The logistics industry is known for its complex and data-intensive nature. Tracking the exact whereabouts of a product from the warehouse to a customer’s doorstep, for example, entails frequent data capture. This process involves collecting information from multiple sources such as barcodes, text and objects, and converting it all into an electronic format that can enable better outcomes for the business, including more strategic decision-making. 

But getting it wrong can have the opposite effect, and hold businesses back. 

Outdated data-capture technology and strategy hinder efforts at accuracy and agility. What’s more, manual methods, legacy data-capture tools and basic spreadsheets aren’t streamlined or real-time enough to stay on top of the data crucial to large-scale supply chains. This results in slow, inaccurate decision-making and increased operational costs.

Despite these shortcomings, the logistics industry is notoriously slow to advance technologically. While other sectors like retail race ahead, S&P reports that 31% of shipping and logistics firms have yet to even define a formal digital transformation strategy.

As economic pressures continue, logistics companies can no longer wait. Adopting a smarter data-capture strategy has become essential. This comprehensive approach involves hardware, software and connectivity strategies that modernize how companies track items while gathering, analyzing and interacting with data. It removes the barriers to effective analysis of the data gathered, helps enhance accuracy and productivity, and reduces the likelihood of mistakes. From warehouses to the frontline, it cultivates both data democratization and a two-way flow of information.

The logistics industry’s strategy and process behind data capture needs to shift to become smarter, regardless of the tools deployed, in order to capture, combine and analyze multiple data sources and avoid potential negative impacts. They include the following:

Elevated operating costs. In 2021, Gartner found that poor data quality costs organizations an average of $12.9 million yearly. This can happen through product or shipment mislabeling, inventory errors or a host of other factors.

To reduce the cost of operations, companies must take two key steps: get end-to-end visibility into inventory, and use advanced analytics to make informed decisions. This is only possible with a smarter approach to data capture on the front line. In the process, businesses can eliminate error and capture more accurate and comprehensive data by supplementing manual data collection.

Negative employee experience and lower retention. Companies frequently put the customer or end-user above all. The customer experience is at the forefront of decision-makers' minds, which is valuable when considering revenue. However, employee experience has become more of a concern in recent years, and rightfully so. In 2023, Qualtrics found that 38% of employees agree they’re at risk of burnout because of inefficient work processes.

Deprioritizing employee experience is an easy way to drive up business costs, though unfortunately a common one. In addition to fair labor practices, it’s important to look at the day-to-day experience of employees. Is bending over repeatedly to get right next to a barcode for scanning causing back pain? Are the majority of tasks manual, menial and uninspiring?

With workflows automated and employees upskilled with data, it’s not just one department or team that stands to benefit — it’s the entire organization. When data-capture practices are outdated, training costs will rise significantly. Having to teach new technology to employees, rather than handing them a device with an intuitive interface, takes far more time and has a drastically different learning curve, reducing efficiency and leading to high staff turnover.  

A smarter data capture approach not only increases profitability but also assists with the high turnover rate problem — 80% of frontline workers think businesses that rely on technology and mobile devices attract and retain more employees. 

Safety and compliance issues. Non-compliance can be hugely costly. Think of items that require age-verified delivery, such as alcohol. Improper processes can result in unsafe situations for minors and heavy fines for businesses that have supplied controlled substances to underage customers.

Offering these items can boost profit margins, but only if done safely. The ability to quickly and reliably scan an identification card with the same device that scans other inventory isn’t just convenient for drivers. It can make a world of difference for public safety, and reduce the risk of heavy fines.

Poor resilience and flexibility. In today's data-driven world, businesses that stick with manual and labor-intensive data-capture practices will see far worse resilience and flexibility. For example, last-mile companies won’t be able to scale or respond appropriately to peak periods like the holidays because they have the wrong technology in place.

By moving away from manual and legacy processes, and investing in smart data-capture practices and strategy, logistics organizations can keep costs under control, run their operations more efficiently, and keep employees happy.

Christian Floerkemeier is chief technology officer and co-founder of Scandit.