MDF is essentially the process of estimating the future quantity and quality of people required. This process is typically preceded by deciding on the number of hours that are available. Once that is done; determining the quality and quantity is usually a logical step. As easy as it may sound, demand forecasting is a vital and a very complicated part for many organizations out there. It is also required that one must consider several factors - both internal and external while making such forecasts or predictions. To elaborate on the above, Demand Forecasting helps in determining the number and type of personnel/ human resources that might be required in the future. The purpose of supply forecasting is to determine the size and quality of present and potential human resources available from within and outside the organization to meet the future demand of human resources.
Acquiring and Placing the best talent and highly qualified candidates in the right designation is already a very complex and difficult task, especially when such requirement occurs in the middle of a skilled labour shortage!
In todays world of frequent changes occuring all acorss the globe, it has become very difficult for an entity to fill up labour requirement gaps. This concern about workforce skills shortage is something that is creating a ruccus for a majority of the companies out there and these entities are not able to fill positions which in turn is damaging implications for both - short and long term outlook of the business.
However, there have been a few globally accepted ways by which one can address this issue. They can be listed as:
- Train Existing Employees
- Adaptability - apply workforce skills in a different way
- Re-evaluate recruiting practices
- Partnering with nearby educational facilities
- Use of contingent workers
Now, since we have a better and deeper understanding of the problem at hand, we are going to shift our focus towards a much more grave concern - which is about forecasting these talent shortages beforehand and being ready to cater to them the moment they occur.
In order to fill up this predicament, we are going to implement the use of data analytics - essentially a model that will best fit the purpose of MDF. This project is going to display the embodiment of the process of automating manpower needs depending upon upcoming circumstances or time, to be specific.
The end result will be something like a dashboard/ interface that will help organizations predict or forecast Manpower Demand from time to time which in turn will increase productivity as well as lead to optimum utilization of resources as well as maximized performance.
Another area of concern, at this point in time, is to come up with a predictive and accurate model that will help organizations identify time periods of uncertainty and shortage in their labour force so they will have ample amount of time to prepare themselves for it.
The long production lags to product skilled professionals is the core and mandate of manpower forecasts. Proper Manpower Forecasts well in advance facilitates planning education and training. It can be classified as an effort to ensure that the required manpower, both in terms of quality and quantities are available at the time when they’re needed the most, or more ideally, demanded. Shortcomings in the labour market is another major reason for manpower forecast. The manpower market is often characterized by long lags in the supply side and short lags in the demand side. Therefore, supply is to be planned in order to meet the demand. If this is not doctored in the right way, problems such as occupation-education correspondence may occur and this may lead to mounting educated unemployed or inadequately trained people taking up different jobs, for which they’re probably not competent enough. Manpower Forecasts are looked upon as a medium to ignite correction of labour market distortions.
No matter how accurate or perfect a model is, one should be prepared for unforeseen circumstances like –
• Economic Development
• Social, Political & Legal Challenge
• Technical Changes over time
As mentioned earlier, this project aims at developing a dashboard/ interface that will help entities plan future shortcoming related to MDF. The way we intend to go ahead with this project can be broken down into the following steps –
• Collecting/ Gathering datasets related to Industries, Labour Markets, Jobs and Students Immigrating to the country
• Cleaning & Pre-Processing
• Running various checks for model compatibility
• Checking for accuracies & autotuning/ error checks for better forecasted results
• Integrating forecasted visuals on a single dashboard for better understanding and decision making