Study
Forrester TEI Study
Published on 02 September 2026
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The Total Economic Impact™ Of Huwise
Total Economic Impact
A Forrester Total Economic Impact Study Commissioned By Huwise, September 2026
Cost Savings And Business Benefits Enabled By Huwise Data Product Marketplace
This study is commissioned by Huwise and delivered by Forrester Consulting.
Despite significant investments in data lakes, warehouses, and catalogs, many organizations still struggle to realize meaningful, day‑to‑day business value because data remains difficult to find, access, and reuse across business teams and AI agents. Solutions that simplify and scale data consumption enable organizations to better leverage their data assets, resulting in faster decisions, operational efficiency and productivity, and better use of existing data resources.
Huwise is a data product marketplace built on top of existing data solutions to organize and distribute data products to human and AI systems. By enabling self‑service discovery, use, access, and governance of trusted data products, Huwise can reduce manual data delivery and decrease duplicate analytics effort across teams. In doing so, the solution helps organizations more fully realize the value of prior data investments by increasing organizationwide data reuse, adoption, operational efficiency, and productivity.
Huwise commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying its data product marketplace solution. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Huwise on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four decision-makers with experience using Huwise. For the purposes of this study, Forrester aggregated the experiences of the interviewees and combined the results into a single composite organization with 10,000 employees globally.
Interviewees reported that prior to using Huwise, their organizations operated in a fragmented data environment with multiple disconnected business intelligence (BI) tools, dashboards, and data platforms. Business users struggled to find, understand, use, and trust data products due to overly technical interfaces, inconsistent definitions, duplicated metrics, and limited documentation, while data assets had low visibility and reuse by business teams and in AI use cases. Access to data was largely IT-driven, slow, and difficult to scale, leading analysts and data teams to spend excessive time preparing data rather than delivering insights.
With Huwise, interviewees saw a shift to a centralized, internal data product marketplace that unified access to governed data products. Their organizations were able to make trusted data products easy to discover, understand, and reuse through self-service, reducing dependency on IT and duplicate analytics work.
Key results from the investment include increased data reuse, faster access to data for business users and AI agents, and improved productivity across analytics and data engineering teams.
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
The financial analysis that is based on the interviews found that a composite organization experiences benefits of $7.8 million over three years versus costs of $1.4 million, adding up to a net present value (NPV) of $6.5 million and an ROI of 474%.
“Huwise makes it much easier for nontechnical users to find and work with data without needing a data expert to prepare it for them. … By giving users prepackaged, well-defined data products through Huwise, we reduce the need for them to understand all the underlying complexity, which makes data much more accessible.” — VP, enterprise data and analytics, enterprise software
Drivers leading to the Huwise investment
| Role | Industry | Region | Employees |
|---|---|---|---|
| Chief data officer (CDO) | Financial services | France | 350,000 |
| VP, enterprise data and analytics | Enterprise software | North America, EMEA, and Asia‑Pacific operations; customers worldwide | ~20,000 |
| Group CDO and group head of data management | Insurance and risk management | France, with global presence, operating in 100+ countries across Europe, Americas, Asia‑Pacific, Middle East & Africa | ~5,000 |
| IoT, smart sensors, and data solutions lead | Environmental services | France, with global operations across Europe, North America, Asia‑Pacific, Middle East, Africa, and Latin America | ~200 |
Interviewees noted how their organizations struggled with common challenges, including:
“Our main challenge is the fragmentation of assets because of all the legacy products and data solutions we have. It becomes very difficult for users to find and access data because they don’t know exactly what is available.” CDO, financial services
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. The composite organization is a large European-headquartered enterprise with global operations across approximately 50 countries. It generates around $5 billion in annual revenue and employs about 10,000 people worldwide. The organization operates a highly complex data environment that includes cloud data platforms, on‑premises systems, BI tools, APIs, and external data sources. Prior to adopting Huwise, data access and analytics were fragmented across multiple tools, leading to inconsistent definitions, duplicated dashboards, low data reuse, and heavy reliance on IT and data teams for routine data requests.
Deployment characteristics. The composite organization deploys Huwise incrementally, beginning with a limited rollout to data teams and priority use cases following a short implementation period. It layers the solution on top of existing data platforms, BI tools, and metadata systems, enabling fast technical setup without major infrastructure changes. As part of the proof of concept, Huwise is introduced to employees in data-centered roles (e.g., analysts, engineers, BI specialists), comprising approximately 2% of the organization. Adoption then gradually expands to employees across more functions, business units, and regions as use cases mature. Due to the platform’s user-friendly interface, users require minimal training and reach productive usage within less than one year, supporting enterprisewide scale over time.
