The Total Economic Impact™ Of Witboost
Cost Savings And Business Benefits Enabled By Witboost
A Forrester Total Economic Impact™ Study Commissioned By AgileLab, May 2024
According to Forrester’s research, organizations currently modernizing their data management platforms are looking to enable data across multiple domains, support agility with trusted data, and connect data across growing data silos.1 This analysis found that by using Witboost, organizations experience significant efficiency savings throughout data projects’ lifecycles and in large, companywide transformation initiatives.
Witboost is a platform that streamlines complex data projects across various platforms and enables data practitioners to automate tasks through its three core capabilities: Build, Govern, and Discover. Respectively, they enhance the development experience of data producers, streamline data governance processes, and facilitate business-driven data discovery. This unified approach empowers enterprises to fully utilize their data without platform-specific hurdles, leveraging automation and fostering smoother collaboration across teams.
AgileLab commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Witboost.2 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Witboost on their organizations.
Return on investment (ROI)
320%
Net present value (NPV)
$11.43M
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed the representative of an organization with experience using Witboost. Forrester used this experience to project a three-year financial analysis.
The interviewee, who is the head of data architecture at a financial services firm, noted that prior to using Witboost, their organization was struggling with finding and utilizing data due to the absence of a centralized platform. This led to lack of data discovery and use and a duplication of data. However, prior attempts yielded limited success, leaving them with bottlenecks in data development, a complex setup with data dispersed across different platforms and teams, not allowing for real data interoperability.
After the investment in Witboost, the interviewee’s enterprise has realized full interoperability, regardless of where the data comes from. Key results from the investment include cost savings in large, companywide transformation programs, productivity savings in the development of data projects, efficiency savings in discovery and project management, improvements in governance processes, and data storage cost avoidance.
Key Findings
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits include:
- Cost savings in large, companywide transformation programs of $7.7 million. Large, companywide transformation initiatives include both regulatory as well as business initiatives. Throughout the three-year analysis, the interviewee’s organization can save between 30% and 50% of the cost associated with these large, companywide initiatives due to Witboost’s usage across the organization. The savings are seen as Witboost enables coordination between different departments and regions and provides a single platform for everyone to work on, as well as the ability for its users to get to insights they could not reach before.
- Efficiency savings in the development of data projects of $1.8 million. By leveraging Witboost’s development templates, enabling self-development, and automating end-to-end provisioning, developers realize between 70% and 80% efficiency savings in the development of both smaller and larger data projects.
- Discovery and project management efficiency savings of $4.2 million. When working on data projects, the project managers involved realize between 50% and 65% efficiency savings within the three-year analysis period on both project management activities as well as on the discovery phases at the beginning of a data project lifecycle due to the Witboost platform. These savings are enabled by leveraging Witboost’s Marketplace for data discovery and searching and by having the project team working on the same platform, therefore significantly reducing the complexity of their prior work environment of working on different platforms and solutions.
- Efficiency savings on governance processes of $190,000. Witboost provides built-in governance gates and checks as part of managing a data project into production, hence users can realize efficiency savings thanks to automations around the governance processes every data project needs to go through.
- Data storage cost avoidance of $1.1 million. Witboost helps the interviewee’s organization realize cost savings by avoiding data duplication, resulting in significantly lower data storage.
Unquantified benefits. Benefits that are not quantified for this study include:
- Improved time to market. On top of improving from a developer and business-user efficiency standpoint, the interviewee also notes their organization benefits from improved time to market for its data projects, ultimately leading to a positive financial benefit for the organization.
- Ability to execute more programs in parallel. Due to Witboost’s capabilities and through decentralizing development the interviewee’s organization executes multiple programs in parallel.
- Improved governance. Thanks to Witboost, the interviewee says their organization can apply the same regulations and policies to all use cases, ensuring governance consistency across its entire operations.
- Full interoperability. Through Witboost, the interviewee’s organization could build full interoperability across data platforms while allowing for use cases to be exposed across the organization and enabling new insights.
- Improved employee experience. Through increased automation, employees can focus on more value-added tasks, resulting in increased employee satisfaction.
Costs. Three-year, risk-adjusted PV costs for the interviewee’s organization include:
- Subscription costs of $885,000. AgileLab charges organizations based on the number of monthly active users in the Witboost platform.
