Revenue management is the application of disciplined analytics that predict consumer behaviour at the micro-market levels and optimize product availability, leveraging price elasticity to maximize revenue growth and thereby, profit. The primary aim of revenue management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers’ perception of product value and accurately aligning product prices, placement and availability with each customer segment.
Revenue management to this point had been utilized in the pricing of perishable products. In the 1990s, however, the Ford Motor Company began adopting revenue management to maximize profitability of its vehicles by segmenting customers into micro-markets and creating a differentiated and targeted price structure. Pricing for vehicles and options packages had been set based upon annual volume estimates and profitability projections. The company found that certain products were overpriced and some were underpriced. Understanding the range of customer preferences across a product line and geographical market, Ford leadership created a Revenue management organization to measure the price-responsiveness of different customer segments for each incentive type and to develop an approach that would target the optimal incentive by product and region. By the end of the decade, Ford estimated that roughly $3 billion in additional profits came from revenue management initiatives.
The public success of Pricing and Revenue Management at Ford solidified the ability of the discipline to address the revenue generation issues of virtually any company. Many auto manufacturers have adopted the practice for both vehicle sales and the sale of parts. Retailers have leveraged the concepts pioneered at Ford to create more dynamic, targeted pricing in the form of discounts and promotions to more accurately match supply with demand. Promotions planning and optimization assisted retailers with the timing and prediction of the incremental lift of a promotion for targeted products and customer sets. Companies have rapidly adopted price markdown optimization to maximize revenue from end-of-season or end-of-life items. Furthermore, strategies driving promotion roll-offs and discount expirations have allowed companies to increase revenue from newly acquired customers.
This category of revenue management involves redefining pricing strategy and developing disciplined pricing tactics. The key objective of a pricing strategy is anticipating the value created for customers and then setting specific prices to capture that value. A company may decide to price against their competitors or even their own products, but the most value comes from pricing strategies that closely follow market conditions and demand, especially at a segment level. Once a pricing strategy dictates what a company wants to do, pricing tactics determine how a company actually captures the value. Tactics involve creating pricing tools that change dynamically, in order to react to changes and continually capture value and gain revenue. Price Optimization, for example, involves constantly optimizing multiple variables such as price sensitivity, price ratios, and inventory to maximize revenues. A successful pricing strategy, supported by analytically-based pricing tactics, can drastically improve a firm’s profitability.
When focused on controlling inventory, revenue management is mainly concerned with how best to price or allocate capacity. First, a company can discount products in order to increase volume. By lowering prices on products, a company can overcome weak demand and gain market share, which ultimately increases revenue. On the other hand, in situations where demand is strong for a product but the threat of cancellations rooms (e.g. hotel rooms or airline seats), firms often overbook in order to maximize revenue from full capacity. Overbooking’s focus is increasing the total volume of sales in the presence of cancellations rather than optimizing customer mix.
Price promotions allow companies to sell higher volumes by temporarily decreasing the price of their products. Revenue management techniques measure customer responsiveness to promotions in order to strike a balance between volume growth and profitability. An effective promotion helps maximize revenue when there is uncertainty about the distribution of customer willingness to pay. When a company’s products are sold in the form of long-term commitments, such as internet or telephone service, promotions help attract customers who will then commit to contracts and produce revenue over a long time horizon. When this occurs, companies must also strategize their promotion roll-off policies; they must decide when to begin increasing the contract fees and by what magnitude to raise the fees in order to avoid losing customers. Revenue management optimization proves useful in balancing promotion roll-off variables in order to maximize revenue while minimizing churn.
Revenue management through channels involves strategically driving revenue through different distribution channels. Different channels may represent customers with different price sensitivities. For example, customers who shop online are usually more price sensitive than customers who shop in a physical store. Different channels often have different costs and margins associated with those channels. When faced with multiple channels to retailers and distributors, revenue management techniques can calculate appropriate levels of discounts for companies to offer distributors through opaque channels to push more products without losing integrity with respect to public perception of quality.
Since the advent of the Internet the distribution network and control has become a major concern for service providers. When the producer collaborates with a powerful provider, sacrifices may be necessary, particularly concerning the selling price/commission rate, in exchange for the capacity to reach a certain clientele and sales volumes.
RM for Multiple Customer Segments
In the concept of revenue management, we need to take care of two fundamental issues. The first one is how to distinguish between two segments and design their pricing to make one segment pay more than the other. Secondly, how to control the demand so that the lower price segment does not use the complete asset that is available.
