Improve planning with comprehensive sales forecasting

If the owner of your business wants to expand to a new State, would you have the sales forecasting figures to know whether the business can afford to do that or not? Or, if you had to produce a 3–year solvency projection for the CEO, is your sales forecasting process robust enough to support a reliable analysis?

Many businesses do sales forecasting in isolation without incorporating other essential business data, making it hard to answer these big questions as well as more day-to-day tasks like inventory management.

Fortunately, if you’re a finance or sales manager for an established or new business, you can use a sales analytics software, part of a bigger financial planning and analysis platform, to automate your sales forecasting and include all the necessary factors needed to inform effective decisions.

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The sales forecast process

Sales forecasting is a critical process for businesses to predict revenue, allocate resources, and set strategic goals. Here’s how to approach:

1. Gather Data

A solid sales forecast begins with reliable data. Ideally you have a BI and FPA platform that collects and consolidates data from your ERP and a variety of sources. This tech assistance for managing the data ensures your forecasting is always up-to-date.

Historical sales data: Past performance trends offer valuable insights into seasonal patterns and sales cycles.

Market trends and industry data: External factors like market demand, competitor activity, and broader economic indicators shape sales potential.

Customer data: Analyze customer purchasing behaviors, preferences, and segmentation to fine-tune predictions.

HR, marketing, CRM, product data: Consider internal factors such as staffing changes, product launches, new branches, or marketing campaigns that could influence sales.

2. Choose your sales forecasting method

Depending on your business needs, we recommend selecting a forecasting method that balances speed and accuracy such as:

Historical forecasting: Projects future sales based on past performance, ideal for businesses with stable trends.

Intuitive sales forecasting: Relies on expert judgment and insights, especially useful for new businesses or unpredictable markets.

Pipeline forecasting: Uses active sales opportunities to predict outcomes, relying on CRM data.

Opportunity stage forecasting: Breaks down forecasts by sales funnel stages to improve precision for sales reps.

Length of sales cycle forecasting: Estimates revenue based on the time required to close deals, often integrating CRM and ERP data.

Multi-variable sales forecasting: Incorporates multiple drivers like market trends, pricing, and customer behavior. This sophisticated approach requires a tool like Phocas BI and FPA and its built-in sales forecasting software which can deliver driver-based forecasting and nuanced and actionable insights to feed into the multi-variable sales forecast.

3. Build and Review Forecasts

Once data is gathered and a methodology chosen, develop your forecasts.

Historical forecasting: Simple and achievable in tools like Excel, making it accessible for most teams.

Pipeline, opportunity stage, and length of sales cycle forecasting: These depend on accurate data integration between CRM and ERP systems for reliable revenue reporting.

Multi-variable forecasting: This is the most advanced and complex method, requiring bespoke software like Phocas for multiple data points to be incorporated into the models

Regularly review and refine your forecasts to adapt to actuals and changes coming in with the new data. The connected nature of Phocas and; the ease of switching between actuals and budgets make data-driven forecasting more accessible.

The challenge of forecasting sales

Forecasting your future sales can be time-consuming and mentally draining, especially when you don’t have the tools to integrate data from multiple sources. However, the first step in fine-tuning your sales forecasting method is identifying your business’s specific challenges.

Here are some typical sticking points many retail, distribution and wholesalers wrangle with daily.

Incorporating margins across multiple products

It’s common for a company’s sales force to have a wide range of products powering its current sales, each with its own profit margins. Even though high-level numbers can be useful, if you drill down to the granular details of your profit margin figures, the data you get can is informative.

For example, let’s say your company provides HVAC products in three states. You help customers assess their needs based on their requirements and sell them the right fit unit and then you install, configure, and maintain their systems. Your profit margins are based on a complex combination cost of goods sold, delivery, labor and equipment costs for maintenance as well as varying revenue from installation fees and paid maintenance packages.

With planning tools you can perform sales forecasts that factor in varying sales levels for each of these product lines.

As importantly, you can decide which products to double down on and which to consider phasing out. Using automated BI and FP&A tools, you can answer these questions in moments and make more informed decisions.

Factoring in margins in different regions

For companies operating in multiple geographic regions, sales figures may be different due to various market trends and factors. For instance, in some areas, business customers expect to — and can afford to — pay more for the same or similar service in other regions.

When these numbers vary considerably, it can be difficult to perform accurate sales forecasts, especially when you have to consider the length of the sales cycle forecasting. However, this can make it easier for your marketing team to target specific groups of customers.

On the other hand, using a data platform that collects and analyzes data throughout the sales cycle, you can isolate your regional sales and then share the data your team need to make decisions accordingly.

