How to Optimize for Accurate Sales Forecasting

While the past two to three years have shown particular levels of unpredictability, the nature of business today tells us that markets will only become faster-evolving and more complex to navigate as time goes on. Customers are using multiple channels to connect with companies. Globalization and increased connectivity mean geopolitical factors will impact business more heavily than ever. Rapid advances in technology mean that companies must be ready to change and adapt at short notice.

While the overwhelming majority of sales organizations use forecasting as part of their strategy, far fewer are able to achieve high levels of accuracy. 

What is holding these organizations back?

There are common challenges sales organizations encounter when implementing a sales forecasting strategy, including siloed teams, decentralized data sources, too much subjectivity, and failure to plan for disruption. Let’s take a closer look at each of these challenges.

Decentralized data sources

Accurate data is the cornerstone of sales forecasting. When a company’s data is decentralized—living in different systems or siloed by department—it’s impossible to make informed forecasts because pieces of the puzzle are missing.

For example: performance metrics from marketing campaigns can inform sales teams about levels of market interest for particular products. Without that information, product-based sales forecasts are nothing more than educated guesses.

Siloed teams

Siloed teams are common because in traditional business settings, it was historically practical for individual departments to operate on their own. In today’s interconnected world, it’s no longer possible. 

Companies with siloed teams are slower to react, less able to anticipate potential problems, and less informed when it comes to building strategy and making decisions. On the other hand, companies with high levels of alignment and collaboration are able to share insights that inform smarter decision making and more accurate forecasting.

For example: when finance and sales teams are aligned, finance can share budget plans that show anticipated marketing resource allocation. When sales teams are informed about planned investment in particular campaigns or other marketing efforts, they can align their sales forecasts accordingly.

Too much subjectivity

It’s the age-old struggle of the optimistic salesperson: wishful thinking. Or, even worse, the salesperson who only gives deal visibility at the latest stage of the deal when it is practically closed anyway. In the past, when data analytics were slow and less comprehensive, it was common, and even expected, that some level of intuition would be part of every sales forecast. After all, there was nothing else to go on.

Today, that’s not the case. Companies with the right technology in place have access to sophisticated analytics that make objectivity attainable. Allowing wishful thinking to take over in today’s sales environment can lead to financial losses in the forms of unused inventory, overhiring, or poor marketing and sales ROI.

Failure to plan for disruption

In 2023, the inevitability of disruption is clearer than ever. It’s a mistake for companies to make sales forecasts based strictly on current conditions or a long-time status quo. 

The nature of business today tells us that markets will only become faster-evolving and more complex to navigate as time goes on. Customers are using multiple channels to connect with companies. Globalization and increased connectivity mean geopolitical factors will impact business more heavily than ever. Rapid advances in technology mean that companies must be ready to change and adapt at short notice.

What does it all mean for sales forecasting? In short, businesses must adopt adaptive forecasting methods that allow them to consider and prepare for multiple financial scenarios based on a wide range of factors.

They can do it with adaptive forecasting software. Using AI-powered analytics and high levels of automation, adaptive forecasting software not only uncovers every potential future scenario but analyzes the likelihood that each will actually occur. While more traditional versions of sales forecasting happen periodically, adaptive forecasting takes a continuous approach and provides real-time visibility into short- and long-term predictions.

Using Artificial Intelligence in Sales Forecasting

In recent years, artificial intelligence (AI) has revolutionized the way businesses operate. One area where AI has made a significant impact is in sales forecasting. Sales forecasting is a critical aspect of any business, as it helps businesses plan their strategies and make informed decisions. AI can assist in sales forecasting by analyzing large data sets, identifying trends, and providing accurate predictions. 

Improved forecasting accuracy

One of the main benefits of using AI in sales forecasting is its ability to provide accurate predictions. Traditional forecasting methods are based on historical data and assumptions. However, AI can analyze vast amounts of data from various sources, including customer interactions, market trends, and social media, to identify patterns and make accurate predictions.

Faster decision-making

In today's fast-paced business environment, speed is crucial. AI-powered sales forecasting tools can analyze data in real-time, providing businesses with up-to-date information. This information can help businesses make informed decisions quickly and stay ahead of the competition.

Reduced costs

Traditional forecasting methods require manual data collection and analysis, which can be time-consuming and expensive. AI-powered sales forecasting tools can automate this process, reducing the need for manual labor and lowering costs. Additionally, accurate forecasting can help businesses reduce inventory costs and optimize their supply chain, further reducing costs.

Better resource allocation

Accurate sales forecasting allows businesses to allocate resources more effectively. For example, if a business predicts that demand for a particular product will rise, it can increase production to meet that demand. Conversely, if demand is predicted to decrease, the business can reduce production to avoid excess inventory.

AI has numerous benefits in sales forecasting. From improved accuracy and faster decision-making to reduced costs and better resource allocation, AI can help businesses stay ahead of the competition and provide a better customer experience. As AI technology continues to evolve, it is likely that its impact on sales forecasting will only increase.

How to Optimize For Accurate Sales Forecasting

Keep an eye on market trends

During unpredictable times, it is crucial to keep an eye on market trends. Monitor changes in consumer behavior, supply chains, and any new regulations or policies that may impact the market. By doing so, businesses can identify potential risks and opportunities and adjust their forecasts accordingly.

Utilize data analytics

Data analytics is an excellent tool for accurate forecasting in unpredictable times. By analyzing large data sets, businesses can identify patterns and trends, which can help them make more accurate predictions. Utilize data analytics tools such as machine learning and artificial intelligence to gain insights into a more predictable revenue stream.

Consider alternative scenarios

During unpredictable times, it is important to consider alternative scenarios. This may include scenarios such as a prolonged economic downturn or a sudden recovery. By considering different scenarios, businesses can be better prepared for any outcome and adjust their sales forecasts accordingly.

Collaborate with industry experts

Collaborating with industry experts is an excellent way to gain insights into the market and make more accurate sales forecasts. Consult with experts in your industry and seek their advice on market trends, consumer behavior, and supply chain. This can help businesses make more informed decisions and adjust their sales projections  accordingly.

Be flexible

Finally, it is important to be flexible. Business conditions can change rapidly, and it is crucial to be able to adapt quickly. This may involve making changes to the business model, adjusting pricing strategies, or exploring new markets. By staying flexible, businesses can better navigate unpredictable times and emerge stronger.

How Xactly Forecasting® Supports You In Unpredictable Times

By utilizing AI, keeping an eye on market trends, utilizing data analytics, considering alternative scenarios, collaborating with industry experts, and staying flexible, businesses can call accurate sales forecasts in unpredictable times. Remember that unpredictable times are temporary, and by staying focused on the core aspects of your business, you can emerge stronger when conditions stabilize. In our next blog, titled Sales Forecasting 101, Vol. 3: Data Sources to Use in Your Sales Forecasting, we’ll cover the importance of forecasting data to help formulate strategy and action to drive your business forward.

Ready to take the next step in your forecasting journey? Check out our on-demand webinar Predict Real Revenue with Xactly Forecasting® for insights on how having the right data and level of visibility will deliver more accurate sales forecasts and accelerate predictable revenue.

Watch here!