Your Guide to Data Analytics and Internal Audit

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Big data is collected and stored everywhere and over the last decade organizations around the world are figuring out how to use analytics to generate valuable and actionable insights. Data analytics can be enabled throughout a company to streamline shipping, enhance customer service, and create personalized marketing experiences. Each functional team in an organization, from Sales to Human Resources, has a unique opportunity to apply data analytics. One important team that needs to climb aboard is Internal Audit.

Internal Audit partners with the business to help each team run more efficiently and effectively, which generates ideas for improvement and innovation while also prioritizing risk management and internal control. While tasked with looking externally to evaluate other departments, Internal Audit sometimes lags in self-reflection and internal improvement. One example of this delayed improvement is in the use of advanced analytics.

Benefits of Data Analytics

Currently, big data is transforming a myriad of industries. Most famously in sports, there was the ‘Moneyball’ phenomenon of the 2002 Oakland Athletics. Within the movie, The Oakland Athletics general manager, Billy Beane, relied heavily on data analytics to analyze data, with the goal to quantify his players’ performance based on objective data. This use of big data allowed a team on a tight budget to remain competitive. See below for how the application of big data with Internal Audit can help your team remain competitive:

1. Enhanced Risk Management – Attempting to review and evaluate all data manually is a labor-intensive and unrealistic approach. When an auditor uses limited data sampling methods to compensate for what would otherwise be information overload, it can result in gaps in risk management. Important outliers and patterns can surface when assessing a full data set. An example of this is journal entry testing. With an appropriately built program, a listing of all journal entries can be processed, identifying which entries are of substantial risk (i.e., recorded on a weekend or night, not consistent with prior billings, etc.). Data analytics techniques such as this can help the team mitigate these risks by quickly reviewing enormous quantities of data.

2. Operate More Efficiently and Effectively – The application of analytics in each stage of the audit process can help improve the audit quality and speed of testing. With knowledge of transaction requirements and data analytics, Internal Audit can select samples that are likely to be documented exceptions in sample testing. For example, when evaluating Travel and Entertainment reimbursements, the Auditor can select transactions without an attached receipt file, which would not comply with the policy limits. With a large data set and a well-designed analytics program, the system can automatically run various tests, reporting the outcome in a consumable format.

3. Streamlined Reporting – The power of data analytics can be used to create more effective reports. Raw data obtained from the business can be converted into graphs and charts to aid in communicating audit background and the impact of findings.

Obstacles to Data Analytics

Like the challenges the 2002 Oakland Athletics faced in the playoffs, such as player injuries, any internal audit team will face obstacles while bringing analytics into the centerfold. See below for challenges we see often and solutions to overcome them:

1. Overcoming the Learning Curve – Data analytics can be an overwhelming concept for the team due to specialized jargon and unique technical concepts. Like everything else, the best first step is to start small. Encourage your team to explore various online resources and courses to familiarize themselves with the world of data analytics (i.e., Microsoft courses, professional articles, Coursera). Allowing your team to learn independently and then share ideas to help avoid groupthink and jumping to quick conclusions. It is best to wade into the world of data analytics applications, starting slow, rather than jumping into the deep end and quickly being in over your head. This approach sustainably builds your team’s capabilities while overcoming the learning curve.

2. Juggling Data Analytics Innovation with Current Projects – It is critical that the team start treating data analytics as a mandatory part of risk evaluation and testing. During the planning, fieldwork and reporting stages, the Audit team should work to include data analytics as much as possible, documenting their approach. This approach ensures the Internal Audit team’s focus on data analytics opportunities at all stages, increasing the proportion of audits utilizing analytics. While the Audit team considers data with each step, documentation is key as it allows others to walk along the beaten path and build upon the concepts for further improvement.

3. Choosing the Right Data Analytics Tools – A data analytics platform is a tool that supports the team throughout the stages of collecting, storing, cleaning, organizing, and modeling raw data. There are several platforms that can be used, like Power BI (Business Intelligence), Qlik, R-Studio and Idea. While exploring analytics, it is best to start with what is available, which is typically Microsoft Excel. Starting in Excel allows the team to take in ground-level data analytics concepts. The next major step in your data analytics journey is understanding which platforms other business teams use. This will prevent your team from having to recreate the data analytics wheel and have an internal network to aid in knowledge sharing. Additionally, if Internal Audit performed data analytics on a business function’s data, from a data setup and cleaning perspective, it would be easiest to complete the analytics testing on the same platform utilized by the business. It is beneficial to collaborate with the business, and it could help your team grasp data analytics concepts.

Next Steps

Whether the question is how to create an all-star baseball team or how Internal Audit can better manage risks, data analytics is the answer. Data analytics is a tool utilized by a growing number of Internal Audit teams. Regardless of where your organization stands with its audit analytics transformation journey, Sikich can help you modernize in a way that fits your team’s goals. The key to acquiring these benefits is successful implementation and transition. For data analytics coaching, contact our team at Sikich today.

This publication contains general information only and Sikich is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or any other professional advice or services. This publication is not a substitute for such professional advice or services, nor should you use it as a basis for any decision, action or omission that may affect you or your business. Before making any decision, taking any action or omitting an action that may affect you or your business, you should consult a qualified professional advisor. In addition, this publication may contain certain content generated by an artificial intelligence (AI) language model. You acknowledge that Sikich shall not be responsible for any loss sustained by you or any person who relies on this publication.

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