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Forecasting optimal staffing levels for different times and areas of the casino

Introduction

It is a fact that the global gambling industry has grown progressively with the help of technological changes and one of the biggest transformations seen in the recent years include the application of ML and AI to determine the right staff strength for casinos. Just like any other business, casinos have to deal with the problem of how to provide enough staff to attend to the needs of their clients while at the same time controlling on the costs of employment. This has made it possible to use artificial intelligence and machine learning in determining the right staff requirement based on such factors as the number of customers, time of the day, season, and different sections of the casino. This is because AI when applied in this manner does not only improve on the overall management of the business but also the experience of the customers. This paper will focus on the various issues that affect the gambling industry in determining the right staff requirement, the existing AI solutions, the advantages that come with the implementation of such solutions and the ROI of such investments.

Challenges

The gambling industry especially the casinos has some challenges when it comes to the forecasting of appropriate staffing levels. A major challenge is the uncertainty in the number of customers that can be expected at any given time, which may change depending on several factors including time of the day or week, season or event. This creates a problem in the scheduling of the staff and this may lead to either having few staff to attend to the customers and hence provide poor service or having many staff members than what is necessarily required and hence high costs. Another problem is the variety of positions in a casino, every position needs certain abilities and differs in the level of contact with the customers. Also, the uncertainty of the gambling business which is affected by such factors as legal and regulatory frameworks, competition, and macroeconomic environment, is the further challenge to the staffing requirements prediction.

AI Solutions

With the current challenges, AI and ML solutions have been identified to be solution-oriented. Traditional Machine Learning models are trained with historical data to make forecasts and allocate staff appropriately. For example, in casinos, AI can help in understanding the customer behaviour and pattern to schedule the staff accordingly for peak hours. There are also other advanced algorithms that are used to optimize the staffing of different departments in a casino with an aim of maximizing on profitability. Besides, AI can also be employed in a casino to forecast changes in the environment, for instance, the effects of new laws or economic conditions, thus enabling the casino to make changes in staffing requirements before they occur. Some of the casinos that have already adopted the use of artificial intelligence include Marina Bay Sands in Singapore and the Venetian in Las Vegas.

Benefits

There are a lot of advantages of the application of AI and ML in the forecasting of the optimum staff requirements in casinos. The most important one being the enhancement in the efficiency of the operations which results in reduced costs through effective staff scheduling. It also results in increased efficiency in the customer service department as the casinos are able to meet their staff requirements in the right manner at the right time. Furthermore, the use of AI enables better decision-making and therefore casinos are able to manage their resources in a better way. For instance, through understanding the areas of the casino that generate most of the revenue at certain time intervals, management can easily decide on where to invest more of their staffing resources.

Return on Investment

It is possible to realize a high ROI when AI and ML are adopted in the determination of the right staffing requirements. AI technology does not come cheap initially and this can be a barrier to entry, however, the cost of sub optimal staffing can be much higher in the long run. For example, a study by McKinsey & Company revealed that organizations that have adopted AI in workforce planning have been able to cut down on labor expenses by 20%. In addition, enhanced customer service increases customer satisfaction and loyalty as well as frequent spending hence improving the return on investment. Also, casinos can avert fines and bad press by ensuring that they have enough staff to meet set rules.

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