This guest blog post about data comes to us via the ADP blog Spark and written by Jim McGeady.
Collecting and analyzing the right data can be crucial to manufacturing firms when production and profitability have been impacted by changes and uncertainty.
Today’s work environment is as unpredictable as ever, especially in the manufacturing world. There are many factors to deal with including safety precautions, staffing uncertainty, capacity limitations, and supply chain disruptions.
Thus, manufacturing data analysis becomes even more important as you try to identify new production goals, estimate work orders and measure productivity in your new environment.
The importance of data
As you adjust your manufacturing process, staffing, and other areas, you need a way to measure whether your assumptions were accurate, and the changes were appropriate. That way, you can identify areas that can be improved through further retooling, retraining, and redesigning. Without data, it’s difficult for management to decide where to focus their time and efforts.
In particular, focus on time data and performance data. With time data, you not only want to look at hours worked and labor costs, but you want to be looking at employee and machine time spent on direct work, indirect work, and being idle. With performance data, you want to be measuring output, the scrap rate, the impact on labor standards, piece rate bonuses, and the total cost of production. Now may be the perfect time to use this data to recalibrate benchmarks and labor standards.
With this information, you can start seeing how your changes are impacting your overall costs, profitability and timelines. That way you can set production targets, delivery timelines, employee expectations and customer commitments appropriately. You can also compare with your past performance to truly understand the financial and productivity impact of this new environment.
The new environment: Many changes all at once
It’s daunting for manufacturers to track all the changes they have had to make in the COVID-19 environment.
Examples of common changes include:
- Restricting the number of workers or modifying workplace traffic patterns in order to maintain social distancing.
- Spacing workers farther apart and redesigning shop floors and assembly lines accordingly.
- Reducing production targets to account for capacity, labor and supply chain changes.
- Modifying shift schedules as a potential solution to capacity and safety constraints.
- Using contractors or cross-training workers to fill gaps in labor coverage.
Regardless of how many changes like this have been made, every one of these changes could have had a major impact on production, downtime, capacity and work order estimates. So how could you identify the impact of any given change so that you could potentially address issues and make improvements?
Employee task level data is key
Tracking employee level data throughout the day is the key to finding and fixing possible inefficiencies in your manufacturing process from new adjustments. But capturing all this data manually is difficult and often impossible. Trying to do so manually would likely be very error prone. Employees would need to take time off the line to record this information or try to remember or estimate the time and write it down after the fact.
Manufacturing companies can use new technology like hybrid biometric scanners that can help track employee movements throughout the day.
This is where technology comes in handy, so you can track this employee data faster, automatically and more accurately. Barcode scanning of activity codes — even for activities such as idle time, hand washing and transit — makes it easier for people to switch tasks while the data is immediately input into their timecards to record stop/start times and durations. Workers can also enter quantities, scrap, yield and other useful production information without leaving their workstations. This not only helps employees track their time, but it helps you gather the detailed data needed to perform your analyses.
For analysis purposes, the timekeeping system can upload employee activity and work-level information into your MRP and ERP systems. Using this type of technology can help you keep up with all this crucial employee-level data, even as the number of workplace changes add up.
Data can be used for workplace productivity improvements, and also help you with job costing, work order status reporting, quality control and determining the profitability of different project types. It could even help you determine the cost of supply chain disruptions.
Inform your strategy
Every business is a little different when it comes to its situation in the post-COVID-19 world. Regardless of your strategy, plans and expectations have been reset, often based on many assumptions. You may have predicted some things correctly but may need to improve in other areas.
As you begin to work again in the new environment, maximizing manufacturing productivity and optimizing your operations may feel like starting over. History and pre-existing standards and results may not be very helpful as you move forward.
Success starts with capturing the right data in this new environment. Gather as much as you can, ideally in real time, and make it regularly available for analysis. By doing so, you can continually improve and make more informed decisions as you try to predict what productivity and good performance should look like while your ramp-up and return-to-work strategy evolves.
Are you interested in learning how your manufacturing firm can improve your productivity through data collection? Click here to contact us!
