How Data Analytics Can Refine Fashion Fulfilment Operations

By Sebastian Titze

Through data analytics tools, distribution centres for fashion products can uncover the effectiveness of their handling systems. We explore why data analytics is important to fashion fulfilment and how fashion companies can use their data to improve their processes and operations management.

What is data analytics to the fashion logistics industry?

What are we actually talking about when we refer to data analytics for a fashion logistics house? We’re referring to the process of collecting the immense amount of information that a fashion distribution centre generates – through its operators and its equipment – and storing it as data.

The data collected during a centre’s fulfilment processes normally relates to either its operations or its equipment:

• Operations: How items (including returns) are unloaded, stored, sorted, conveyed, packed and shipped.
• Equipment: How well the warehouse control system (WCS) and sortation system are operating.

Why is data analytics important to fashion fulfilment centres?

In today’s complex fashion logistics, facilities are under constant pressure to optimise their processes for greater efficiency. This demand for enhanced performance arises among other, already challenging factors, including:

• Omnichannel sales: Operations must run smarter and faster to handle B2B and B2C.
• Seasonal demand fluctuation: Requires a flexible solution without reaching overcapacity.
• Overstocking, out-of-stock situations: Requires visibility into demand.
• Returns: Smarter ways are needed to manage enormous amounts.
• Manual labour: Unloading, picking, packing and assessing returns are labour intensive.
• System failures and downtimes: Same-day delivery means facilities have no room for delays.

With these issues, fashion fulfilment houses need a practical solution to their everyday operations. And that’s where data analytics has an important role to play.

How fashion logistics facilities can use data

Through data capture and analysis, fashion logistics facilities can gain insights to improve their material handling systems. The data collected can help provide a clear view of how a system is performing. Data assists facilities to understand what and why something has happened. They can then react when certain digital preconditions are met.

Here are some of the tools or methods that use data in a structured way:

How do fashion fulfilment centres gather data?

So, where in their operations are fashion fulfilment and distribution centres producing their data? There are several sources:

• WCS: Gathers data from various PLCs (Programmable Logic Controller) in the sortation system and other products such as picking systems, scanners and robots. The PLCs detect all kinds of information, or raw data, from these systems such as temperature, vibrations, power consumption, processing speed and much more. If you’re wanting to find out more about how this data is gathered, read here.
• Equipment sensors: Sensors attached to equipment can collect data.
• Intelligent cameras: These capture data such as movement patterns, item sizes and open spaces. Through image analytics software that employs machine learning technology, a picture of an item can be categorised into its type.

Some facilities may use a combination of the above data-gathering methods. The collected data can then be used to reveal the WCS’s performance, condition and efficiency. From there the facility can optimise the fulfilment or distribution processes and make continuous improvements.

For example, the system may discover that certain types of packaging often result in manual sortation. Or that every time the conveyor belt reaches a certain temperature, a breakdown occurs. Or perhaps a particular pattern of vibrations from the chutes shows that the machines are performing poorly. Analysing this type of data will result in complete transparency for a fashion logistics house.

However, the analysis and interpretation of that data may take the special skills of a system integrator with a deeper understanding of the WCS to achieve optimal system performance.

Possibilities with predictive analytics

In the process of digitalisation, fashion logistics companies will reach a certain level of digital maturity. At this point, with the data gathered and experience gained over time, they will be able to reach a predictive level where they start recognising patterns that the human eye would never detect.

Fashion fulfilment centres can take advantage of these predictive analytics to optimise the maintenance, operations and management aspects of the system:

• Maintenance: Maintenance staff get a full overview of the system status and maintenance needs. They can use data to prevent breakdowns and detect when a specific spare part will need to be replaced, resulting in less budget spend on maintenance.
• Operational: Operational professionals are able to navigate through recommendations and proposed actions to make sure the handling system continues to operate as efficiently as possible.
• Management: Managers get a complete overview and understanding of what lies behind the OPEX and future CAPEX needs for both short and long-term planning.

Conclusion

The use of data and data analytics tools can assist fashion distribution centres in understanding what is happening at their facilities, why it’s happening and what’s going to happen in the future. They can provide an easy and intuitive overview of current operations, upcoming events and maintenance status. Data analytics tools are critical components for any facility looking for insight into its maintenance, operations and management issues and seeking to improve performance and efficiency.