Finding 6-7 figures through Business Process Improvement
Whether you’re selling products or services, the goal of every business leader is always the same: learn, improve, and evolve. It’s human nature to improve, and business is no different. But this professional growth will only come through business process improvement. By pausing, evaluating, and re-evaluating throughout the lifespan of your business, you’ll be able to find the practices that work, ditch those that don’t, and reach your potential.
What are the steps for process improvement?
There are many ways to shake up your business processes. The terminology differs, but ultimately, each methodology comes down to the same core elements. But there’s one step that often gets left out on the curb. And we get it! The first five steps are tough enough. Hey, any change is a challenge. But committing to this sixth step ensures that the first five weren’t for nothing.
This is how to continuously improve your business:
Step 1: Discovery
The first step is acknowledging where your processes could use some help. This doesn’t have to get too far into the weeds, but having a good idea of where your business sees hiccups is necessary. Many businesses will bring in a consultant to start high-level, learn your entire process, and leave no stone unturned. Now, they can also use technology to quicken the process and understand your processes more thoroughly.
Step 2: Measurement
Once you’ve uncovered where your processes need adjusting, it’s time to measure. This step will help you prioritize where you’ll need to put in the most effort and which processes should be changed first. These markers will also serve as initial benchmarks, so you’ll understand whether your new course of action is making a difference.
Step 3: Analysis
This is where you’ll have to do some soul searching. Do you understand the most crucial needs of your business? What metrics are most important for your organization?
Combining these questions with your findings will help determine the direction you’ll need to take. Keep in mind that process improvement is unique to your organization and will look different depending on your industry or departments.
Step 4: Transformation
This is where your hard work becomes actionable. After discussing new methods with stakeholders, it’s time to implement them and start transforming your business. You may have determined you need more automation or you’ve found processes that no longer serve your business.
As these new changes unfold, remember to monitor them closely and continue to gather data on your key metrics.
Step 5: Assessment
After your first round of changes, it’s time to go back and assess your progress. Sometimes your process is already good, but outside challenges like lengthy setups, resistance from team members, or under-communicating your initiatives can cause setbacks.
Here is where you can revisit your benchmarks. Those will be crucial in determining whether your process actually failed or if it was caused by outside forces.
Step 6: Iteration (The most important one!)
Process improvement isn’t a once-in-a-lifetime task. It’s a continuous exercise that should be repeated as trends, technology, and your business evolve. After you’ve gone through the process once, it’ll be easier for you to repeat and make the necessary changes to ensure your business thrives, whatever comes your way.
Case Study
Many years ago, I was part of a team working for a data-centric company facing significant challenges in two critical areas:
Processing Time: We were concerned about the amount of time it took for a specific batch of data, given a particular size, to traverse our system.
Processing Capacity: We were also grappling with the limitations on how much data our infrastructure could physically process each day.
Discovery: The Introduction of Process Mapping to Aid in Measuring
To address these challenges, we embarked on a process mapping journey. Process mapping involves creating a visual representation of the entire data processing pipeline while meticulously measuring processing times and analyzing performance at various stages. This approach allowed us to gain valuable insights.
Analysis: Identifying Bottlenecks
Through our analysis, we recognized that reducing the size of data batches could indeed decrease processing time, albeit at the expense of increased labor and diminished processing capacity. However, we soon discovered that there were several bottlenecks hindering our efficiency, with two primary ones closely linked:
Number of Processing Nodes: The hardware capacity for processing.
Number of Staff: The human resources performing the work.
Additionally, we stumbled upon a third consistent bottleneck that became apparent only after we mapped the process and systematically measured each step:
Data Copy Time: We realized that data was being copied multiple times throughout the pipeline, independent of actual data processing. By measuring the various points in our process, we determined that, in a given batch that took 30 hours to process, a significant portion (10-12 hours) was consumed by redundant data copying.
Transformation: Innovative Solutions
At this juncture, the value of fresh perspectives became evident. We devised a solution that harnessed virtualization technology. Instead of copying data multiple times to individual virtual machines sharing the same hardware infrastructure, we implemented a method where data was copied to a virtual drive and simply detached and reattached to the virtual machines as required. This single change resulted in a remarkable 60%-70% reduction in data copy time.
Assessment: Impressive Outcomes
After implementing this transformation, we reevaluated our process. The results were astounding. This single alteration not only saved us a substantial six-figure sum annually in labor costs but also significantly enhanced our system's capacity to process data, adding another six to seven figures' worth of data processing capabilities without any additional infrastructure investment.
Iteration: A Continuous Improvement Journey
Implementing this change opened the door to a new era of thinking. By utilizing the virtualization tools at our disposal, we achieved further improvements in performance and introduced a range of changes that substantially reduced the risk of processing errors. This demonstrated the power of continuous improvement and innovation in addressing complex data processing challenges.
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