Answer 8 questions. See how you rank against industry peers, get a dollar estimate of addressable inefficiency, and a prioritized roadmap — in under 3 minutes.
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Step 1 of 8
What is your company's annual revenue?
Used to anchor dollar waste estimates and benchmark your data investment against industry norms. Baseline: dbt Labs State of Analytics Engineering 2024; Salesforce State of Data and Analytics 2023
What industry are you in?
Data team sizing norms and SaaS spend benchmarks vary significantly by sector. Source: a16z SaaS benchmarks, OpenView SaaS survey 2023, HIMSS analytics (healthcare)
How big is your dedicated data team?
Includes data engineers, analysts, and data scientists — not BI consumers or business stakeholders. Source: dbt Labs State of Analytics Engineering 2024; Fivetran Enterprise Data Infrastructure Benchmark 2025
Estimated annual waste so far: calculating...
Who owns data decisions today?
Data accountability gaps are one of the strongest predictors of poor data ROI. Organizations with a dedicated data leader are significantly more likely to report trusted reporting and faster time-to-insight. Source: Gartner CDAO Survey 2024; Salesforce State of Data and Analytics 2023
Estimated annual waste so far: calculating...
How many data sources or systems do you work across?
Includes CRM, ERP, marketing platforms, billing systems, product databases, spreadsheets. Each additional source adds ~15% maintenance overhead. Source: Fivetran Enterprise Data Infrastructure Benchmark 2025 (avg 328 pipelines; 53% of engineering time on maintenance); Fivetran AI & Data Readiness Survey 2025
Estimated annual waste so far: calculating...
How reliable is your reporting today?
Poor data quality costs organizations an average of $12.9M per year (Gartner). Only 57% of data leaders are fully confident in their data accuracy. Over 25% of organizations lose more than $5M annually to data quality issues. Source: Gartner 2021; Salesforce State of Data and Analytics 2023; IBM Think, The True Cost of Poor Data Quality, 2026
Estimated annual waste so far: calculating...
How long to answer a new business question with data?
Data workers in organizations without strong data infrastructure spend 30–40% of their time just finding data, and another 20–30% cleaning it — leaving less than half their time for actual analysis. Source: McKinsey Digital; McKinsey State of AI 2024 (63% of leaders cite data inaccuracy as primary AI concern)
Estimated annual waste so far: calculating...
Annual spend on data tools and SaaS?
Includes BI tools, data warehouse, ETL/ELT, CRM, marketing automation. Average SaaS utilization is 56%, meaning ~44% of spend delivers no value. The average enterprise spends $29.3M on data programs annually, with $4.2M going to data integration alone. Source: Productiv SaaS Trends 2023; Zylo SaaS Management Index 2023; Fivetran Enterprise Data Infrastructure Benchmark 2025
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