Despite the necessity of forecasting, businesses do not utilize demand planning software to its full potential. Industry research has shown that many businesses cannot meet consumer demand due to poor demand forecasting or manual methods of forecasting. Most businesses depend predict their forecast sales figures based on guesswork which is a huge mistake. For predicting market conditions, companies should utilize demand planning software which can assist in planning their cash flow and production needs.
What is Demand Forecasting?
Demand forecasting predicts future sales for a particular product over a certain period using past sales data. Demand forecasting is essential for business management as it provides various benefits. Business professionals use quantitative and qualitative methods, and choosing the proper forecasting technique is essential for meeting objectives.
Several operations depend on demand planning, such as financial planning, sales operations, supply chain planning, marketing initiatives, inventory planning, customer service capabilities, supply chain management, production planning, and new product development.
Advanced machine learning and artificial intelligence algorithms are being integrated into demand planning software to predict trends and patterns from all available data and generate accurate forecasts.
Need for Demand Planning Software
Demand planning software streamlines the complexities of the demand planning process. Forecasting software provides users various benefits, ranging from improved forecast accuracy to obtaining real-time demand forecasting updates. Businesses can achieve productivity and achieve cost savings in the long term. Demand forecasting software can improve the supply chain management process through improved accuracy. The expenses of labor costs can be reduced significantly, and precious time can be saved by utilizing robust software compared to manual forecasting.
Therefore, the need to choose the right demand forecasting software can be understood, and it is not a simple task.
Features to Look For in Demand Forecasting Software
Businesses should consider the features of a particular software and decide whether their business would benefit. An efficient demand planning software helps you meet your business’s evolving needs and align with the sales and operations planning processes.
Businesses should be able to supervise the demand planning process, allow collaboration, and make the process faster. You should be able to receive the notification of completion and approval of forecast updates through automatic email notifications. The regular and daily tasks should be automated, like data preparation which liberates the planners to monitor exceptions and work in coordination with the sales and operations department. It yields productive outcomes and helps you to adapt to external pressures and influences.
- Business Needs
Organizations should undergo an extensive planning process for setting their objectives and understanding what their needs are before they start to look for the perfect demand forecasting software. Software that is ideal for one company may not be perfect for another. Planners should identify the features they need for their businesses and invest accordingly. For example if the Demand planning software has AI and ML capabilities it can help in the case of new product launches or when considering opening a new storefront.
The software should also seamlessly integrate with your company’s existing management system. Customization and compatibility are important factors for companies when deciding between different software options.
- Segmentation Analysis
Segmentation analysis is an essential part of demand planning software, and it enables you to categorize markets, customers, groups, and other aspects for supporting planning and development. It allows planners to inspect and adjust targets and forecasts for particular segments and supervise KPIs for judging performance.
- Consensus Demand Planning
Demand planning software should provide solutions for a variety of needs of business users for different needs. You should be able to view plans on an Excel spreadsheet, online, or your mobile device. It should also offer cost allocation, disaggregation, cell locking, and aggregation. The software should enable multistep processes of consensus demand planning by aligning the future demand with sales and marketing processes. The software should be easily accessible, secure cloud solution that allows better communication across every department.
- Promotion Planning
Promotion planning is an essential factor in driving demand in the retail sector. An efficient demand planning tool should optimize the utility of marketing strategies, tools, and resources for promoting a service or product. Access to trade advertisements results in real-time when they are running, enables you to obtain optimum results.
- Data Integration
Data integration is a necessary component of every demand planning software, enabling you to integrate your transaction data and master data from the different source systems for utilization in various planning applications. In demand forecasting, you have to link with different data sources to obtain information about the current and future demand. Integrating with every source system allows businesses to make decisions depending on information from inside and outside sources.
- Product Lifestyle
When searching for demand forecasting software, the software should be able to plan for new products and phase-outs such that you can picture your product’s life cycle. For planning these processes, the system should be able to include curve-fit modelings, like modeling and cannibalization models. Moreover, producing tailored customer models should be an option, not requiring the assistance of outside experts.
Fountain9 offers expert assistance to retail businesses to estimate demand accurately with their demand planning software, Kronoscope, which considers 9 unique factors that influence demand. The software is powered by artificial intelligence and machine learning algorithms that learn from past historical trends and consider external factors such as seasonality and promotions to generate accurate forecasts for meeting consumer demand.