Leveraging Data Entry Services for Wage & Hour Case Discovery
So much has changed for the global labor force over the past 2 years. With the pandemic creating a new standard of work-from-home positions, the vast majority of the workforce will continue to show up at the office day to earn their paycheck. Drill down a little further and you’ll find that most of those workers are hourly employees responsible for clocking in and out each day to record time worked as well as meal and break periods. Many employers have transitioned to digital timekeeping methods, but a third of all time tracking systems are outdated. That brings us to the humble timecard – 38% of employers in the US still rely on paper timesheets and timecards to record employee hours. In a recent survey, 80% of respondents reported that 75-80% of the timesheets that they receive need to be corrected in some form.
Decreasing the Risk of Time Theft
Whether from the employee or employer’s perspective – the danger is apparent. Anything from a clerical error or a misinterpretation to outright time theft can occur. Wage and hour disputes are some of the most common when talking about labor and employment law. The US Department of Labor approaches it as a key topic with an entire section of their website devoted to outlining rights and responsibilities of all parties. Nonetheless, in any given year the top 10 wage and hour class action matters may be valued at $500 million and in those suits as well as smaller matters, vast amounts of punch and pay data must be scoured to determine fault. Whether digital or paper records were kept often matters little in these situations as they all must be converted and consolidated for review by analytics experts and attorneys alike. So, how do we get there?
Very often, the answer is through painstaking data entry efforts which remain the only effective way to reconstruct daily reporting that is often handwritten or borderline illegible due to poor image quality. The technology just isn’t there yet to extract the information at a high enough level of accuracy to make the case. Data entry is laborious and time-consuming work but nonetheless essential in cases like this. Imagine a wage and hour dispute involving just 10 employees over a 4-year span. At 26 biweekly timecards or payroll reports, that’s roughly 13,000 lines of data consisting of multiple data points to review and record individually. Who’s got the time to invest in that?
A reliable “go to” partner or data entry services can play a pivotal role here as part of a robust litigation support apparatus. Manual review is required to at least render the data usable for higher level interpretation, but utilizing in house resources is cost prohibitive and quite frankly a waste of valuable time. Outsourcing data entry to seasoned professionals that specialize in these tasks is the way to go. By tapping a data entry services company, you’re able to get the job done quickly, accurately and on the cheap making minimal investment in time and money to get the information you need fast.
In a very recent case study, 247Digitize sifted through 1.5 million images to identify 16 different iterations of employee time sheets and record 3.1 million data points. The goal was to find out whether employees had been properly advised of the company break policy and whether they had availed themselves of those periods. Overall, the project took just 4 weeks to complete – a fraction of the time and of course the cost to perform the same data entry work internally.
When we think of Labor Day – when we’re not thinking about one last summer fling – we often think of tradesmen and tradeswomen. They are dedicated people that specialize in one particular skill and the ones we put our trust in to get the job done right. Data entry itself is a trade and one we’ve been proud to offer our esteemed clients in the labor and employment sector for over 15 years. The next time your firm or client finds themselves in litigation or discovery matter requiring data entry, think 247Digitize and contact us today for a quote.
