Predicting Reasonable Notice Using Machine Learning

If an employer intends to terminate an employee without cause, the employer is generally obligated to provide the employee with a reasonable amount of notice. What constitutes a “reasonable” amount of notice is one of the most commonly disputed employment issues, and with good reason: not only is it a nuanced legal matter, but it also has direct ramifications for the bottom line of both the employee and the company.The amount of reasonable notice required by the common law depends on a variety of factors, often called the Bardal factors, such as the age of the employee, the length of service, the character of employment, and the availability of similar employment. Some organizations simplify further by offering one month of reasonable notice per year of service.While the guiding Bardal factors are well-established and rules of thumb frequently used, reasonable notice cases are multi-faceted and do not easily lend themselves to simple tallying up of factors or static calculations. A static approach is unable to adequately account for varying circumstances in a given situation and cases that appear to have similar facts can yield divergent outcomes.Employment Foresight is the first software to utilize the power of machine learning to predict reasonable notice awards. Employment Foresight draws upon thousands of previously decided cases to accurately predict reasonable notice awards within 8% of the actual notice period awarded by the court.

How is Employment Foresight Different?

Employment Foresight is the first of its kind to leverage machine learning to capture more than 20 factors in a highly nuanced, dynamic manner. In contrast, the predictive value of existing tools is limited by the small number of factors they consider (usually only 3 or 4) and the reliance on simple averages.Our research lawyers have mapped each case according to all of the factors that have been demonstrated to be the most relevant in court decisions on reasonable notice. We translate the unstructured data of actual court rulings into structured data points, allowing us to quantify pieces of information that capture all of the Bardal factors. Machine learning finds hidden patterns in the data, and the algorithm reflects the way judges have weighed the various factors in actual cases.Employment Foresight is incredibly accurate at predicting reasonable notice. Consider the following 10 recent case examples. To be clear, these are cases that Employment Foresight had never seen before. Our program had not been trained on these cases. For comparison, we also ran these cases through three other reasonable notice tools that are available online or for purchase.

Employment Foresight correctly predicted 9 of these 10 recent cases, and got within 2 weeks of the 10th case. For each prediction, we give a range of just 1 or 1.5 months. Other available tools provide ranges that are either excessively wide or incorrect.

Let’s look at two of these recent cases in a little more depth:

Case Study 1: Liebreich v. Farmers of North America, 2019 BCSC 1074

Shannon Liebreich, aged 49, worked as a dependent contractor for a group of entities called the Farmers of North America for 14 years before being terminated without cause. She held various management positions and was the acting Chief Operating Officer for one of the related entities in the group.

The Court reviewed notice periods awarded to other dependent contractors in senior positions and adjusted the award based on the fact that Ms. Liebreich is younger than the other cases provided and the fact that she did not continuously hold the senior management positions throughout her tenure of employment.

How much notice would a court award? If you examine precedents in British Columbia, for dependent contractors between the ages of 40 to 50, the average award would be 9 months. Other online calculators do not distinguish between dependent contractors and employees and predicted a much higher notice award ranging up to 18 months.

Employment Foresight predicted a notice period of 15-16.5 months. Our analysis took into account all Bardal factors as well as the fact that Ms. Liebreich was a dependent contractor, the fact that she was working in a specialized field (agriculture) with limited opportunities available and the fact that she was terminated solely because the employer was in financial difficulty. The Court awarded a notice period of 15 months. Neither using simple averages nor other online calculators could uncover the patterns in the data that allowed Employment Foresight to arrive at an accurate prediction.

Case Study 2: Dalskog v. Crowsnest Pass Ecomuseum Trust Society, 2019 ABPC 36

Meghan Dalskog, worked as the Executive Director for a museum. She worked for 6 months before she was terminated and was still a probationary employee at the time of termination. She had relocated for this position from Vancouver Island to Crowsnest Pass, BC. The Court determined that she was relatively young but also worked in a specialized field and had specialized skills from her previous experience as a museum manager and curator.

How much notice would a court award? If you take a rule of thumb approach of 1 month for every year worked, one would expect that Ms. Dalskog would be entitled to less than 1 month of notice. Other online tools give ranges that are excessively wide (the tools we examined returned likely ranges of up to 9 months) or provide narrower answers that are simply inaccurate.

Employment Foresight predicted a notice period of 2-3 months. Our analysis took into account all Bardal factors as well as the fact that the employee had relocated for this position and that she was working in a specialized field with limited employment opportunities available. The court awarded 9 weeks (2.2 months). Neither the rule of thumb nor using simple averages will uncover the patterns in the data that allowed Employment Foresight to arrive at an accurate prediction.

Key Takeaways

Employment Foresight’s accuracy is achieved by using machine learning to assess 22 factors that have been carefully selected for their legal significance. Employment Foresight leverages the power of machine learning to provide accurate predictions driven by comprehensive data.

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