Efficiency is an important competitive advantage for your supply chain. One way to improve processes is through operations analytics, which is why supply chain giants such as DHL and Kuehne + Nagel invest heavily in those tools. Operations analytics give these logistics giants an advantage when it comes to efficiency, but how are they leveraging this data to improve their processes?
Firstly, because they invest in data collections systems, they collect data on all goods movements no matter how small. In a typical sophisticated warehouse, you will find a data system to track inventory movement, MHE usage, labor hours, productivity, and inbound and outbound loads.
Secondly, logistics industry titans combine data from various systems and analyze it to formulate process-improving insights. Logistics giants are able to turn data into actionable insights because they invest in personnel and analytics software.
So, what are the benefits of continual operations analytics?
1. Identifying and reducing hidden idle time
Small windows of unnecessary idle time are productivity’s silent killer. More often than not, operators experience small durations of idle time. Individually, these windows of idle time can go unnoticed, but over the course of a year, they can add up to a lot of wasted time. For example, 15 minutes of hidden idle time a day for a warehouse of 100 people can add up to 6,500 hours wasted in a year, which can amount to losing between $120K and $150K.
Analytics can help identify these small windows of idle time. If you discover that there are 2 minutes of idle time when operators go to the printer, you can get a faster printer or change the printing process to eliminate that waste. Proper operations analytics can help you track, identify, and reduce idle time.
2. Identifying and avoiding possible bottlenecks
In most cases, bottlenecks get noticed after they occur. These backups usually start slowly. Analytics can help you identify a dislodge in operations processes ahead of time by using historical or real-time productivity data. For example, if two subsequent operational functions have different processing speeds, the likelihood of a bottleneck is high if the first function is the fastest. Analytics can help you identify subsequent processes that are susceptible to dislodging so you can reallocate labor from the faster function to the slow function and avoid a possible bottleneck. Without analytics, you might not be able to identify and prevent an impending bottleneck.
3. Ability to control operations
Operations analytics dashboards can give you an objective overview and understanding of your operational activities. Having an objective understanding of operations enables you to optimally allocate team members to job functions, postpone non-core functions during peak times, and call for optimal overtime or time off. Poor allocation of team members can result in bottlenecks or additional operational costs. Failing to call for sufficient time-off during slow periods can result in unnecessary additional labor costs, while failing to call for enough overtime can render you unable to deliver orders to customers on time.
4. Improve material handling equipment (MHE) purchasing practices
Operations analytics can shine a light on how you use MHE and thusly can be crucial in your MHE purchase decisions. If you don't analyze MHE usage, there is a possibility of over-investing in MHE, which leads to idle capacity, or under-investing, which can slow down your operations. Operations analytics help you to systematically optimize MHE purchases as well as maintenance schedules to reduce downtime.
5. Ability to set objective budgetary targets
Operations analytics allows you to forecast future performance for set operational goals and budgetary targets. Operational targets set a standard for your team’s operation. Moreover, operational targets and can be used to enforce accountability within your team.
Operations analytics encompasses demand planning to inform your inventory, hiring, and capital investment decisions. These types of decisions take time and resources, and operations analytics can give you a head start in the planning process.
In conclusion, consider investing in analytics as you would consider any other business investment decision: If you pay $80K a year for analytics, but in return you gain more than $80K, then it is a worthwhile investment. Big industry players invest in analytics because it gives them a competitive advantage and furthers their growth.