- Implementation, professional services, and ongoing management costs of $2.7 million. Additional costs are associated with the initial implementation of the Witboost platform, the professional services that go on top of the subscription cost to help the interviewee’s organization leverage the platform to its fullest potential, and the resources the interviewee’s organization dedicates to ongoing management of the Witboost platform. The professional services are an optional add-on for organizations using Witboost, and the interviewee’s organization leverages such services during the implementation phase.
The interview and financial analysis found that the representative’s organization experiences benefits of $14.99 million over three years versus costs of $3.57 million, adding up to a net present value (NPV) of $11.43 million and an ROI of 320%.
Key Statistics
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Return on investment (ROI)
320%
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Benefits PV
$14.99M
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Net present value (NPV)
$11.43M
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Payback
8 months
Benefits (Three-Year)
Cost savings in large, companywide transformation programs Productivity savings in the development of data projects Discovery and project management efficiency savings Improvements in governance processes Data storage cost avoidanceTEI Framework And Methodology
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Witboost.
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 Witboost can have on an organization.
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Due Diligence
Interviewed AgileLab stakeholders and Forrester analysts to gather data relative to Witboost.
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Interview
Interviewed the representative of an organization using Witboost to obtain data with respect to costs, benefits, and risks.
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Financial Model Framework
Constructed a financial model representative of the interview using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewee.
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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 AgileLab 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 Witboost.
AgileLab 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.
AgileLab provided the customer name for the interview but did not participate in the interview.
Consulting Team:
Elina Bauwens
Elia Gollini
Drivers leading to the Witboost investment
Interviewee’s Organization
Forrester interviewed the representative of an organization with experience using Witboost. Their organization has the following characteristics:
- $15 billion in revenue.
- European operations.
- 60,000 employees.
- Centralized data technology team with 25 members.
- 65 data projects developed per year.
- Total volume of data of 6.5 petabytes.
Key Challenges
Before engaging with Witboost, the interviewee noted that their organization had challenges with dispersed data being stored across three main data platforms throughout the organization. The interviewee mentioned their organization wanted to go through a data mesh journey because it wanted to build a federated data architecture.
The interviewee noted how the organization struggled with common challenges, including:
- Reliance on multiple platforms where the data resides. The interviewee highlighted how before working with Witboost, their organization had to identify, find, and move data across the main platforms it leverages when working with data projects. This led to difficult processes around finding and utilizing data due to the absence of a centralized platform, ultimately leading to lack of data discovery and use.
- Lack of data interoperability. The interviewee underlined how before using Witboost, their organization’s lack of interoperability across its data and data reusability was also a key issue. On top of these issues, the interviewee also highlighted high levels of data duplication due to lack of interoperability across the different platforms in which data is stored.
- Absence of self-discovery. The interviewee noted how before Witboost, there was no possibility for data consumers, who are stakeholders from different departments within their organization, to go self-discover and self-use data.
- Bottlenecks due to centralization. Before engaging with Witboost, the interviewee’s organization was adopting a centralized approach with a centralized team which created bottlenecks in data development.
Use Case Description
The interviewee’s organization operates in the financial services industry and has decided to adopt Witboost in order to connect different data platforms, improve agility, and enable a platform that provides a single view on data. In the first year after Witboost’s implementation, the interviewee noted their organization develops 65 data projects in Witboost. This amount increases throughout the years as the platform becomes more widely adopted within the organization’s different departments and operating countries. Eventually the number of data projects developed in Witboost stabilizes after three years, which is when the Witboost platform has reached the envisioned adoption levels. The centralized data technology team is made up of 25 individuals, while there are around 400 users using the Witboost platform (including customers) in Year 1. The interviewee says their organization uses Witboost for the following use cases:
- Ability to connect different data platforms.
- Possibility of having all data products in one marketplace.
- Ability to govern data in one platform.
- Data mesh implementation.3
For this use case, Forrester has modeled benefits and costs over three years.
