manufacturing • Senior principal engineer |
Chemicals | North America | ~50 plants |
In asset-intensive industries like oil and gas, chemicals, and manufacturing, the interviewees’ organizations often struggled with modernizing their facilities and equipment and with siloed technologies that do not communicate well across systems. Interviewees said operational data was frequently inaccessible, outdated, and incomplete — mostly unstructured (or even existing only on paper) and therefore difficult to use for advanced analytics or decision-making. These limitations created significant barriers to efficiency, innovation, and digital transformation at the interviewees’ organizations.
Interviewees noted how their organizations struggled with common challenges, including:
Inaccessible data. The interviewees’ organizations struggled to access critical operational data when needed. Data was scattered across multiple siloed systems, often requiring manual effort to locate and extract. Interviewees noted that even when data existed, it was poorly organized and lacked context, making it difficult to use for troubleshooting or timely decision-making.
Operational inefficiencies. Disconnected systems and outdated processes created bottlenecks across operations. Interviewees highlighted that incomplete or unstructured data limited the ability to apply advanced analytics or automation. As a result, their teams relied on manual workarounds, reducing productivity and hindering digital transformation efforts.
In searching for an industrial AI and data platform, interviewees looked for a solution that:
Provided out-of-the-box functionality without the need to dedicate hefty development resources to implementation.
Contextualized unstructured data and made it searchable.
Provided interoperability with a wide range of IT, OT, and engineering systems and provided a single repository and source of truth for operational data.
Had a modern interface that was easily understood and navigated by a wide range of users, both technical and nontechnical.
Helped implement and scale projects faster across different sites with AI, therefore accelerating time to value.
Based on the interviews, Forrester constructed a TEI framework, a composite company, and an ROI analysis that illustrates the areas financially affected. The composite organization is representative of the interviewees’ organizations, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:
Description of composite. It is a global B2B conglomerate within an asset-intensive industry. It employs more than 3,000 staff with around 1,000 of those operating primarily onsite, for instance, as engineers, technicians, and managers. The composite operates 10 different sites with an average of 30,000 to 50,000 equipment items tagged per site.
Deployment characteristics. The composite organization starts the Cognite deployment at two of its sites, scaling up to three more sites in Year 2, and a further five in Year 3 for a total of 10.
$5 billion in annual revenue
3,000+ employees
1,000 technicians and engineers across 10 sites
30,000 to 50,000 equipment items tagged per site
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Incremental profit from production optimization | $850,000 | $4,250,000 | $8,500,000 | $13,600,000 | $10,671,300 |
| Btr | Improved onsite staff efficiency | $1,559,250 | $3,898,125 | $7,796,250 | $13,253,625 | $10,496,529 |
| Ctr | Reduction in unplanned downtime | $2,160,000 | $5,400,000 | $10,800,000 | $18,360,000 | $14,540,646 |
| Total benefits (risk-adjusted) | $4,569,250 | $13,548,125 | $27,096,250 | $45,213,625 | $35,708,475 |
Evidence and data. With Cognite, one of the fundamental benefits interviewees experienced was the unification of their organizations’ OT and IT data into one connected platform. This allowed easy, real-time visibility across critical operational data like sensor readings, energy consumption meters, equipment performance metrics, and maintenance logs.
The senior director of digital manufacturing at a chemicals company shared: “Better visibility to data was the ultimate driving force of digitalization. Once we built the data engine, we came to a tipping point where we could suddenly do a lot more. … We’ve built multiple use cases and apps — energy management, maintenance avoidance, [and] a combination of top-line and bottom-line improvements.”
A senior manager of technology at an oil and gas company shared a similar view, “We have a vision of building more autonomous, self-optimizing plants by 2030, and knew that we had to make an investment in our data infrastructure to enable all that.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Cognite is deployed to two sites in Year 1, three more in Year 2, and five more in Year 3.
In the first two years, it experiences a 1% improvement in throughput attributable to Cognite. As teams become more proficient and process mature, Cognite enables more advanced use cases and automation, enabling further optimization (2%) from Year 2.
Risks. Factors that could impact this benefit include the following:
User adoption of Cognite. Interviewees described that a key step in the project implementation was educating and training onsite users to get them on board with a new way of working.
Change management practices. Having data on a platform alone does not drive value. Organizations must also be agile enough to apply the derived insights into their processes and workflows.
Availability of data modeling skills and resources within the organization.
Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $10.7 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Sites | Composite | 10 | 10 | 10 | |
| A2 | Average production value per site | Composite | $500,000,000 | $500,000,000 | $500,000,000 | |
| A3 | Percentage of Cognite deployment | Interviews | 20% | 50% | 100% | |
| A4 | Improvement in throughput attributed to Cognite | Interviews | 1% | 2% | 2% | |
| A5 | Increase in production throughput attributed to Cognite | A1*A2*A3*A4 | $10,000,000 | $50,000,000 | $100,000,000 | |
| A6 | Profit margin | Composite | 10% | 10% | 10% | |
| At | Incremental profit from production optimization | A5*A6 | $1,000,000 | $5,000,000 | $10,000,000 | |
| Risk adjustment | ↓15% | |||||
| Atr | Incremental profit from production optimization (risk-adjusted) | $850,000 | $4,250,000 | $8,500,000 | ||
| Three-year total: $13,600,000 | Three-year present value: $10,671,300 | |||||
Evidence and data. Interviewees said that despite efforts to digitalize machinery in their heavy-asset industries, many assets were still incompatible with modern data architecture. As a result, a significant portion of industrial and operational data was still stored in silos on-premises, or existed only in physical form (e.g., paper).
Interviewees shared that in their prior environment, onsite engineers and technicians often had to depend on physical interactions with machinery and equipment to get data from these systems. This meant physically traveling to production sites or oil-producing facilities, resulting in a lot of wasted time. Furthermore, because systems were not well-integrated, they also spent a lot of time looking up data and information sheets on different legacy systems. This also created a big information divide between teams located onsite and offsite (e.g., in offices).
With Cognite, interviewees integrated data from many disparate industrial systems into one platform. Further, with the help of AI agents, they were also able to quickly ingest and contextualize (often unstructured) data, thus saving time on searching for information. Because there was now a single source of truth for data, collaboration between onsite and offsite teams also improved.
The chief digital officer at an energy company estimated that they reduced their maintenance team headcount requirements by 10%.
Interviewees in the oil and gas industry were especially concerned about optimizing staff efficiency while they were onsite and shared the common view that minimizing dependency on offshore staff was crucial, since that in turn minimized travel costs, emissions, and safety risks.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
There are 1,000 onsite staff, including engineers, technicians, floor managers, etc.
The staff members spend approximately 30% of their time on the job traveling around the site to access data from different machinery and searching for information on various systems.
Cognite cuts down the time the staff spends finding data and information on different platforms by 25%.
Risks. Factors that could impact this benefit include the following:
The starting state of industrial IT and OT systems, for instance, how much has been done to digitalize these assets.
The complexity and amount of data to be integrated
Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $10.5 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| B1 | Onsite staff members | Composite | 1,000 | 1,000 | 1,000 | |
| B2 | Average time spent offshore or in production/manufacturing facilities | Composite | 30% | 30% | 30% | |
| B3 | Reduction in time spent onsite with Cognite | Interviews | 25% | 25% | 25% | |
| B4 | Fully burdened annual salary for an onsite staff member | Composite | $165,000 | $165,000 | $165,000 | |
| B5 | Productivity recaptured | TEI methodology | 70% | 70% | 70% | |
| Bt | Improved onsite staff efficiency | B1*B2*B3*B4*B5*A3 | $1,732,500 | $4,331,250 | $8,662,500 | |
| Risk adjustment | ↓10% | |||||
| Btr | Improved onsite staff efficiency (risk-adjusted) | $1,559,250 | $3,898,125 | $7,796,250 | ||
| Three-year total: $13,253,625 | Three-year present value: $10,496,529 | |||||
Evidence and data. Interviewees said another benefit of contextualizing unstructured data was more usable and accessible information for analysis. Cognite helped interviewees’ organizations unlock data that was previously inaccessible, which proved invaluable for use cases like root cause analysis.
Interviewees noted that prior to Cognite, it was time-consuming to gather data from multiple sources and systems, and collaboration between onsite specialists and remote analysts was much more limited and siloed. As such, it could take months for teams to figure out and resolve performance anomalies.
The chief digital officer at an oil and gas company shared that, especially with the help of Cognite’s root cause analysis (RCA) agents, data access improved and became easier to access for wider group of users, which sped up root cause analysis by around 70%, and in some sites, even upwards of 80%. Similarly, the senior manager of technology at a second oil and gas company said that this allowed them to process their RCA backlog more effectively: “When you truly understand the root causes of the problems you’re seeing, it reduces the probability of recurrence. So it improves reliability, reduces costs, eliminates human errors, etc.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Prior to Cognite, the composite organization typically completed five major RCAs per site each year. Cognite reduced time and effort spent on a major RCA by 60%, allowing the composite to complete eight more RCAs per year at each site.
Each RCA completed saves 10 hours or production downtime avoided. The value of each hour of production is worth $150,000 in revenue.
Risks. Factors that could impact this benefit include the following:
Baseline asset productivity.
Resources that an organization can dedicate to working on RCAs.
Availability of data modeling skills and resources within the organization.
Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $14.5 million.
