The Total Economic Impact™ Of Glean
Cost Savings And Business Benefits Enabled By Glean
A Forrester Total Economic Impact™ Study Commissioned By Glean, September 2024
As organizations have moved to adopt cloud storage solutions and software-as-a-service (SaaS) applications, the number and variety of data sources in which they keep their enterprise documentation and data have grown. As a result, it has become increasingly difficult for employees to know how to find this documentation when needed. Solutions like Glean look to solve this problem, enabling employees to quickly access all of an organization’s knowledge from a single tool using search and generative artificial intelligence (genAI).
Glean connects to enterprise data sources, whether cloud-based or on-premises, to index and build a knowledge graph of an organization’s documents, employees, and communications. Glean provides search results and answers powered by genAI in response to user queries, including a conversational interface for interacting with and getting answers from company data. Results from Glean are personalized to the user based on the user’s access permissions, role, frequent collaborators, and current and recent projects. In addition, Glean serves as a platform for building genAI applications, allowing companies to develop chatbots and other custom AI use cases that are securely grounded in their organization’s data.
Glean commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Glean.1 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Glean on their organizations.
Return on investment (ROI)
141%
Net present value (NPV)
$15.6 million
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four representatives with experience using Glean. For the purposes of this study, Forrester aggregated the interviewees’ experiences and combined the results into a single composite organization that is a global organization with 10,000 employees and $13 billion in revenue.
Interviewees said that prior to using Glean, their organizations experienced “SaaS sprawl” — their data was spread across numerous data sources, including cloud storage solutions and SaaS applications. Some of these organizations sought out third-party solutions or built homegrown solutions to address the issue. However, limitations in these search tools and the expense to build and maintain them resulted in the organizations still suffering from data silos and employee information overload.
The interviewees noted that after the investment in Glean, organizational data became easier and more intuitive to access for all employees using Glean. Key results from the investment include employees spending less time searching for information and more time getting important work done, faster onboarding and improved time to effectiveness for new employees, and a reduction in the number of support requests related to finding and accessing enterprise data.
Key Findings
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
- Additional productivity from search improvements of up to 110 hours per employee per year. With Glean, employees spend less time searching for the data they need to complete their tasks and more time being productive. Instead of spending hours going through various data sources and applications looking for what is needed, employees simply search in Glean and receive relevant search results and genAI answers with citations. This provides the composite organization with a three-year risk-adjusted PV of $23.2 million.
- Faster onboarding of 36 hours per new hire. Because information is easier to find, new employees are onboarded faster and can become effective employees more quickly. This provides the composite organization with a three-year risk-adjusted PV of $1.7 million.
- Reduction in support requests of 20%. Because the composite’s employees can find the data they need more easily, they send fewer requests to IT support for help with finding and accessing that information. As a result, IT support requests fall by 20%, leading to a three-year risk-adjusted PV of $450,000 for the composite organization.
- Technology savings of $566,000 annually. After deploying Glean, the composite organization decommissions a limited third-party solution that it previously deployed. This results in a three-year risk-adjusted PV of $1.3 million.
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
- Security. Glean improves the security posture of the composite because it leverages built-in connectors to access the company’s data, rather than needing to connect SaaS providers’ native AI solutions to data sources, creating more end points for potential attacks.
- User adoption. Unlike prior attempts to solve the SaaS sprawl problem, Glean is adopted by the vast majority of the composite’s employee base quickly, so savings are not only actually achieved but also achieved faster.
- Employee satisfaction and retention. Glean also improves the composite’s employee satisfaction scores because employees experience less daily frustration attempting to find needed data and failing. The experience improves so much that Glean also serves as an employee retention tool.
- Time to value. By reducing the amount of time spent searching for data, Glean also improves the time to value of employees’ work. For example, by accessing bug data and customer reporting, engineering teams can release updates faster, and by accessing pitch decks and battlecards faster, sales teams can close deals more quickly.
- Partnership. The composite also benefits from Glean’s high level of customer service; any issues are addressed and solved quickly.
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
- Glean fees. The composite organization chooses to leverage Glean’s fully managed SaaS offering, paying $40 per user, which includes basic discounting. It would pay $35 per user if it chose to self-host but would then incur extra expenses related to storage, compute, and labor. The composite spends a three-year risk-adjusted PV of $10.5 million on Glean fees.