Quantified benefit data
Total Benefits
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Cost savings in large, companywide transformation programs | $1,530,000 | $3,570,000 | $4,462,500 | $9,562,500 | $7,694,065 |
| Btr | Productivity savings in the development of data projects | $313,630 | $647,504 | $1,335,496 | $2,296,630 | $1,823,624 |
| Ctr | Discovery and project management efficiency savings | $568,620 | $1,440,504 | $3,285,360 | $5,294,484 | $4,175,766 |
| Dtr | Improvements in governance processes | $34,020 | $68,040 | $136,080 | $238,140 | $189,398 |
| Etr | Data storage cost avoidance | $175,500 | $386,100 | $842,400 | $1,404,000 | $1,111,544 |
| Total benefits (risk-adjusted) | $2,621,770 | $6,112,148 | $10,061,836 | $18,795,754 | $14,994,397 | |
Cost Savings In Large, Companywide Transformation Programs
Evidence and data. The interviewee highlighted how using Witboost has contributed significantly to cost savings around large, companywide, and multiyear transformation initiatives. Such initiatives include both regulatory initiatives, such as the implementation of country or regional new regulatory requirements, and business initiatives that impact a large amount of employees across the organization. Witboost has helped the interviewee’s organization reduce the cost for such initiatives due to its governing, automating, and enforcing capabilities, as well as the enablement of templates, integration of different data platforms, and faster development capabilities.
Modeling and assumptions. Based on interview data and secondary research, Forrester assumes the following:
- The average cost of a large, companywide transformation initiative is $10 million per annum and the organization undergoes two initiatives in Year 1 and three in Years 2 and 3.
- As the initiatives are not purely data-related, there is a 30% attribution of the cost that is data related. This percentage is assumed to increase in Years 2 and 3 to 35% as there is a substantial trend towards AI/machine learning (ML), there will therefore be an increased focus in projects that impact and improve data management and governance in coming years. Forrester research suggests that 60% of workers will use their own AI to perform their tasks and 84% of AI decision-makers have said that their executives are ready to adopt genAI.4
- The percentage saved to deliver the initiatives due to Witboost is assumed to grow from 30% in Year 1 to 40% in Year 2 and 50% in Year 3 as the interviewee’s organization becomes more familiar with Witboost and as usage increases.
Risks. This benefit may vary for organizations based on the following:
- The amount of large, companywide transformation initiatives a company undergoes and the initiatives’ size and complexity.
- The industry a company is in and the associated importance of data in the initiatives it undergoes.
- The data technology landscape and complexity the company faces.
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 $7.7 million.
Cost Savings In Large, Companywide Transformation Programs
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Total number of large, companywide transformation programs | Interview | 2 | 3 | 3 | |
| A2 | Average annual cost of large, companywide transformation programs | Interview | $10,000,000 | $10,000,000 | $10,000,000 | |
| A3 | Percentage of data related cost of the program | Interview | 30% | 35% | 35% | |
| A4 | Percentage saved to deliver initiative due to Witboost | Interview | 30% | 40% | 50% | |
| At | Cost savings in large, companywide transformation programs | A1*A2*A3*A4 | $1,800,000 | $4,200,000 | $5,250,000 | |
| Risk adjustment | ↓15% | |||||
| Atr | Cost savings in large, companywide transformation programs (risk-adjusted) | $1,530,000 | $3,570,000 | $4,462,500 | ||
| Three-year total: $9,562,500 | Three-year present value: $7,694,065 | |||||
Productivity Savings In The Development Of Data Projects
Evidence and data. The interviewee pointed out that one of the key benefits of the Witboost solution is its ability to ease the development of data projects. Data projects consist of data requests from the whole business, and they could be simple requests or very complex ones including the creation of data products. The developers working on such requests have seen substantial productivity savings since using Witboost. Witboost enabled the savings through the usage of templates, self-development capabilities, and automation of, for example, servers’ provisioning. Moreover, Witboost acts as the single source of truth for the interviewee’s organization and all data projects are discoverable through Witboost’s marketplace, enhancing developers’ productivity.
- The interviewee reported their organization experienced time savings of 70% for simple data projects and 80% for complex data projects.
- An example of a simple data projects can be a request of exposing data to create an API Dashboard. Complex data projects are those that need near-real-time data.
- Development activities needed to provide a cloud infrastructure include opening a request, its estimation and allocation of budget by the cloud engineering team, the provision of the budget, and the implementation by the cloud engineering team. This processes is eliminated by Witboost as the infrastructure can be self-provisioned leveraging standard templates.
Modeling and assumptions. Based on interview data and secondary research, Forrester assumes the following:
- The number of data projects doubles in Years 2 and 3, while after Year 3 it stabilizes. By then, Witboost will be rolled out throughout the interviewee’s organization.