Reduction in time taken to complete RCAs with Cognite
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| C1 | Major RCAs performed without Cognite | Interviews | 5 | 5 | 5 | |
| C2 | Reduction in RCA time and effort with Cognite | Interviews | 60% | 60% | 60% | |
| C3 | Major RCAs performed with Cognite | C1/(1-C2) | 13 | 13 | 13 | |
| C4 | Downtime avoided with each RCA completed (hours) | Interviews | 10 | 10 | 10 | |
| C5 | Value of each production hour | Composite | $150,000 | $150,000 | $150,000 | |
| C6 | Sites with Cognite deployed | A1*A3 | 2 | 5 | 10 | |
| C7 | Profit margin | Composite | 10% | 10% | 10% | |
| Ct | Reduction in unplanned downtime | (C3-C1)*C4*C5*C6*C7 | $2,400,000 | $6,000,000 | $12,000,000 | |
| Risk adjustment | ↓10% | |||||
| Ctr | Reduction in unplanned downtime (risk-adjusted) | $2,160,000 | $5,400,000 | $10,800,000 | ||
| Three-year total: $18,360,000 | Three-year present value: $14,540,646 | |||||
Interviewees mentioned the following additional benefits that their organizations experienced but were not quantified for the study:
The transition toward more autonomously run plants. To address the increasing difficulty of attracting talent, several interviewees described their organizations’ vision of building (or retrofitting existing plants to become) digitalized and autonomized “plants of the future” within the next five to 10 years. They noted that the establishment of a data operations platform like Cognite was crucial groundwork to enabling further digital transformation efforts.
Better business decision-making through data democratization and improved collaboration. Interviewees said Cognite greatly expanded the number of employees that now have easy, shared access to accurate, contextualized data. Remote/offsite employees received a better understanding of what was happening onsite, which improved collaboration between onsite and remote teams.
The reduction of health and safety risks. By minimizing the time that employees had spent onsite — especially field visits for general inspections — interviewees’ organizations not only saved on travel time and costs but also reduced employees’ exposure to health and safety risks in hazardous areas.
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Cognite and later realize additional uses and business opportunities, including:
More advanced uses of AI for analytics. Each interviewee described a broad range of use cases for Cognite and shared similar sentiments that with genAI and agentic AI, there were even more possibilities for what they could do with Cognite.
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Dtr | Cognite subscription fees | $0 | $192,500 | $1,320,000 | $2,200,000 | $3,712,500 | $2,918,802 |
| Etr | Implementation and project management costs | $1,435,606 | $445,500 | $964,034 | $1,016,389 | $3,861,529 | $3,400,956 |
| Total costs (risk-adjusted) | $1,435,606 | $638,000 | $2,284,034 | $3,216,389 | $7,574,029 | $6,319,758 |
Evidence and data. Interviewees said Cognite subscription fees vary based on several factors, including the number of deployment sites, the volume of tags used, the types of data integrated (e.g., time series, P&IDs, 3D models, etc.), and the number of data services used.
Core service components accounted for in this financial model included data extraction and integration, data contextualization and modeling, AI-powered search, visualization, as well as AI-powered analytics.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Cognite is deployed at two sites in Year 1, three more in Year 2, and five more in Year 3, with an average of 30,000 to 50,000 tags per site.
Subscription fees in Year 1 are based on Cognite’s Quick Start offering to help organizations accelerate their time to value.
Risks. Factors that could impact this cost include deployment scope and services required as described above.
Results. To account for these risks and varying factors, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.9 million.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| D1 | Cognite subscription fees | Composite | $175,000 | $1,200,000 | $2,000,000 | |
| Dt | Cognite subscription fees | D1 | $0 | $175,000 | $1,200,000 | $2,000,000 |
| Risk adjustment | ↑10% | |||||
| Dtr | Cognite subscription fees (risk-adjusted) | $0 | $192,500 | $1,320,000 | $2,200,000 | |
| Three-year total: $3,712,500 | Three-year present value: $2,918,802 | |||||
Evidence and data. Interviewees said their organizations took very different approaches to implementation and ongoing project management. While half of the interviewees’ organizations depended largely on third-party partners for major technology projects like Cognite, the other half took a more hands-on approach with the implementation and project management because, according to the interviewees from these organizations, digital transformation was a core part of their organization.
Regardless of the approach, interviewees said that deployment was greatly sped up with the use of AI to contextualize data. For instance, one interviewee related that Cognite’s AI contextualization made it possible for them to digitalize and contextualize all their physical and/or unstructured files in the first place, reducing the average time taken from 5 minutes to 45 seconds per document.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite takes a hands-on approach to implementation and project management, dedicating a team of six IT and operational staff to oversee the initial implementation over a nine-month period. Once the first sites are set up, a team of four stays on within the project team to scale the implementation across further sites.
