Intact Analytics Use Case: Risk-Based Audit Planning
Risk-based audit planning is one of the trickiest things in audit-, certification- and standard management to get right.
Even though many industry professionals dedicate a lot of their resources to risk-based audit planning, very few get it right.
Relying on human intelligence alone to go through mountains of data to then decide where to focus your risk-based attention is simply not working the way it is supposed to be. We have seen this for decades in the audit and certification industry and were dissatisfied with how inefficient and ineffective the current process is.
Smart audits have often been described as the future of auditing. There is no better way to utilize your audit data than to integrate smart, risk-based audit planning. Intact Analytics uses the power of artificial intelligence to semi-automate risk-based auditing.
Let AI do the time-consuming data work for you, save time and get better results – easy as that.
AI in Risk-Based Audit Planning – How Does It Work?
Maybe you are wondering how artificial intelligence will work exactly in risk-based audit planning and how you will benefit.
Put simply, Intact Analytics uses several predefined rules, based on your experience, Natural Language Processing and learning algorithms to do the following:
- Instantly analyze large amounts of data for high-level results and trends
- Discover trends, connections between topics, and risk factors
- Lets you predict non-conformities & more based on audit history
These will enable you to optimize your risk-based audit planning. Work better, faster, and smarter.
Read further and learn what functionalities are involved in the process and how different user roles benefit from them.
Intact Analytics Functionalities
(Business)-Rules
Explorative, Rule-Based Planning
Intact Analytics lets you utilize your staff’s expertise and deep business understanding in the form of rule-based panning. Your team will define business rules together with our team to set Intact Analytics up for success.
Intact Analytics uses explorative, rule-based planning to get suggestions for audits and where to focus your attention. E.g. if the last audit was below 70% and had a major, you can add a risk-based remote audit. Additionally, the functionality lets you explore last findings in the same company or similar companies and add risk topics to an audit.
See how that plays out for common roles in risk-based audit planning:
- Planner (Audit Level): Get suggestions for audits, easily. Intact Analytics scans the data and suggests audits based on results and trends. E.g. if the last audit was below a certain threshold and had a major findings, a risk-based audit should be added.
- Planning Manager (Aggregated Level): Helps you decide, where the focus for the next batch of audit planning should be based on trends and past results. E.g. topic, regions, sectors, trends, patterns, correlations.
AI – Predictive Analytics
Intact Analytics’ predictive analytics helps you to focus your attention, where it is needed.
Predict non-conformities and areas where they might occus based on audit history and comparably auditees. Additionally, you can predict the probability of non-conformities for specific audits and entire areas.
See how that plays out for common roles in risk-based audit planning
- Planner (Audit Level): Intact Analytics helps you predict non-conformities based on audit history and similar auditees. Additionally, you can predict which audits have a high probability to have non-conformities. Based on these information, you can plan your audits faster and better.
- Planning Manager (Aggregated Level): Predictive Analytics enables you to discover common patterns. E.g. which non-conformities will occur in which region, sector, sections, etc. Execute planning management based on data-based predictions and suggestions and make the right decisions.
AI – Natural Language Processing
Natural language processing helps you discover in-depth insights: E.g. how many topics/risks were flagged and in which sector/region as well as trends, patterns, and correlation.
Through this knowledge, your team can access insights into written information directly, previously only accessible by in-depth analyses by your team.
Act on complex written data now.
See how that plays out for common roles in risk-based audit planning
- Planner (Audit Level): Helps you plan better through past written results. Shows you e.g. if the topic “listeria” is in the non-conformity or any other free text field of past audits, if the topic critical control point (CCP) is in the mitigation description of last audit.
- Planning Manager (Aggregated Level): Grants you access to high-level audit result data and lets you plan better for the future. Shows you how many topics/risks were flagged. E.g. in which sector/region, trends, patterns, correlations.
Difference to Business Intelligence
To people unfamiliar with the topic, the difference between Artificial Intelligence (AI) and Business Intelligence (BI) is unclear at first glance. However, the difference is significant. Both tools have their legitimacy and specific use cases, but BI tools cannot cover what AI tools can.
Simply put, AI tools in general and Intact Analytics specifically a true “workhorse,” A full-scale software tool, and not just visualizations. It provides no-code SQLs, flagging and inspection of individual audits, and ready-to-use tools for reviewers.
Meaning that Intact Analytics performs tasks and analyses for you previously done by humans, whereas BI solutions “only” show you what’s there in a structured way.
Learn More
Interested in more? Book a free product demo today and get full insight into the product!
Book a Demo
Book a Free Demo TodayWe promise to amaze you.
We promise to amaze you.