Process Improvement: Avoiding Challenges in Measuring Success
Business process improvement initiatives are paying off across the industry, but how do you measure success?
We share four challenges you may encounter in this process. Many companies find success with individual business process improvement (BPI) projects, but struggle to overcome initial challenges or identify exactly where to begin their improvement efforts There are also companies.
Whether the team has a continuous improvement program or this is his first BPI effort, understanding how to anticipate challenges in measuring success will help both on paper and in practice.
Challenges in Measuring Business Process Improvement Effectiveness
The most common challenges we see when running and measuring BPI projects are unclear performance metrics, data access issues, lack of resources for interpretation, and fear of personal consequences. If you're struggling to decide which process to improve first, anticipating these four common roadblocks can help minimize resistance. Encountering resistance everywhere, these roadblocks can guide your team's efforts before embarking on business process improvement initiatives.
BPI is difficult to measure due to these challenges. Some will happen before the project starts, but being prepared for them can reduce team setbacks and increase success rates. These roadblocks often result from inefficient or outdated processes that need to be addressed before any BPI initiative can begin.
Common Challenges in Measuring Success
When evaluating the performance of a BPI project after the fact, the following four common measurement challenges can reveal where improvements can be made for the next project.
Unclear or useless KPIs Measurement choices can impact the success of BPI initiatives before they are launched. You need to define how to measure process performance, set priorities, and guide your team. These measurements may come from your current or desired process, and may require multiple metrics to get the full picture.
We also need to be aware of the processes affected by the results we want to improve.
For example, return on investment (ROI) is often a benchmark for project success. ROI measures the profitability of an investment so that it can be compared to other investments. The goal is to measure the return on investment for that cost.
An ROI analysis indicates a level of commitment to understanding and measuring the business value created by a BPI investment, but there may be other measures that look directly at the process rather than the outcome. These measurements not only capture visible changes more accurately, but also help in process improvement efforts.
Let's take a look at one specific process operation that could be improved: product movement within the oven. A specific nitrogen flow is required at a specific temperature and time. A production line must move at a constant speed. Deviations in any of these measurements will result in variability in the process. Lack of accurate data on all of these parameters delays identification of the root cause of variability. These metrics drive the process.
2. Data Access Issues When Measuring BPI
Performance management efforts can be delayed or completely derailed when the data and IT systems associated with the project or process in question are difficult to access. For example, related data can be stored on different platforms, complicating One Source of Truth. How do you decide which data points to focus on and how do you make them visible to relevant stakeholders?
The bigger the company, the more data theaters there are. interact with each other. To ensure that you have access to a single source of truth, see the current state of your processes and map which data is used for which metrics. Do you have a process in place to check the single source of truth when a data point is missing or wrong? should be visible in one place.
3. Lack of Resources for Interpretation
Even with the best data systems, the time and access required to interpret data for reports and dashboards can waste team resources. A streamlined process should minimize the amount of data interpretation required.
But what if BPI projects streamline data processes? The availability of skilled resources and labor in the current climate should be considered. You should also check if this project is wasting resources on other parallel projects or if the team is prioritizing skills elsewhere.
A common solution is to automate the measurements to limit the need for interpretation from the outset. Automation applies to rule-based data. Previously, multiple locations had to be manually visited to collect all the data, but with machine learning, humans are only involved at the critical decision points. As you build automation into your process, ask which steps in your process are slowing you down the most. For example, how can you set aside problematic items that are not optimized because they contain additional questions or decisions needed to move forward?
Letting automation do some of the work frees up human resources to tackle harder problems and interpret them on a larger scale.
4. Fear of Personal Consequences
You may worry that changing how you measure it will affect your tangible success. Using more precise methods of measuring success can lead to discrepancies between past performance and what the new system is showing.
This difference often discourages stakeholders from taking more accurate measurements when older measurements give a better view of process performance. Improving alignment and understanding across the team, especially among leaders, will help the team as a whole understand when change is happening and what it means for them. Talking candidly to your leadership team can help you get a sense of potential performance bells and whistles early in a project. Around these goals, the change management process begins to take shape.
In the long run, prioritizing accuracy over pats on the back based on inaccurate or incomplete performance stats will lead to real, tangible improvements.
Conclusion
The purpose of process improvement is to make business operations easier, more efficient, and improve performance. These four common obstacles can slow, fuel, or cloud process improvement initiatives. Focusing process over results in measurement, aligning data sources and resources for interpretation, and communicating clear goals and change management across the team will lead to success.