What this article is about :

Mastering the Analyze, Improve, and Control Phases of DMAIC

How to get real value and lasting results from your process improvements?  This is where stone turns to gold, so make sure you avoid common mistakes and learn from the wisdom of successful improvement projects– read the full article now!

Introduction

In the world of business improvement, the DMAIC method is a key approach for enhancing processes and achieving excellence. DMAIC stands for Define, Measure, Analyze, Improve, and Control. It offers a clear, data-driven path to solving problems and improving efficiency. In a previous article , we highlighted common pitfalls on the foundational phases: Define and Measure. https://kaleo-performance.com/en/dont-fall-down-the-rabbit-hole-mastering-define-and-measure-in-dmaicv/

Today, we focus on the Analyze, Improve, and Control phases. These steps are crucial for finding the root causes of issues, putting effective solutions in place, and making sure those improvements last. Knowing the common mistakes and best practices gathered from dozens of projects I coached will greatly boost the success of your improvement projects and will ensure you solve the right problems the right way… and ensure they remain solved!

Analyze Phase: Finding the Root Causes

The Analyze phase is where data is turned into useful insights, and root causes are investigated. This phase can be tricky and often lead teams off track if not handled carefully.

The 5 Most Common Mistakes in Analyze Phase:

1. Surface-Level Analysis:

Teams often stop at identifying symptoms rather than digging deeper to find the real root causes. A typical example is blaming contact center agents for poor customer satisfaction, when a number of issues upstream may lead to unhappy customers reaching out to customer service

💡 Resolution: Deep Root Cause Analysis: 

Use tools like Fishbone Diagrams and the 5 Whys to dig deeper and find the real root causes. For example, asking “Why?” repeatedly can help peel back layers of symptoms to reveal underlying issues like process inefficiencies or resource constraints. These are my favorite improvement tool, always leading to eye opening sessions when the right stakeholders are around the table, and à key success factor for the improvement phase.

🔬 Example: In a healthcare setting, a hospital found that patient readmission rates were high. Initial analysis pointed to poor patient education. However, by employing Fishbone Diagrams and the 5 Whys technique, they uncovered that inadequate discharge processes and inconsistent follow-up care were the root causes. Addressing these areas significantly reduced readmissions.

 

2. Too Much Reliance on Tools: 

While tools are important for data analysis, depending on them too much without critical thinking can be a problem. Using statistical tools (like Minitab) to identify trends is helpful, but without understanding the context behind the data, teams might misinterpret the results. This is all the more true with large subsets of data, and I remember a team who had mixed different data sources, with different currency, and was drawing false conclusions

💡 Resolution : Balance Tools with Critical Thinking: 

While tools provide valuable data, balancing their use with critical thinking ensures a comprehensive understanding. For instance, combining data from tools with insights from frontline employees can provide a more complete picture. Spending an hour or a day on the floor will ensure you understand the data.

🔬 Example: A manufacturing company used statistical analysis software to evaluate defect rates. They noticed a spike in defects but failed to consider that they had switched suppliers. By visiting the production floor and interviewing staff, they realized the new supplier’s material contributed to defects, allowing them to address the issue more effectively.

3. Ignoring Data Changes

Data naturally changes over time due to various factors like market conditions or operational adjustments. Ignoring these changes can lead to wrong conclusions. For example, seasonal variations in sales data should be considered to avoid misinterpreting a temporary dip as a long-term trend. 

💡 Resolution: Consider Data Changes: 

Use statistical methods to understand and account for natural data changes. For example, control charts can help distinguish between normal variations and significant changes that require attention. I recommend to collect at least one year of historical data to uncover effects like month end close, year end close, or such processes that could impact your data.

🔬 Example: A retail company analyzing sales data over a holiday season misinterpreted a drop in sales as a failure of a marketing campaign. On reviewing a year’s worth of data, they identified that the dip was part of a seasonal trend rather than a permanent shift, leading them to adjust their strategies accordingly.

4. Confirmation Bias

This happens when teams focus only on data that supports their existing beliefs, ignoring data that contradicts them. For example, if a team believes that a particular marketing strategy is effective, they might overlook data suggesting otherwise, leading to ineffective decisions.

💡 Resolution: Challenge Assumptions: 

Actively seek out data that challenges your assumptions. For example, if a team assumes that a price reduction will increase sales, they should also explore data on customer loyalty and product quality to ensure a well-rounded view.

🔬 Example: A tech startup assumed their app’s new feature would lead to increased user engagement. However, by collecting user feedback and analyzing engagement metrics, they discovered that most users preferred existing features. This led them to invest in improving what users already valued rather than pursuing new, unwarranted features.

5. Poor Data Segmentation

Not dividing data into meaningful groups can hide important insights. For example, analyzing overall sales data without segmenting by region or product line might mask regional performance issues or successful product categories.

💡 Resolution: Effective Data Segmentation:

Divide data into relevant groups based on factors like time, location, or process conditions. For example, segmenting customer feedback by demographic groups, by channel, …  can reveal specific preferences and pain points, guiding targeted improvements.

🔬 Example: An airline analyzing passenger feedback on services conducted a general survey. However, after segmenting the data by flight class, they discovered that first-class passengers had significantly different pain points than economy class passengers. This segmentation allowed them to tailor improvements effectively to each customer group.

Improve Phase: Developing Effective Solutions

The Improve phase is about creating and implementing solutions that address the root causes identified earlier. This phase also has its own set of challenges.

The 4 Most Common Mistakes in the Improve Phase:

1. Rushing Solutions:

Teams may quickly implement solutions without proper evaluation of the options and testing. For example, setting up a new process without pilot testing can lead to unforeseen issues and resistance from users, resulting in wasted resources and frustration, and will compromise the roll out of other improvement.

