Companies must handle fluctuating demand for their products even in the best market conditions. Failure to keep up can result in revenue loss as dissatisfied consumers turn to competitors while having too much inventory can increase overhead costs.
If you can’t precisely estimate demand, managing stock levels is nearly impossible. Using spreadsheets to forecast demand will only result in more errors and wasted time for your finance and operations departments.
The Issues with Demand Forecasting Using Spreadsheets
Spreadsheets can be an effective and low-cost tool for demand forecasting if your company is just getting started. However, once you reach 1,000 SKUs, spreadsheet restrictions become a problem. Spreadsheets can’t handle that level of complexity while still providing a complete view of the company. Collaboration and security are significant flaws, and they don’t interact well with ERP and sales source systems. Spreadsheets, in other words, obstruct effective supply chain management and demand forecasting.
Here are six reasons why you should stop using spreadsheets to anticipate demand:
- Issues with Data Integrity Demand forecasting necessitates the gathering of historical sales data from ERP source systems, which is a lengthy procedure. Putting together a comprehensive picture from all of that data is much more difficult. You’ll spend a lot more time on consolidation if your spreadsheets are separate from your data sources. Furthermore, every time someone manually manipulates data in a spreadsheet, the risk of human mistakes increases.
- Collaboration is lacking. In order to develop an accurate prediction, demand forecasting requires finance and operations managers to work with other parts of the company. Spreadsheets aren’t built for multiple users with complex requirements and aren’t well suited for collaboration. The bigger the number of users who interact with the spreadsheet, the greater the risk of data integrity issues. And if errors are introduced into the data, your demand estimates are jeopardized.
- There is no version control. Demand projections are manually produced, disseminated, and gathered in spreadsheets, resulting in version control concerns. Multiple versions make it difficult to track down the most recent modifications to a spreadsheet, putting additional load on the demand forecasting team. Spreadsheets are also susceptible to manipulation due to a lack of controls when it comes to data access restrictions.
- Scalability is not possible. Spreadsheets, on the other hand, cannot scale if your firm is fast expanding. To manually rebuild demand planning and forecasting models every time a basic assumption changes, such as a rapid increase in sales orders, you’d need a lot of time, patience, and strong access constraints. In a fast-paced corporate climate, you must devote your time on analysis rather than manually maintaining the demand forecast model. While spreadsheets are useful for projecting demand for a small number of SKUs, they are less useful when evaluating business expansion plans such as new product releases or regional diversification. The current spreadsheet-based demand forecasting procedure will struggle to handle the volume of data and perform what-if scenarios for speedy decision-making in these scenarios.
- Scenario analysis is lacking. Spreadsheets can also erode confidence by leaving you with no clear solutions to business-critical “what-if” concerns. What if a key supplier experiences unanticipated issues and has to postpone delivery dates? You can plan for the unexpected with an agile supply chain strategy. When you rely entirely on spreadsheets as your primary planning tool, however, this is simply not possible. A spreadsheet can only do so much analysis, and depending on it for scenario planning necessitates a high level of expertise. Any large change to the model will almost certainly necessitate extensive, time-consuming, and error-prone revisions.
- Incorporating historical data is difficult. Predictive demand forecasting combines historical data with statistical models from the industry, allowing you to create an initial demand plan that may be tweaked as needed. Using spreadsheets to extract historical data from many source systems and evaluate it using forecasting methodologies to predict performance is extremely tough. The inability to change demand forecast models to reflect changing assumptions is due to the laborious nature of copying and pasting data and dealing with a large number of spreadsheets.
With NetSuite, you can accurately forecast demand.
Demand forecasting accuracy leads to more accurate downstream demand plans, which increase profitability and keep customers happy. Companies that use NetSuite ERP and Planning and Budgeting from SCG Team have real-time access to financial and operational data without having to manually move data. They can employ predictive demand forecasting capabilities for seasonality and intermittent demand to quickly examine multiple demand scenarios and respond to changing market conditions and assumptions. As a result, data integrity is enhanced, communication is improved, and controls are improved across departments, all inside a single system.
NetSuite Planning and Budgeting from SCG Team allows you to plan at the customer, location, and item hierarchy level, including SKUs, items, product lines, and more. This information is automatically available in NetSuite, where it may be utilized to develop a demand plan and buy orders. Demand forecasting allows your company to make more informed purchasing and stocking decisions. Using sales data and market research to plan demand can help your company remain ahead of the competition and thrive.
To learn more, contact the SCG Team to learn how to prepare for the future with demand forecasting using NetSuite Planning and Budgeting.
