Whether it’s to see what lottery tickets to buy, if they should make a career change, or when to make their big move to a new country, it would be helpful to take a peek into the future.
Trying to see the future and expect what could be around the corner is something that takes place in boardrooms every day, thanks to business forecasting. While forecasting is the process of making predictions of the future based on past and present data, business forecasting is different.
What is business forecasting?
Business forecasting is a prediction or projection of future developments in business, such as spending, potential revenue, and sales. It can also determine how to allocate budgets and plan for upcoming expenses during a period of time.
This form of business analytics combines information taken from past circumstances with an accurate picture of the present state of the economy to predict future outcomes for a business. When used correctly, it can help plan ahead for your organization’s needs, which will raise the chance of staying profitable through a variety of situations.
If you need to learn something specific about business forecasting and what it can do for your organization, jump ahead to:
Importance of business forecasting
Think about the sheer number of decisions your company makes on a daily basis. No matter the decision, or the processes your company engages in, the business should have used some sort of forecasting to support what conclusion they come to.
Whether the forecasting is based on predictive analytics or just a gut feeling, it’s obvious that all industries rely on business forecasting. It just depends on how it’s used.
Business forecasting can be used in many ways, but it's typically used for:
Strategic planning and decision-making (long-term goals)
Finance and accounting (budget and cost controls)
Marketing (pricing of products and consumer behavior)
Operations and supply chain (inventory and production)
In addition, forecasting allows organizations to improve profits and can be an essential tool when it comes to eliminating waste. Some examples are:
Missed due dates
Missing strategic opportunities
Related: If you’re interested in making the most of business forecasting to prepare for possible budget changes, then check out the best budgeting and forecasting software.
These business forecasting tools will help companies estimate future revenues and expenses across multiple departments or business entities, while also creating forecasts for each department.
It’s clear that the more accurate business forecasting is, the more effective strategies and project plans will be. Because of this, it’s crucial to completely understand business forecasting to give your organization a competitive advantage and the ability to expect the unexpected.
Business forecasting vs scenario planning
One of the new forecasting techniques that’s making its way through industries is “scenario forecasting”. Some businesses are turning to this scenario method to come up with a more strategic direction for their organization.
In scenario planning, companies develop a plan that will identify major changes that could happen and determine the possible effects those changes will have on their day-to-day operations.
The next step is to map out ways they would react if those occurrences were to take place in the hopes that doing so will make them better prepared if an economic crisis occurred.
So why would a business choose scenario planning over business forecasting? Traditional forms of business forecasting aren't always able to keep up with the rapid pace in which the modern world moves. While it is able to anticipate specific events over a period of time, some organizations are turning to scenario planning to look at and think about their economic future.
Business forecasting data sources
How accurate the forecast is going to be depends on the data you collect during the process. Before you begin to collect data, ask yourself a series of questions that will shape your plan for data collection:
Why are you collecting data in the first place?
What kind of data are you looking to collect?
When will the collection of this data take place?
Where will this data be collected?
Who is going to do the collecting?
How will it be collected?
Of course, your answers are going to depend on your unique situation.
Perhaps you’re collecting to learn more about your customers, or maybe for a better way to reduce spending at certain points in your supply chain. Also consider if you want to collect your data by the hour, day, week, or even month.
There’s a lot you’ll need to iron out, but once you have a fully laid out plan it’s important to understand the two sources where data can be collected.
Primary sources of data are collected using reporting tools and predictive analytics software. This first-hand data is collected personally by those assigned the task, as they provide raw information and first-hand evidence.
Examples of primary sources include interviews, questionnaires, polls, observations, or experiments.
Secondary sources of data have been collected by others and provide second-hand information and commentary from others.
This could include official reports from various governments, publications, journals, newspapers, magazines, or a financial statement from a bank.
How does forecasting work?
The process of business forecasting may look different depending on your industry and the overall goal you intend to come to once the process is complete.
Regardless, most forecasts are going to follow a 5-step process.