- Integration and testing. It takes the composite two weeks to test built-in connectors for eight data sources and one month to build, integrate, and test customer connectors for its remaining two data sources. This results in a three-year risk-adjusted PV cost of $85,000.
- Ongoing management. The composite uses one full-time equivalent to manage Glean on an ongoing basis, resulting in a three-year risk-adjusted PV cost of $415,000.
The representative interviews and financial analysis found that a composite organization experiences benefits of $26.6 million over three years versus costs of $11.0 million, adding up to an NPV of $15.6 million and an ROI of 141%.
Key Statistics
-
Return on investment (ROI)
141%
-
Benefits PV
$26.6 million
-
Net present value (NPV)
$15.6 million
-
Payback
<6 months
Benefits (Three-Year)
Productivity from search improvements Productivity from faster on-boarding of new hires Productivity from less search assistance Technology savingsTEI Framework And Methodology
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Glean.
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 Glean can have on an organization.
-
Due Diligence
Interviewed Glean stakeholders and Forrester analysts to gather data relative to Glean.
-
Interviews
Interviewed four representatives at organizations using Glean to obtain data about costs, benefits, and risks.
-
Composite Organization
Designed a composite organization based on characteristics of the interviewees’ organizations.
-
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.
-
Case Study
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.
Disclosures
Readers should be aware of the following:
This study is commissioned by Glean 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 Glean.
Glean 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.
Glean provided the customer names for the interviews but did not participate in the interviews.
Consulting Team:
Nick Mayberry
Drivers leading to the Glean investment
Interviews
| Role | Industry | Region | Percentage Of Employees Using Glean |
|---|---|---|---|
| Director of design and engineering | Data management | Global | 97% |
| Head of digital workplace | Data storage | Global | ~100% |
| Employee experience engineering lead | Financial technology | Global | 83% |
| Senior manager of product and technology | Telecom | North America | 100% |
Key Challenges
Before investing in Glean, either the interviewees’ organizations had no enterprise search deployed — they used only whatever native search tools came with their various data sources — or they had some limited enterprise search across data sources, whether homegrown or from a third party.
The interviewees noted how their organizations struggled with common challenges, including:
- Siloed data sources. Each interviewee shared that their organization’s documentation was stored across various data sources. Knowing where to find any given file was frustrating, negatively impacting employee experience. The senior manager of product and technology from the telecommunications industry said: “We want our business units to have autonomy to move quickly, but that resulted in a very disassociated IT landscape. All our information was spread out across different SaaS solutions.” Furthermore, different native search tools worked differently, requiring employees to have knowledge of the ins and outs of each native search tool, making native search even more difficult to use moving between numerous data sources.
- Information overload. Additionally, each interviewee noted that their organization had developed a plethora of important knowledge management documentation over the years. However, numerous versions of the same documentation existed, and it became difficult for employees to locate the most updated and therefore most useful knowledge they needed to complete their tasks. The head of digital workplace from the data storage industry said: “We want to give our employees a wealth of information, but now there is just too much. After an employee thought they solved the first challenge of where the documentation sat, they then had to figure out if it was the most recent version, which may sit in another repository.”
- Limitations of search. Organizations that had some search capabilities found them to be limited. Native search tools were naturally limited to their own data sources. The financial technology organization had deployed a homegrown search solution, but it was limited to the company’s own intranet. The data storage company used a third-party enterprise search tool, but it lacked functionality and was used by only two teams.
Composite Organization
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 four interviewees, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:
Description of composite. The composite is a global organization with 10,000 employees and $13 billion in annual revenues. It is experiencing a number of challenges as the amount of information it has created has grown. Internal employee experience surveys show that employees feel there is too much documentation, that it is not clear where this information can be found, and that there are outdated versions of too much of this information. It does not have the requisite knowledge or resources to build a robust, cross-platform, homegrown enterprise search tool.
Deployment characteristics. The composite has 10,000 total employees spread across its global footprint. It has eight current data repositories where information needed for employee tasks is kept. One of these is the company’s own intranet, and another is an older system. Both of these repositories require a custom integration with Glean. The six remaining repositories are modern cloud SaaS applications and leverage built-in connectors to integrate with Glean. Additionally, the composite integrates a new cloud-based application in each of Years 2 and 3. Lastly, the composite decides to utilize Glean’s fully managed SaaS model, where Glean handles the setup and management of a composite-dedicated cloud instance for Glean.
