The Improve phase represents a critical juncture in the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, where theoretical solutions transform into tangible operational changes. Despite its importance, this phase frequently becomes a stumbling block for even experienced practitioners, resulting in failed implementations, wasted resources, and organizational resistance. Understanding these common pitfalls and their prevention strategies can significantly increase your project success rate and deliver measurable business value.
This comprehensive guide explores seven prevalent implementation failures during the Improve phase, providing practical examples, sample datasets, and actionable strategies to ensure your process improvement initiatives achieve their intended objectives. You might also enjoy reading about Solution Documentation: Recording Your Improvements for Future Reference.
Understanding the Improve Phase in Lean Six Sigma
Before examining specific mistakes, it is essential to understand the Improve phase’s role within the broader DMAIC framework. This phase focuses on developing, testing, and implementing solutions that address root causes identified during the Analyze phase. The primary objectives include generating creative solutions, evaluating potential improvements through pilot testing, and developing implementation plans that minimize disruption while maximizing benefits. You might also enjoy reading about Pilot Testing in Six Sigma: How to Test Solutions Before Full Implementation.
The Improve phase demands a delicate balance between innovation and practicality, requiring teams to consider technical feasibility, financial implications, organizational readiness, and change management requirements. When executed properly, this phase delivers quantifiable improvements in key performance indicators while building momentum for sustained organizational change. You might also enjoy reading about How to Generate Improvement Solutions: Brainstorming Techniques for Six Sigma Teams.
Mistake 1: Insufficient Solution Validation Before Full-Scale Implementation
One of the most costly mistakes organizations make is rushing from solution identification directly to full-scale implementation without adequate validation. This approach assumes that theoretical solutions will perform as expected in real-world conditions, often leading to expensive failures and damaged credibility for improvement initiatives.
Real-World Example
Consider a manufacturing company that identified machine setup time as a primary contributor to production delays. After analyzing the data, the team proposed implementing a new quick-changeover system across all 15 production lines simultaneously. The initial analysis suggested this change would reduce setup time from an average of 45 minutes to 20 minutes per changeover.
Without pilot testing, the company invested $200,000 in equipment modifications and operator training. However, upon implementation, they discovered that the new system actually increased setup time to 52 minutes during the first month due to unforeseen complications with tool storage logistics and operator confusion about the new procedures.
Sample Data Comparison
Projected Results (Without Pilot Testing):
- Current average setup time: 45 minutes
- Expected setup time: 20 minutes
- Projected improvement: 55.6% reduction
- Annual time savings: 2,600 hours
Actual Results (Without Pilot Testing):
- Actual average setup time: 52 minutes (first month)
- Actual change: 15.6% increase
- Lost productivity: 728 hours in first month
- Financial impact: $182,000 in lost productivity plus $200,000 in upfront investment
Prevention Strategy
Implement a structured pilot testing approach that validates solutions on a small scale before full deployment. Select one or two production lines as pilot sites, run the new process for at least two to four weeks, and collect comprehensive data on performance metrics, operator feedback, and unexpected challenges. Use this information to refine the solution, adjust training materials, and develop contingency plans before broader implementation.
A proper pilot test would have revealed the tool storage issues and operator confusion, allowing the team to address these problems with minimal financial exposure. The revised implementation could then achieve the targeted improvements with significantly lower risk.
Mistake 2: Neglecting Stakeholder Engagement and Change Management
Technical excellence alone cannot guarantee successful implementation. Many improvement initiatives fail because teams focus exclusively on process mechanics while overlooking the human elements of organizational change. Resistance from operators, supervisors, or management can derail even the most technically sound solutions.
Real-World Example
A healthcare organization implemented a new patient intake process designed to reduce waiting times from 35 minutes to 15 minutes. The technical analysis was thorough, and the pilot test showed promising results. However, the project team failed to adequately involve front desk staff in solution development and provided minimal explanation about why changes were necessary.
When implementation began, staff members viewed the new process as additional work rather than an improvement. They continued using workarounds from the old system, resulting in a hybrid approach that actually increased average waiting times to 42 minutes and created significant confusion for patients.