Quantified benefit data as applied to the composite
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Accelerated time to insight and improved productivity for business users | $1,015,750 | $2,031,500 | $2,539,375 | $5,586,625 | $4,510,205 |
| Btr | Improved productivity in data search and preparation for data teams | $1,200,000 | $1,200,000 | $1,200,000 | $3,600,000 | $2,984,222 |
| Ctr | Reduced analytics effort and duplication for data teams | $89,600 | $89,600 | $89,600 | $268,800 | $222,822 |
| Dtr | Avoided IT costs | $44,800 | $44,800 | $44,800 | $134,400 | $111,411 |
| Total benefits (risk-adjusted) | $2,350,150 | $3,365,900 | $3,873,775 | $9,589,825 | $7,828,660 |
Evidence and data. Although they already had data catalogs in place, interviewees described similar challenges with training business users to access and use the data available to them. This resulted in poor user adoption and engagement, with one interviewee describing that they saw “less than two users per report” created on average.
Interviewees reported several improvements in how end users interacted with data:
The simplicity of the Huwise user interface enabled self-service data consumption for users without data analytics expertise. As a result, the CDO in financial services said they’d seen a significant reduction in the number of data requests or tickets from employees.
The shift to a centralized data product marketplace also improved employees’ trust in data. At an enterprise software company, Huwise helped to break down data silos and eliminate duplicate reports and dashboards. The VP of enterprise data and analytics shared that having a common, certified view of sales and marketing metrics such as annual recurring revenue, churn, pipeline, and usage reduced discussions on data validity and improved collaboration between sales and marketing teams.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Risks. Some factors that can impact how much time savings end users experience include:
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.5 million.
“With data readily available through Huwise, someone can now assemble in an hour what would have taken them a week before, because I just have the data ready.” VP, enterprise data and analytics, enterprise software
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| A1 | Employees | Composite | 10,000 | 10,000 | 10,000 |
| A2 | Percentage of employees with data-centered functions | Interviews | 5.0% | 10.0% | 12.5% |
| A3 | Employees with data-centered functions | A1*A2 | 500 | 1,000 | 1,250 |
| A4 | Daily time spent searching for and validating data (hours) | Interviews | 0.50 | 0.50 | 0.50 |
| A5 | Time savings on data search and validation | Interviews | 50% | 50% | 50% |
| A6 | Total time savings on data search and validation for business users (hours) | A3*A4*A5*250 | 31,250 | 62,500 | 78,125 |
| A7 | Fully burdened hourly rate for an employee | Composite | $40.63 | $40.63 | $40.63 |
| At | Accelerated time to insight and improved productivity for business users | A6*A7 | $1,269,688 | $2,539,375 | $3,174,219 |
| Risk adjustment | ↓20% | ||||
| Atr | Accelerated time to insight and improved productivity for business users (risk-adjusted) | $1,015,750 | $2,031,500 | $2,539,375 |
Three-year total: $5,586,625Three-year present value: $4,510,205
Evidence and data. Business end users were not the only ones who benefited from using a data product marketplace. Data analysts well trained in working with data also benefited from having a unified platform as the ease of discovery sped up their data search.
One interviewee described that data product reuse also significantly increased among power users like data scientists and analysts. While they previously spent most of their time preparing raw data, analysts could now easily find and pull data from existing reports.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Risks. Some factors that can impact how much time savings data analysts experience include:
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.0 million.
“Before, data was not always gathered in the same database or location, so it was very difficult to merge and cross-analyze data. It was a game-changer for us to have Huwise to gather data of different formats together.” IoT, smart sensors, and data solutions lead, environmental services
“Huwise helps us focus on productivity and trust. Someone can assemble an analysis in an hour that used to take a week because the data is already available. And when they’re done, the result is correct because they’re using the same trusted data as everyone else instead of creating their own version.” VP, enterprise data and analytics, enterprise software
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| B1 | Employees | Composite | 10,000 | 10,000 | 10,000 |
| B2 | Percentage of employees in data/analytics/BI functions | Interviews | 2.0% | 2.0% | 2.0% |
| B3 | Daily time spent searching for and preparing data (hours) | Interviews | 1.2 | 1.2 | 1.2 |
| B4 | Time savings on data search and preparation | Interviews | 50% | 50% | 50% |
| B5 | Total time savings on data search and validation for data team (hours) | B1*B2*B3*B4*250 | 30,000 | 30,000 | 30,000 |
| B6 | Fully burdened hourly rate for a data analyst | Composite | $50.00 | $50.00 | $50.00 |
| Bt | Improved productivity in data search and preparation for data teams | B5*B6 | $1,500,000 | $1,500,000 | $1,500,000 |
