Perks and Pitfalls of Training

June 1, 2017

Few can argue that we are in the midst of a data explosion. The digital universe will double every two years, a 50-fold growth from 2010 to 2020. We are drowning in data, but starved for information. Turning all that data into actionable insights requires the use of technology and proper training. You simply cannot have one without the other.

The IIA Standards state that, “…internal auditors must consider the use of technology-based audit and other data analysis techniques.” While the adoption of data analytics has grown over the past 25 years, the use of analytics remains at basic levels in most organizations. Deloitte’s 2016 Global Chief Audit Executive Survey stated that of the 86 percent of respondents who use analytics, only 24 percent use them at an intermediate level and 7 percent at an advanced level.

One of the top barriers to increased use of data analytics technology is the availability of skilled talent. The same survey shows internal audit leadership expects the use of data analytics to grow during the next few years. If auditors are required to use technology, growth is anticipated and the benefits are obvious, why aren’t more organizations providing staff with training?

Let’s be honest, professional training is one of the first items to get cut during a budget crunch. What management fails to realize is the impact this can have on the organization as a whole. During our 25 years of helping professionals adopt and use data analytics, we’ve seen the benefits of good training and the impact poor training can have on an organization. We’ve even seen how it can elevate an entire team of internal auditors, as it has with the University of Texas System.

A University That’s Getting it Right

About four years ago, The University of Texas System Administration Audit Department created a Data Analytics Program (Program) which would be responsible for providing services related to data analytics to the institutional audit departments upon request. Management placed an emphasis on providing universal testing tools, training, and a dedicated person to serve as an internal consultant.

The Chief Audit Executive appointed data analytics specialist Erin Baker to help streamline the data acquisition process across multiple entities and environments, and develop IDEAScripts to simplify and standardize analysis. Baker, who is a Certified IDEA Data Analyst (CIDA), led the initiative to incorporate the use of data analytics within the System of 14 internal audit departments. A group of staff attended an on-site training course led by authorized IDEA instructors, and Baker built her skills by attending additional IDEA training over the past few years to keep her skills sharp.

Baker applied what she learned in training and built user-friendly, menu-driven tools to help the internal auditors acquire data based on their specific environment, analyze data in key financial areas, extract and index outliers for further investigation and review the results. She developed a Financial Activity Tool to provide basic summaries of activities related to multiple financial processes, which is used for risk assessment development and change management for departmental audits. She also developed a Procard Tool and a Travel & Entertainment Tool, both of which are used across multiple institutions.

With expert training and management-backed resources, the function of the internal auditor evolved into one of a trusted advisor providing creative, valuable solutions. Even the auditees gained more meaningful insights from the data they received. With an effective data analytics program underway, the Program has shifted its focus towards providing training and consulting to the institutional audit departments. The UT System program is a powerful example of what is possible when management encourages the growth and development of its auditors in utilizing data analytics.

Struggle vs. Success

It has become a common practice within many industries to have staff learn data analysis on their own, with little if any support. Organizations that take this approach neglect to calculate the unnecessary hours spent on experimentation and repairing work compromised by human error – not to mention the inherent frustration one experiences when learning via trial-and-error.

Another training shortcut is pass-it-on training. Similar to the communication exercise where one person whispers something to the next, and by the end of the row, the phrase bears no resemblance to the original statement. Sending one person to training and asking them to pass their knowledge along to the next person, who in turn trains someone else, is a random walk. There is no consistency with this approach, and it often does more damage than good.

Tell me and I forget, teach me and I may remember, involve me and I learn. Benjamin Franklin was spot-on in describing how people retain information. Hands-on training is the most effective approach when helping staff learn something as complex as data analysis programs. Online training and professional resources can be effective tools for building technical skills, but they simply do not replace the experience of classroom instruction. We start with the basics of data acquisition and preparation, and then build on those skills to help attendees gain confidence in using the software. Investing in professional training for staff not only makes the organization “smarter” and more efficient; it increases staff retention, boosts moral and improves the quality of work.

Craving Training: Where to Start

Technology can make work easier, but it also requires willingness to spend some time learning. Finding the right training resource can make or break your experience. We advise our clients to start with some informational “Getting Started” webcasts to familiarize new users with what the software looks like. Most software tools offer tutorials, which are a great starting point for self study. How-to videos provide another opportunity to get acquainted with the software prior to attending training.

We also recommend new users have a project in mind, no matter how small, before attending training. This helps quickly reinforce the training. Start with the end in mind. If some preliminary work can be done to acquire data from the system prior to training, it helps to stay on track when they return to the office.

After some initial exploration of the software, we recommend entry-level hands-on instruction. Nothing beats being in a classroom with fellow professionals and digging into the software step by step. We begin where the analysis work begins – data acquisition and importing. One of the most common things we hear from those who tried first learning IDEA on their own is, “If I had known what you showed me in training, I could have saved hours on this project!” Hands-on learning reinforces the skills needed to apply data analysis in a way that saves time and effort – and that’s the end goal.

Depending on how quickly you absorb information, move along to intermediate courses or topic-specific seminars to build your proficiency. Take advantage of professional groups, conferences, webcasts, software user groups and other learning opportunities to keep the momentum going.

Some other things to keep in mind:

Start with ROI in mind – We advise clients to go after the “low-hanging fruit” where they can see a fast return, such as duplicate detection.
Be prepared to make mistakes – While we’re conditioned to avoid mistakes, it’s unrealistic. In fact, mistakes can often provide you with more than one way to reach the outcome you’re working to achieve.
There are no stupid questions – You won’t help yourself by holding back. Our 20-minute rule is designed to prevent frustration, even for the simplest of tasks. If you need help using IDEA, simply ask us for help!

GOOD NEWS!

With each new release, data analytics tools are getting easier to use. IDEA has a Windows-based user interface, so many new users find it familiar upon their first use. IDEA Version 10 includes a Discover task designed to automatically populate a visual dashboard to identify specific data types and perform analytics with just a few clicks to uncover trends, outliers and anomalies. Point-and-click analytics have (thankfully) arrived, but still require skills for data acquisition, analysis and automation of repeatable processes.

Knowledge comes from use and practice. Organizations are most successful when they support staff in their professional growth. The transformation to becoming a data-driven company can yield better insights, opportunities and success – it all begins with empowering people.

About the Author

Carolyn Newman

Carolyn Newman has spent the past 25 years helping thousands of organizations employ technology to gain maximum value from their data and improve business processes. She brings more than 25 years of experience in public accounting, auditing and consulting to her role as president of Audimation Services. She is an active member of the AICPA, IIA, ISACA and Texas Society of CPAs.

Visit audimation.com for more information.

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