For instance, suppose you have a location in New York that generates 30% more revenue than one in New Hampshire. At the same time, the New Hampshire office costs 25% less to operate each year. To further complicate matters, the New Hampshire products generate profit margins 12% higher than those of the New York office.

When deciding how to adjust your staffing, services, bonus pay structure, and more, you can leverage a BI and FP&A platform.

For example, your sales team and sales leaders could use the consolidated data from both branches to build a sales model that compares each location's most important key performance indicators (KPIs) side by side. Then, you can generate an apples-to-apples comparison that considers a range of regional factors, giving you the most profitable sales process for your market.

Forecasting sales for many SKUs

When considering the sales from the bottom up for a large number of SKUs, you should keep in mind several factors, such as:

• Seasonal differences. Some items may sell more during certain seasons than others.
• Customer preferences as they impact sales. Customer demand may fluctuate more drastically for some items than for others.
• Supply chain factors. Supply chain issues may result in delivery delays, inventory surpluses, or shortages that impact pricing or availability.

However, you can use data analytics to segment your sales figures, taking the factors that impact each SKU into consideration. Your software can project your sales performance for each SKU and include variances according to the factors that apply to each one.

Then, you can use the software to make a projection that incorporates the data for all your products.

The advantage of scalability

Scalability is one of the most powerful advantages of a business planning and analysis solution, especially if your sales goals increase over time. Instead of manually creating SKU profiles for each item you have to add to your system, automatic data syncing can keep your sales reporting inline with your inventory tracking.

In addition, you get a centralized source of information you can use to automatically integrate data across multiple systems. For instance, you can incorporate product supply levels from your inventory management system, using them to identify seasonal trends. You can then use that data to decide when to restock certain items or negotiate bulk pricing discounts with suppliers.

A Business Intelligence and Financial Planning and Analysis (BI and FP&A) platform: the key to accurate sales forecasting

A BI and FP&A platform serves as a sales forecasting tool—the brain of your revenue management system allowing you to carry out many use cases.

Deep data analysis

Whether you’re trying to identify historical trends, isolate customer buying behavior based on customer demographics, or consider market factors, a BI and FP&A platform is your central intelligence hub. It can organize and analyze this data, as well as produce ad-hoc reports that streamline the decision-making process.

Detailed forecasting

Using a BI and FP&A platform, you can get granular with your sales forecasting, segmenting it according to sales reps, products, margins and locations. And as the market evolves and the competitive landscape shifts, your forecasting system can adjust, revealing insights to keep you a step ahead.

Advanced scenario planning

Instead of taking a reactive approach, you can start planning for the future by using a BI and FP&A platform to model several scenarios. For example, you could decide which services to cut back on and which to increase if revenue drops below a certain level. You can also decide how to adjust your marketing spending if sales rise above a certain level over a specific period.

Growth measurement

Measuring and reacting to sales growth is often not as simple as looking at a few end-of-year figures in graphs. To enable genuine agility, you need the real-time data you get with a BI and FP&A system.

For example, you could establish KPIs for individual SKUs. If these hit their desired levels ahead of schedule, this could inform decisions regarding:

• How to reallocate marketing funds for promoting these items
• How to adjust supply levels in a way that ensures the availability of these products or services
• How hitting these KPIs early impacts your overall progress toward your yearly growth goals

Leveraging real-time updates

With a fully integrated BI and FP&A solution, data from many sales pipelines from another system’s stream is constant, allowing you to make real-time decisions that support progress toward your benchmarks. Instead of having to place several calls to different departments asking for information, you have the info you need right there on your screen.

For instance, you can see how product sales react to a promotion in real-time. If you attend a tradeshow, you can see how this impacts sales right away with all sales coded from that event. By charting the impact, you can judge the effectiveness of the tactics. In this way, you can use real-time updates to build a data-driven forecasting model that helps market existing and new products.

How sales forecasting informs budgeting

Because a BI and FP&A solution consolidates data from enterprise resource planning (ERP) solutions and other data sources, you have this information on hand to make better budgeting and forecasting decisions.

Your sales revenue, which typically serves as the foundation for building a budget, is front and center. You don’t have to worry about missing historical sales data because the solution unifies everything under a single umbrella. Also, since you have access to other integrated data from your ERP, you can see, in real-time, how sales affect your overall business health.

Phocas is the perfect tool to leverage data to perform accurate, comprehensive sales forecasts and then bridge up to a comprehensive budget model. Phocas, a comprehensive BI and FP&A solution, unifies information on all of your SKUs from all of your locations, enabling the use of detailed sales and margin figures to make reliable decisions.