A strategic push to implement a data analytics program can play an important role in optimizing your facility operations including your outbound parcel planning. A robust data analytics plan empowers your team to make data-driven decisions, optimize operations, and ultimately can enhance customer satisfaction while reducing costs. The key to success is to identify which types of data are available and develop a structured approach to gather which is most advantageous.
There are many ways of collecting, dissecting and communicating data but in general there are three broad categories that much analysis falls into:
- Descriptive Analytics: Descriptive analytics involves summarizing historical data to understand what has happened in the past. In warehouse operations, descriptive analytics can be used to analyze historical sales data, inventory levels, order volumes, and other key metrics to gain insights into past performance and trends.
- Predictive Analytics: Predictive analytics utilizes historical data and statistical algorithms to forecast future trends and outcomes. In warehouse operations, predictive analytics can be used for demand forecasting, inventory optimization, and predicting equipment maintenance needs. By analyzing historical data and external factors, predictive analytics can help warehouse managers make informed decisions about resource allocation and planning.
- Prescriptive Analytics: Prescriptive analytics goes beyond predicting future outcomes to provide recommendations on the best course of action to achieve desired outcomes. In warehouse operations, prescriptive analytics can help optimize processes such as inventory management, order picking, route optimization and carrier selection. By considering constraints and objectives, prescriptive analytics can provide actionable insights to improve operational efficiency and effectiveness.
The start to any of this is to collect as much applicable historical data as possible and create a streamlined ongoing method to collect future data that you may not be gathering yet. To analyze parcel operations this could include:
- Parcel dimensions (length, width, height)
- Weight of parcels
- Carrier selection
- Destination addresses
- Delivery times
- Shipping costs
- Any special requirements or instructions for certain destinations
The next step from this data is to calculate basic statistics such as average shipment weight, cost, parcels per carrier or route and identify any important historical trends. Although the past is not necessarily the best indicator of future performance, particularly if you’re contemplating major operational changes, it does provide a starting point for predictive analysis.
A strong data analytics program provides fulfillment operations with both valuable insights into current operational performance as well as opportunities for continuous improvement. By regularly analyzing key performance indicators (KPIs) such as order accuracy, cost per shipment and on-time delivery, you can identify key areas for improvement, implement targeted process enhancements, and improve overall efficiency.
Jim McLafferty is the Director of Post & Parcel Sales at DMW&H. With over 30 years of experience in the material handling industry, Jim is a thought leader in the design and implementation of parcel handling systems to support first-, middle- and last-mile requirements. He can be reached at JMcLafferty@dmwandh.com or 201.635.3439. Email info@dmwandh.com for more information.
Link to Parcel Industry’s Article