Choose a problem: This can be anything from, “Will people buy a new high-end food mixer?” or even something like, “What will our sales be at the end of the fiscal year?”
Choose a data set: In the second step of business forecasting, the forecaster will pinpoint all of the relevant variables needed to consider and decide how the data will be collected.
Choose a model: The forecaster will then pick the model that’ll best fit the dataset and the selected variables, as well as any assumptions needed to simplify the process.
Analyze the data: Using the model, thedata is then analyzedand a forecast will be made based on that analysis.
Verify the forecast: The forecaster will then compare the forecast to what actually happened so that they can better determine what to adjust in the future. They will also identify problems if the forecast wasn’t accurate.
Business forecasting methods
When it comes to the approach of business forecasting, there are many ways you can go about it. Which method you decide to go with is going to depend on what kind of data you have, how much of it you have, and what you’re looking to better understand using your forecast.
Qualitative forecasting models
One of the most common methods of business forecasting is qualitative forecasting, which uses the opinion and judgment of consumers and experts.
This method becomes useful if your business has insufficient historical data to make any relevant statistical conclusions and is usually for short-term predictions. When this happens, your business should bring in a forecasting expert to piece together what bits of data you do have to try and come to a qualitative prediction from the information that is known.
This method is also used when there’s little known about the future of your industry. In this case, relying and making predictions based on historical data is useless if the data isn’t relevant to the undiscovered future your business is approaching.
An example of this is when a product is first introduced to the market. Think back to June 2007 when the very first iPhone was released. Since the data would be scarce, Apple had to use human judgment and rating schemes to turn qualitative information into estimates.
Qualitative forecasting models should be used in predicting the short-term success of a company, product, or service, due to its limitations in data.
There are four general approaches to qualitative forecasting.
1. Historical analogy
The most commonly used approach is historical analogy, which is based on the belief that future trends will develop in the same direction as past trends. Basically, it’s the assumption that the future will be similar to the present and not enough will change to cause a sustainable impact.
An example would be when a business takes the current year’s performance and uses it to base a prediction on what the next year will look like.
2. Panel of executive opinion
This method is sometimes also referred to as the jury-of-expert-opinion approach.
It combines and averages the views of upper management about a proposed future event. Generally, executives from different departments, such as marketing, sales, and finance, come together to form a prediction even though elaborate data is lacking.
3. Market survey
In this approach, those doing the forecasting can poll, whether it be in in-person or using an online questionnaire, customers or clients about expected future behavior.
For instance, you can choose to ask your customers how likely they’ll be to purchase a product that offers a new feature or solves a current pain point. The goal of this method is to ask a set of “experts”, also known as your consumers or potential customers, what they will do next.
4. Delphi Technique
This technique is similar to the market survey approach, but instead of polling customers, you’re polling a panel of experts and gathering their opinions on a specific topic. The experts each express their opinion without knowing who the other experts are and or their responses. These opinions are then compiled into a forecast.
Since there is an element of anonymity, a pattern of future events can be determined based on reducing the “crowd effect” in which the experts are all gathered in one room and agree with one another.
Quantitative forecasting models
On the other hand, there’s quantitative forecasting, which is used where there is accurate data available to predict future events. This is done by pulling patterns from data that allow for probable outcomes.
While qualitative relies on experts and a human element, quantitative is strictly based on data, as well as statistical methods or mathematical models.
In this method, the data of past performance of a product is used and analyzed to establish a trend or a rate of change. This type of data can include sales numbers and housing prices as a way to connect variables to establish a cause-and-effect relationship for the benefit of your business.
There are three main types of quantitative forecasting:
1. Time series forecasting
Time series forecasting is the method of using past data to predict future events. When businesses are able to track what happened in the past, forecasters can have a better than average prediction about what awaits in the future.
This method proves to be the most useful when there’s an abundance of historical data available to combine trends and seasonal factors into the historical data.
2. The indicator approach
As the name suggests, the indicator approach depends on the relationship between two variables, or indicators. By taking a closer look at the relationships and then understanding where the indicators are leading, you can estimate the performance of the indicators that are falling behind by using the leading indicator data.
