In the consumer packaged products industry, it’s not just about selling more but also about selling it more profitably. The nature of the industry requires the goods to be replaced or restocked on a regular basis that requires accurate ordering of the products in the store. A sales representative takes about 30-40 minutes in ordering per store leading to an average cost of $45 – $55 per order. This forms a big chunk of the OpEx in the sales and distribution industry and while every company’s goal is to maximize its earnings, they are striving to reduce their sales and distribution operating expenses.
65% of DSD operators’ primary target is to reduce their operating expenses. When we look at the business operations, it is observed that the manual order taking procedure is one of the key drivers of high sales and distribution operational expenses for the sales and distribution companies in the CPG business.
Due to inefficiencies in the order taking process, sales and distribution companies are incurring additional operating expenses and losing revenue. Let’s have a look at these inefficiencies.
High velocity CPG items demand multiple sales visits for order taking, an expensive proposition that puts pressure on Operational expenses.
It takes a lot of time to manually examine and enter orders. A significant amount of effort is spent analyzing inventory and then creating an order for the retail business. Because of the time required, sales representatives are unable to spend more time with store managers discussing more products and ideas, as well as covering a good number of stores in a single day. resulting in increased trips or missed sales opportunities.
In manual processes, human errors are common, resulting in inaccurate orders. As a result of inaccurate orders, the retail outlets are overstocking or facing stock outs. Overstocks result in returns, which leads to loss, whereas stock outs result in a loss of sales and consumer dissatisfaction.
Contractual labor accounts for 45-60% of the sales force. The availability of sales personnel is critical to the order taking process. In case of their unavailability due to planned vacation, etc. a high level of contractual labor is required, which is an additional operational expense.
Throughout its business processes, the consumer packaged goods industry generates a huge amount of data that businesses may utilize to make better decisions and increase profitability. As a result of the vast amount of data available, AI has gained in popularity, however, it is still underutilized. Artificial intelligence has a huge potential to help organizations save expenses and increase revenues. Few examples of AI being used in CPG business are forecasting demand, inventory management, supply chain optimization, consumer sentiment analysis, and a bot to automatically answer customer inquiries.
With the help of artificial Intelligence you can even transform the manual order taking process and reduce the sales and distribution operating expenses.
Artificial intelligence can generate accurate orders utilizing data-driven methods and robust AI/ML algorithms that can easily adjust to shifting inventory and demand trends. This reduces understocking and overstocking of the products.
Artificial Intelligence (AI) can generate the orders before you reach the stores that assist you to take the orders quickly.
Artificial Intelligence, using Machine Learning and Time Series algorithms, can forecast the order a few days ahead of time. This reduces the reliance on sales representatives’ availability and eliminates the requirement to hire contract laborers.
It is predicted that by 2024, there will be an increase of 20-25% in the utilization of AI/ML solutions for Order Forecasting.
Now think of a scenario in which a sales representative visits a retail outlet with the order quantity already in hand. All they have to do now is double-check whether the suggested order is correct. Isn’t this going to make the order generation process easier and quicker?
Quantiphi provides a One-Click Order Generation Solution called OrderSmartTM that saves time and money by providing highly accurate order suggestions.
OrderSmartTM is a scalable predictive ordering solution that uses proprietary AI and ML algorithms to transform the manual sales-order generation process. OrderSmartTM transforms manual processes of order generation at the Store-SKU level, reduces costs and effort, and improves operational efficiency. OrderSmartTM was jointly built by Quantiphi along with CONA – Coke one North America ( IT platform for North American Coke Bottlers) to transform the manual sales order generation process for the bottlers.
Interested in exploring the capabilities of OrderSmartTM for your business? Reach out to our experts now!