Forecasting Using Quantitative and Qualitative Techniques

Introduction

Modern world companies face challenges in making crucial decisions that affect their future under unpredictable circumstances. This requires decision-makers to have an understanding in a business environment, including the competition and demand of their products to come up with achievable goals (Chambers, Johnston, & Slack., 2010). When a company is in this situation, it has to use forecasting.

Forecasting is primarily a practice of making statements about issues before results. Just like prediction, forecasting involves the use of formal statistics methods mainly fixed on time series that are both longitudinal and cross-sectional (Chambers et al., 2010).

Personal Experiences

My personal experiences through forecasting have been through the management of my salon. I prefer to use the qualitative method of forecasting in decision making. Briefly, let us look at the nature of the business. My hair salon is stylish, modern, and offers a variety of services including massage, haircuts, hair treatment, pedicure, manicure among others. Since my target customers work during the day the peak time is in the evenings, weekends, and festive season.

The business is very unpredictable hence qualitative forecasting allows me to use my experience to make decisions; like when to increase the number of staff and when to limit them, hence appreciating the wealth of experience in the business. Needless to say, I prefer decisions made spontaneously to avert a challenge. I have more trust in my judgment and advice from my friends than the figures generated by a computer.

In Qualitative forecasting, one can foresee fluctuations of sales and immediately make necessary changes unlike in quantitative forecasting, which limits itself to the use of past data for future predictions (Leger, n.d., para. 1). The qualitative forecasting method is flexible. It allows the management of my business to use data that are not in numeric form when making decisions.

Since quantitative forecasting heavily depends on the data collected in the past, in terms of sales trends, it fails to recognize or recommend new business catchment locations. It is not possible to use a quantitative forecasting technique for a new product in the market since there are no earlier data on sales (Mason, 2006).

Also, I found out that earlier data collected in the past is important only if a competitor comes in and has better and more affordable products and services. At times, there is no enough time for data collection to use in quantitative techniques. The qualitative technique enables me to compete efficiently and keep up with the changing business world. When there is a new style, such as making hair, or new and better products, I have to effect the change to keep my customers. Through this method, I see the fluctuations that are in the business.

Managers, from my experience, are more confident with a personal decision and not computer-generated figures. Therefore, it is also important to note that both quantitative and qualitative forecasting techniques help in making final decisions and not making the decision.

Conclusion

In this paper, I have extensively developed an insightful analysis of both quantitative and qualitative forecasting. The two forecasting methods are very beneficial especially in the modern business world which faces many challenges. The knowledge of both qualitative and quantitative forecasting is very important in my business.

References

Chambers, S., Johnston, R., & Slack, N., (2010). Operations management with MyOMLab. Italy: Prentice Hall.

Leger, S., (n.d.). The Advantages of Demand Forecasting. Web.

Mason, N., (2006). Forecasting Techniques Part 1: Quantitative Methods. Web.