| Risk adjustment | ↓20% | ||||
| Btr | Improved productivity in data search and preparation for data teams (risk-adjusted) | $1,200,000 | $1,200,000 | $1,200,000 |
Three-year total: $3,600,000Three-year present value: $2,984,222
Evidence and data. Interviewees highlighted that prior to adopting Huwise, data analytics teams received frequent, repetitive data requests from business users, many of which required recreating similar datasets or reports multiple times. This led to duplicated effort across teams, complexity in establishing a single source of truth, and inefficient use of analyst resources. With Huwise, business users were able to self-serve from a centralized repository of curated data products, significantly reducing the volume of incoming requests. Analysts also benefited from increased reuse of existing data assets, minimizing the need to rebuild similar reports or datasets from scratch.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Risks. Some factors that can impact the reduction of duplicated work include:
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $223,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| C1 | New data products created before Huwise (annually) | Interviews | 160 | 160 | 160 |
| C2 | New data products created with Huwise (annually) | 25%*C1 | 40 | 40 | 40 |
| C3 | Analyst time to create a new data product (hours) | Interviews | 16 | 16 | 16 |
| C4 | Reduction in time to create a new data product (hours) | 50%*C3 | 8 | 8 | 8 |
| C5 | Total time savings on data product creation (hours) | (C1*C3)-(C2*C4) | 2,240 | 2,240 | 2,240 |
| C6 | Fully burdened hourly rate for a data analyst | TEI methodology | $50.00 | $50.00 | $50.00 |
| Ct | Reduced analytics effort and duplication for data teams | C5*C6 | $112,000 | $112,000 | $112,000 |
| Risk adjustment | ↓20% | ||||
| Ctr | Reduced analytics effort and duplication for data teams (risk-adjusted) | $89,600 | $89,600 | $89,600 |
Three-year total: $268,800Three-year present value: $222,822
Evidence and data. Interviewees reported that prior to Huwise, fragmented data environments drove significant reliance on IT support for data access, troubleshooting, and tool-related issues. For instance, with each new data report or dashboard that data analysts had to build, IT teams were involved in activities such as building custom data connections and ensuring the right data access.
Additionally, there were often multiple overlapping tools and data licenses across departments due to lack of standardization. With Huwise providing a unified platform for data access and consumption, organizations experienced a reduction in IT support tickets related to data issues as well as improved visibility into tool usage. This also enabled consolidation of redundant tools and licenses, lowering overall IT spend.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Risks. Some factors that can impact IT cost savings include:
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $111,000.
“We managed to reduce our dependence on IT systems and saved time and money by using some features directly on the Huwise platform.” IoT, smart sensors, and data solutions lead, environmental services
“We retired 278 dashboards … and expect to take about $10 million of cost out of the old environment.” VP of enterprise data and analytics, enterprise software
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| D1 | IT support tickets avoided with Huwise | C1-C2 | 120 | 120 | 120 |
| D2 | IT time spent per support ticket (hours) | Interviews | 6 | 6 | 6 |
| D3 | Total IT time avoided with Huwise (hours) | D1*D2 | 720 | 720 | 720 |
| D4 | Fully burdened hourly rate for an IT employee | Composite | $50.00 | $50.00 | $50.00 |
| D5 | IT support costs avoided | D3*D4 | $36,000 | $36,000 | $36,000 |
| D6 | Data licenses avoided | 50%*B1*B2 | 100 | 100 | 100 |
| D7 | Average annual license fees | Composite | $200 | $200 | $200 |
| D8 | Total license fees avoided | D6*D7 | $20,000 | $20,000 | $20,000 |
| Dt | Avoided IT costs | D5+D8 | $56,000 | $56,000 | $56,000 |
| Risk adjustment | ↓20% | ||||
| Dtr | Avoided IT costs (risk-adjusted) | $44,800 | $44,800 | $44,800 |
Three-year total: $134,400Three-year present value: $111,411
Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:
“With Huwise, users can explore the data without coding and technical expertise. It gives more autonomy to end users, and it’s easy for them to consume datasets that are clean, in good quality, and stable.” CDO, financial services
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Huwise and later realize additional uses and business opportunities, including:
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
Quantified cost data as applied to the composite
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Etr | Huwise license fees | $0 | $308,000 | $385,000 | $495,000 | $1,188,000 | $970,083 |
| Ftr | Implementation and deployment costs | $162,150 | $93,449 | $93,449 | $93,449 | $442,497 | $394,544 |
| Total costs (risk-adjusted) | $162,150 | $401,449 | $478,449 | $588,449 | $1,630,497 | $1,364,627 |
Evidence and data. Interviewees reported that Huwise license fees were structured as an annual subscription and scaled over time as usage expanded across teams, use cases, and data volumes. License costs typically increased as organizations onboarded more users, integrated additional data sources, and extended Huwise to support broader AI‑driven use cases.
