Cost-effective warehouses rely on accurate and timely data collection. However, the process can be both time consuming and prone to errors. Thankfully, the technology exists to overcome both these challenges, as Charlie Brackley, Sales Manager at Harland Simon, explains.
We all know that in a successful warehouse everything runs smoothly at minimum cost and maximum throughput. There are several factors that contribute to this, not least a knowledgeable, engaged and motivated workforce.
However, in terms of technology, at the heart of effective warehouse management is data collection. Without that, you operate blind and the entire storage and handling operation quickly falls apart.
The two main measures of effective data collection are rapid retrieval speeds and pinpoint accuracy. In other words, the faster and more precise the information supplied, the more efficiently the warehouse can operate.
With data collection, ‘the sooner the better’ is almost inevitably the best answer to the question ‘when do you want it?’ Speedy delivery is not enough on its own, however. In fact, it’s worse than useless if the data is inaccurate because all you will be doing is delivering the wrong items quickly.
This can happen for a number of reasons, but one of the most common is inaccurate inputs. Garbage in, garbage out is well known to computer programmers. It refers to the fact that any system is only as good as the data it is given to work with.
Indeed, while scanning pallets and drop locations manually increases the likelihood of human error, computers are by no means infallible.
By supplying inaccurate data, the wrong locations can be entered and stock can end up in the wrong place. This leads to:
- Time wasted locating misplaced pallets
- More likelihood of mis-picks
- Additional resources required to remedy errors
Ultimately, your warehouse won’t run as efficiently as it could.
The processes that tend to result in the most input mistakes and waste the most time are pallet and location scanning. So how can they be made faster and error-free? The answer lies, at least in part, in emerging technologies such as automatic identification and data capture (AIDC). While this may incur additional investment, its reliability in collecting data and the time it will save by removing a manual process and avoiding errors will ensure it pays for itself relatively quickly.
AIDC refers to the methods of automatically identifying objects, collecting data about them, and entering that data directly into a computer system with no human involvement.
An AIDC system, such as my own company’s Vero, will digitally track the movement of pallets and inventory in three dimensions and in real-time, so every element of a pallet and forklift truck’s journey is recorded and monitored.
AIDC accelerates pallet movements and improves data accuracy to save time and increase productivity. Each pallet can be moved up to 15 seconds faster than with manual scanning, an impressive saving of more than four hours for every 1,000 pallets moved.
Automating data collection also offers bonus benefits. For example, since AIDC digitally tracks the movement of pallets and inventory in three dimensions and in real-time, every element of a pallet and forklift truck’s journey is recorded and monitored. This is useful to keep track of the warehouse operation and pinpoint problems should they arise. Recording and measuring data also allows further steps to be implemented to ensure forklift truck drivers work more safely and efficiently.
So specifying AIDC really is a no-brainer: it offers numerous benefits including the elimination of data errors, better inventory accuracy with less inventory reconciliation effort and a time saving of around one hour per 250 pallets moved. On top of this, data is recorded and can be reported on and analysed for tracking and continuous improvement purposes.