Capacity Optimization

Planning for peak demand while average overall demand remains considerably lower poses a significant concern in various sectors, leading to a waste of resources.

In the case of roads, cities and regions allocate significant resources to build and maintain roads capable of handling peak traffic flows. However, during non-peak hours, these roads are underutilized, wasting resources, increasing maintenance costs, and causing unnecessary congestion during peak periods. Similarly in the hotel industry, hotels are built with numerous rooms to cater to seasonal or event-driven peaks in demand. However, during off-peak periods, a substantial number of these rooms remain unoccupied, resulting in wasted resources like energy, water, and staff. And this underutilization of resources happens in many other sectors like parking spots, restaurants, travel seats, and theatres.

To address these issues, better demand forecasting and resource allocation strategies are necessary. Organizations face increasing pressure to operate leaner and smarter. They are finding innovative ways to maximize efficiency and make the most of available resources. Dynamic pricing is a game-changing strategy that can significantly support optimal Capacity Optimization.

In this article we will explore how dynamic pricing increases the potential of businesses by optimizing Capacity Optimization by redistributing demands, reducing the peak demand spikes, and increasing the demand on otherwise periods of low demand. This needs a proactive and forward-thinking mindset, as well as a willingness to challenge traditional practices and explore new methodologies.

  • Variable Pricing for Demand Reshaping

Dynamic pricing is typically designed to increase prices when demand is high, penalizing consumption during periods of high demand, and incentivizing consumption through discounting in periods of low demand. This action balances the demand and prevents overutilization of capacity. By charging higher prices during peak periods, businesses can optimize their capacity, avoid overcrowding, and provide better service to customers.

  • Cost reduction through lowering down the peak demand

By reshaping the demand, the capacity or infrastructure requirement to meet the peak period demand is lowered. Hence, businesses are now able to provide same level of service with lower service capacities resulting in cost savings.

Let’s take an example of a bus service running between two cities. Consider the seat demand data shown in Table 3 below. We can notice that the demand pattern is highly variable, with maximum demand of 125 seats falling on a Sunday, and minimum demand of 50 seats falling on Tuesday, Wednesday, and Thursday, totalling to a weekly demand of 600 seats. At a flat price of Rs. 100 per seat, the bus service is generating a weekly revenue of Rs. 60,000.

Let’s consider a scenario where we increase the ticket prices on high demand days (Fri, Sat, Sun) to Rs. 120 from the current Rs. 100 per seat and reduce the ticket prices on low demand days (Tue, Wed, Thu) to Rs. 80 per seat from the current Rs. 100 per seat. So overall the price increases and price reductions are matching to each other and are of a similar magnitude of change. Let’s assume that due to the price change, the resulting re-shaped demand is as shown in Table 4 below.

While the overall weekly demand and level of service in the market has remained at 600 seats, we can notice that the peak day demand has reduced to 100 seats from 125 seats earlier (Table 3 above). To meet the weekly demand, now only a capacity of 100 seats per day vis-à-vis 125 daily seats in the earlier scenario. This represents a 20% reduction in the capacity requirement, which will lead to a significant cost reduction in providing the bus service.

  • Increase in Revenues

Consider the same situation as above, at the resulting new demand pattern the weekly revenues are going up from Rs. 60,000 per week to Rs. 62,000 per week. This is when a balanced price change was applied (same magnitude of price increase vs price decrease), and the overall demand remained at earlier levels of 600 seats per week.

  • Continuous Monitoring and Adaptation

Dynamic pricing continuously monitors market dynamics and adapt strategies accordingly. This helps businesses stay updated on industry trends and track competitor behaviour. With dynamic pricing, businesses can change prices in real-time to make the most of their available capacity. It helps them make sure they’re using their capacity efficiently.

For instance, airlines often adjust their prices based on factors such as holidays, peak travel seasons, or local events. By continuously monitoring these trends, they optimize their Capacity Optimization and revenue by setting prices accordingly.

  • Data-Driven Insights for Capacity Planning

Dynamic pricing strategies rely on accurate data analysis and insights. By leveraging data from past sales and market trends, businesses can make informed decisions regarding capacity planning. These insights help determine optimal resource allocation, staffing levels, and production schedules to meet anticipated demand.

Data-driven insights can be used to conduct price elasticity analysis, which helps determine how sensitive customer demand is to changes in price. This analysis allows businesses to identify the price points at which demand becomes elastic or inelastic and make informed decisions about pricing adjustments to maximize revenue while maintaining optimal Capacity Optimization

Our dynamic pricing tool Viaje.ai empower businesses to meet customer demands more effectively. Through dynamic pricing, businesses align their pricing strategies with the demand fluctuations, striking a balance between supply and demand. This not only optimizes Capacity Optimization but also improves operational efficiency and enhances the overall customer experience.

Book a Free Demo! of our automated retail solutions or contact our optimization experts at info@sciative.com.

To know more about our AI-powered dynamic pricing tool BRIO, reach out to us.

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