- The split between simple and complex data projects is 60/40 in Year 1, changing to 55/45 in Year 2 and 50/50 in Year 3. This is due to the current trends towards AI/ML that will potentially increase the complexity of data requests and projects.
- The time it used to take the interviewee’s organization’s developers to develop a simple data project was around 24 days. Complex data projects needed 39 days.
- The average fully burdened hourly rate for a developer is $63 based on an annual salary of $130,000. The standard TEI burden rate is 35% and accounts for additional costs of employment, such as benefits (e.g., healthcare, insurance, bonuses, etc.), technology, office space, and employer taxes.
- A productivity capture rate of 50% is applied as a TEI standard as it can be assumed that only a certain part of the time saved is reallocated by users to productive work.
Risks. This benefit may vary for organizations based on the following:
- The number of data projects an organization has per year and the split between simple and complex ones.
- The complexity of the IT and regulatory environment they operate in.
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 $1.8 million.
Productivity Savings In The Development Of Data Projects
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| B1 | Total number of data projects | Interview | 65 | 130 | 260 |
| B2 | Percentage of simple to medium complexity data projects | Interview | 60% | 55% | 50% |
| B3 | Time spent on development activities for a simple to medium complexity data project before Witboost (hours) | Interview/24 days | 193 | 193 | 193 |
| B4 | Percentage time savings on simple to medium complexity data projects development due to Witboost | Interview | 70% | 70% | 70% |
| B5 | Subtotal: Hours saved on simple to medium complexity data projects due to Witboost | B1*B2*B3*B4 | 5255 | 9635 | 17518 |
| B6 | Percentage of complex data projects | Interview | 40% | 45% | 50% |
| B7 | Time spent on development activities for a complex data project before Witboost (hours) | Interview/39 days | 315 | 315 | 315 |
| B8 | Percentage time savings on complex data projects development due to Witboost | Interview | 80% | 80% | 80% |
| B9 | Subtotal: Hours saved on complex data projects due to Witboost | B1*B6*B7*B8 | 6552 | 14742 | 32760 |
| B10 | Fully burdened hourly salary for developer | TEI standard | $63 | $63 | $63 |
| B11 | Productivity percent capture | TEI standard | 50% | 50% | 50% |
| Bt | Productivity savings in the development of data projects | (B5+B9)*B10*B11 | $368,977 | $761,770 | $1,571,172 |
| Risk adjustment | ↓15% | ||||
| Btr | Productivity savings in the development of data projects (risk-adjusted) | $313,630 | $647,504 | $1,335,496 | |
| Three-year total: $2,296,630 | Three-year present value: $1,823,624 | ||||
Discovery And Project Management Efficiency Savings
Evidence and data. The interviewee noted that Witboost not only benefited developers but could also lead to significant efficiency savings for business users. In fact, due to its discovery ability, data consumers identify the right data to use for a data project much faster when using Witboost. On top of this, Witboost helped project managers manage their time more effectively and reduced the amount of time needed to dedicate to managing data projects.
Modeling and assumptions. Based on interview data and secondary research, Forrester assumes the following:
- The number of data projects doubles in Years 2 and 3, while after Year 3 it stabilizes and stops its growth. By then, Witboost will be rolled out throughout the interviewee’s organization.
- The split between simple and complex data projects is 60/40 in Year 1, 55/45 in Year 2, and 50/50 in Year 3. This is due to the current trends towards AI/ML that will potentially increase the complexity of data requests and projects.
- The project management (PM) effort required in simple data projects is of 0.2 FTEs, while for complex ones is of 0.6 FTEs.
- The percentage of time saved on project management efforts due to Witboost is assumed to grow from 50% in Year 1 to 60% in Year 2 and 65% in Year 3 as the interviewee’s organization becomes more familiar with Witboost and increases usage throughout the organization.
- The average fully burdened annual salary for a business user is $108,000. The standard TEI burden rate is 35% and accounts for additional costs of employment, such as benefits (e.g., healthcare, insurance, bonuses, etc.), technology, office space, and employer taxes.
- A productivity capture rate of 50% is applied as a TEI standard as it can be assumed that only a certain part of the time saved is reallocated by users to productive work.
Risks. This benefit may vary for organizations based on the following:
- The number of data projects an organization has per year and the split between simple and complex ones.
- The time taken by business users/PM in the discovery phases on data projects as well as the time taken for project management work.
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 $4.2 million.
