Process improvement is moving fast, and the economics are showing up clearly. For example, the U.S. cost of poor quality is estimated at about $2.7 trillion each year, roughly 12% of GDP, which makes the case for fixing process waste more urgent than ever. At the same time, automation coverage across core back office processes is at 45% for 2024, leaving a wide gap between what teams are measuring and what they are actually automating.
Key Takeaways
- 38% of organizations say their AI initiatives are focused on improving customer service processes (e.g., call handling, knowledge retrieval) as reported in 2024
- 76% of organizations use workflow automation to improve efficiency (survey-based adoption/usage share)
- In a 2023 survey of operations leaders, 58% reported that continuous improvement reduced operational risk (percent respondents)
- Process mining tools are expected to grow from $1.0B in 2023 to $5.0B by 2030 (CAGR 23%)
- The global robotic process automation (RPA) market is projected to reach $12.8B by 2030 (from $1.9B in 2022), reflecting a high-growth period
- The global business process management (BPM) software market is forecast to grow to $17.8B by 2028 (from $9.1B in 2020)
- The U.S. Department of Commerce estimated that the cost of poor quality was about $2.7 trillion annually in the US (about 12% of GDP)
- A meta-analysis reported that Six Sigma projects achieve average cost savings due to reduced defects and variation; improvements in process capability translate into measurable financial benefits
- In healthcare quality improvement, reducing avoidable complications has been estimated to save $1.7B annually in the US, supporting process improvement investments
- In a JAMA Network Open study, a workflow redesign reduced median time-to-treatment by 36% (measured change after implementation)
- After implementing Lean initiatives, manufacturers in a 2020 peer-reviewed study reduced defect rates by 45% (measured before/after)
- In a study of process redesign in call centers, average handle time decreased by 14% after workflow optimization (measured reduction)
- In a 2024 Gartner survey, 51% of respondents reported implementing process automation technologies (e.g., RPA, workflow automation) to improve business process efficiency
- According to iGrafx 2023 BPM trends, 72% of surveyed organizations use some form of process documentation/visualization
- In a 2022 Capgemini survey, 63% of organizations reported having a formal process improvement program
AI and process improvement programs are delivering measurable gains in efficiency, quality, and time to treatment.
Related reading
01 · Category
Industry Trends3 stats
01
38% of organizations say their AI initiatives are focused on improving customer service processes (e.g., call handling, knowledge retrieval) as reported in 2024https://www.gartner.com/en/newsroom/press-releases/2024-08-08-gartner-survey-finds-47-percent-of-organizations-have-implemented-at-least-one-ai-use-case
02
76% of organizations use workflow automation to improve efficiency (survey-based adoption/usage share)https://www.k2.com/wp-content/uploads/2023/01/K2-2023-Workflow-Automation-Report.pdf
03
In a 2023 survey of operations leaders, 58% reported that continuous improvement reduced operational risk (percent respondents)https://www.pmi.org/learning/library/continuous-improvement-operational-risk-survey
Interpretation
Industry Trends Interpretation
Under industry trends in process improvement, organizations are increasingly using automation and AI to drive measurable operational gains, with 76% leveraging workflow automation for efficiency and 38% applying AI to strengthen customer service processes, while continuous improvement reduced operational risk for 58% of operations leaders in 2023.
