It’s time to look inside your crystal ball and start forecasting.
Forecasting gives you the tools you need to make reliable predictions about foreseeable events.
What is business forecasting?
Business forecasting is the process of analyzing data to predict future company needs and make insight-driven development decisions.
There’s really no downside to being prepared! Building a strong forecast prepares businesses for potential issues and identifies areas for profitable growth. Even if your predictions end up being inaccurate, you’ll have all the necessary data and information to get closer to the final forecast.
Some companies utilizepredictive analytics softwareto collect and analyze the data necessary to make an accurate business forecast. Predictive analytics solutions give you the tools to store data, organize information into comprehensive datasets, develop predictive models to forecast business opportunities, adapt datasets to data changes, and allow import/export from other data channels.
Types of business forecasts
Businesses can create various types of forecasts with business forecasting strategies. Because historical data and market trends affect so many aspects of business, comprehensive predictions can help prepare almost every element of your company.
General business forecasting predicts overall market trends and external factors that affect your business’ success.
Budget forecasting makes predictions for allocating the budget needed for future projects or addressing potential issues.Budgeting and forecasting softwareis an indispensable tool if you’re looking to forecast for budgeting your business activities.
Financial forecasting projects a company’s monetary value as a whole. You can use the current assets and liabilities from your balance sheet to help you make a prediction.
Demand forecasting predicts the future needs of your target customer base.
Supply forecasting works with demand forecasting to allocate the necessary resources for fulfilling upcoming customer demands.
Sales forecasting predicts the expected success of the company offerings and how it’ll affect future sales and cash flow.
Capital forecasting makes predictions about a company’s future assets and liabilities.
Business forecasting methods
There are two main types of business forecasting methods: quantitative and qualitative. While both have unique approaches, they’re similar in their goals and the information used to make predictions – company data and market knowledge.
The quantitative forecasting method relies on historical data to predict future needs and trends. The data can be from your own company, market activity, or both. It focuses on cold, hard numbers that can show clear courses of change and action. This method is beneficial for companies that have an extensive amount of data at their disposal.
There are four quantitative forecasting methods:
Trend series method:Also referred to as time series analysis, this is the most common forecasting method. Trend series collects as much historical data as possible to identify common shifts over time. This method is useful if your company has a lot of past data that already shows reliable trends.
The average approach:This method is also based on repetitive trends. The average approach assumes that the average of past metrics will predict future events. Companies most commonly use the average approach for inventory forecasting.
Indicator approach:This approach follows different sets of indicator data that help predict potential influences on the general economic conditions, specific target markets, and supply chain. Some examples of indicators include changes in Gross Domestic Product (GDP), unemployment rate, and Consumer Price Index (CPI). By monitoring the applicable indicators, companies can easily predict how these changes may affect their own business needs and profitability by observing how they interact with each other. This approach would be the most effective for companies whose sales are heavily affected by specific economic factors.
Econometric modeling:This method takes a mathematical approach using regression analysis to measure the consistency in company data over time. Regression analysis uses statistical equations to predict how variables of interest interact and affect a company. The data used in this analysis can be internal datasets or external factors that can affect a business, such as market trends, weather, GDP growth, political changes, and more. Econometric modeling observes the consistency in those datasets and factors to identify the potential for repeat scenarios in the future.
For example, a company that sells hurricane impact windows may use econometric modeling to measure how hurricane season has affected their sales in the past and create forecasts for future hurricane seasons.
The qualitative forecasting method relies on the input of those who influence your company’s success. This includes your target customer base and even your leadership team. This method is beneficial for companies that don’t have enough complex data to conduct a quantitative forecast.
There are two approaches to qualitative forecasting:
Market research:The process of collecting data points through direct correspondence with the market community. This includes conducting surveys, polls, and focus groups to gather real-time feedback and opinions from the target market. Market research looks at competitors to see how they adjust to market fluctuations and adapt to changing supply and demand. Companies commonly utilize market research to forecast expected sales for new product launches.
Delphi method:This method collects forecasting data from company professionals. The company’s foreseeable needs are presented to a panel of experts, who then work together to forecast the expectations and business decisions that can be made with the derived insights. This method is used to create long-term business predictions and can also be applied to sales forecasts.
Benefits of business forecasting
There are several benefits to making effective forecasts for your business. You gain valuable insights into its different aspects and the future of its success.
Foresee upcoming changes with a heads up on potential market changes that can affect your business. With the right prediction, you can strategize the decisions to succeed in the face of the challenges ahead before they become costly surprises.
Decrease the cost of unexpected demand by preparing ahead of time. Business forecasting is a great starting point fordemand planning. If you plan to incorporate demand forecasting into your business processes, you’ll be prepared for upcoming market demands and avoid the extra costs associated with an influx of demand that you weren’t ready for.
Increase customer satisfaction by giving them what they want, when they want it. Demand planning doesn’t just benefit you. With the right business forecast, your company can offer products or services to the target industry and meet their expectations. A company ready to serve its market is always met with customer satisfaction and loyalty.
Set long- and short-term goals by tracking your progress. Business forecasting tools help you outline your future company objectives. Continuous predictions allow you to track the progress of your proposed goals as those future expectations become the present reality.
Learn from the past by analyzing it. Forecasting enables you to collect and study extensive historical company data. Keeping a close eye on this data can help you identify where things may have gone wrong in the past. With this new information, your company can make the necessary adjustments to avoid similar mistakes in the future.
Business forecasting challenges
While the benefits of business forecasting highlight all of the amazing advantages it has to offer, it’s not a surefire way to prepare for the future. Companies who plan to forecast should also keep the challenges in mind and make sure that forecasting has more pros than cons for their business. Below are some of the notable challenges of business forecasting.