Modeling and assumptions. Based on the interviews, Forrester assumes the composite organization licenses Huwise on a subscription basis with costs that increase over time as adoption scales. The composite organization begins with a lower license fee in Year 1, reflecting an initial rollout to core data teams and priority business users and expands usage in Years 2 and 3 as adoption grows across business functions, regions, and AI use cases.
Risks. Actual license fees may vary based on the following factors:
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 $970,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| E1 | Huwise license fees | Composite | $280,000 | $350,000 | $450,000 | |
| Et | Huwise license fees | E1 | $0 | $280,000 | $350,000 | $450,000 |
| Risk adjustment | ↑10% | |||||
| Etr | Huwise license fees (risk-adjusted) | $0 | $308,000 | $385,000 | $495,000 |
Three-year total: $1,188,000Three-year present value: $970,083
Evidence and data. Interviewees described the technical setup as relatively fast, with most effort focused on documentation, governance alignment, and change management. They noted that as a SaaS platform with an intuitive design, Huwise was easy to use and administer. Interviewees also highlighted strong vendor support during early dashboard and use‑case development, which helped accelerate initial adoption.
They reported a fast learning curve and noted that the consumer‑grade user experience enabled analysts and business users, including low‑data‑literacy users, to become productive with minimal or no formal training.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Risks. Actual implementation effort may vary depending on the complexity of existing data infrastructure and number of integrations required.
Results. To account for these risks, Forrester adjusted this cost upward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $395,000.
“Technically speaking, it is really quick to implement. If you already have high data maturity, it’s a matter of weeks.” CDO, financial services
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| F1 | Platform setup and configuration time (hours) | Interviews | 80 | |||
| F2 | Data source integration time (hours) | Interviews | 60 | |||
| F3 | FTEs involved in implementation | Interviews | 3 | |||
| F4 | Total IT time spent on implementation (hours) | (F1+F2)*F3 | 420 | |||
| F5 | Fully burdened hourly rate for an IT employee | D4 | $50.00 | |||
| F6 | IT implementation costs | F4*F5 | $21,000 | |||
| F7 | Data analyst onboarding time (hours per FTE) | Interviews | 12 | |||
| F8 | Total time spent on onboarding for data analysts (hours) | F7*B1*B2 | 2,400 | |||
| F9 | Business user onboarding time (hours) | Interviews | 4 | 4 | 4 | |
| F10 | Business users onboarded | 5%*A1 | 500 | 500 | 500 | |
| F11 | Total time spent on onboarding for business users (hours) | F9*F10 | 2,000 | 2,000 | 2,000 | |
| F12 | Fully burdened hourly rate for a data analyst/employee | TEI methodology | $50.00 | $40.63 | $40.63 | $40.63 |
| F13 | Total onboarding effort | (F8+F11)*F12 | $120,000 | $81,260 | $81,260 | $81,260 |
| Ft | Implementation and deployment costs | F6+F13 | $141,000 | $81,260 | $81,260 | $81,260 |
| Risk adjustment | ↑15% | |||||
| Ftr | Implementation and deployment costs (risk-adjusted) | $162,150 | $93,449 | $93,449 | $93,449 |
Three-year total: $442,497Three-year present value: $394,544
Consolidated Three-Year, Risk-Adjusted Metrics
Cash Flow Chart (Risk-Adjusted)
Cash Flow Analysis (Risk-Adjusted)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($162,150) | ($401,449) | ($478,449) | ($588,449) | ($1,630,497) | ($1,364,627) |
| Total benefits | $0 | $2,350,150 | $3,365,900 | $3,873,775 | $9,589,825 | $7,828,660 |
| Net benefits | ($162,150) | $1,948,701 | $2,887,451 | $3,285,326 | $7,959,328 | $6,464,033 |
| ROI | 474% | |||||
| Payback | <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 Huwise.
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 Huwise can have on an organization.
Interviewed Huwise stakeholders and Forrester analysts to gather data relative to its data product marketplace.
Interviewed four decision-makers at organizations using Huwise 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.”
Present value (PV). The present or current value of (discounted) cost and benefit estimates given at an interest rate (the discount rate). The PVs of costs and benefits feed into the total NPV of cash flows.
Net present value (NPV). 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.
Return on investment (ROI). A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
Discount rate. 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%.
Payback. The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
APPENDIX A
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 Huwise 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 the Huwise data marketplace solution for any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect’s business. Forrester believes that this analysis is representative of what companies may achieve with Huwise based on the inputs provided and any assumptions made. Forrester does not endorse Huwise or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, Huwise and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein. The interactive tool is provided ‘AS IS,’ and Forrester and Huwise make no warranties of any kind.
Huwise 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.
Huwise provided the customer names for the interviews but did not participate in the interviews.
Consulting Team:
Josephine Phua
PUBLISHED
September 2026
This study is commissioned by Huwise and delivered by Forrester Consulting.