Machine Learning a 21st Century Time Saver for the Trades Industry
Client information, job details and supplier invoices are essential elements to the trade service industry and must always be correct and up-to-date. Unfortunately, in reality businesses must commit significant amounts of time to administrative tasks like manual data entry, which can be a momentum staller.
Fortunately, the digital age has produced a number of solutions which help to minimise time theft and reduced profits as a result of manual processes, and the onus is on Australia’s trade businesses to embrace these solutions as they become more readily available.
Data feeds, for example, have rapidly become an essential part of a trade business’ digital arsenal and why the industry should increase its focus on the concept known as machine learning.
What is machine learning?
Machine learning is part of the broader definition of artificial intelligence, but there is nothing sci-fi about it. It uses sophisticated mathematical algorithms and process information to identify patterns, make suggestions and identify problems for example without constant assistance from human beings. Much like how a person would make a decision in life based on knowledge, memory and experience, machine learning involves using statistics and algorithms to process and identify patterns in data.
Today, such data is delivered into a machine through dedicated feeds. Data feeds are integrated into a machine’s programming and provide ongoing streams of structured data, making it possible to have new content or updates delivered to a computer or mobile device as soon as it is published from one or more
Machine learning is already used widely but is such an automotive convenience that it sometimes fades into the background without being fully recognised as an important and interesting component of technology. Social networking is a prime example of machine learning, from pulling status updates,
photos, videos and ‘like’ activity onto a news feed.
What impact is it having on the trade service industry?
Machine Learning is having a significant impact on the trade service industry due to its ability to decrease the time needed to complete administrative tasks and increase efficiency and workload capacity, which directly correlates to a business’ earning potential. In other words, the less time staff need to be behind a computer inputting job information, the more time they have on site and in completing billable tasks.
Using past examples of different formats and information, machine learning can be used by businesses to read new incoming documents not previously seen to suggest the content and context of the information and automatically process it. The more information and examples that flow through the system with
feedback from people indicating whether the interpretation was accurate or not, the better the machine learning algorithms get at understanding and being able to automatically process information.
As a major job management company operating across the world, simPRO offers machine learning capabilities available today for the benefit of customers. simPRO’s Data Feed add-on is one simPRO solution that uses complex algorithms to draw information from multiple electronic formats, like PDFs and
Excel documents, and correctly applies the information to client updates, purchase orders, job requests and work orders. simPRO’s Data Feed utilises machine learning to take extracted information from various sources not integrated with simPRO and accurately allocate it to workflows.
Machine learning and data feed adoption is on the rise in Australia’s trade service industry, but businesses are growing increasingly time-poor due to current market and industry demands and the constant strain of keeping profitable.
It is time machine learning received greater notoriety for trade businesses to be better informed on how it is a step in the right direction towards becoming more productive, streamlined and overall more successful.
Article written by Curtis Thomson - simPRO Director. Find out more about simPRO - www.simpro.com.au.