What is Forecasting, and What Is It Used For?
Competition and continuous evolution are just two of the characteristics that describe the dynamism of today’s market.
For this reason, today more than ever one of the main objectives of companies is to monitor and predict those factors that mainly influence the profitability and productive efficiency of the company.
It is undeniable that analyzing large amounts of data and identifying significant trends and patterns in order to estimate what will be based on what has already been is a rather arduous task, as well as potentially expensive in terms of time-consuming. For this reason, traditional methodologies have today been replaced or accompanied by more modern approaches that see the use of cutting-edge technologies such as Machine Learning.
Demand forecasting
Among the relevant factors for an effective business strategy, there is undoubtedly demand forecasting, which is the process of forecasting the demand for a product or service in a future and specific period of time. This analysis allows to optimize production, reduce waste, maximize profits and customer satisfaction, avoiding decisive events such as lack or excess of stock.
Cost forecasting
Another important and equally crucial factor is cost forecasting, which helps to estimate future costs supporting budget-related decisions.
Both see as a key point the (sales, volumes and past expenses), as well as the consideration of market trends, economic indicators or demographic indices.
Machine Learning Forecasting
One of the most innovative methods today for carrying out these analyzes makes use of Machine Learning techniques such as time series analysis or regression, using more advanced platforms or hard-coding approaches. All this sees the use of algorithms capable of generating predictions based on large amounts of historical data such as those mentioned above. An advantage not to be underestimated is that the areas of use can be multiple, with a wide differentiation between the sectors that see the adoption of this type of investigation particularly advantageous.
Forecasting Use Cases
Fashion Industry
A fashion company wants to obtain a quantitative estimate of expected sales for a specific type of clothing during the winter period.
Predictive models can make use of potentially significant data for the required objective, not only as historical data on sales of the specific type of clothing, but also data on marketing campaigns (advertising investments or activities aimed at increasing sales), economic data (inflation, fluctuations in the exchange market or other elements that could affect the purchasing power of consumers) or data related to fashion trends (frequency of searches related to the product of interest on the web, reactions on social networks related to similar products, etc …).
As highlighted in our article, Business Intelligence can be a valid tool to analyze the seasons of the fashion world and obtain crucial information for sales forecasting. Through the analysis of historical and market data, it is possible to identify trends, patterns and correlations that allow to predict future demand and optimize sales strategies.
Insurance Industry
An insurance company wants to predict the costs associated with possible risk scenarios to prepare for unexpected events such as natural disasters or fraud.
Examples of useful information for the purpose can be historical data related to such events (number of claims related to natural disasters and fraud, average amount of compensation and annual frequency for each of them, etc …), as well as weather data.
Pharmaceutical Industry
A pharmaceutical company is interested in forecasting the demand for a specific drug, targeted at a particular target, over the next year.
In this case, valid input data could be historical sales data, demographic data (quantitative data on the type of population that most frequently uses the drug), clinical data, regulatory data, etc.
Supply Chain Sector
A group of food stores needs an estimate of the demand for a specific food produced by them, together with a forecast of the distribution costs associated with it, in the next six months.
Here too, thanks to the use of data on sales of the product in particular, as well as data related to trends or promotions associated with it, it is possible to generate a forecast on the demand referred to the required time frame. For transport costs, information relating to the distances to be covered and the times to be respected could be helpful, as well as fuel and courier rates.
These and many other applications are examples of how this type of analysis can be a winning weapon for countless business processes.
Blue BI for Forecasting
Blue BI has created a solution for Forecasting that, thanks to a hybrid, statistical and ML approach, generates reliable forecasts based on the data that differentiate the evolution of companies in the market, overcoming the risk of the “gut feeling”.
BBI x Forecasting helps companies to overcome the obstacle of traditional forecasts, often made on the basis of intuition, in favor of analytical processes that exploit automation, AI and ML.
Write to us for more information!
We realize Business Intelligence & Advanced Analytics solutions to transform simple data into information of freat strategic value.