Quantified benefit data as applied to the composite
Total Benefits
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Productivity from search improvements | $6,912,000 | $9,792,900 | $11,718,000 | $28,422,900 | $23,180,849 |
| Btr | Productivity from faster onboarding of new hires | $622,080 | $699,840 | $777,600 | $2,099,520 | $1,728,130 |
| Ctr | Reduction in support requests | $146,880 | $200,880 | $200,880 | $548,640 | $450,468 |
| Dtr | Technology savings | $509,760 | $509,760 | $509,760 | $1,529,280 | $1,267,698 |
| Total benefits (risk-adjusted) | $8,190,720 | $11,203,380 | $13,206,240 | $32,600,340 | $26,627,145 | |
Productivity From Search Improvements
Evidence and data. Each of the interviewees shared that their organization’s employees benefited from time savings and increased productivity after deploying Glean. Whether switching from using only native search in cloud applications or a mixture of native search and homegrown search, the interviewees shared that Glean performed better, returning results faster and returning more accurate results.
They noted that Glean returns results faster because it integrates with all the organization’s data sources, whether on an intranet or in the cloud. Employees can go to Glean to find any document that resides within any integrated information repository instead of going from app to app using native search or hunting through directories. The head of digital workplace from the data storage industry said: “One team’s biggest complaint was that they did not have a dedicated app or group of apps to store their knowledge, where other teams typically did. Glean removed this problem altogether because it no longer matters where the information lives. Glean surfaces it.”
The senior manager of product and technology from the telecommunications industry noted that their organization was experiencing substantial time savings for call center employees in particular. Although the organization was still working on a defensible metric for how much time was saved in the call center, the senior manager of product and technology was able to share that a conservative estimate for savings in that unit alone was $8 million annually. The head of digital workplace from the data storage industry similarly noted: “We’re especially seeing time savings accrue in customer support. Before, they had to go through multiple systems to find the release note or other information, but with Glean the answer is at the tip of their fingers wherever the source document resides.”
According to the interviewees, Glean also returned more accurate results because it understands the company’s knowledge graph. Glean layers onto each search the specific company context. This means that Glean can surface results from third-party apps with more relevance to the user than that third-party app’s native search. The director of design and engineering from the data management industry said: “We only started appreciating the power of Glean when we looked at outside tools. The AI add-ons native to third-party apps work fine, but they don’t have the company context. You can enable that, but it comes with security exposure. You don’t have to bring more context to Glean.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
- The composite has 10,000 total employees and 93% are Glean users at full adoption.
- The composite has eight data sources before deploying Glean. It deploys and integrates a new data source in Years 2 and 3.
- The average user saves 60 hours annually utilizing Glean for search rather than native search tools for data sources.
- Each user that adopts Glean’s genAI capability saves an additional 50 hours per year. The adoption of genAI is slower, with 10% adoption by Year 2 and 20% adoption by Year 3. The interviewees’ organizations adopted these genAI features as add-ons, but Glean customers since May 2024 have access to these capabilities built into the license. As a result, genAI capability adoption may accelerate at these companies, along with the associated benefits.
- The average fully burdened hourly rate for an employee is $40.
- The average employee uses 50% of their returned time productively.
Risks. The value of improved employee productivity from utilizing Glean for enterprise search varies with:
- The total number of employees adopting Glean.
- The adoption curve of Glean’s genAI.
- The fully burdened hourly rate of the average Glean user.
- The productivity recapture rate of the average Glean user.
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 $23.2 million.
