What is the difference between qualitative and quantitative techniques of forecasting?

Forecasts are infamously difficult to trust. 

Your weather app says it’s going to be sunny on Saturday? You still might want to have a backup plan for your picnic.

In sales, forecasting is a practice that’s been around for a long time, but its accuracy has often failed to escape the realm of long-range temperature predictions. 

And yet, getting it right can be a huge advantage for your organization. As author, speaker, and educator Drew Boyd explained in his LinkedIn Learning course, “Sales forecasting is an essential activity for almost any business because it impacts everything: your company, your customers, and your business partners.”

Effectiveness in this area requires an understanding of the two main models of sales forecasting and how to best activate one or both.

Why is sales forecasting so important today?

As Boyd noted, sales forecasting affects many different parts of a business. First of all, it can be a basic level-setter for expectations within the sales team. But your forecast also tends to have broader implications, making an impact on things like:

• Company finances: Sales forecasts can affect stock prices and investment decisions.
• Salesforce management: Territory planning, quota-setting, and performance measurement are all influenced by the sales forecast.
• Business operations: Other departments often depend on sales forecasts to inform their own efforts – for instance, how much product to manufacture, or how to staff the customer service team.

Don’t let perfect be the enemy of good in your forecasting approach.

“Let's face it, all forecasts are wrong,” said Boyd. “Sure, once in a while, you might get a perfect prediction. Hey, but don't count on it.”

The idea of modern sales forecasting is not to predict the future with complete accuracy. It’s to find the right processes that help you reduce uncertainty, plan better, and continually optimize your strategy.

“Forecasting is about managing just how wrong your forecast is, not how right it is,” according to Boyd. “The distance between actual results and expected results is a risk to your business. And that risk can be significant, even deadly.”

The quantitative and qualitative models of sales forecasting can both help you close that gap.

Quantitative sales forecasting: It’s all about data.

This method of forecasting involves using the past to hypothesize the future. 

“I want you to think of past sales data as holding a treasure trove of information about the future,” Boyd urged. “In each time period, when your company was selling its products and services, many things were happening in terms of competitive actions, consumer trends, and changes in the overall economy. Each sales figure has something to teach you about the future.”

To do quantitative sales forecasting well, you’ll want your historical sales data to be two things: clean, and abundant. The more you have, and the more you can trust it, the better this will go.

“Ask your finance or IT partner to help you collect the most accurate and comprehensive data that's available,” advised Boyd. From there, you can employ a few different techniques:

• The rollover technique. A basic method for stable-revenue companies. The sales forecast for the next period is simply the actual sales results from the previous time period. “You'd be surprised how this very simple approach can be effective for many business models,” said Boyd.
• Moving averages. Take the average of several previous time periods and use that number to forecast the next time period. (For example: September’s forecast is the average of monthly sales from April through August).
• Smoothing. Similar to moving averages, but with a weighting factor applied to the current period. It sounds a little complicated, but Boyd explains how to calculate it clearly in the course, and this technique is quite beneficial in that it accounts for trends and seasonality.

Qualitative sales forecasting: Straight from the source.

This method involves gaining insight directly from customers or experts. It can be a good replacement for quantitative forecasting if you lack solid data, or you have a convoluted sales cycle. It can also be a good complement to almost any data-driven model.

“Depending on the type of business you're in, your customers might have insights about their future buying patterns to produce a forecast that is even more accurate than historical data,” said Boyd. 

“For example, a customer might know when something will happen to their business where they need to order more product from you. Or just the opposite, they may know when something bad will happen, like losing a big contract, or discontinuing one of their products.”

The first step in qualitative forecasting is, naturally, getting buy-in from your customers. Boyd acknowledged that there can be sticking points, such as confidentiality or fear of perceived commitment to the forecast. 

Simply have a conversation and spell out the ‘why’ for them. “Hey, if they can help you do a better job by reducing back orders or overstocks, they win too,” noted Boyd.

Once they’re on board, you can analyze cues of future buying patterns. What is their sales forecast? How much do they trust it? Are they hiring or shrinking staff? What initiatives do they have in the works?

“The key to using customer input is to track its accuracy just as you do with quantitative techniques,” said Boyd. He suggested keeping a running tally of multiple forecast types against actual results and then comparing the margins of error.

Other techniques for qualitative sales forecasting include soliciting estimates from your reps or distributors, and using a panel of industry experts.

Sales forecasting through disruptive events is very possible.

Plenty of companies had very stable and dependable sales forecasts up until March of 2020, when everything was cast awry. It was enough to make many throw their hands up and say, “Why bother?”

Boyd had some dedicated guidance for managing your forecasting strategy when the unexpected happens.

“Don't panic and assume that all your forecasting work is now obsolete, or that forecasting is impossible because of this major shock to the business,” he offered. “Forecasting is not impossible, but you may need some adjustments in your forecasting process to get that error factor back down to manageable levels.”

In these situations, his first piece of advice was to stick with your current forecasting approach and keep tracking it against a persistent rollover benchmark. Over time, a technique like smoothing will adjust itself to radical swings. 

“Markets tend to correct themselves or find a new normal, so hang in there and keep the forecasting wheels turning,” he said.

His second tip is one that probably best addresses the question laid out in the title of this post. Which is better: quantitative or qualitative forecasting? Why not both?

“Consider adding more qualitative methods to supplement your quantitative techniques. That means using customers, sales reps, and expert panels to help you sort out the mess and pinpoint where the uncertainty is.”

In general, a combination of data and direct input is going to give you the clearest picture of what lies ahead, especially in times of great change and disruption.

Regardless of how you forecast, LinkedIn Sales Insights can help. Learn more about the platform here.

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