6 Non-Technical Ways to Unlock the Value of Data Analytics
Auditors have been using data analytics in one way or another for over a decade, and yet most struggle to maximize the value this tool can offer.
While some audit organizations have matured over the years and gained tremendous value from using data analytics, others struggle to use data analytics consistently and obtain valuable results. Many audit organizations have also witnessed a decline in their performance after losing key employees that became data analytics experts through the course of their work.
What drives these variations in results?
There appears to be consensus on the actions that can be taken to increase the value gained from data analytics in a legislative audit office or an internal audit department. Surprisingly, to some, these actions are not centred around technology. Instead, they ask auditors to:
1. Demonstrate visionary leadership
The role of audit executives is to be advocates for their vision and to convince key team members to share in the same vision. The best performing audit organizations have leaders that are very clear on the role that data analytics will play in their success.
2. Focus on stakeholder satisfaction
Many auditors still do not recognize stakeholder needs and how critical it is to manage and satisfy stakeholder expectations. Many public sector organizations are very invested in data analytics and there is an expectation for auditors to do likewise.
3. Implement risk-based audits
Risk-based audits are a great way to ensure that your team is using resources optimally while adding value where it matters. In that context, data analytics is a useful tool to assess risks and flesh out for management their magnitude and how they can be mitigated. This emphasis on risk will maximize the value that could be derived from your investment in data analytics.
4. Use, share and repeat
Auditors document and standardize everything done in an engagement but many do not do the same with data analytics. There are tremendous efficiencies to be gained from sharing, reusing and making analytics repeatable. Don’t reinvent the wheel.
5. Adopt a disciplined approach to data analytics
Great auditors always demonstrate superb discipline. They plan meticulously, scope rigorously, and validate their findings. This discipline and the underlying principles that drive it should be adhered to when using data analytics during the audit process.
Document obsessively and ensure that your data analytics procedures are well aligned with your audit strategy. It is critical that you don’t succumb to the temptation of pursuing random juicy findings (what auditors often refer to as a ‘fishing expedition’).
6. Commit to staff development
The most effective data analysts are those that demonstrate critical thinking, not those that are more agile at using software. A focus on the contextual use of analytics software is key to obtaining value from an investment in people and technology.
All these actions are not about deploying fancy software, expensive hardware, and legions of data science experts. Non-technical factors can make or break your data analytics strategies. Implemented with determination and vigor these actions can be the building blocks that enable auditors to maximize the value they get from using data analytics and develop new insights into an organization’s performance.
This article was written by Yves Genest and Andrew Simpson. Genest is Vice President, Products and Services with the Canadian Audit and Accountability foundation, where he is responsible for leading the performance audit and parliamentary oversight products and services, including training, professional development, community outreach, research, and methodology development. Simpson has decades of experience in the information systems audit and security business; specifically data analytics, interrogation and forensics. He is a regular contributor to various auditing conferences and is acknowledged as an expert on continuous controls monitoring and revenue assurance.
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