Sample Stakeholder Analysis Data
Pre-Implementation Stakeholder Assessment:
- Front desk staff awareness of project: 40%
- Staff understanding of benefits: 25%
- Staff involved in solution design: 15%
- Management support communicated: 60%
- Training completion rate: 85%
Post-Implementation Results:
- Average patient waiting time: 42 minutes (20% increase)
- Process compliance rate: 55%
- Staff satisfaction with changes: 30%
- Patient complaints: Increased by 35%
Prevention Strategy
Develop a comprehensive change management strategy that begins during the Define phase and continues through Control. Identify all stakeholders who will be affected by changes, assess their current engagement levels, and create targeted communication plans. Include frontline workers in solution design sessions, clearly articulate the benefits for different stakeholder groups, and establish feedback mechanisms that allow concerns to be addressed proactively.
For the healthcare example, involving front desk staff from the beginning would have identified implementation concerns earlier and built ownership of the solution. Regular communication from leadership about the importance of reducing patient waiting times would have provided context and motivation for the changes.
Mistake 3: Implementing Solutions That Do Not Address Root Causes
A surprisingly common mistake involves implementing solutions that address symptoms rather than underlying root causes. This often occurs when teams feel pressure to show quick results or when they skip rigorous root cause analysis during the Analyze phase. The resulting improvements are temporary at best and often create new problems elsewhere in the process.
Real-World Example
An e-commerce company experienced high customer complaint rates about order accuracy, with an error rate of 8.5% (85 errors per 1,000 orders). Surface-level analysis suggested that warehouse pickers were making mistakes, so the company implemented a solution requiring pickers to scan items twice before placing them in shipping boxes.
Initially, the error rate dropped to 7.1%, which seemed like progress. However, this improvement plateaued, and order processing time increased by 22%, creating shipping delays and additional customer complaints. Further investigation revealed the actual root cause: the warehouse management system displayed confusing product codes that looked similar for different items, causing pickers to select incorrect products.
Sample Data Analysis
Symptom-Based Solution Results:
- Initial error rate: 8.5%
- Post-implementation error rate: 7.1%
- Improvement: 16.5% reduction in errors
- Order processing time increase: 22%
- Customer satisfaction: Decreased by 8%
Root Cause-Based Solution Results:
- Solution: Redesigned product code display system
- Final error rate: 2.3%
- Total improvement: 72.9% reduction from baseline
- Order processing time: Unchanged
- Customer satisfaction: Increased by 18%
Prevention Strategy
Invest adequate time in thorough root cause analysis before jumping to solutions. Use structured tools such as 5 Whys, Fishbone Diagrams, and Failure Mode Effects Analysis to dig beneath surface symptoms. Validate suspected root causes with data before developing solutions. Create clear linkages between identified root causes and proposed solutions, ensuring each solution directly addresses a verified underlying issue.
In the e-commerce example, completing a proper root cause analysis would have revealed the confusing product code system. Addressing this root cause delivered substantially better results than the symptom-focused double-scanning approach, while also improving processing efficiency rather than degrading it.
Mistake 4: Poor Project Planning and Resource Allocation
Successful implementation requires careful planning, adequate resources, and realistic timelines. Many projects fail because teams underestimate the complexity of implementation, fail to secure necessary resources, or establish unrealistic deadlines that force rushed execution and corner-cutting.
Real-World Example
A financial services company launched an initiative to reduce loan processing time from 14 days to 7 days. The project team developed an excellent solution involving process automation and restructured approval workflows. However, their implementation plan allocated only two weeks for testing, training, and deployment, with a budget that covered software licensing but not the IT resources needed for system integration.
Implementation began on schedule but quickly encountered problems. The IT department could not provide integration support within the compressed timeline due to other priorities. Training sessions were rushed and incomplete. The new system launched with known bugs that the team planned to fix “later.” Within three weeks, loan processing time had actually increased to 19 days as staff struggled with the partially functional new system while trying to maintain service levels.
Sample Project Planning Comparison
Inadequate Planning Approach:
- Planning timeline: 2 weeks
- IT resources allocated: 0 FTE
- Training time per employee: 2 hours
- Testing period: 3 days
- Contingency budget: $0
- Result: Processing time increased to 19 days
Adequate Planning Approach:
- Planning timeline: 8 weeks
- IT resources allocated: 1.5 FTE
- Training time per employee: 8 hours with hands-on practice
- Testing period: 4 weeks including parallel processing
- Contingency budget: 15% of project budget
- Result: Processing time reduced to 6.8 days
Prevention Strategy
Develop detailed implementation plans that account for all activities, dependencies, and resource requirements. Break down implementation into manageable phases with clear milestones and success criteria. Secure resource commitments from all necessary departments before beginning implementation. Build contingency time and budget into plans to accommodate unexpected challenges. Establish clear governance structures with decision-making authority to resolve issues quickly.
