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How does business intelligence software help with forecasting?

4 mins to read
How does business intelligence software help with forecasting?

In the face of unstable market and economic conditions, business people need to use several measures to stay ahead of the market. Sales forecasting is one effective lever to pull.

Businesses that can forecast future trends have a strong advantage. Not only will it put you several steps ahead of your competitors, but it will also help you stay flexible during uncertain times. As a result, sales forecasting should be an established component of a business’ strategic budget plan.

Financial planning and analytics and business intelligence solutions can assist business people in shaping forecasting models and can also increase the efficiency and effectiveness of demand forecasting and inventory management. Here's how.

1. Data accuracy

Sales forecasting should answer questions relating to what you’re going to sell, to whom you’re going to sell it and when you will make the sale. The key benefit of using a business intelligence solution for sales forecasting is to store and manage your data from multiple sources (ERP, CRM, spreadsheets of sell-thru data) in one location. This data flow operates in real-time and the comprehensiveness of your sales data allows you to forecast in detail considering volume, price, margin, product category and sales rep.

Carrying out sales forecasting as part of the budgeting process is best practice. Using the in-built workflows, the budget builder can collaborate with sales managers in each division of the business to create a sales forecast. This detailed method of sales forecasting adds so much more value than a generic 10% stretch of historical data for every sales person that is common technique used.

With a data platform the sales forecast can be tailored to the nuances of each market, customer buying behaviour, seasonality, set by margins or the performance of your sales people. The workflows allow finance to drive the forecast by different variables and pass control over to the sales manager to to build an accurate model that reflects customer demand in each region and market conditions.

2. Visualizations

A crucial tool for forecasting future trends is data visualization, which is often built-in to FP&A tools like Phocas in the form of charts, graphs, maps, dashboards, and other visual elements to communicate data insights and trends. Data visualizations can help finance and sales professionals present and explore data in an intuitive and interactive way, and highlight key findings and recommendations. For example, data visualization can help people to compare scenarios, track performance, or identify outliers based on product movements and delays in supply chain management.

3. Timeliness

All too often, finance and sales managers spend weeks building sales forecasts. The lack of a single data platform causes business people to spend days tracking down information and compiling the multiple data sources from spreadsheets into more spreadsheets, prolonging a process that could have been done within minutes if supported with the right technology. With FP&A and BI software in hand, you can access many different types of data in the one platform and tap into historical data, seasonal data and current trends.

As well as being able to forecast in more detail, you also have a way to compare actuals to budgets each week or month. By leveraging this real-time data and applying the inbuilt advanced analytics techniques embedded in the FP&A and business intelligence platform, sales people and accountants can make timely adjustment to forecasts. This ensures you have enough product to meet demand or address unexpected spikes in demand.

4. Valuable insights

The most important aspect of using business intelligence for forecasting is the access to data analysis which can help shape future outcomes. With strong data quality and the automation of rolling results, sales managers can carry out data mining and drill into the data to determine what areas are on track and the reasons why other areas are underperforming.

The integration of business intelligence and financial planning and analysis tools into ERP systems helps improve sales forecasting capability, and lets sales and finance managers plan proactively. By leveraging BI + FP&A, businesses can access comprehensive dashboards and real-time analytics that provide a clear picture of current sales trends and future projections. This capability enables sales teams to identify patterns and correlations within their data, uncovering valuable insights that might be missed through traditional analysis methods. For instance, sales managers can anticipate customer behavior, optimize pricing strategies, and identify the most promising market segments, leading to more accurate and reliable forecasts.

Last month we identified the healthcare sector was producing some outstanding results. So, we were able to divert some of our sales effort away from low performing sectors into those that appeared to be more lucrative. That was really good,”

Howard Barr, General Manager at Woodberry.

Business intelligence facilitates the continuous improvement of sales forecasting by incorporating machine learning algorithms and advanced analytics techniques. These tools can analyze vast amounts of financial and operational data to refine forecasting models over time. This iterative process ensures that forecasts remain dynamic and responsive to changing market conditions. Additionally, BI platforms with FP&A offer collaborative features like workflows, allowing different stakeholders to share insights and align their tactics. This cross-functional approach not only enhances the accuracy of sales forecasts but also creates a more responsive and efficient business and smarter decision-making.

Business Intelligence platforms combined with FP&A tools have been proven to improve the forecasting process, to ultimately deliver more accurate and detailed forecasts.

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Written by Katrina Walter
Katrina Walter

Katrina is a professional writer with experience in business and tech. She explains how data can work for business people without all the tech jargon. She is always on the look out for new ways data is being used by business people to know more and be sustainable.

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