Maximizing ROI with Better Demand Planning from Thousense Lite's blog

The idea is to identify the process management areas that need to be addressed and then define the related metrics that can be monitored and translated into ROI when a manufacturer must evaluate the efficacy and accompanying return on investment (ROI) of a volume planning process. Although there are many key parts connected to demand planning, producers should pay particular attention to a few key areas to achieve the largest process improvement. Before beginning a project, a company must carefully analyze these emphasis areas and ensure that it can accurately quantify worth, and ROI based just on the economy of the component that is being enhanced.

Prediction accuracy is the most crucial starting point for every project aimed at improving the demand planning process. A prediction is only as accurate as the information you rely on to commit to and develop it. Forecasting accuracy is the primary business metric that determines the efficacy of the balance of the demands planning process at any manufacturer. Your forecast is subject to inaccuracies and variations if you are just capturing a part of the information.

One of the most frequent errors is relying just on past data when forecasting and failing to delve far enough into the supply part of the company. For this reason, expanding the scope of the market through a strategic planning process constitutes the initial step in increasing prediction accuracy. This indicates that for many manufacturers, the forecasting process must be extended as far as is practicable to the retail location to collect a more comprehensive demand signal. Demand Planning should involve all parties involved in the forecasting process, including corporate sales teams, outside rep companies, distributors, and important clients.

Changing the forecast cycle times is one area where businesses may gain significantly and see an immediate and big ROI. By doing this, manufacturers can gain better insight into predicted changes as they happen, improving their ability to handle exceptions. The truth is that businesses that estimate and adhere to a strategy on a quarterly run the danger of having excess inventory. A quarterly assessment and prediction just do not work anymore because so much can alter in just one week.

With the latest technologies available, businesses may now collect data in real-time, so they can make decisions based on events that are happening that day rather than waiting a week to compile and analyze the data. Businesses that use technology that enables near-real-time data collection have already been able to shift their forecast planning cycles from monthly to weekly. As the data are current rather than being reviewed after one month, this modification can result in a huge return on investment. According to experience, businesses that switch to weekly forecasting rather than monthly forecasting would see higher inventory turns, better streamlined and optimized stock levels, greater client retention rates, and higher margins.

Improvements in forecast accuracy would immediately impact inventory management, another operational area that needs careful assessment. There are numerous facets to managing inventory, but for this article, we'll concentrate on two aspects: on-hand stock and inventory turns, which are common to most manufacturers.

Order management systems and inventory managers will feel confident enough to tighten the weeks-on-hand and safety helps capture inventories across items if they have a reliable demand master plan that everyone trusts. To enable more precise forecasting, it is crucial to provide the ability to link current inventory data to demand prediction data. This entails giving up-to-date backlog and shipping data in line with the forecast data. Together with forecast input from the field, this creates a behavioral link between forecast and shipments, which heightens accountability.

Reducing the inventory reserves at all stages of the supply chain, which results in lower costs for carrying inventory and write-offs, serves as the benchmark for this area.

Customer Satisfaction Forecast accuracy helps with improved inventory management which helps with better lead time management, which can decide the fate of a relationship with customers in a cascading connection.

To maintain the most satisfied clients for the highest priority clients, according to revenue, competitive situations, or other business partnership drivers, the quantification areas for client satisfaction include reducing scarcity and stockouts, rising order fill rates, and optimizing supply/demand matching. You may develop a deeper connection with your consumers by getting to know them better and more frequently, as well as by better understanding the demands they have. This will ultimately be advantageous for both firms.

Manufacturers can continuously enhance their demand planning process by enhancing and measuring business operational efficiencies in three important areas. This enables these businesses to make more lucrative business decisions while still having enough time to realize a return from those decisions. A more thorough demand planning method also implies that revenue and margin forecasts can now be made with confidence. This is crucial since there is a great deal of pressure on the bottom-line measurements, which can result in "misses" that have a significant impact on the company's valuation. This is where, Thousense, an AI ML-based forecasting tool comes into play with the solution to all your demand forecasting needs.