Distribution
Blog Post
Cimcorp’s Adam Higgins explains why using data driven workflows provide greater returns than fitting technology into existing operations. For many companies looking to make the leap from manual materials handling to automation, their plan is to have robotics and advanced systems take over existing warehouse processes. They will do their homework and find some notable suppliers in the market. Then, they reach out to these vendors and explain their current setup and operational needs. They will often ask how the technology can work within these parameters.

While automation can certainly replace existing, manual processes, companies that plan to do more or less the same material handling flow – just using robots – are actually missing a greater window of opportunity. By automating, they have the opportunity to reevaluate their operations and look for ways to leverage these systems for more efficient product handling.

Thinking outside the box                                  

When an organization is used to legacy processes, it is easy to remain fixed on how to make automated systems fit the current way of doing things. “We need orders picked and ready for loading two hours ahead of a truck’s arrival. We need to keep like-SKUs together in the warehouse.” Instead, consider thinking outside of the box and be open to adapting processes to work better with the automation.

For instance, rather than prepare orders two hours in advance, the speed and accuracy of a material handling system can enable just-in-time order fulfillment. Facilities can pick and prepare orders within minutes of a truck’s arrival, streamlining storage and retrieval and eliminating the need for space-consuming staging areas. Moreover, something that seems counterintuitive like random SKU allocation may be more efficient than standard SKU allocation, when the software can look for the best way to execute a given set of orders.

Finding the right strategy and systems to put in place takes more than guesswork and trial and error. It requires a scientific approach that looks at the hard data of their products and material flow. Fortunately, manufacturers do not have to go at it alone. They can supply their data to the system’s provider, who will then run analysis to come up with a solution.

Running the numbers

Using historical data, such as order lines and a SKU master table, the provider can crunch the numbers, run simulations and pinpoint the best strategy for automation. They can help figure out the “sweet spot” in operations, where facilities can get more for less. Instead of a large-scale project that aims to install robots in every corner of the warehouse, the provider can look at the data and determine how to minimize the amount of machinery and keep it affordable, while still maximizing the results.

For instance, in an e-commerce goods-to-person application, the trends in the data may present an opportunity to batch many small orders together so that they are fulfilled at the same time by the worker. A smart application can determine an optimal batch size and which orders fit well together to minimize the amount of robot and manual work required.

Moreover, the data can sometimes show new opportunities for improvement beyond the initial project. For instance, health and beauty care company L’Oréal originally wanted to automate to reduce its facility’s operation hours from three shifts to two and improve outbound order accuracy. It decided to implement a layer pick system, which would enable the company to pick a wide variety of products with a single machine and create customer orders in any sequence. Looking at the design of the system, L’Oréal found it could go a step further and implement a forward reserve cascading replenishment system to handle 6,000 pallets per month, reducing forklift travel within the 680,000-square-foot facility. For even greater efficiency, popular SKUs are stored within 200 feet from the induction stations. Now, L’Oréal is capable of handling 1 million cases per month.

Automation enables manufacturers to do more than just replicate existing processes. It gives them the opportunity to improve, innovate and transform their warehousing operations. Doing so requires taking a hard look at data. They can work one on one with their systems’ provider to crunch the numbers, devise the right strategy and do things smarter. 

Author Adam Higgins

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