A realistic implementation plan would have identified IT resource needs upfront, allowed adequate time for testing and training, and built in contingency for unexpected issues. This approach requires more patience initially but delivers sustainable results much faster than rushed implementations that must be fixed repeatedly.
Mistake 5: Inadequate Measurement Systems for Tracking Improvements
You cannot manage what you cannot measure. Many improvement initiatives fail to establish robust measurement systems that accurately track performance before and after implementation. Without reliable data, teams cannot verify whether solutions are delivering expected benefits, identify emerging problems, or make evidence-based adjustments.
Real-World Example
A logistics company implemented a new route optimization system intended to reduce fuel costs by 15% and decrease delivery times by 20%. The project team calculated these projections based on theoretical modeling but failed to establish baseline measurements for actual fuel consumption and delivery times before implementation. They also did not create a system for ongoing data collection after the new routing system went live.
Six months after implementation, leadership asked for results. The team could not provide concrete evidence of improvement because they lacked both baseline data and post-implementation measurements. Anecdotal feedback from drivers was mixed, with some reporting improvements and others claiming the new routes were longer and less efficient. Without data, the company could not determine whether the substantial investment in the new system had delivered any value.
Sample Measurement System Framework
Inadequate Measurement Approach:
- Baseline data collection: None (theoretical estimates only)
- Data collection frequency: Ad hoc
- Metrics tracked: Fuel costs only (monthly aggregates)
- Data reliability: Unknown
- Ability to prove improvement: None
Robust Measurement Approach:
- Baseline data collection: 8 weeks of detailed daily data
- Data collection frequency: Automated daily tracking
- Metrics tracked: Fuel consumption per route, delivery times, miles driven, on-time percentage, customer satisfaction
- Data reliability: Validated through multiple sources
- Actual verified improvements: 12% fuel reduction, 18% delivery time improvement
Prevention Strategy
Establish comprehensive measurement systems during the Measure phase and maintain them throughout implementation and beyond. Collect detailed baseline data for all relevant metrics before making any changes. Implement automated data collection wherever possible to ensure consistency and reduce manual effort. Validate measurement system accuracy through Gauge R&R studies or similar methods. Create visual dashboards that make performance trends immediately visible to all stakeholders.
For the logistics example, collecting detailed baseline data would have provided clear targets and enabled accurate assessment of improvement. Ongoing automated tracking would have quickly identified routes where the new system was not performing as expected, allowing for rapid adjustments.
Mistake 6: Failing to Plan for Solution Sustainability
Many improvement projects achieve initial success only to see performance gradually deteriorate back to previous levels. This regression occurs when teams focus exclusively on implementation without planning for long-term sustainability. Without proper controls, training reinforcement, and ongoing monitoring, even successful solutions eventually fail.
Real-World Example
A manufacturing facility successfully reduced defect rates from 4.2% to 1.1% through improved quality control procedures and operator training. The project team celebrated success, documented the new procedures, and moved on to other initiatives. However, they did not establish ongoing auditing processes, refresher training schedules, or performance monitoring systems.
Over the following 18 months, defect rates gradually increased to 3.7% as operators slowly reverted to old habits, new employees received inconsistent training, and process documentation became outdated as informal modifications accumulated. The organization had achieved temporary improvement but failed to sustain it, essentially wasting the initial project investment.
Sample Performance Tracking Over Time
Without Sustainability Planning:
- Month 0 (pre-implementation): 4.2% defect rate
- Month 3 (post-implementation): 1.1% defect rate
- Month 6: 1.4% defect rate
- Month 12: 2.3% defect rate
- Month 18: 3.7% defect rate
- Sustainability: Failed
With Sustainability Planning:
- Month 0 (pre-implementation): 4.2% defect rate
- Month 3 (post-implementation): 1.1% defect rate
- Month 6: 1.0% defect rate
- Month 12: 0.9% defect rate
- Month 18: 1.0% defect rate
- Sustainability: Successful with continuous improvement
Prevention Strategy
Build sustainability planning into the Improve phase rather than treating it as an afterthought. Develop control plans that specify monitoring frequency, responsible parties,