Productivity From Search Improvements
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| A1 | Total employees | Composite | 10,000 | 10,000 | 10,000 |
| A2 | Percent active users of search | Interviews | 80% | 93% | 93% |
| A3 | Percentage of total Year 3 data integrations completed | Interviews | 80% | 90% | 100% |
| A4 | Annual time saved searching (hours) | Interviews | 60 | 65 | 70 |
| A5 | Average fully burdened hourly rate of pay for an employee | TEI standard | $40 | $40 | $40 |
| A6 | Productivity recapture rate | Composite | 50% | 50% | 50% |
| A7 | Average fully burdened hourly rate of pay for an employee | TEI standard | $40 | $40 | $40 |
| A8 | Productivity recapture rate | Composite | 50% | 50% | 50% |
| At | Productivity from search improvements | A1*A2*A3*A4*A5* A6 | $7,680,000 | $10,881,000 | $13,020,000 |
| Risk adjustment | ↓10% | ||||
| Atr | Productivity from search improvements (risk-adjusted) | $6,912,000 | $9,792,900 | $11,718,000 | |
| Three-year total: $28,422,900 | Three-year present value: $23,180,849 | ||||
Productivity From Faster Onboarding Of New Hires
Evidence and data. In addition to saving the broader employee base time on every search they did for company files and documentation, Glean’s faster and more accurate results also enabled new hires to onboard faster. The employee experience engineering lead from the financial technology industry said: “We have a massive onboarding document, and now it’s fully indexed by Glean. We’re saving between one day and one week of time per new employee when it is all added up.”
Glean’s positive impact on new hires went beyond the onboarding process. The senior manager of product and technology from the telecommunications industry said: “We’re still tracking it, but so far I think the biggest benefit is that employees six months and under are performing better than longer-term employees. Our hypothesis s that these folks aren’t bogged down by their time-consuming prior habits and are using Glean from Day 1.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
- Employee turnover averages 6%, with 600 new hires made each year. The total number of employees remains approximately stable.
- Each new hire saves 36 hours during the onboarding process because of easier search with Glean compared to new hires before Glean deployment.
- The average fully burdened hourly rate for an employee is $40.
Risks. The value of improved productivity from easier onboarding with Glean will vary based on:
- The total number of new hires.
- The average fully burdened hourly rate of these hires.
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 $1.7 million.
Productivity From Faster Onboarding Of New Hires
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| B1 | Average new hire rate | Composite | 6% | 6% | 6% |
| B2 | Reduced hours to onboard | Interviews | 36 | 36 | 36 |
| B3 | Average fully burdened hourly rate of pay for an employee | TEI standard | $40 | $40 | $40 |
| Bt | Productivity from faster onboarding of new hires | A1*B1*B2*B3*A2 | $691,200 | $777,600 | $864,000 |
| Risk adjustment | ↓10% | ||||
| Btr | Productivity from faster onboarding of new hires (risk-adjusted) | $622,080 | $699,840 | $777,600 | |
| Three-year total: $2,099,520 | Three-year present value: $1,728,130 | ||||
Reduction In Support Requests
Evidence and data. As the broader employee base was able to find better information faster, they relied less on other people to help them find the information they needed. The head of digital workplace from the data storage industry said: “We’re using Glean to get rid of the concept of individuals as knowledge centers. There’s always someone that everyone goes to for help, and as Glean becomes a part of our culture, people are leaning into it, relying on self-help via Glean rather than on the individual expert.”
The director of design and engineering from the data management industry shared that their firm is approaching this benefit in a more targeted fashion by developing chatbot versions of internal experts. The director said: “We’re building Glean chatbots as subject matter expert (SME) replacement or augmentation. We have experts internally who are constantly being asked questions by others, but they also of course have their day jobs to attend to. By building the AI bot of that expert, we’re not only freeing them up to focus on higher-value opportunities, we’re virtually multiplying their time to respond to questions and share their knowledge with the wider workforce.”
The core quantification for this benefit that interviewees were able to provide was a decrease in help desk tickets. The employee experience engineering lead from the financial technology industry said: “Glean has helped us reduce the burden on help desk support staff. We’ve seen a 20% decrease in general support tickets, and we’re seeing that questions that need an answer, as opposed to an action, are going down dramatically.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
- The composite has 20 total help desk professionals.
- Support requests are reduced by 20% at full adoption of Glean.
- The average fully burdened annual rate of a help desk professional is $80,000.
- The average help desk professional uses 75% of their returned time productively.
Risks. The value of reducing support requests will vary with:
- The total number of help desk professionals.
- The average fully burdened annual rate of a help desk professional.
- The average productivity recapture rate of a help desk professional.
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 $450,000.
