Long after the angst of choosing the right software has passed, you may be uncertain about what to do with it. Sometimes, new IDEA users find themselves in a rut – only using IDEA as a data importing and conversion tool, or for sampling. It happens. This intermittent use of such a powerful tool can be prevented with a few simple changes.
Longtime IDEA user Jeremy Clopton, Director with BKD, shared his recommendations for using IDEA to its fullest extent with fellow IDEA users at the 5th IDEA User Conference in Orlando back in May. Jeremy knows a thing or two about developing and implementing successfully data analytics programs for Fortune 500 companies, and serves as a data analytics champion for the BKD Forensics & Valuation Services division. He also has the unique merit of earning both IDEA and ACL certifications.
When it comes to testing, just about everyone pulls a sample. The go-to sample sets of 30% or 50% of the population are extremely inadequate, especially when you have the power to analyze 100% of the data. Samples are simply not enough to see what is transpiring in the business. The same holds true if you’re using IDEA exclusively for data conversions when it is capable of so much more.
Perhaps this limited use is fueled by fear that you might automate yourself out of a job. Nothing could be further from the truth. You may be overlooking the opportunity to add value back into the business. The chance to be the resource the c-suite turns to when they need to know something.
Data analytics is defined as, “processes and activities designed to obtain and evaluate data to extract useful information and answer strategic questions.” You must first shift your mindset in using IDEA to get relevant information that can be used to answer strategic questions.
What strategic question would you like answered? Is there something management has wanted to know for months, that you might be able to find out in a few hours? The fastest way to gain “raving fans” is to help them get answers or recover costs.
Is management concerned about meeting compliance standards? Are there uncertainties about whether fraud or corruption exists within the organization? How about whether employees are using corporate credit cards in accordance with company policies? Perhaps it would be helpful to see patterns or trends in the sales cycle or production costs. Whatever the question may be, the answer lies somewhere within the data.
This brings us to the ever-popular topic of big data. The value of data analytics is actually data minimization. While every organization may have large volumes of complex and abundant data, it’s probably not all useful. The goal is to figure out how to apply technology to answer strategic questions, and gain meaningful insights. Here are some simple steps to follow:
With a vision in mind, a plan in place and your team built, it’s time to get management on board. It’s critical to not only fund your software needs and required training, but to get the “higher ups” engaged and excited about what you’re working towards.
Once again, there needs to be a mindset change. This time it’s getting others to see that internal audit is a valuable, helpful resource within the company. At some point, the organization will actually look forward to working with audit. How? By becoming a trusted advisor. By using the right tools to get information the business has not been able to answer thus far.
Getting there will require you to overcome some challenges. Many fear just the process of starting. Clopton says most auditors are afraid of “breaking the data.” He reminds us this is impossible, especially when using a purpose-built tool like IDEA that provides read-only access and ensures data integrity. Start small, and with something accessible to ease yourself into the process.
Nothing will win you rapid accolades like recovering costs. Clopton recommends starting with corporate credit cards for these reasons:
Things to Keep in Mind
Common Fraud Detection Tests
Automation & Continuous Auditing
Once you’ve established a good process for the ad-hoc analysis, you can move towards continuous auditing. First determine how you plan on managing the results. If you, or the involved departments, cannot manage the results you get, then change the structure. For example if you run analytics on vendors weekly, but it takes AP three weeks to review the exceptions, consider running them monthly rather than weekly to avoid a backlog of work.
How do you plan on communicating the value of what you’re doing to management and key stakeholders? Measure your success and work to quantify your results.
Using the duplicate key and duplicate key exclusions features within IDEA, you could easily demonstrate thousands in recovered payments that may only take you a few hours to perform. There are consulting groups that will search for duplicate payments and charge 30-40% of the recovery amount. Perhaps your analysis of credit card data uncovered tens of thousands in losses. Won’t that make it easier for you to ask management, “Where else can we recover costs, and can we attend training to help us learn how analyze those areas?”
Working with IT – Communication is key. Find someone to help interface with IT who “speaks the language” of IT. Remember they are constantly working to keep up with changes in technology and business, and compliance is of the utmost importance to them. Data access and security is critical, so communicate the benefits of the tools you’re using to address those concerns.
Obtaining Data – Avoid going back to IT multiple times by thinking and planning ahead. What data do you need for the analysis and follow up? Get what you need upfront to save time and effort.
Eliminate Silos – Make analytics part of what you do, not in addition to what you do. Bring others into the fold and work to become a data-driven organization. Get others involved in what you’re doing and regularly communicate wins to demonstrate the value of using data to gain insights. The momentum of a strong data analytics program will not stop if knowledge is shared.
Move from Reactive to Proactive – If you’re only looking for red flags to occur, your approach is not proactive enough. Data analysis needs to run at the speed of the business process. It’s easier to stop funds from going to out the door than to try and recover them.
Think Outside Audit for Tech-Savvy People – There are creative, resourceful people within every organization. They may not be auditors, but they may have the right mindset to use data in creative ways to answer strategic questions.
No Data? No Problem – Don’t let data availability stop you. Begin to capture it however you can. Almost every organization has some type of ERP system. Microsoft Excel and Access are also great tools to capture data. Clopton recommends Smartsheet®, a cloud-based solution for data collection and project management.
Remember that not all valuable information is in numeric format. Text data is just as important, including social media, emails, reputational risks, etc. Perform data quality checks regularly to be sure the data is collected accurately.
Success using data analytics needs to begin with small steps along a well-charted route. Set reasonable, achievable goals, measure your success as you go, and communicate your wins to build support among management. Accept that there will be some failures along the way, but use those as opportunities to learn and grow. Get creative and engage others within your organization. Your efforts will not go unnoticed.
Content gathered from a presentation delivered by Jeremy Clopton during the 5th IDEA User Conference. Jeremy is a member of the BKD Forensics & Valuation Services division. He specializes in data analytics with applications in fraud prevention and detection, risk assessment and business intelligence.