The Power of Microsoft Access to Handle Large Data Sets in Litigation

By Lorène Becker
June 15, 2020

As businesses grow and get more complex, so does the size of their data. Businesses often maintain their data on systems such as SAP, Oracle or their own proprietary software. This data is important in the discovery process but it is becoming more common for parties in litigation to produce electronic data sets containing hundreds of thousands, to even millions of rows. The large size of these data sets often leads to concerns that the data will be cumbersome, time-intensive and costly to work with, but it doesn’t have to be given the power of Microsoft Access. Specific requested data sets can be exported from these systems to Access, which provides a valuable tool to translate the data into useful and relevant information in response to complex questions.

Access, a database management system, allows for quick and efficient querying of data across a wide range of data types and sizes. Access provides tools to extract, identify, analyze, and summarize information such as counting, summing, and averaging the data by one or several attributes. Data sets can be joined given a common field or compared to identify records unique to each. Additionally, calculations requiring several steps can be automated by developing a set of nested queries within Access.

The use of Access is beneficial in any type of lawsuit that involves large data sets. Queries can be customized to the needs and facts of the specific case, and easily refined as the case evolves.  As discovery continues, updated data sets can be integrated quickly into the queries already created. In addition, Access has built-in features to export the results into Excel, allowing for the efficient preparation of final deliverables such as exhibits or demonstratives.

Let’s illustrate the power of Access. Say there is a dispute that requires the calculation of the amount owed by an oil and gas operator to several vendors on 100 properties or wells. To make things more complicated, there are alternate dates on which the amount owed needs to be determined, which vary by property and vendor. The electronic invoice and payment activity produced contains tens of thousands of rows. With the data available in Access, however, a set of queries is created to derive the amount owed by vendor and property as of any requested date. The calculations are performed efficiently through Access and allow, as an example, for the sensitivity testing of alternative dates which can assist legal teams in deciding which legal strategies to pursue. Additionally, with the queries already developed, expanding the calculations to incorporate additional data required in discovery, such as more properties or a longer time period, is quick.

Another example is a wage and hour lawsuit involving 500 claimants wherein workers were solely compensated by commissions on the sales they generated, irrespective of the number of hours worked. The commissions detail is produced, containing each sale and commission generated by each worker over a three-year period. Separately, the time collection records are produced, consisting of each log in and log out by each worker over the same three-year period. Each data set easily amounts from thousands to millions of rows, with the only common field between the two being the worker identification number. How long will it take to determine which worker was not paid at least minimum wage or overtime pay?

With the power of Access, a series of queries is developed to calculate the effective hourly rate paid by week to each worker based upon the compensation paid and hours worked derived from each data set. From there, the amount of damages for unpaid minimum wage and overtime pay is quantified. These calculations are used, for example, to assess a client’s potential exposure which can prove invaluable in assisting with settlement purposes. By using Access, having 50 or 500 claimants does not significantly increase the time and cost associated with performing these calculations.

In some cases, a challenging aspect of large data sets is understanding the data provided, generally requiring a data dictionary and sometimes interviews or depositions of relevant individuals. However, once the data is understood, Access allows for these large data sets to be handled in a dynamic, efficient and cost-effective manner, as shown by the above examples, providing great value to clients. Given the power of Access, the sheer size of data sets should no longer be a source of concern, and instead should be viewed as an asset.

For additional insight, please contact Lorene Becker, CPA, CFE (lbecker@cw-cpa.com) at Compton & Wendler.