DLF
The Context
In the dynamic and highly competitive agribusiness market, innovation and efficiency are essential to maintaining a solid position. In the United States, the seed industry is a clear example of this requirement, characterized by its diversity and focus on technology and biotechnological research.
Companies in this sector are constantly challenged to develop seeds that are resistant to diseases, insects and adverse weather conditions, in addition to improving their yield and quality. This demanding environment has led companies like DLF, a leader in the supply of grass seeds, forage and other crops in the United States and in more than 80 countries, to seek innovative solutions to optimize their processes and make the supply chain more efficient.
Within this context of needing to stay at the forefront of the industry, DLF decided to take a technological leap to optimize its seed reporting data and positively impact data quality along with implementing time and cost savings.
The Challenge
Throughout its operations, DLF’s work in the field of technology and research has generated a large amount of information that is used to produce customized grass varieties with improved characteristics, based on the needs of its clients.
Considering the quantity of data managed monthly, which comes from 18 different laboratories, the main challenge faced by the company's supply chain was the manual entry of the Seed Analysis Reports into the Navision ERP system. These laboratory results are critical to quality control measures and decision-making processes throughout the entire supply and distribution chain.
The reports, which are generated in PDF format, required extensive review and entry into the Navision ERP system, resulting in a significant investment of time and resources. Annually, this process took a total of 880 hours.
Considering that the company managed the review and entry of nearly 500 monthly reports, there was a pressing need to address the situation and automate the process to optimize data entry into the system.
Our Proposal
The NEORIS proposal involved the implementation of a robust automation framework. Using the power of Robotic Process Automation (RPA), through AI Builder, NEORIS introduced an innovative solution known as the Seed Enhancer Bot. This specialized bot further improved automation capabilities by streamlining the management of lab results within the system. With the Seed Enhancer Bot, manual entry of reports was completely eliminated, ensuring swift data input while upholding the utmost quality standards.
The Solution
Embarking on a 12-week journey, the RPA project for DLF was meticulously organized to ensure successful and systematic execution. The first week was dedicated to extensive planning to achieve a clear understanding of the project objectives and client requirements. Subsequently, in the following two weeks, the design phase was carried out, where the foundations for the next automated solution were set into place.
For the construction phase, which spanned eight weeks, an agile delivery approach was adopted, with a commitment to deliver automation for two laboratories on a weekly basis. This dynamic strategy ensured constant progress and allowed us to work in a flexible environment with the ability to adapt to the changing needs of the project.
For the testing stage, a week of dedicated work was stipulated to validate the functionality and reliability of the automated system. Afterwards, we engaged in a week of constant attention, focusing on post-implementation support and the resolution of any immediate concerns that arose.
By adopting an Agile methodology for the project, we facilitated the team’s open communication, achieving rapid adaptation to changing requirements and continuous improvement throughout the project lifecycle. The iterative nature of Agile Project Management was instrumental in achieving efficiency and responsiveness to meet project objectives.
The Results
Through automated workflow, the average time per PDF report was significantly reduced by 5 minutes and the data entry process was also accelerated. This solution not only increased operational efficiency but minimized the potential for human error associated with manual data entry.
The successful implementation of this automated system ensured a smooth and error-free process for managing Seed Analysis Reports within the Navision ERP system, thus marking a crucial achievement for our digital consulting portfolio.
This project achieved significant results that contributed to the company's operational efficiency. Some of the results and benefits could be summarized as follows:
- Total savings (annualized): $20,000 USD
- Hours saved (annualized): 880
- Improvement in Process Efficiency by 63%
- Improvement in Data Accuracy by 95%
Testimonials
“The adoption of RPA has significantly improved the efficiency of the Seed Analysis Data Entry Process. It has also improved data accuracy by reducing human errors when entering data into Navision. This drives better decision making by providing reliable data to identify patterns, trends and insights.”
Pamela Valenzuela, NEORIS RPA Delivery Manager“The main challenge of this project was to identify all the business scenarios in order to build and train an optimal AI model for each Test Type and Laboratory. In addition, setting up proper configurations during the model training stage was essential to achieve accurate data extraction.”
Julio Luna, NEORIS RPA Developer“Implementing RPA has been a welcoming experience and first foray into automation. It has turned a tedious and time-consuming task into a background task. We look forward to exploring new opportunities with RPA and other automated services.”
Susanna Sieke, Seed Enhancement Director, DLF"Utilizing RPA for some of our daily data entry functions will allow us to free up time for our employees to focus on tasks that are more valuable uses of our talents and resources. It will allow us to be more proactive on a daily basis as we will not be as burdened with time-consuming, yet still business essential, tasks."
Matt Jackson, DLF Grower Services Administrative Manager