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Data Analytics Can Be Big for Small and Medium-Sized Business

Paul PocalykoBy Paul W. Pocalyko, CPA, CFF, CFE | Hill International Inc.

MoneyLife100Every time I discuss the use of data analytics with a business owner I get a similar response: “We don’t have time to analyze those details.” The vast amount of analytical work performed in today’s business environments is through the use of rudimentary spreadsheets that typically focus on some level of retrospective review of budget to actual performance. In addition, many researchers, as reported in this study, have concluded that user-prepared spreadsheets have a significant likelihood of errors.

In this blog I look at three common concerns registered by business owners and see if some simple data analysis of the accounting and business information can provide some insight into managing these areas.

Cash Flow – Every business requires oversight of the cash situation. Cash inflow needs to exceed cash outflow – a fairly basic concept. The accounting and related business data can aid in improving cash flow. For example, a comparison of customer payment history through a customer payment report, readily available in most accounting software, can quickly identify the slow-paying entities. It is important to know who those slow-paying customers are and balance the sales relationship with the credit being extended. An owner needs to know the likely timeframe that payment will be received, but far too often business owners fail to manage the sales cycle for customers who have historical slow payment patterns.

Accounts payable data can also serve to aide in the evaluation of cash outflows. Some simple questions can be answered with the data:

  • Have you analyzed total payments to each vendor or supplier and sought to maximize potential discounts from your largest providers?
  • Have you verified that the payment cycles are being maximized and that due dates on invoices correspond to the payment dates being utilized?

Vendor history reports can be a useful data point to make these determinations.

Sales Volume – There is no magic bullet to increase sales, but there are data points available in the accounting information to provide insight to the business owner. Inherently, most business owners know who the large customers are and what products have the best margins. That is often the focus of the marketing strategy. What they do not always understand is at what frequency those high margin items sell and what other smaller customers are buying high-margin products. Sales history data is readily available to identify those trends. In addition, that data can be used to evaluate the low-margin products and low-volume customers to in part effectuate a better marketing strategy.

Every business is different and every product mix carries unique elements. The ability to identify those traits and the impact on sales volumes can often be discovered through simple comparisons of the sales history data.

Employees – Being able to attract, train, and retain qualified employees is a challenge for any business owner. How can data analytics possibly aid in that process? There is a large volume of information related to performing predictive analysis on employee retention and turnover. While those efforts do provide meaningful outcomes they require a great deal of work and planning.

More simply, quick employee surveys can be performed to gain data on issues that your particular business may be facing. Example include questions on floating holidays versus designated holidays, timeliness of reviews by team leaders, adequacy of training, and the quality of the work environment. Simple surveys can provide important data to run the company.

For example, long ago I had a discussion with a human resource (HR) leader in a firm regarding employee retention and success. The discussion turned to career advancement and leadership roles within the company. The CEO asked the HR director to determine what made certain people succeed while other with similar credentials and skills often failed to advance. The CEO wanted the answer quickly.

The HR leader knew the core leadership team of about 20 people and had access to certain data. A quick survey was circulated to gather additional data points that included a few simple questions:

  1. What types of projects have been the most helpful in your career advancement?
  2. What people in the organization have aided in your career advancement?
  3. Prior to joining the organization what best prepared you for the job?

To question one, most cited working on large projects in team environments; to question two, almost to a person, they identified others within the 20 person management team; and to question three, many cited education from highly regarded credentialed university programs. The HR director had used a simple data analytic tool to confirm that success was linked to the following:

  1. Working successfully on project teams
  2. The ability to collaborate effectively with others in the organization
  3. Education from university’s that prioritized preparing students for the industry

Summing It Up – These three areas are only a few examples of how a small to medium-sized business can make improvements by looking at data that are already in their systems. Many other simple data analytic tests and comparisons can be performed in other areas to help a business grow and prosper. None of these tests take great investments in time. They can, however, yield large financial gains and operational improvements.

Paul W. Pocalyko, CPA, CFF, CFE, is senior vice president, construction claims and consulting services, at Hill International Inc. in Philadelphia. He can be reached at PaulPocalyko@hillintl.com.

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