Data is often underutilized. The opportunity to use data analytics to gain insights, add more value and unravel opportunities are endless. We’ve rounded up a few, fairly-unconventional, ways CaseWare IDEA® users are exploring data in innovative ways.
Let’s start with CaseWare’s Chief Product Strategist Alain Soublière who talked with Accounting Today about conducting mood analysis of social media data using Python, which is now integrated into IDEA. Here’s what he had to say:
“We are looking at tweets and also social media to see what is the mood, basically, of those tweets. Are they negative? Are they positive? It is searching for specific words that are negative, neutral or positive. And, at the end, we can tell that there’s a trend, for example, in social media for that specific company that is negative or positive. … It’s a new risk that in the past auditors didn’t have to worry about.”
Regardless of the question you’re asking, if data is available, you can most likely find the answer.
At Huntington Ingalls Industries, data analytics is used across multiple departments outside of audit including engineering, quality and safety. The company’s Chief Audit Executive tasked senior audit specialist, Rick Fowler, with performing an advisory service on the company’s culture. Their goal was to look at different elements of the company that were already being measured to see if they might impact or influence the culture and values.
Manufacturing companies already collect and store performance data for reporting purposes. The audit team at Huntington Ingalls are combining safety data and employee surveys to identify trends in the company’s culture. By pairing up different data sets, they are comparing whether ethics is impacting engagement or vice versa.
Using regression analysis, auditors look at correlations between employees working overtime and the number of accidents that occurred. While they didn’t find any correlations between the two, their use of analytics has helped management answer questions and make decisions backed by data, rather than an educated guess.
Stream is one of the largest direct selling companies globally and a leading provider of energy. Stream’s primary sales channel consists of a direct sales model, with more than 100,000 independent sales associates. Each commission check contains at least 25 data points that must be verified for accuracy. (And you guessed it, they were performing the verifications manually.) Stream’s Director of Internal Audit, who has used IDEA for more than a decade, put IDEA to work.
Auditors test for duplicate checks, recalculation of associate point requirements to ensure they meet eligibility requirements, and accuracy of level payouts. Macros help the audit team analyze millions of data points each month within a few minutes and identify defects in the system. Looking well beyond analyzing financial data, they also use IDEA to analyze customer data such as usage rates during times of disaster and smart meters capturing and comparing usage among neighbors. Audit has become the go-to source to help the company answer tough questions.
Next up – a touchy topic for some, but one deserving our attention because it is a booming business. Legal cannabis is also a complex business – filled with risks and regulations. It’s an all-cash business where inventory must be packaged, labeled and tracked at every phase, from seed to sale. Each item purchased to support the business from a tiny bag to a greenhouse building is hand-entered into QuickBooks because there are no purpose-built tools available – at least none that work as intended. Companies are audited every year by both the IRS and the state where they operate. (Let’s take a moment to repeat that…every year these businesses are audited by both entities.)
Experienced auditor and data analytics enthusiast Theresa Gruppo entered the legal cannabis business on a mission to help her client tighten up processes and maintain profitability. She quickly discovered that while the cannabis industry is ripe with opportunities, it is also plagued with risks, inefficiencies and mismanaged business practices.
She used IDEA to pull and prepare data for analysis from different sources including QuickBooks, inventory tracking systems, CRM information and print reports. Using IDEA, Theresa tracked inventory to identify which plants sold best to increase product production based on demand.
Analyzing costs and overproduction helped the company achieve higher levels of productivity. Sales transactions, cash flow and invoice tracking data are now analyzed regularly, giving stakeholders information they didn’t have previously to make better decisions. Daily, monthly and annual reporting is simplified, and even automated, which reduces the amount of pre-audit prep work.
For those who travel frequently, airline performance matters. Passengers are at the mercy of the airline they choose the moment they lock that big metal door. During his 40+ year career, Scott Jones has done his fair share of traveling. His passion for flying, coupled with his natural curiosity about using data to get answers, prompted him to use IDEA to measure airline performance and share his process with other professionals to demonstrate the unconventional ways data analytics can be used across all aspects of the business.
An honest look at performance can only come from analyzing objective data. Scott took the Department of Transportation (DOT) Airline Delay Database, which contains on-time statistics stored in a CSV table, ranging from 2014 to 2017 and imported it into IDEA. He verified the data to ensure integrity, completeness and reliability. Using the data visualization features in IDEA, he established “personality” criteria for the data such as carrier, weather, minutes delayed, etc. Each airline was assigned unique codes to help average the delay information. Scott used a visualization tree to gauge performance levels and summarized the data within IDEA. Considering airlines with more flights have more opportunities to delays and safety issues, he created a new metric to unify and weigh performance levels.
To measure safety performance, Scott used National Transpiration Safety Board (NTSB) Accident Data, an XML database that required data preparation before it was analysis-ready. He used several of IDEA’s built-in functions including:
Scott joined the DOT and NTSB Carrier data together and summarized it using a performance dashboard to get a quick summary of performance levels. Similar to weighing the DOT delay data, he assigned values to the combined data based on the severity of the incident or issue. For example, a fatality ranks significantly higher than security or weather delays. Scott’s airline performance analysis can be applied to any performance analysis, including competitive analysis or product comparisons.
Like many experienced professionals with success using analytics to answer complex questions, Scott uses his Airline Performance Presentation to help others understand the power of using IDEA. From joining and normalizing data stored in disparate systems to using data visualization to gain quick insights, he proves data analytics can help us make better business decisions…and in this case, choose an airline with information backed by data rather than instinct. Read more by visiting the Key Performance Initiatives Blog.
This compilation of stories may vary by industry and objective, but they have one thing in common – each professional dared to ask the same question, “could we use data analytics for this?” Not surprisingly, the answer is most likely, “Yes we can!”
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