Reduction In Support Requests
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| C1 | Total number of help desk professionals | Composite | 20 | 20 | 20 |
| C2 | Support request reduction rate | Interviews | 17% | 20% | 20% |
| C3 | Fully burdened annual rate for a help desk professional | Composite | $80,000 | $80,000 | $80,000 |
| C4 | Productivity recapture rate | Composite | 75% | 75% | 75% |
| Ct | Reduction in support requests | C1*C2*C3*C4*A3 | $163,200 | $223,200 | $223,200 |
| Risk adjustment | ↓10% | ||||
| Ctr | Reduction in support requests (risk-adjusted) | $146,880 | $200,880 | $200,880 | |
| Three-year total: $548,640 | Three-year present value: $450,468 | ||||
Technology Savings
Evidence and data. The interviewees shared that their organizations reduced various categories of technology-related expenses after deploying Glean. These included third-party search tools, homegrown search tools, and the labor costs of integrating various data sources and SaaS platforms with each other.
The telecom firm and the data storage company both moved away from limited third-party search tools that they had invested in. The senior manager of product and technology from the telecommunications industry said: “We were using different solutions across different platforms, sometimes unified by team or role. For example, we used a security-documentation-specific search tool for security documentation, which we decommissioned once Glean was deployed. We did not have a unified search platform until Glean.” The head of digital workplace from the data storage industry said: “We had an enterprise search tool that we decommissioned because it was only used by marketing and engineering. It was a highly customized application that someone had to maintain.”
The employee experience engineering lead from the financial technology industry said that their organization had been in the process of developing a homegrown enterprise search tool when it evaluated and chose Glean instead. This interviewee said, “This enabled us to deprecate the homegrown search tool, saving a few hundred thousand dollars that it would have cost us to run and maintain that tool on an ongoing basis.”
The director of design and engineering from the data management industry shared that it saved labor costs associated with integrating its various data sources with each other. The director said: “We’ve eliminated a lot of the extra point-to-point integration and the labor associated with it. Because we have centralized all the knowledge and use cases on Glean, we don’t need to integrate the data sources to each other.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
- The composite decommissions a prior technology solution that cost about 10% as much as Glean.
- This solution required 0.75 FTEs to manage it.
Risks. The value of technology savings will vary with:
- The number of existing technologies that can be decommissioned, including third-party enterprise search and homegrown enterprise search.
- The associated labor to manage these technologies on an ongoing basis.
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 $1.3 million.
Technology Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| D1 | Cost of decommissioned technology | Interviews | $446,400 | $446,400 | $446,400 |
| D2 | Time cost to manage this technology | Interviews | $120,000 | $120,000 | $120,000 |
| Dt | Technology savings | D1+D2 | $566,400 | $566,400 | $566,400 |
| Risk adjustment | ↓10% | ||||
| Dtr | Technology savings (risk-adjusted) | $509,760 | $509,760 | $509,760 | |
| Three-year total: $1,529,280 | Three-year present value: $1,267,698 | ||||
Unquantified Benefits
Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:
- Security. The interviewees noted that Glean helped to improve their security posture and maintained permissioning when compared to the native AI add-ons for their data sources and SaaS solutions. For example, the director of design and engineering for the data management industry said: “The native AI add-ons require integrations into the tool so they can have better AI. This brings security exposure as it creates additional endpoints. But because Glean has done the integrations, you don’t need to bring more context to Glean, sharply reducing this increase in exposure.”
- User adoption. The interviewees shared that user adoption was relatively easy with Glean. The head of digital workplace from the data storage industry said: “Adoption was very good. Within 90 days, we had 80% adoption.” The employee experience engineering lead from the financial technology industry shared: “Glean deserves much of the credit for fast user adoption; they’ve built a good product. But our strategy also helped. Instead of doing a typical change management campaign, we just incorporate Glean into something they were already using: our intranet search.” The senior manager of product and technology from the telecom industry stated, “It’s easy to get adoption with Glean because it works just like popular search engines.”
- Employee satisfaction and retention. Interviewees also expressed that employee satisfaction improved after the deployment of Glean and that it could serve as a retention tool. The director of design and engineering from the data management industry said: “In our employee surveys, those that felt they were effective at their job went from the 60s before Glean to the 80s after it. Glean was very frequently referenced by users as helping them do their job. The senior manager of product and technology from the telecom industry shared, “Glean has improved worker satisfaction by making it easy to get stuff done.” On retention, the head of digital workplace from the data storage industry stated: “We’ve gotten such an overwhelmingly positive result among employees, it is now a retention tool. Glean is a way of life now. We can’t take it away. At a minimum, our folks wouldn’t go and work for a company without it.”
