Business process improvement initiatives are delivering results across industries, but how do you measure success? We share four challenges you might face during this process.
While many companies have seen success in their individual business process improvement (BPI) projects, others struggle to move past initial challenges or aptly identify where to begin in their improvement efforts.
Whether your team has a continual improvement program or this is your first BPI effort, understanding how to anticipate challenges in measuring success will benefit your efforts both on paper and in practice.
Challenges in Measuring Business Process Improvement Effectiveness
The most common challenges we see with executing 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 obstacles could reveal the path of least resistance. If you’re met with resistance all over, these obstacles can guide your team’s efforts before you begin a business process improvement initiative.
BPI success is often difficult to measure due to these measurement challenges. Some happen before your project even begins, and preparing for them will help your team curb setbacks and increase success rates. Often, these obstacles come from inefficient or outdated processes you need to address before getting to your BPI initiative.
Common Challenges in Measuring Success
If you want to evaluate your BPI project’s performance post-mortem, these four common measurement challenges may shed light on where you can improve for the next project.
1. Unclear or Unhelpful Performance Metrics
Your choice of measurement may impact the success of your BPI initiative before it even begins.
Your team must align on the definition and prioritization of how you’ll measure process performance. These measurements might come from your current process or desired process, and you might need multiple indicators to make the complete picture. You’ll also want to note any processes impacted by the results you want to improve.
For example, the go-to measurement of project success is often return on investment (ROI). ROI evaluates the profitability of an investment and lets you compare that profitability against other investments. It aims to measure the investment’s return relative to its cost.
While ROI analysis demonstrates a level of commitment to understanding and measuring the business value generated by BPI Investments, there may be other measurements that deal directly with process instead of output. These measurements will not only more accurately capture the changes you see, but they will guide your process improvement efforts.
Let’s look at helpful metrics for a specific process leadership could ask you to improve: the movement of products through a furnace. It requires a specific flow of nitrogen at a specific temperature and time. The production line must move at a specific rate. If any of these measurements are off, you will get variation in the process. If you don’t have accurate data on all those parameters, it will delay your identification of the root cause of variation. These metrics will govern your process.
2. Data Access Issues When Measuring BPI
Difficulties with data access and the information technology systems involved with your target project or process can slow down – or outright derail – your performance management efforts. For example, you may store the relevant data across different platforms, complicating your one source of truth. How will you determine which points of data to focus on, and how will you guarantee relevant stakeholders can view those?
The larger your company, the more theatres of data interact with each other. To make sure you have access to a definite source of truth, look at your process’s current state and map which data you’re using for which metrics. If any data points are missing or incorrect, do you have a process in place to check with your one source of truth? You’ll want to align your metrics to a specific data source, or determine one location to direct data so it’s possible to see everything in one location.
3. Lack of Resources for Interpretation
Even if your data systems are in tip-top shape, the time and access required to interpret data into reports or dashboards might prove a resource strain for your team. If you have tight processes, you should be able to minimize the amount of data interpretation needed.
But what if your BPI project is tightening a data process? You’ll want to factor in the availability of skilled resources and labor in the current climate. You’ll also want to see if this project will strain resources due to other concurrent projects or if your team prioritizes their skills elsewhere.
A common solution is to look toward automation for measurement to limit your interpretation need from the start. Automation applies to rules-based data. Where before, a person would have to manually access multiple sites to gather all the data, machine learning only involves humans at key decision points. When incorporating automation into your process, ask which steps of the process hold you up the most. For example, how do you set aside problem items that don’t get streamlined because they have an additional set of questions or decisions needed to move forward?
Letting automation do some of the lift for you will free up human resources to tackle the harder questions and interpret with a larger scope.
4. Fear of Personal Consequences
You may fear that changing the way you measure may change how much success you see. Once you harness a more accurate way of measuring success, you’ll likely see a discrepancy between how you used to perform versus what your new system shows.
We often see this difference deter stakeholders from more accurate measurements if the old measurements show their process’s performance in a better light.
By increasing alignment and understanding across your team, especially with higher-ups, the whole team will understand when the change is coming and what it will mean for them. Being upfront with your leadership team achieves transparency around the potential bell curve of performance in the early stages of your project. Your change management process will begin to take shape around these goals.
In the long run, prioritizing accuracy versus a pat on the back based on inaccurate or incomplete performance statistics will drive real, tangible improvement.
The point of process improvement is to make your business operations easier and more streamlined, leading to increased performance. These four common roadblocks can delay, extend and muddy your process improvement initiatives. Prioritizing process over the outcome in your measurements, aligning your data sources and resources for interpretation, and communicating clear objectives and change management across your team will lead you toward success.