Discovery And Project Management Efficiency Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| C1 | Total number of data projects | Interview | 65 | 130 | 260 |
| C2 | Percentage of simple to medium complexity data projects | Interview | 60% | 55% | 50% |
| C3 | Percentage of complex data projects | Interview | 40% | 45% | 50% |
| C4 | Average amount of PM effort required per simple to medium complexity data project (FTEs) | Interview | 0.2 | 0.2 | 0.2 |
| C5 | Average amount of PM effort required per complex data project (FTEs) | Interview | 0.6 | 0.6 | 0.6 |
| C6 | Percentage time saved on project management effort due to Witboost | Interview | 50% | 60% | 65% |
| C7 | Fully burdened annual salary for a business user | TEI standard | $108,000 | $108,000 | $108,000 |
| C8 | Productivity percent capture | TEI standard | 50% | 50% | 50% |
| Ct | Discovery and project management efficiency savings |
((C1*C2*C4)+(C1* C3*C5))*C6*C7*C8 |
$631,800 | $1,600,560 | $3,650,400 |
| Risk adjustment | ↓10% | ||||
| Ctr | Discovery and project management efficiency savings (risk-adjusted) | $568,620 | $1,440,504 | $3,285,360 | |
| Three-year total: $5,294,484 | Three-year present value: $4,175,766 | ||||
Improvements In Governance Processes
Evidence and data. The interviewee highlighted how their organization made significant improvements from a governance standpoint by leveraging Witboost. The interviewee’s organization established and enforced clear standards for data governance, including internal, industry-specific, and government standards/regulations and ensured each project goes through the needed governance checks before it gets released. Witboost enabled the interviewee’s organization to fully automate these governance processes, saving resources valuable time, improving time to market, and reducing risk of compliance issues or delays in product releases since governance checks before Witboost were human-driven and error-prone. This benefit does not account for the improved time to market or reduced risks, but rather measures the efficiency savings resulting from the automation of the governance checks.
Modeling and assumptions. Based on interview data and secondary research, Forrester assumes the following:
- The number of data projects doubles in Years 2 and 3, while after Year 3 it stabilizes. By then, Witboost will be rolled out throughout the interviewee’s organization.
- Every data project goes through two governance checks.
- The average fully burdened annual salary for a business user is $108,000. The standard TEI burden rate is 35% and accounts for additional costs of employment, such as benefits (e.g., healthcare, insurance, bonuses, etc.), technology, office space, and employer taxes.
- The percentage of time saved on governance checks is 100% as the tasks are fully automated.
- A productivity capture rate of 70% is applied as a TEI standard as it can be assumed that only a certain part of the time saved is reallocated by users to productive work. This percentage is higher than the previous ones used in the case study as the governance tasks will be fully automated.
Risks. This benefit may vary for organizations based on the following:
- The number of data projects an organization has per year.
- The industry they operate in, and the number of governance checks projects have to go through and the complexity of the checks.
- The extent to which the governance checks can be fully automated.
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 $189,000.
Improvements In Governance Processes
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| D1 | Total number of data projects | Interview | 65 | 130 | 260 |
| D2 | Average number of data governance checks per data project | Interview | 2 | 2 | 2 |
| D3 | Overall effort required for data governance checks before Witboost (FTEs) | Interview | 0.5 | 1 | 2 |
| D4 | Fully burdened annual salary for a business user | TEI standard | $108,000 | $108,000 | $108,000 |
| D5 | Percentage time saved on data governance processes due to Witboost | Interview | 100% | 100% | 100% |
| D6 | Productivity percent capture | TEI standard | 70% | 70% | 70% |
| Dt | Improvements in governance processes | D3*D4*D5*D6 | $37,800 | $75,600 | $151,200 |
| Risk adjustment | ↓10% | ||||
| Dtr | Improvements in governance processes (risk-adjusted) | $34,020 | $68,040 | $136,080 | |
| Three-year total: $238,140 | Three-year present value: $189,398 | ||||
Data Storage Cost Avoidance
Evidence and data. The interviewee highlighted how the nature of Witboost helped their organization managing its data better. As the interviewee’s organization has data residing in three different platforms, there are several issues of data duplication, leading to increased storage costs. Witboost helped mitigate these costs and avoid data duplication.
Modeling and assumptions. Based on interview data and secondary research, Forrester assumes the following:
- The total amount of data stored is assumed to grow by 10% in Year 2 and by 20% in Year 3.
