Empowering Audits with Innovation: IGB Berhad's Journey with Arbutus Analyzer
“Adopting Arbutus Analytics has been a game-changer for our audit processes. The solution is not only user-friendly, but also powerful enough to handle complex data analysis with ease. Sampling is a word of the past, as we can now analyze large datasets in their entirety, enabling more accurate insights. Its simplicity in adoption, coupled with its significant impact on our auditing capabilities, has allowed our team to increase productivity, improve accuracy, and make more informed decisions. Partnering with Quaditix was key in ensuring a smooth transition, and we are now empowered with a tool that elevates both the quality and efficiency of our audit work.“
Christine Ong
Head of Group Internal Audit at IGB Berhad
Challenges and Opportunities
IGB Berhad’s internal audit processes previously relied heavily on Excel for data analysis, which proved to be inefficient and time-consuming, particularly when handling large datasets. Auditors had to manually clean, sort, and analyze vast amounts of data, which not only consumed significant man-hours but also limited the depth and accuracy of insights derived from the audits. The manual nature of the process increased the risk of errors, inconsistencies, and delays, making itchallenging to maintain audit efficiency and effectiveness.
Recognizing these challenges, the organization sought a more robust and scalable solution to enhance its audit capabilities. The ideal solution needed to:
- Streamline data analysis to improve efficiency and accuracy in audit processes.
- Handle big data effectively while remaining user-friendly and accessible.
- Eliminate the need for complex programming, allowing auditors to focus on analysis rather than coding.
- Enable staff across all levels to perform analytical tasks with ease, fostering a more data-driven audit approach.
By addressing these key requirements, IGB Berhad aimed to modernize its audit processes, reduce manual effort, and enhance decision- making through more sophisticated data analysis capabilities.
Consideration and Decision-Making
During the evaluation phase, IGB Berhad explored several analytical tools, considering factors such as cost, functionality, support, ease of use, and implementation timelines.
Why Arbutus Analyzer?
Simplified User Experience:
The user-friendly design of Arbutus Analyzer, with its intuitive drop-down workflows and absence of complex programming requirements, made it easier for all levels of staff to learn and adapt to the tool. This simplicity reduced the learning curve and ensured a smoother transition for new team members.
Compatibility with Diverse Data Sources:
Arbutus Analyzer supported multiple data formats, including Excel, CSV, and various database outputs, enabling seamless integration with IGB Berhad’s existing systems. The ability to access and analyze data from various formats ensured the tool could adapt to the company’s diverse datasets. This capability reduced the time and effort spent on reformatting, cleaning, or restructuring data files.
Knowledge Sharing Among Team Members:
IGB Berhad encouraged a collaborative environment where team members shared insights, workflows, and best practices with one another. This approach created a culture of continuous learning and minimized the impact of individual departures.
Ensuring Effective Knowledge Transfer
One of the primary challenges IGB Berhad faced during the adoption of Arbutus Analyzer was the risk of knowledge loss due to staff turnover within the audit team.
This concern was critical because maintaining consistency and expertise in audit processes required all team members, including new hires, to be proficient with the tool.
Implementation
The implementation of Arbutus Analyzer at IGB Berhad was seamless and efficient, thanks to proactive involvement from the IT team during the consideration phase.
Comprehensive Training:
Quaditix conducted hands-on training sessions for all audit team members during the implementation phase. These sessions focused on practical, real-world applications, ensuring that staff could immediately apply what they learned.
Accessible Learning Resources:
To supplement the training, the team leveraged a robust suite of e-learning modules provided by Quaditix. These resources offered self-paced learning opportunities, making it easier for staff to revisit key concepts as needed.
Ongoing Customer Support:
The Quaditix support team played a crucial role in addressing queries and providing guidance, particularly in the early stages of adoption. Staff were encouraged to reach out to the support team whenever they encountered challenges, fostering confidence in using the tool.
Integration:
Integration required no major modifications to the company’s existing IT infrastructure. This minimized implementation complexity, reduced costs, and ensured the tool could be deployed quickly. The tool was designed to extract only the relevant data from IGB Berhad’s operational and financial systems, ensuring efficient and focused analysis. This centralized approach eliminated the need to replicate entire datasets, reducing system overhead and maintaining data security.
Application:
IGB team staff were able to see firsthand how the tool enhanced their workflows. This approach helped bridge the gap between theoretical training and practical application, making learning more effective and relevant.
By combining structured training, accessible resources, and a supportive implementation approach, IGB Berhad successfully mitigated concerns related to knowledge transfer, ensuring that its audit team could confidently and consistently use Arbutus Analyzer for enhanced data analysis.
Impact
The implementation of Arbutus Analyzer has brought transformative changes to IGB Berhad’s audit operations. By addressing critical challenges and streamlining processes, the tool has delivered tangible improvements that align with the company’s strategic goals.
Key Benefits:
Increased Productivity:
Arbutus Analyzer significantly reduced the time required for data preparation and analysis. Tasks that previously consumed countless man-hours, such as cleaning, sorting, and organizing voluminous datasets, are now streamlined and automated. This productivity boost allows auditors to focus more on high-value activities such as identifying trends, uncovering risks, and delivering actionable insights.
Enhanced Data Analysis:
With Arbutus Analyzer’s robust analytical capabilities, the audit team can now interrogate datasets more comprehensively. The ability to perform in-depth analysis on entire data populations, rather than just samples, has increased the accuracy and reliability of findings. This capability not only improves audit quality but also ensures compliance with regulatory and operational standards.
Upskilling Staff:
The intuitive nature of Arbutus Analyzer has sparked interest among younger auditors, fostering a culture of continuous learning and technological adoption. By equipping staff with advanced tools, IGB Berhad has empowered them to enhance their technical proficiency and take ownership of more sophisticated analytical tasks. This investment in skill development also contributes to employee
satisfaction and retention.
These outcomes have not only reinforced LPPSA’s reputation as a reliable and transparent statutory body but have also positioned the organization as a leader in adopting innovative audit practices.
Future Plans
Continuous Monitoring for Strategic Alignment:
Building on the success of Arbutus Analyzer, IGB Berhad plans to explore
continuous monitoring capabilities. This approach will enable the company
to transition from periodic audits to real-time oversight of critical processes.
Continuous monitoring will allow for proactive identification of anomalies,
risks, and inefficiencies, ensuring that audit and compliance functions are
always aligned with strategic goals.
By leveraging Arbutus Analyzer’s full potential, IGB Berhad is not only
enhancing its current audit processes but also positioning itself as a
forward-thinking organization that prioritizes innovation and data-driven
decision-making.
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