- Time to value. The interviewees also said that because Glean reduced the time to find information, certain searches by certain users would increase the time to value of those users’ revenue-related activities. For example, the head of digital workplace from the data storage industry shared: “Our engineering team uses Glean to search across multiple engineering systems at once to understand bugs for customers, look up code, and find release notes. This improves the time to release of our updates and therefore provides value to our customers earlier.” This interviewee continued: “Our sales team uses Glean to find the latest sales information, pitch decks, battlecards, and competitive information. It’s been huge for them. They now really have the company’s knowledge at their fingertips and can get to closing deals faster.”
- Partnership. Interviewees also stated that Glean was able to build a strong and trusted partnership with their organizations. For example, the senior manager of product and technology from the telecom industry noted: “Glean is the easiest vendor we’ve ever had to deal with. They’ve been very white-glove, very easy to communicate with, and they get things resolved quickly. I feel like we have a solid partnership.”
Flexibility
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Glean and later realize additional uses and business opportunities, including:
- Internal network effects. The interviewees shared that Glean’s building of an index of company knowledge creates internal network effects that are powerful but difficult to quantify. For example, the director of design and engineering from the data management industry shared: “One of the most powerful examples of Glean’s indexing is the ‘stumble upon.’ It’s ‘Oh, I stumbled upon this wiki or conversation or document that I didn’t know existed,’ and they’ll resurrect it because it may serve a purpose of theirs or for others.” The employee experience engineering lead from the financial technology industry shared another example, saying, “We’ve heard that Glean’s index has created passive collaboration opportunities by informing one team what another team is doing, while it also enabled developers to learn how to develop in a new code without having to go spend hours hunting down documentation.”
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).
Quantified cost data as applied to the composite
Total Costs
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Etr | Glean licensing fees | $0 | $3,840,000 | $4,464,000 | $4,464,000 | $12,768,000 | $10,534,035 |
| Ftr | Integration and testing costs | $72,512 | $7,040 | $7,040 | $0 | $86,592 | $84,730 |
| Gtr | Ongoing management costs | $0 | $151,360 | $176,000 | $176,000 | $503,360 | $415,286 |
| Total costs (risk-adjusted) | $72,512 | $3,998,400 | $4,647,040 | $4,640,000 | $13,357,952 | $11,034,051 | |
Glean Licensing Fees
Evidence and data. The interviewees shared paying Glean fees based on the number of total seats accessing Glean. Some interviewees’ organizations chose to host Glean using their own cloud services, while others chose to use Glean’s managed services. In the former case, organizations paid less per seat but incurred additional costs for cloud or onsite infrastructure and for labor to manage this infrastructure. In the latter case, organizations paid higher per-seat fees and saved on such costs.
Modeling and assumptions. For the composite organization, Forrester models:
- The composite pays $40 per user for Glean, which includes basic volume discounting, and it takes advantage of Glean’s managed services.
- The composite would pay $35 per user if it chooses to host Glean itself.
Risks. Total Glean fees will vary with:
- The total number of Glean users.
- Whether the organization self-hosts Glean or uses Glean’s SaaS offering.
Results. Because Glean provided the pricing for the composite organization, Forrester did not adjust this cost for risk, yielding a three-year, total PV (discounted at 10%) of $10.5 million.
Glean Licensing Fees
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| E1 | Glean licensing fees | Glean | $0 | $3,840,000 | $4,464,000 | $4,464,000 |
| Et | Glean licensing fees | E1 | $0 | $3,840,000 | $4,464,000 | $4,464,000 |
| Risk adjustment | 0% | |||||
| Etr | Glean licensing fees (risk-adjusted) | $0 | $3,840,000 | $4,464,000 | $4,464,000 | |
| Three-year total: $12,768,000 | Three-year present value: $10,534,035 | |||||
Integration And Testing Costs
Evidence and data. The interviewees’ organizations incurred limited costs associated with integrating their data sources with Glean, and interviewees said these costs were limited by the fact that Glean comes with a number of prebuilt connectors for the most popular data sources, limiting the integration time for these connectors to simplify testing. Interviewees also shared that for data sources without prebuilt connectors, their organizations experienced internal labor costs associated with both building the integrations and testing them.