- The amount of data duplication avoided due to Witboost is assumed to be 10% in Year 1, 20% in Year 2, and 40% in Year 3 when the scale of Witboost has increased and most of the data duplication can be avoided.
Risks. This benefit may vary for organizations based on the following:
- The amount of data an organization stores.
- The costs faced by an organization to store its data.
- The amount of data duplicated.
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 $1.1 million.
Data Storage Cost Avoidance
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| E1 | Total amount of data stored (TBs) | Interview | 6,500 | 7,150 | 7,800 | |
| E2 | Average monthly cost of storing 1 TB of data | Assumption | $25 | $25 | $25 | |
| E3 | Amount of data duplication avoided due to Witboost | Interview | 10% | 20% | 40% | |
| Et | Data storage cost avoidance | E1*(E2*12)*E3 | $195,000 | $429,000 | $936,000 | |
| Risk adjustment | ↓10% | |||||
| Etr | Data storage cost avoidance (risk-adjusted) | $175,500 | $386,100 | $842,400 | ||
| Three-year total: $1,404,000 | Three-year present value: $1,111,544 | |||||
Unquantified Benefits
The interviewee mentioned the following additional benefits that the organization experienced but was not able to quantify.
- Improved time to market. Witboost did not only lead to improvements from a data producer and data consumer standpoint, but the interviewee also mentioned benefits from improved time to market for its data projects. Users of Witboost work faster and save time, so the data projects deliver value in the market in a reduced time, ultimately improving the bottom-line.
- Ability to execute more data platforms in parallel. Witboost enables the interviewee’s organization to decentralize development. As a result, the interviewee said Witboost users execute multiple data platforms in parallel, which in turn contributes to their organization’s ability to meet demands and deliver its results in time.
- Improved governance. By using Witboost, the interviewee said their organization can apply the same regulations and policies to all use cases, ensuring governance consistency across its entire operations. This benefit can result in overall risk reduction.
- Full interoperability. Through Witboost, the interviewee’s organization could build full interoperability across data platforms, which is something that was not possible before working with Witboost. At the same time, Witboost allows for use cases to be exposed across the entire organization and to be discoverable by users in different teams, departments, and countries. This includes the possibility to work with data from countries that have a much different and complex digital ecosystem and enables new insights from data that was not possible prior to the investment to Witboost.
- Improved employee experience. As Witboost increases automation, employees working on data projects are able to focus on more value-added tasks, resulting in increased employee satisfaction.
Flexibility
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Witboost and later realize additional uses and business opportunities, including:
- Easier integration of data from new companies or markets. By using Witboost, the interviewee said their organization achieves higher levels of flexibility as new countries, markets, technologies, teams, and companies’ data can be easily integrated and leveraged through the Witboost platform. This makes the interviewee’s organization more agile in the way it can scale its operations across industries and geographies.
- Incentivized self-service, agility, and innovation. The interviewee’s organization has experienced use cases in which stakeholders have developed a project without detailed planning or any budget preallocated for the work. They have done so because the Witboost users had the interest to start using the Witboost platform as they thought that this could bring them benefits in their day-to-day work. This is possible with Witboost as, once a data project is developed, it is exposed in the marketplace and available for use across the organization.
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).
Quantified cost data
Total Costs
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Ftr | Subscription costs | $0 | $325,500 | $358,050 | $390,600 | $1,074,150 | $885,282 |
| Gtr | Implementation, professional services, and ongoing management costs | $1,025,200 | $554,400 | $673,200 | $792,000 | $3,044,800 | $2,680,605 |
| Total costs (risk-adjusted) | $1,025,200 | $879,900 | $1,031,250 | $1,182,600 | $4,118,950 | $3,565,887 | |
Subscription Costs
Evidence and data. AgileLab charges Witboost’s users on a monthly active user basis on top of a standard fixed fee.
Modeling and assumptions. To quantify this cost, Forrester assumes the following:
- The fixed fee is set at $110,000 per year.
- The number of monthly active users increases by 10% each year from 230.
- Pricing may vary. Contact AgileLab for additional details.
Risks. This cost may vary for different organizations based on the following:
- The scale of deployment and the number of monthly active users of Witboost.
- The organization’s region, exchange rates, and change over time.
Results. To account for these risks, Forrester adjusted this cost upward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $885,000.