To gain completely from revenue management, the manufacturer needs to minimize the volume of capacity devoted to lower price segment even if enough demand is available from the lower price segment to utilize the complete volume. Here, the general trade-off is in between placing an order from a lower price or waiting for a high price to arrive later on.
These types of situations invite risks like spoilage and spill. Spoilage appears when volumes of goods are wasted due to demand from high rate that does not materialize. Similarly, spill appears if higher rate segments need to be rejected due to the commitment of volume goods given to the lower price segment.
To reduce the cost of spoilage and spill, the manufacturer can apply the formula given below to segments. Let us assume that the anticipated demand for the higher price segment is generally distributed with mean of DH and standard deviation of σ H
CH = F-1(1-PL/PH, DH, σH) = NORMINV(1-PL/PH, DH, σH)
CH = reserve capacity for higher price segment
PL = the price for lower segment
PH = the price for higher segment
An important point to note here is the application of differential pricing that increments the level of asset availability for the high price segment. A different approach that is applicable for differential pricing is to build multiple versions of product that focus on different segments. We can understand this concept with the help of a real life application of managing revenue for multiple customer segments, that is, the airlines.
RM for Perishable Assets
Any asset that loses its value in due course of time is considered as a perishable item, for example, all fruits, vegetables and pharmaceuticals. We can also include computers, cell phones, fashion apparels, etc.; whatever loses its value after the launch of new model is considered as perishable.
We use two approaches for perishable assets in the revenue management. These approaches are:
- Fluctuate cost over time to maximize expected revenue.
- Overbook sales of the assets to cope or deal with cancellations.
The first approach is highly recommended for goods like fashion apparels that have a precise date across which they lose a lot of their value; for example, apparel designed for particular season doesn’t have much value in the end of the season. The manufacturer should try using effective pricing strategy and predict the effect of rate on customer demand to increase total profit. Here the general trade-off is to demand high price initially and allow the remaining products to be sold later at lower price. The alternate method may be charging lower price initially, selling more products early in the season and then leaving fewer products to be sold at a discount.
The second approach is very fruitful here. There are occurrences where the clients are able to cancel placed orders and the value of asset lowers significantly after the deadline.
RM for Seasonal Demands
One of the major applications of revenue management can be seen in the seasonal demand. Here we see a demand shift from the peak to the off-peak duration; hence a better balance can be maintained between supply and demand. It also generates higher overall profit.
The commonly used effective and efficient revenue management approach to cope with seasonal demand is to demand higher price during peak time duration and a lower price during off-peak time duration. This approach leads to transferring demand from peak to off-peak period.
Companies offer discounts and other value-added services to motivate and allure customers to move their demand to off-peak period. The best suited example is Amazon.com. Amazon has a peak period in December, as it brings short-term volume that is expensive and reduces the profit margin. It tempts customers through various discounts and free shipping for orders that are placed in the month of November.
This approach of reducing and increasing the price according to the demand of customers in the peak season generates a higher profit for various companies just like it does for Amazon.com.
RM for Bulk and Spot Demands
When we talk about managing revenue for bulk and spot demand, the basic trade-off is somewhat congruent to that of revenue management for multiple customer segments.
The company has to make a decision regarding the quantity of asset to be booked for spot market, which is higher price. The booked quantity will depend upon the differences in order between the spot market and the bulk sale, along with the distribution of demand from the spot market.
There is a similar situation for the client who tends to make the buying decision for production, warehousing and transportation assets. Here the basic tradeoff is between signing on long-term bulk agreement with a fixed, lower price that can be wasted if not used and buying in the spot market with higher price that can never be wasted. The basic decision to be made here is the size of the bulk contract.
A formula that can be applied to achieve optimal amount of the asset to be purchased in bulk is given below. If demand is normal with mean µ and standard deviation σ, the optimal amount Q* to be purchased in bulk is:
Q* = F-1(P*, μ, σ) = NORMINV(P*, μ, σ)
P* = probability demand for the asset doesn’t exceed Q*
Q* = the optimal amount of the asset to be purchased in bulk
The amount of bulk purchase increases if either the spot market price increases or the bulk price decreases.
We can now conclude that revenue management is nothing but application of differential pricing on the basis of customer segments, time of use, and product or capacity availability to increase supply chain profit. It comprises marketing, finance, and operation functions to maximize the net profit earned.