Modeling and assumptions. For the composite organization, Forrester models:
- The composite integrates a total of 10 data sources with Glean by Year 3.
- Of the eight existing data sources at the time of Glean deployment, six have prebuilt connectors and two do not.
- Prebuilt connectors for the composite require two weeks of testing time each.
- Custom connectors require one month of testing time each.
- In Years 1 and 2, the composite deploys one new data source each, both of which come with prebuilt connectors in Glean.
Risks. The cost to integrate and test Glean will vary with:
- The total number of data sources required to be connected to Glean.
- The mix of prebuilt connectors and custom integrations required based on these data sources.
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 $85,000.
Integration And Testing Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| F1 | Built-in integrations needed | Composite | 6 | 1 | 1 | 0 |
| F2 | Time to test per built-in connector (hours) | Interviews | 80 | 80 | 80 | 0 |
| F3 | Custom integrations needed | Composite | 2 | 0 | 0 | 0 |
| F4 | Time to build and test a custom connector (hours) | Interviews | 172 | 172 | 172 | 0 |
| F5 | Average fully burdened hourly rate for an employee involved in integration | TEI standard | $80 | $80 | $80 | $0 |
| Ft | Integration and testing costs | (F1*F2+F3*F4)* F5 |
$65,920 | $6,400 | $6,400 | $0 |
| Risk adjustment | ↑10% | |||||
| Ftr | Integration and testing costs (risk-adjusted) | $72,512 | $7,040 | $7,040 | $0 | |
| Three-year total: $86,592 | Three-year present value: $84,730 | |||||
Ongoing Management Costs
Evidence and data. Lastly, interviewees said their organizations experienced ongoing management costs related to troubleshooting, testing if new documents are showing up in Glean, help desk tickets, and any custom development utilizing Glean. Most interviewees shared requiring one employee full-time or two employees part-time to manage Glean.
Modeling and assumptions. Forrester models that the composite needs one FTE to manage Glean.
Risks. The cost of ongoing management will vary with:
- How frequently checks are run to ensure new documents appear in Glean.
- Any future decisions to custom build utilizing Glean.
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 $415,000.
Ongoing Management Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| G1 | FTEs needed to manage Glean | Interviews | 0 | 1 | 1 | 1 |
| G2 | Fully burdened annual rate for an IT professional | Composite | $160,000 | $160,000 | $160,000 | |
| G3 | Percentage of time needed to manage Glean | Composite | 0% | 86% | 100% | 100% |
| Gt | Ongoing management costs | G1*G2*G3 | $0 | $137,600 | $160,000 | $160,000 |
| Risk adjustment | ↑10% | |||||
| Gtr | Ongoing management costs (risk-adjusted) | $0 | $151,360 | $176,000 | $176,000 | |
| Three-year total: $503,360 | Three-year present value: $415,286 | |||||
Consolidated Three-Year Risk-Adjusted Metrics
Cash Flow Chart (Risk-Adjusted)
Total costs Total benefits Cumulative net benefits-
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.
Cash Flow Analysis (Risk-Adjusted)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($72,512) | ($3,998,400) | ($4,647,040) | ($4,640,000) | ($13,357,952) | ($11,034,051) |
| Total benefits | $0 | $8,190,720 | $11,203,380 | $13,206,240 | $32,600,340 | $26,627,145 |
| Net benefits | ($72,512) | $4,192,320 | $6,556,340 | $8,566,240 | $19,242,388 | $15,593,094 |
| ROI | 141% | |||||
| Payback | <6 months | |||||
Appendix A: Total Economic Impact
Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists vendors in communicating the value proposition of their products and services to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior management and other key business stakeholders.
Total Economic Impact Approach
-
Benefits represent the value delivered to the business by the product. The TEI methodology places equal weight on the measure of benefits and the measure of costs, allowing for a full examination of the effect of the technology on the entire organization.
-
Costs consider all expenses necessary to deliver the proposed value, or benefits, of the product. The cost category within TEI captures incremental costs over the existing environment for 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. Having 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 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.
Appendix B: Endnotes
1 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists vendors in communicating the value proposition of their products and services to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior management and other key business stakeholders.
PDF 