Picture this:
You’re a CRO that just landed a new client: an input company looking for crop protection research in support of a new potential product. You’ve been tasked with conducting field trials in different locations around the globe to test for marketability in those geographies and to collect the necessary data for regulatory approval. You’ll be planning and conducting the trial and doing all associated data analysis, creating the dossier for the regulatory agency, and supporting regulatory affairs efforts.
You put your best team on the job, including a top-notch research scientist, numerous experienced agricultural technicians, a quality assurance manager, and a data analyst with years of experience. Your technical writer has written thousands of dossiers over the years. Even your field technicians are some of the best in the business – you’ve put together an A-team to make sure you nail this work.
Your research scientists and agricultural technician start planning the trial, creating detailed trial protocols and treatment tables of different options, and gathering feedback from the client and the global team. The client is referencing past trials and past trial data, but when they share the data with you, it’s in a format that’s difficult to analyze within your current system because the categorization is different from your own standards.
After much back and forth the team finally nails down the trial protocol and sends it to the client to review. The client approves it and emphasizes that they want to be in the loop throughout the entire trial to ensure protocols are followed and the data is collected correctly.
Your team gets to work. But soon, it seems that there’s confusion about the protocol. All of a sudden, you’re scheduling conference calls and trying to track down tasks, and helping the team plan out the day-to-day execution to ensure the client is satisfied with the trial performance.
The agricultural technicians begin the data collection process, and all seems to be going well. Eventually, the client starts asking for reports on the status of the trial and the data collected so far.
So, the research scientist and agriculture technician start working with the project manager to define reports that meet the client’s needs. The first time they attempt to run the report, it takes multiple days to compile all the data from the different systems and sources! That doesn’t even include the cross-trial analysis of legacy data. And exporting the reports is another issue entirely.
While this reporting is happening, the research scientists notice a series of issues in the data. Some is missing from certain trials – some manual data, and some collected in differing systems. They’re also finding outliers and struggling to standardize data and data types.
The client is becoming frustrated with the time it’s taking to get things done. Your team is struggling to make all the different systems work – the systems for planning, the systems for operating the trial, and the systems for data management.
If this situation sounds familiar, it’s because it’s not unheard of. CROs are often stitching together multiple systems and numerous data types between what’s available to their company and what’s required by the client. This process can be time-consuming, frustrating, and sometimes even a total barrier to success.
It’s time to put away the needle and thread and stop patching together systems to make a trial run. With cloud-based solutions vs legacy software, CROs and sponsor companies can run seamless trials focused on operational excellence and high-quality data analysis.
Legacy Solutions in a Patchwork
Today, a field trial might require one system for planning the trial – selecting a design, optimizing for the geography, identifying treatments, and more. These systems aren’t always user-friendly and require a high degree of experience to use.
The trial might require a project management tool, too. Depending on the size and scope of the company and trial, this tool can be used to manage tasks, check in with team members, and even overcome language and time zone barriers.
Data collection often requires multiple systems. From complex automated data collection systems to mobile data collection that can be challenging in certain environments or lighting to pen and paper style data collection, all that information must be centralized, standardized, and aggregated. All of these different systems and file types have to be connected for analysis. Often, data analysis itself requires a unique software solution.
Reporting to customers or providing internal visibility can require yet another system or series of systems to visualize data and make it understandable.
These many systems and file types create efficiency challenges. Manpower is necessary to manually handle data, creating room for human error and requiring hours of work. Collaboration becomes challenging when stakeholders and clients can’t access the information they need on the timeline they need it, hindering decision-making and complicating necessary teamwork.
Cloud Computing in Agriculture Streamlines Processes
Cloud computing in agriculture has a lot of promise in a lot of areas. From on farm experimentation to global CRO-led field trials, cloud computing, and cloud-based platforms offer end-to-end capabilities for streamlining processes and increasing efficiency.
Cloud-based agronomic solutions avoid the legacy format requiring files to be manually shared amongst collaborators. With cloud-based platforms for agricultural applications, all team members can access data – often even in real time. Collaboration and decision-making can happen faster when data visualization and reporting aren’t an arduous manual process.
Cloud-based platforms for agronomic field trials can be the singular platform that includes all the capabilities and functionality needed for executing a complex field trial or farm experiment. From planning to management to data collection and analysis, only cloud computing can provide the access and capabilities needed to create an end-to-end solution.
In the scenario above, you can imagine having a single system to share within and outside of the organization that works wherever trials are conducted. The solution covers data collection and storage from the first trial to the most recent trial, creating a warehouse of data that’s a single central source of truth. It’s possible to analyze and report on this data, creating single-trial or cross-trial analyses.
And all of this is possible without integration projects and IT professionals spending hours building singular, centralized data views.
Agmatix & Cloud-Based Agronomic Solutions
Agmatix is a global company developing solutions to grow data for impact. Its Agronomic Trial Solution is one of the company’s data-driven agri solutions built on cloud computing.
Agronomic Trial Management is designed as an end-to-end cloud-based system that supports every step of the trial process. Trial designs come together easily and quickly with drag-and-drop functionality. Hundreds of treatment combinations are available. And once the trial is ongoing, research scientists, trial coordinators, and field technicians get full visibility and control of the trial and related resources. Stakeholders can always be up-to-date on the trial status.
The system is built to enable communication between all stakeholders, the team executing the trial, and clients. Agronomic data is accessible and shareable to the people who need it – even people who are partners outside your organization.
Data collection, once a particular pain point for patchworked systems and file types, can be seamless. With a digital notebook, high-performing mobile data collection, and real-time results, you can be confident in the quality of the data and move efficiently towards putting it to work.
Cloud-based agronomic solutions create efficiency gains, increase data integrity, increase innovation, reduce risk, and create competitive advantages as companies can move to market faster. The end-to-end capabilities of Agmatix’s Trial Management System help CROs and companies to execute seamless and efficient trials.