02 · Category
Market Size10 stats
01
Process mining tools are expected to grow from $1.0B in 2023 to $5.0B by 2030 (CAGR 23%)https://www.fortunebusinessinsights.com/process-mining-market-107746
02
The global robotic process automation (RPA) market is projected to reach $12.8B by 2030 (from $1.9B in 2022), reflecting a high-growth periodhttps://www.marketsandmarkets.com/Market-Reports/robotic-process-automation-market-598.html
03
The global business process management (BPM) software market is forecast to grow to $17.8B by 2028 (from $9.1B in 2020)https://www.marketsandmarkets.com/Market-Reports/business-process-management-market-246.html
04
The global IT service management (ITSM) market is projected to reach $24.2B by 2028 (from $12.4B in 2022)https://www.marketsandmarkets.com/Market-Reports/it-service-management-market-214043.html
05
Lean Six Sigma training spend in the US was estimated at approximately $2.3B in 2023 (market spending estimate)https://www.ibisworld.com/industry-trends/experts/lean-six-sigma-training-market-size
06
The global workflow management market is expected to reach $12.5B by 2028 (from $5.4B in 2021)https://www.globenewswire.com/news-release/2023/02/06/2609691/0/en/Workflow-Management-Market-to-Reach-12-5-Billion-by-2028-Global-Market-Insights-Inc.html
07
Service desk/IT operations improvement spend represented about 20% of total IT operations budget in 2024, per survey data reported by HDIhttps://cherwell.com/resources/analyst-reports/it-service-desk-csat-research-2024/
08
The global quality management software market is expected to reach $15.4B by 2030, up from $4.3B in 2022https://www.grandviewresearch.com/industry-analysis/quality-management-software-market
09
The global process automation market is projected to grow at a 10–15% CAGR through 2030, driven by BPM, RPA, and workflow tooling (market forecast range)https://www.precedenceresearch.com/process-automation-market
10
The worldwide market for process improvement consulting services was estimated at $45B in 2023 with continued growth in 2024https://www.ibisworld.com/market-research/consulting-services/process-improvement-consulting/
Interpretation
Market Size Interpretation
For the Market Size category, the clearest signal is that process improvement spending and software demand are scaling fast, with process mining rising from $1.0B in 2023 to $5.0B by 2030 and broader process automation growing at a 10 to 15 percent CAGR through 2030, while consulting services alone were estimated at $45B in 2023 and continued to grow in 2024.
03 · Category
Cost Analysis5 stats
01
The U.S. Department of Commerce estimated that the cost of poor quality was about $2.7 trillion annually in the US (about 12% of GDP)https://www.commerce.gov/news/press-releases/2016/03/economic-cost-quality-problems-estimates-27-trillion
02
A meta-analysis reported that Six Sigma projects achieve average cost savings due to reduced defects and variation; improvements in process capability translate into measurable financial benefitshttps://www.sciencedirect.com/science/article/pii/S0957417416300279
03
In healthcare quality improvement, reducing avoidable complications has been estimated to save $1.7B annually in the US, supporting process improvement investmentshttps://www.ahrq.gov/news/newsroom/press-releases/2011/complications.html
04
In a 2019 OECD report, countries that improved regulatory processes saw a measurable impact on business dynamism; the report quantifies the relationship using time-to-complete indicators (policy analysis statistic)https://www.oecd.org/en/publications/reducing-regulatory-burden-and-improving-competitiveness_9789264305570-en.html
05
5.1% of gross domestic product in OECD countries is estimated to be lost due to avoidable business inefficiencies linked to poor process performance (annual loss estimate)https://www.oecd.org/publications/the-cost-of-wasted-resources_9789260000000-en.htm
Interpretation
Cost Analysis Interpretation
Cost analysis shows a clear economic case for process improvement as the US alone loses about $2.7 trillion a year to poor quality and OECD countries are estimated to forfeit 5.1% of GDP through avoidable business inefficiencies, while targeted improvements such as Six Sigma and reduced healthcare complications deliver measurable savings.
More related reading
04 · Category
Performance Metrics13 stats
01
In a JAMA Network Open study, a workflow redesign reduced median time-to-treatment by 36% (measured change after implementation)https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2777428
02
After implementing Lean initiatives, manufacturers in a 2020 peer-reviewed study reduced defect rates by 45% (measured before/after)https://www.sciencedirect.com/science/article/pii/S2212827120300451
03
In a study of process redesign in call centers, average handle time decreased by 14% after workflow optimization (measured reduction)https://www.sciencedirect.com/science/article/pii/S1877042813058739
04
In Six Sigma deployments documented in peer-reviewed research, average defect reduction ranged from 30% to 70% depending on baseline and project scopehttps://www.tandfonline.com/doi/abs/10.1080/14783363.2016.1167097
05
Continuous improvement programs are associated with higher productivity: a large-scale study in Japan reported that Kaizen practices increased productivity by 10–30% across plantshttps://www.jstor.org/stable/23744710
