By Christopher T. Kosty, CPA, CIDA

The COVID-19 pandemic changed how we work. Can you, with confidence, say your business processes currently are optimized for the new workplace environment, or are you still patch-working through the stay-at-home orders? Remote work is here to stay, but so too are other technologies such as data analytics, automation, and business intelligence. These strategies will be more critical as we move forward, and it’s well past time to embrace technology beyond just “getting by.”

Data Analytics

Data analytics is the process of accessing, cleansing, transforming, and modeling data with the goal of answering business questions, identifying trends and abnormalities, and, ultimately, driving data-driven decision making. It may sound complex, but really most companies already use data analytics every day. Although it is certainly not the most efficient or effective method, if you export data from a system, reformat it in Excel, added formulas or calculations, and email that report to somebody, then you have performed a simple data analysis project.

Business Process Automation

Business process automation is a technology-enabled streamlining of a business process for simplicity to achieve digital transformation, increase service quality, improve service delivery, or contain costs. Business process automation comes in a variety of formats, including macros, scripts, or bots (robotic process automation). Bots efficiently deliver repetitive, deterministic, high-volume tasks quicker and more consistently. They are integrated within an existing IT infrastructure, work 24/7, and operate at a faster pace than traditional methods. Bots thrive at performing high-volume, repetitive tasks, and are a cost-efficient way to become more efficient while increasing employee satisfaction and capacity to perform more valuable tasks.

Business Intelligence

Business intelligence combines much of what is described above with elements of data mining, data warehousing, and data visualization. Business intelligence is used to answer business questions using data in an efficient and effective manner that is easy to interpret and communicate. There are many different business intelligence platforms in the marketplace, but all aim to streamline the reporting and decision-making processes while relying on data to do so.

A driving force behind the above concepts is the impact of data integrity and how it directly impacts the validity of any analysis or process being performed. Having confidence in the data is a requirement for any data-driven culture to be successful. Trusted inputs lead to trusted results. If there are more exceptions present in your process than there are rules, automation will be difficult to implement. If data doesn’t exist, is incomplete, or is of low quality, then data integrity will be negatively impacted and the quality of the corresponding analysis will suffer. The entire life cycle of a well-thought-out and organized data analysis environment will use a combination of technology and rules-based logic to create checks and balances throughout the process to ensure strong data integrity and produce results that can be relied on with confidence.

The impact on capacity and day-to-day operations is where these technologies provide the most value. To highlight how, let’s look at the Excel reporting example I cited earlier as a baseline. The time spent to perform that process as laid out will vary depending on the size, complexity, and frequency of the report’s specific needs. Additionally, there will be correspondence on the backend (or along the way) to discuss the results of this analysis and answer questions about potential abnormalities or trends. Conservatively, if we assume this process takes four hours and is performed weekly, that comes to 208 hours in a year, or about 10% of a single employee’s time (assuming a 2,080-hour-a-year salaried employee).

By using a combination of data analytics, business process automation, and business intelligence, the entire process could be performed automatically: you would show up to work on Monday morning with the completed report (including abnormalities, trends, and other exceptions identified for you) fully distributed and waiting in your inbox.

Efficiency is the eye-popping benefit, but effectiveness (i.e., accuracy) of those results is equally as important. The potential for human error is constrained to the development and configuration of these tools; whereas performing these processes manually creates additional potential for human error at every touchpoint along the way. Further, the effectiveness of these processes creates one source of the truth, meaning that a single report containing the source data and analysis has been automatically generated and distributed. There aren’t multiple versions creating ambiguity and raising the question, “Is everybody looking at the same thing?” A few examples of where this is a pain point for organizations include cross-departmental reporting, multiple locations, and, more recently, employees working in different environments.

These concepts are arguably more important now than ever before. A data-driven culture will ease the challenges of optimizing existing business processes. With the technologies outlined here and a targeted data strategy, organizations can make data-driven business decisions with confidence and clarity in a remote environment, if we’re all back in the office, or in a likely hybrid work environment.

Christopher T. Kosty, CPA, CIDA, is manager – automation and data analytics process team with Schneider Downs & Co. Inc. in Pittsburgh. He can be reached at ckosty@schneiderdowns.com.

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