Using Data to Determine ROI for Automation
If you manage operations for a warehouse, fulfillment center, or manufacturing, you know all too well that proper material flow can make all the difference when getting inventory out the door or items from point A to point B—especially within a timely manner. While some businesses can stay the course with very few process changes throughout the seasons or yearly changes, other businesses grow, add inventory, or change processes completely. It’s these types of scenarios that can and will make havoc if processes are not properly vetted.
At SSI SCHAEFER, our team of data analysis experts can aid in making those crucial decisions as you optimize material flows. The tough decisions on when it is best to implement an automated solution or even if it’s better to implement a semi-automated system often go unchecked. However, it can be a costly mistake. These types of decisions are often left to hunches or “should we” scenarios without any thought given to data analysis for material handling. Although, a data analysis study can help determine what type of product you need to optimize your material flows and at what optimum time is right for that investment. It can also determine if a process may be better suited with additional labor or a better warehouse management system. It all depends on your data.
Data analysis can help determine where and what to improve.
While most people wouldn’t build a home without a blueprint, many operations teams do change or implement equipment or processes without a full understanding of the outcome. It’s not done on purpose mind you, and it mostly comes in layers of changes over time. So, once something happens within the supply chain or operations, these little changes start to add up. However, just as a patchwork roof will eventually leak, processes that have evolved will eventually break down if not vetted by proper data analysis. And, a complete analysis for material handling may be exactly what is needed to help streamline operations for your company. Over time, changes happen, product innovation occurs, and processes or changes are implemented. A complete data analysis can take existing processes and do a deep dive into predictive analytics to see where bottlenecks are most likely to occur, understand what changes need to happen, and vet out equipment implementations before capital is spent.
Input, analysis, and planning accordingly for best results.
Wondering what type of data is needed for analysis? It’s pretty easy, but most data analysis circles around the following types of data:
Item Master Data
Goods in Data
Data is then validated and prepared for analysis. The data is then simulated for various scenarios based on potential processes, equipment, and labor. This type of data can also come from the client or additional market analysis with third-party big data types that can be used to layer in scenarios, which mostly look for peak days, stress tests, balanced scenarios, and critical areas within material handling operations. It’s important to get a well-rounded view of the volume of the actual operation. While your system needs to work during peak season, you also don’t want to over-engineer for two days per year, especially for something that may be better managed with just a simple process change, a better IT software solution, or layout design. These proofs-of-concept are extremely valuable for highly complex systems or new concepts with various process drivers.
Once data is analyzed, one can expect indications of throughput changes, utilization, dwell times, suggested layout changes, IT strategies, and documentation. It really depends on what the data indicates.
How to get started?
Thinking your operations can benefit from a data analysis study? If so, reach out to the SSI SCHAEFER data experts. Our team of data analysts are happy to work with you to determine what is needed for the study and how to get started.