An example of this would be taking a closer look at Gross Domestic Product (GDP) and unemployment rates.
3. Economic modeling
Economic modeling is similar to the indicator approach, but it takes a more mathematical look at trends.
Instead of making assumptions that relationships will stay the same, econometric modeling tests the consistency of datasets over time and the strength of the relationship between the two. Doing so means that this method is often used in academic fields to evaluate things like economic policies.
Qualitative vs quantitative forecasting methods
Now that you have a clear breakdown of the two methods of business forecasting, you’ll need to decide which one is right for your organization. To do that, you’ll need to understand the major differences between the two in a straightforward way.
When to use
When the situation is vague and little data exists
When the situation is stable and historical data exists
Requires experts with experience
Requires econometric and mathematical techniques
Depends on market segment
Depends on the statistics and data
Challenges to business forecasting
If you’re thinking that business forecasting sounds too simple and too good to be true, it’s important that you also consider the challenges you may face along the way. As I said, we all want a crystal ball, and if business forecasting was that, everyone would be reaping the benefits and staying up late at night reading their tea leaves.
While it’s agreed upon that business forecasting is a system that can provide a better view of what awaits for organizations in the future, some may argue it’s a waste of time and resources with little ROI. It’s true that you can follow the steps perfectly, consider all of the elements, and still get it wrong.
There’s no way that your team could manage all of the variables that can impact future events, seeing as there’s always room for error in calculations that make results unpredictable.
It’s impossible to factor in unique or unexpected events, and any assumptions made on data can be dangerous. Black swan events, an unpredictable event that is beyond what is normally expected and has severe consequences, can happen, too.
Note: An example of a black swan event would be the crash of the U.S. housing market in 2008. For instance, you could forecast sky-high traffic numbers for your website or revenue from your sales team, but end up falling drastically short because of inaccurate predictions and forecasting.
You’re not going to have a clear vision of the future when using business forecasting, but any form of insight into potential trends is going to give your organization a competitive edge.
Business forecasting examples
By now it should be obvious that several organizations, regardless of their industry, are able to use business forecasting to their advantage. We asked real-life users of business forecasting if they could share their first-hand experiences and what they’ve learned along the way.
Gene George, owner of Gene George Consulting, uses business forecasting to help education institutes implement data science practices:
“The data I am able to gather from business forecasting combined with my own experience in the industry allows me to define important trends and project what higher education will be prepared to do over the next decade when it comes to implementing analytics.
"It's all a moving target, but business forecast gives me enough confidence to position my company to be successful. I am able to establish a range of services, manage pricing, and estimate revenues. My forecast is detailed enough to let me see the need to be flexible and agile in addressing client needs.”
Alex Birkett, co-founder of Omniscient Digital, uses business forecasting at his content marketing agency:
“We do business forecasting, but with two caveats. First, we're only developing models in order to make better decisions with regards to business actions and content strategy. Second, our model is a 'micro-model' that seeks to maximize the value of content and its business returns in relation to the rest of the business, but not dependent on other channels.
"Therefore, we avoid some of the common challenges and pitfalls of forecasting, the main one being an overconfidence in the veracity of your projections and an overabundance of input variables. The narrower your scope of forecasting (and in fact, the shorter the time horizon), the more accurate things tend to be. All of those caveats in mind, forecasting helps us with resource allocation, prioritization, and also with ongoing analysis of content efforts.”
Open your inner eye
If seeing the future was easy, everyone would be doing it. At the very least, business forecasting provides you with the tools and insights your organization needs to be ready for what could await around the corner.
If you haven’t explored all that it can do for your business, there’s no better time than the present to see what the future could hold.
Mara is a Content Marketing Manager at G2. In her spare time, she's either at the gym, enjoying the great outdoors with her rescue dog Zeke, or right in the middle of a Netflix binge. Obsessions include the Chicago Cubs, Harry Potter, and all of the Italian food imaginable. (she/her/hers)