Knowing how long it takes warehouse workers to complete specific tasks is critical to improving process efficiency and reducing warehouse costs. For this reason, many warehouses undertake time and motion studies to gather data that will enable them to review and potentially change the way in which tasks are carried out.
While time and motion studies serve an important purpose, they carry a number of limitations. Firstly, they are often carried out manually by an external company and can be time intensive and costly. Secondly, as studies are conducted infrequently – just once a year in some warehouses – they provide only a small snapshot of a task. Thirdly, and most importantly, because of the relatively small size of each sample, the collected data won’t reflect the average day for each worker and may not be of a high enough quality to find the best solution to eliminate inefficiencies. For best results, a much large sample which delivers a higher quantity of data is required.
Despite this, we’re firm believers that time and motion studies have a vital role to play in boosting both warehouse productivity and efficiency. The key is to take advantage of methods and technologies that allow the limitations of conventional methods to be overcome – or even bypassed altogether.
We use real time location systems (RTLS) and automated identification and data collection (AIDC) to automatically track the movement of people, inventory and MHE on an on-going, daily basis. It allows for every task and pallet movement to be recorded as part of an error- and effort-free ‘continuous time and motion study’, without the need for help from a costly external specialist. This constant and consistent recording of activities over longer periods minimises the risk of any variables skewing the data. A traditional time and motion study, for example, might encourage workers to make temporary behavioral or procedural changes just to get a better result in the next study, rather than making long-term performance improvements. We also eliminate the risk of any human error occurring during the data collection process, ensuring the quality of data is protected.
Crucially, this high quality data is presented as easily digestible information. With this, warehouse managers are able to develop a much better understanding of how long each activity takes and where there are inefficiencies. They can then make informed decisions based on quality evidence to achieve real efficiency and cost savings.