Case Studies

An electronic system - introducing new way of working

01 December 2019

New national requirements meant an immediate, significant upscaling of data collection activity for AsureQuality’s Tuberculosis (TB) team. With an extremely tight deadline, Agtrac scoped their requirements, supplied and configured the equipment, provided training and centralised their data – all within four weeks. This gave AsureQuality the power to do more, with greater efficiency and ability to deliver on their target.

Expansion meant getting the gear and getting everyone up to speed with the technology so that we could meet the requirements by the time. Now everyone is getting the right information in the right format through quickly so we can get that to our customer.”

Craig Bell, Operations Manager - AsureQuality

 

Initially we had 130-odd staff emailing csv files. Administrators receipted and individually reformatted every file that came though. Then uploaded them. Now we’ve created a favourite that everyone has on their scanner. They literally scan, it connects to an app on the phone, then connects with Datamars Livestock. There’s no more long labour hours.”

“With Datamars Livestock, we could really look at the data and say ‘What can we learn from this? What can we change to improve this?’ Then Agtrac makes it happen.”

Samantha Hawkins, Technical Coordinator - AsureQuality

The Challenge

AsureQuality had one month to move from a standing start to deliver accurate RFID data to their customer for every animal on farm. At peak, this required capturing, transferring and presenting data from 400,000 animals in a month.

AsureQuality’s existing way of working would not meet the deal. Their recording system was resource-hungry, demanding many staff hours to manage the manual upload and transfer of individual data sets. At each transition point, there was an opportunity for error.

The Outcome

Success! Agtrac scoped AsureQuality’s requirements and provided an end-to-end solution to ensure AsureQuality’s new process was fully operational within the timeframe. 

Within four weeks, Agtrac identified, sourced and configured reliable technology. We put in place a change management programme to upskill more than 60 members of AsureQuality’s national field force.

In addition, Agtrac provided AsureQuality with an unexpected boon — Datamars Livestock Management Software. Agtrac centralised AsureQuality data through the Datamars cloud-based online programme which allows all AsureQuality scanned data to be uploaded seamlessly from the scanners’ pre-set favourites. This ensured swift transfer and collation of quality data with minimal staff resource.

The Future

Agtrac remains in regular contact with AsureQuality to monitor data and provide support to AsureQuality administration and their remote field force on request. Agtrac is also on call to troubleshoot technical issues and provide ideas on how to improve data collection, data management, and develop their data interface.

The Project

Within the constraints of AsureQuality’s four-week deadline, Agtrac managed the logistics and supply of a full technology solution (comprising Tru-Test XRS2 stick readers and Zebra ZQ510 barcode printers for each of the 60-plus field staff).

Our subject matter experts designed and delivered customised training for AsureQuality field technicians scattered across six regional hubs. Staff received hands-on instruction on equipment use including data-collection and transfer technology and had ready-access to Agtrac’s responsive support team for troubleshooting and training support.

We created an initial custom configuration of data collection settings installing this ‘TB scan favourite’, on the electronic scanners to standardise the data collection process for all field staff. Alongside AsureQuality, we refined the data collection process, reviewing data through the shared Datamars Livestock Management Software portal.  This fast-tracked simple iterative changes making the collection, collation and data provision easier and faster for staff, and improving data quality.

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