How To Use Data for Business Predictions
Business forecasting is a process that involves using data to make predictions about what will happen in the future of a business. It is used to help decision-makers make decisions based on what has happened in the past.
What Is Business Forecasting?
Business forecasting is a method, usually utilizing technology such as the wafer scale chip, to estimate or predict what will happen in the future based on current and historical data. The data used for forecasting can be data about the past, such as sales data from prior years, expert opinions or known variables.
Why Do Businesses Make Predictions?
Business predictions can be useful for deciding which actions to take. For example, sales predictions help businesses decide how much inventory to order and how many employees to schedule and help with budget planning. Predicting which times of the year may be the busiest can help businesses determine when to hire more employees. Forecasts about expected profits help businesses decide which investments to make, whether to launch new products and help investors decide which companies are likely to increase in value.
What Are the Different Forecasting Methods?
The two main forecasting methods are quantitative and qualitative. Quantitative methods rely primarily on historical data and facts. These methods analyze past trends to predict future trends. To use quantitative methods the period you are forecasting for should match the number of years of historical data. For example, if you have two years of historical data, then your forecasts should go no further into the future than two years.
Three main methods fall under the category of quantitative methods. The first is the naive approach. This method assumes that there will be no change from the current period to the next. This method is often used to create a baseline model.
The moving average approach is used when there are six to nine months of data. To use this approach, a business creates a window of equal-sized periods and then computes the average of the values within the window. For example, if you were analyzing sales data for three months and you sold $100 in month one, $150 in month two and $125 in month three, you would add the three months together to get $375 and then divide that by three to get a prediction of $125 for month four and then for month five you would add $150, $125 and $125 to get $400 and a prediction of $133 for month five.
Exponential smoothing uses a weighted moving average and takes seasonality into account. This method is most useful when there are many years of data to analyze.
What Are the Qualitative Methods?
Qualitative methods rely on opinions and consulting. A business analyst using the executive opinions method asks major stakeholders, such as the CEO and department heads, what they think will happen in the future. This helps with strategic planning and risk identification and mitigation.
The salesforce composite and market survey method relies on estimates from the sales staff. This helps businesses make better predictions about inventory management. It also solicits feedback from consumers through market surveys that help companies assess the popularity of products and identify customer pain points. This helps with determining whether products need upgrades or modifications.
For the Delphi method, a panel of experts provides feedback through interviews and surveys about what they think will happen. This feedback is used in conjunction with other forecasting methods to improve predictions.
What Is the Time Horizon?
The time horizon refers to the interval of time predictions are being made for. Predictions are either short-range, medium-range or long-range. Short-range predictions cover a few weeks and are useful for assessing frequent changes. Medium-range covers a quarter to a year and is useful for sales planning and budgeting. Long-range is anything over a year and is used for strategic transformations.
Business predictions are a valuable tool for decision-makers and investors. By analyzing what happened in the past, businesses can make better decisions about the future.