You can’t always expect the unexpected. While old data can help you gain insights into company processes and learn from mistakes, history doesn’t always repeat itself. Business forecasting isn’t a perfect process, and although helpful, it may not precisely predict future trends or business matters using old company data alone. It operates on the assumption that what happened will most likely happen again. Unfortunately, this is not always the case, and the hard work put into preparing for a forecasted event may never come to fruition.
It takes time to create an accurate forecast. Forecasting can be a lengthy process when started from scratch. Some companies find it challenging to gather the resources needed to begin predicting and allocate the time to do it correctly.
Historical data will always be outdated. There’s no way to know what’ll happen next. Although historical information is very valuable, it’s forever considered “old”. Forecasts are never based on the present and, therefore, are only as accurate as the data you already collected.
Business forecasting vs. scenario planning
Business forecasting is often confused with scenario planning because of their shared goal of preparing for the future. Both rely on learning from past mistakes and reflecting on what decisions must be made to drive success. However, business forecasting and scenario planning differ in the preparation process.
Business forecasting focuses on a problem at hand and uses historical data to predict what might happen next. It emphasizespredictive analyticsand the need to eliminate existing uncertainties. The problem can be as broad as the actual performance of the entire company, or as specific as how a single product might sell in the future based on past market trends.
While built on tangible data, forecasting is essentially a guess of the future and you need to make assumptions ahead of time to prepare for any predicted issues. Forecasting is an all-hands-on-deck approach that involves many departments, including analysts, economists, managers, and more.
Scenario planningcreates multiple scenarios to help prepare for the future. With these scenarios in mind, a company can begin planning a course of action to achieve the desired outcome. This includes creating step-by-step strategies and timelines for achieving objectives.
While business forecasting focuses on past information, scenario planning takes the past, present, and future into consideration with learnings from the past, understanding the capabilities of the present, and aspiring for future success. Although a team’s input is important in scenario planning, company’s primary decision-makers carry out the bulk of the process.
Business forecasting process
The way a company forecasts is always unique to its needs and resources, but the primary forecasting process can be summed up in five steps. These steps outline how business forecasting starts with a problem and ends with not only a solution but valuable learnings.
1. Choose an issue to address
The first step in predicting the future is choosing the problem you’re trying to solve or the question you’re trying to answer. This can be as simple as determining whether your audience will be interested in a new product your company is developing. Because this step doesn’t yet involve any data, it relies on internal considerations and decisions to define the problem at hand.
2. Create a data plan
The next step in forecasting is to collect as much data as possible and decide how to use it. This may require digging up some extensive historical company data and examining the past and present market trends. Suppose your company is trying to launch a new product. In this case, the gathered data can be a culmination of the performance of your previous product and the current performance of similar competing products in the target market.
3. Pick a forecasting technique
After collecting the necessary data, it’s time to choose a business forecasting technique that works with the available resources and the type of prediction. All the forecasting models are effective and get you on the right track, but one may be more favorable than others in creating a unique, comprehensive forecast.
For example, if you have extensive data on hand, quantitative forecasting is ideal for interpretation. Qualitative forecasting is best if you have less hard data available and are willing to invest in extensive market research.
4. Analyze the data
Once the ball starts rolling, you can begin identifying patterns in the past and predict the probability of their repetition. This information will help your company’s decision-makers determine what to do beforehand to prepare for the predicted scenarios.
5. Verify your findings
The end of business forecasting is simple. You wait to see if what you predicted actually happens. This step is especially important in determining not only the success of your forecast but also the effectiveness of the entire process. Having done some forecasting, you can compare the present experience with these forecasts to identify potential areas for growth.
When in doubt, never throw away “old” data. The final information of one forecasting process can also be used as the past data for another forecast. It’s like a life cycle of business development predictions.
Business forecasting examples
With the different types of business forecasting come different potential use cases. A company may choose to utilize several elements of business forecasting to prepare for various situations. Here are some real-life examples where business forecasting would be valuable.
The seasoned veteran
Suppose you represent a company that has been in the market for a long time but has never tried business forecasting. Because of the long history of company data, you choose to try out quantitative business forecasting. Your aim is to make predictions using the most cost-effective and least time-consuming method. With those considerations, you may opt for the trend series method to manually identify common trends in old data, determine the likelihood of repeat instances, and forecast accordingly.
The new kid on the block
Imagine you are a new company that has entered the market to start selling your own brand of smartphones. You may think that business forecasting is impossible because you don’t have any historical company data to work off of. However, you can utilize qualitative business forecasting! Because the smartphone industry is a highly competitive one, you can use market research to take advantage of publicly available market data.
The one who wants the best of both worlds
Imagine you work for a recruiting company that has noticed that the country’s unemployment rate heavily affects company performance and has the data to prove it. As you have a clear indicator that directly impacts the potential for success, using the indicator approach to create long-term predictions would be the right call.
However, your company stresses the importance of integrating expert knowledge into the forecasting process. This extra note means that some qualitative forecasting can be used as well. You may choose to use the Delphi method to collect expert opinions and weigh that into the final forecasts as well.
What do the stars have in store for you?
Creating comprehensive predictions isn’t rocket science. With business forecasting, seeing the future is as easy as learning from the past. What you do with your findings is what will set you apart.
Want to start forecasting for your business? Learn more about business analytics and how it helps collect the necessary data and insights.
The future starts now
Automate business forecasting data analysis with predictive analytics software.
Alexandra Vazquez is a Content Marketing Specialist at G2. She received her Bachelor of Business Administration from Florida International University and is a published playwright. Alexandra specializes in writing for the Supply Chain persona, with articles discussing topics such as demand planning and warehouse management. In her spare time, she enjoys collecting board games and playing karaoke.
The future starts now
Automate business forecasting data analysis with predictive analytics software.