Collecting data and trying to maximize time efficiency in business is similar to budgeting in your personal life. That $6 coffee might seem like a relatively inexpensive purchase, but over time, if you buy a coffee at a dollar less every morning before work, you’ll find yourself saving around $250. Multiply that by 100 people, and that translates into a collective savings of $25,000.

The concept applies to time saved on the shop floor by addressing repetitive and essential tasks. Take barcode scanning: Certain scanners are faster than others, and the difference of just one second per scan has a major impact on efficiency. If a worker performs a thousand scans per day and there are 1,000 workers across a warehouse, they’re saving a million seconds per day — about 12 days of time.

It’s safe to assume that 70% of the added value on the shop floor is created by the hands of human workers, and despite popular belief that that number will drastically decrease with automation, humans will remain at the center of manufacturing, logistics, and the supply chain for the foreseeable future. This ecosystem doesn’t function without a human-centric starting point. Therefore, improving the functions involved in data tracking help maximize output. For example, time is saved by reducing the distance a worker must travel around the warehouse by connecting all scanners to the internet of things.

Additionally, tracking metrics performed by workers as a collective value (overall time saved and increased productivity, for example) can then be collected from wearables to improve workflow efficiency. They can also identify weaknesses in day-to-day operations that were previously going unnoticed. As with the personal spending analogy, once you begin adding up many small amounts and multiply them company-wide, the savings can be astonishing. Companies utilizing the right technology in the warehouse can realize efficiencies of around 20% in some areas.

According to one German study, traveling time in the warehouse accounts for an average of 40% of total picking time. This encompasses the worker going to and from the pickup location and the time spent at that location itself. Scanners digitally hooked up to the IoT would be able to harvest this data, and artificial intelligence could analyze it for improvements. Is there a faster route or preferable order in which items can be picked up?

Programs can be run to determine such variables. Sometimes the most disastrous problem is the one that goes undetected. Recognizing those blind spots through collecting and analyzing data can be a huge game-changer.

When the Suez Canal was blocked for almost six and a half days, Suez Canal Authority chief Osama Rabie noted that $15 million was being lost each day that the crisis persisted. Yet the incident’s true cost was much greater. Being behind a week means the next week is also delayed, causing the following week to be delayed even more as resources are pulled together. This begins to compound and make the situation worse, and the money lost a lot more exorbitant.

On the flip side of this, positive compounding effects can happen to the supply chain by increasing efficiency through new technology. As more time is saved by workers, not only can more be accomplished, but this “created” time can go toward other ways to maximize efficiency and devise innovations that can save even more time in the future.

Finding and investing in technologies that provide process analytics across the warehouse will help companies make better decisions. It can improve efficiency, safety and create the start of a human digital twin, where workers are connected to an evolving IoT and provide the metadata to maximize efficiency. It all starts with putting the worker at the center.

Axel Schmidt is senior communications manager for ProGlove, a developer of industrial wearables for manufacturing, production, logistics and retail.