Subscription Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|---|
| F1 | Subscription annual fee | Interview | $310,000 | $341,000 | $372,000 | ||
| Ft | Subscription costs | F1 | $0 | $310,000 | $341,000 | $372,000 | |
| Risk adjustment | ↑5% | ||||||
| Ftr | Subscription costs (risk-adjusted) | $0 | $325,500 | $358,050 | $390,600 | ||
| Three-year total: $1,074,150 | Three-year present value: $885,282 | ||||||
Implementation, Professional Services, And Ongoing Management Costs
Evidence and data. On top of the subscription fee, the interviewee said their organization engaged AgileLab to help with the implementation and the scale out of Witboost, incurring some professional services costs along with the implementation and ongoing management costs.
- Professional services are leveraged by the interviewee’s organization to realize the full potential of Witboost. The interviewee said their organization has opted to engage with Witboost for professional services to adopt and use the platform. This is not a mandatory item for all customers, but rather an add-on. Witboost can be implemented and adopted without engaging in additional professional services.
- Implementation cost calculates the cost faced by the interviewee’s organization when setting up the Witboost solution.
- Resources dedicated to the ongoing management of the Witboost solution also add to this cost.
Modeling and assumptions. To quantify this cost, Forrester assumes the following:
- Eight resources are involved in the implementation for six months.
- The professional services cost is higher initially as it includes support from AgileLab in the implementation phase, then it flattens out to an average of $15,000 monthly throughout Years 1, 2, and 3.
- Three resources are dedicated to ongoing management of the Witboost solution in Year 1, increasing to four resources in Year 2 and five resources in Year 3 as Witboost’s usage increases throughout the organization.
- The average fully burdened annual salary for a business user is $108,000. The standard TEI burden rate is 35% and accounts for additional costs of employment, such as benefits (e.g., healthcare, insurance, bonuses, etc.), technology, office space, and employer taxes.
Risks. This cost may vary for different organizations based on the following:
- The scale of deployment, complexity of the IT, and the legacy environment may impact the implementation costs.
- The extent to which an organization wants to leverage Witboost’s professional services as opposed to internal resources.
- The amount of resources dedicated to the ongoing management of Witboost will depend on organizational maturity and the scale of deployment.
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 $2.7 million.
Implementation, Professional Services, And Ongoing Management Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|---|
| G1 | Number of resources involved in implementation | Interview | 8 | ||||
| G2 | Length of implementation (years) | Interview | 0.5 | ||||
| G3 | Professional services cost | Interview | $500,000 | $180,000 | $180,000 | $180,000 | |
| G4 | Resources dedicated to ongoing management of Witboost platform | Interview | 0 | 3 | 4 | 5 | |
| G5 | Fully burdened annual salary for a developer | TEI standard | $108,000 | $108,000 | $108,000 | $108,000 | |
| Gt | Implementation, professional services, and ongoing management costs |
(G1*G2*G5)+G3+ (G4*G5) |
$932,000 | $504,000 | $612,000 | $720,000 | |
| Risk adjustment | ↑10% | ||||||
| Gtr | Implementation, professional services, and ongoing management costs (risk-adjusted) | $1,025,200 | $554,400 | $673,200 | $792,000 | ||
| Three-year total: $3,044,800 | Three-year present value: $2,680,605 | ||||||
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 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 Estimates)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($1,025,200) | ($879,900) | ($1,031,250) | ($1,182,600) | ($4,118,950) | ($3,565,887) |
| Total benefits | $0 | $2,621,770 | $6,112,148 | $10,061,836 | $18,795,754 | $14,994,397 |
| Net benefits | ($1,025,200) | $1,741,870 | $5,080,898 | $8,879,236 | $14,676,804 | $11,428,510 |
| ROI | 320% | |||||
| Payback | 8 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
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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.
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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.
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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.
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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 Source: The Future Of Data Management, Forrester Research, Inc., February 9, 2022.
2 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.
3 Forrester defines data mesh as a business-led strategic approach to data and data practices that enables a communication plane between applications, machines, and people. It matches the data, queries, and models to the solution to keep each party — human and machine — in sync and speaking the same language; source: The Modern Data Environment Uses Both Data Fabric And Data Mesh, Forrester Research, Inc., April 26, 2023.
4 Source: Predictions 2024: Artificial Intelligence, Forrester Research, Inc., October 26, 2023.
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