This team is complemented by one to two external technology consultants to build more complex apps and solutions.
All onsite staff undergo a 3-hour training on how to use the Cognite platform at the start of deployment.
Risks. Factors that could impact this cost include the following:
Complexity of operations
The state of digitalization of legacy OT and IT systems.
Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.4 million.
Reduction in time taken to digitalize and contextualize documents
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| E1 | FTEs involved in implementation | Interviews | 6 | |||
| E2 | Implementation period (months) | Interviews | 9 | |||
| E3 | Fully burdened annual salary for an FTE involved in project | Composite | $135,000 | $135,000 | $135,000 | $135,000 |
| E4 | Internal implementation costs | E1*E2/12*E3 | $607,500 | |||
| E5 | FTEs involved in ongoing management of project | Interviews | 4 | 4 | 4 | |
| E6 | Percentage of time spent on project and stakeholder management | Interviews | 75% | 75% | 75% | |
| E7 | Internal ongoing management costs | E3*E5*E6 | $405,000 | $405,000 | $405,000 | |
| E8 | Training time for onsite staff (hours) | Interviews | 3 | 3 | 3 | |
| E9 | Total FTE hours spent on training | E8*B1*(A3−A3PY) | 600 | 900 | 1,500 | |
| E10 | Training costs | E9*B4/2,080 | $47,596 | $71,394 | $118,990 | |
| E11 | Professional service fees | Interviews | $650,000 | $400,000 | $400,000 | |
| Et | Implementation and project management costs | E4+E7+E10+E11 | $1,305,096 | $405,000 | $876,394 | $923,990 |
| Risk adjustment | ↑10% | |||||
| Etr | Implementation and project management costs (risk-adjusted) | $1,435,606 | $445,500 | $964,034 | $1,016,389 | |
| Three-year total: $3,861,529 | Three-year present value: $3,400,956 | |||||
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($1,435,606) | ($638,000) | ($2,284,034) | ($3,216,389) | ($7,574,029) | ($6,319,758) |
| Total benefits | $0 | $4,569,250 | $13,548,125 | $27,096,250 | $45,213,625 | $35,708,475 |
| Net benefits | ($1,435,606) | $3,931,250 | $11,264,091 | $23,879,861 | $37,639,596 | $29,388,717 |
| ROI | 465% | |||||
| Payback period (months) | <6 months |
The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the composite organization’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.
These risk-adjusted ROI, NPV, and payback period values are determined by applying risk-adjustment factors to the unadjusted results in each Benefit and Cost section.
The initial investment column contains costs incurred at “time 0” or at the beginning of Year 1 that are not discounted. All other cash flows are discounted using the discount rate at the end of the year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations in the summary tables are the sum of the initial investment and the discounted cash flows in each year. Sums and present value calculations of the Total Benefits, Total Costs, and Cash Flow tables may not exactly add up, as some rounding may occur.
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Cognite.
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 Cognite can have on an organization.
Interviewed Cognite stakeholders and Forrester analysts to gather data relative to Cognite.
Interviewed seven decision-makers at four organizations using Cognite to obtain data about costs, benefits, and risks.
Designed a composite organization based on characteristics of the interviewees’ organizations.
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.
Employed four fundamental elements of TEI in modeling the investment impact: benefits, costs, flexibility, and risks. Given the increasing sophistication of ROI analyses related to IT investments, Forrester’s TEI methodology provides a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.
Benefits represent the value the solution delivers to the business. The TEI methodology places equal weight on the measure of benefits and costs, allowing for a full examination of the solution’s effect on the entire organization.
Costs comprise all expenses necessary to deliver the proposed value, or benefits, of the solution. The methodology captures implementation and ongoing costs associated with the solution.
Flexibility represents the strategic value that can be obtained for some future additional investment building on top of the initial investment already made. The ability to capture that benefit has a PV that can be estimated.
Risks measure the uncertainty of benefit and cost estimates given: 1) the likelihood that estimates will meet original projections and 2) the likelihood that estimates will be tracked over time. TEI risk factors are based on “triangular distribution.”
The present or current value of (discounted) cost and benefit estimates given at an interest rate (the discount rate). The PV of costs and benefits feed into the total NPV of cash flows.
The present or current value of (discounted) future net cash flows given an interest rate (the discount rate). A positive project NPV normally indicates that the investment should be made unless other projects have higher NPVs.
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
The interest rate used in cash flow analysis to take into account the time value of money. Organizations typically use discount rates between 8% and 16%.
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
1 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
Readers should be aware of the following:
This study is commissioned by Cognite 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 Cognite.
Cognite 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.
Cognite provided the customer names for the interviews but did not participate in the interviews.
Josephine Phua
January 2026
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