💡 Resolution: Systematic Solution Development

 Generate a range of potential solutions and evaluate their feasibility and impact. For example, brainstorming sessions can produce diverse ideas, which can then be narrowed down through feasibility studies and pilot tests.

🔬 Example: A fast-food chain faced high customer wait times. Instead of rapidly implementing a new drive-through system, they conducted a brainstorming session that produced several improvement ideas. They then piloted the most promising solutions, such as menu redesign and staff training, leading to a significant decrease in wait times.

2. Lack of Innovation:

Sticking to traditional solutions may limit potential improvements. For instance, relying solely on cost-cutting measures might provide short-term savings but could overlook innovative approaches like process automation or new market opportunities.

💡 Resolution: Encourage Creativity: 

Set up a brainstorming workshop with an environment that values creative thinking. Encourage employees to think out of the box. Simple creative ideas can lead to breakthrough improvements! I like to use ‘lateral thinking’ where à random word is thrown into the brainstorm to generate creative ideas.

🔬 Example: A multinational company held a ‘Shark Tank’ style competition where employees could pitch innovative ideas. One pitch involved using AI to optimize supply chain logistics instead of simply cutting costs, resulting in more robust solutions that enhanced efficiency without detrimental effects on morale.

3. Not Engaging Stakeholders:

Solutions developed without input from key stakeholders can face resistance. For example, implementing a new workflow without consulting the employees who will use it can lead to low adoption rates and inefficiencies.

💡Resolution: Engage Stakeholders: 

Involve key stakeholders throughout the improvement process. For example, forming cross-functional teams with representatives from different departments will provide diverse perspectives and ensure buy-in, leading to more effective and accepted solutions. Leadership support is a pre-requisite for success!

🔬 Example: A financial institution looked to streamline their loan approval process. By forming a cross-functional team with inputs from sales team, credit officers, and IT, they ensured the solution would be user-friendly and effective, leading to smoother implementation and higher satisfaction among users.

3. Overcomplicating Solutions: 

Complex solutions can be difficult to implement and maintain. For instance, introducing a highly detailed quality control process might be effective in theory but could be impractical for employees to follow consistently, leading to errors and inefficiencies.

💡 Resolution: Keep It Simple: 

Aim for simple, practical solutions that are easier to implement and maintain. Streamlining a process by eliminating unnecessary steps can improve efficiency and reduce the likelihood of errors, ensuring long-term effectiveness. Open your eye for waste!!

🔬 Example: A software company aimed to improve its user interface. They initially proposed a complex overhaul but after reconsidering, they decided to simplify the layout by removing unnecessary features and focusing on core functionalities, which improved user satisfaction significantly while reducing development time.

Control Phase: Maintaining the Improvements

The Control phase ensures that the improvements made through the DMAIC process are sustained over time, maintaining the gains and preventing a return to old, inefficient processes.

The 3 Most Common Mistakes in the Control Phase:

1. Lack of Standardization:

 Without standardized procedures, processes can revert to old habits. For example, if a new customer service protocol is not documented and consistently applied, employees might fall back into previous, less effective practices, undermining the improvements achieved.

💡 Resolution : Standardize and Document: 

Develop clear, standardized procedures and document them thoroughly. For example, creating detailed process manuals and checklists can ensure consistency and provide a reference for all team members, helping to sustain improvements over time.

🔬 Example: A food manufacturing plant improved its production process but failed to document the new methods, resulting in inconsistencies. When they standardized procedures and created detailed manuals, they were able to maintain quality and efficiency over the long term.

2. Lack of Standardization:

 Robust monitoring systems are essential for tracking process performance. I have witnessed several times the “Hawthorne effect” , where individuals modify their behavior in response to being observed or studied, often resulting in temporary performance improvements. Quickly afterwards, performance gets back to previous level as no real improvement was performed.

💡 Resolution : Implement Monitoring Systems: 

Use control charts and dashboards to track process performance in real-time. For instance, setting up automated alerts for key performance indicators (KPIs) can help teams quickly identify and address deviations, ensuring that processes remain stable and within control limits. I recommend to maintain the improvement project open, with regular performance reviews, until the new performance is statistically stable over several periods. Make sure you don’t stop too soon!

🔬 Example: A logistics provider implemented control charts to monitor delivery times post-improvement. This allowed them to identify anomalies, quickly address issues such as route deviations, and maintain high service levels, ultimately enhancing their reliability and customer satisfaction.

3. Neglecting Training:

 Ongoing training is necessary to equip employees with the skills to maintain new processes. For example, failing to provide refresher training on updated safety protocols can result in compliance issues and increased risk of accidents, eroding the benefits of process improvements.

💡 Resolution: Invest in Training:

Provide ongoing training to employees on new processes and procedures. For example, regular training sessions and workshops can keep employees up-to-date on best practices and equip them with the skills needed to maintain improvements, fostering a culture of continuous learning and development. As said earlier, this is easier when teams have been actively involved in the improvement itself.

🔬 Example: A construction company introduced new safety protocols after a series of incidents. They invested in comprehensive training programs, including simulations and refresher courses. As a result, the workforce became adept at following new safety measures, significantly reducing on-site accidents over time.

Conclusion

Mastering the Analyze, Improve, and Control phases of DMAIC is crucial for achieving and sustaining process improvements. By being aware of common mistakes and following best practices, teams can drive meaningful change and ensure long-term success. 

Embracing these insights will lead to significant, sustainable improvements that drive operational excellence and business success. By continuously refining these phases and learning from each project, you will build a culture of continuous improvement that adapts and thrives in an ever-changing business environment.