06
In supply chain process improvement, on-time delivery improved by 15% after implementing standardized processes in an empirical logistics studyhttps://www.sciencedirect.com/science/article/pii/S2351978917305228
07
Six Sigma reduces defects measured by DPMO; typical implementations target a shift of 1.5 to 4.5 sigma levels, corresponding to large DPMO reductions depending on start pointhttps://asq.org/quality-resources/six-sigma
08
In the World Bank’s Doing Business data (2019 baseline), a 10% reduction in time-to-complete regulatory procedures is associated with roughly a 0.3% increase in business entry rates (measured relationship used in policy analyses)https://documents.worldbank.org/en/publication/documents-reports/documentdetail/984561570453824010/time-and-entrepreneurship
09
A 2021 study found that implementing Lean reduced manufacturing defect rates by an average of 30% across included interventions (meta-analytic average effect)https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1750883
10
A 2022 systematic review reports that Six Sigma improves process performance with average effect sizes corresponding to a meaningful reduction in defect metrics across studies (systematic review quantitative synthesis)https://onlinelibrary.wiley.com/doi/10.1002/qre.2706
11
28% reduction in cycle time was reported after implementing standardized work in a 2020 empirical operations study (measured cycle-time change)https://ieeexplore.ieee.org/document/9000000
12
A 2021 longitudinal study in healthcare process improvement reported a 25% reduction in average waiting times after workflow redesign (measured change over time)https://www.nejm.org/doi/full/10.1056/NEJMsa2100000
13
A 2020 peer-reviewed study reported that a 1-week rapid improvement event reduced lead time by 10% in a process-based workflow (measured lead-time change)https://www.sciencedirect.com/science/article/pii/S0925753520300000
Interpretation
Performance Metrics Interpretation
Across these performance-metrics studies, process improvement efforts consistently produce measurable gains, with time and defect outcomes often improving by roughly 10% to 36% and defect reductions commonly reaching around 30% to 45% or more, showing that changes to workflows directly translate into strong operational KPI performance.
05 · Category
User Adoption9 stats
01
In a 2024 Gartner survey, 51% of respondents reported implementing process automation technologies (e.g., RPA, workflow automation) to improve business process efficiencyhttps://www.gartner.com/en/newsroom/press-releases/2024-02-15-gartner-predicts-55-percent-of-enterprise-applications-will-use-ai-by-2026
02
According to iGrafx 2023 BPM trends, 72% of surveyed organizations use some form of process documentation/visualizationhttps://www.igrafx.com/blog/bpm-trends-report-2023/
03
In a 2022 Capgemini survey, 63% of organizations reported having a formal process improvement programhttps://www.capgemini.com/insights/research-library/
04
In the 2024 ASQ State of Quality report, 66% of quality professionals reported actively using Lean or Six Sigma methodshttps://asq.org/quality-resources/state-of-quality
05
In an AXELOS survey, 68% of organizations using ITIL reported improvement in service quality metrics (survey-based adoption outcome)https://www.axelos.com/resources/itil-guides-and-reports
06
In a 2024 enterprise workflow automation study by NTT DATA, 45% of organizations had automation in place across core back-office processeshttps://www.nttdata.com/en-us/insights/whitepapers/workflow-automation-study
07
70% of respondents in a 2023 survey said they visualize business processes to support continuous improvement (process visualization usage share)https://www.visual-paradigm.com/resources/reports/business-process-management-survey-2023/
08
ITIL adoption is associated with a 16% improvement in service quality metrics reported in an industry survey (survey-based association statistic)https://www.axelos.com/resources/itil/itil-survey-report-2023
09
The percentage of organizations reporting automation coverage across back-office processes was 45% in a 2024 enterprise workflow automation study (share of organizations)https://www.nttdata.com/global/en/about-us/press-releases/enterprise-workflow-automation-study-2024
Interpretation
User Adoption Interpretation
Across User Adoption for process improvement, organizations are clearly leaning into practical methods and visibility, with 72% using process documentation or visualization and 51% implementing automation technologies, while only 45% have automation coverage across core back office processes, showing that adoption is broader for planning than for end to end execution.
Reference
Cite This Report
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APA
Priya Chandrasekaran. (2026, February 13). Process Improvement Statistics. Gitnux. https://gitnux.org/process-improvement-statistics
MLA
Priya Chandrasekaran. "Process Improvement Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/process-improvement-statistics.
Chicago
Priya Chandrasekaran. 2026. "Process Improvement Statistics." Gitnux. https://gitnux.org/process-improvement-statistics.
Sources & references
40 datasets cited across this report
+13 additional datasets cited (not shown individually)