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Demand optimization is the application of processes and tools to maximize return on sales. This usually involves the application of mathematical modeling techniques using computer software. [1]
It has particular applications in retail, where merchants wish to identify the best combination of price and promotion to achieve desired sales, gross margin, inventory or market share objectives.
The methods used are similar to those applied in the related field of supply chain optimization, where mathematical algorithms are applied to large databases of sales data to help predict future outcomes. In the case of demand optimization, as well as in house sales history, there may be competitive pricing information.
Because it is still a new field, authoritative data on the benefits of demand optimization is not widely available, although suppliers offer case studies of early adopters which claim rapid return on investment, especially in the optimization of the timing and level of price markdowns.
Microeconomics is a branch of mainstream economics that studies the behavior of individuals and firms in making decisions regarding the allocation of scarce resources and the interactions among these individuals and firms. Microeconomics focuses on the study of individual markets, sectors, or industries as opposed to the national economy as whole, which is studied in macroeconomics.
Mathematical optimization or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.
Satisficing is a decision-making strategy or cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met. The term satisficing, a portmanteau of satisfy and suffice, was introduced by Herbert A. Simon in 1956, although the concept was first posited in his 1947 book Administrative Behavior. Simon used satisficing to explain the behavior of decision makers under circumstances in which an optimal solution cannot be determined. He maintained that many natural problems are characterized by computational intractability or a lack of information, both of which preclude the use of mathematical optimization procedures. He observed in his Nobel Prize in Economics speech that "decision makers can satisfice either by finding optimum solutions for a simplified world, or by finding satisfactory solutions for a more realistic world. Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science".
In economics, profit maximization is the short run or long run process by which a firm may determine the price, input and output levels that will lead to the highest possible total profit. In neoclassical economics, which is currently the mainstream approach to microeconomics, the firm is assumed to be a "rational agent" which wants to maximize its total profit, which is the difference between its total revenue and its total cost.
In computer science, local search is a heuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution maximizing a criterion among a number of candidate solutions. Local search algorithms move from solution to solution in the space of candidate solutions by applying local changes, until a solution deemed optimal is found or a time bound is elapsed.
Managerial economics is a branch of economics involving the application of economic methods in the organizational decision-making process. Economics is the study of the production, distribution, and consumption of goods and services. Managerial economics involves the use of economic theories and principles to make decisions regarding the allocation of scarce resources. It guides managers in making decisions relating to the company's customers, competitors, suppliers, and internal operations.
Vendor-managed inventory (VMI) is an inventory management practice in which a supplier of goods, usually the manufacturer, is responsible for optimizing the inventory held by a distributor.
In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear.
Yield management is a variable pricing strategy, based on understanding, anticipating and influencing consumer behavior in order to maximize revenue or profits from a fixed, time-limited resource. As a specific, inventory-focused branch of revenue management, yield management involves strategic control of inventory to sell the right product to the right customer at the right time for the right price. This process can result in price discrimination, in which customers consuming identical goods or services are charged different prices. Yield management is a large revenue generator for several major industries; Robert Crandall, former Chairman and CEO of American Airlines, gave yield management its name and has called it "the single most important technical development in transportation management since we entered deregulation."
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient algorithm that solves these problems in polynomial time. The ellipsoid method is also polynomial time but proved to be inefficient in practice.
Supply-chain optimization (SCO) aims to ensure the optimal operation of a manufacturing and distribution supply chain. This includes the optimal placement of inventory within the supply chain, minimizing operating costs including manufacturing costs, transportation costs, and distribution costs. Optimization often involves the application of mathematical modelling techniques using computer software. It is often considered to be part of supply chain engineering, although the latter is mainly focused on mathematical modelling approaches, whereas supply chain optimization can also be undertaken using qualitative, management based approaches.
The following outline is provided as an overview of and topical guide to finance:
Economics education or economic education is a field within economics that focuses on two main themes:
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.
Marketing mix modeling (MMM) is statistical analysis such as multivariate regressions on sales and marketing time series data to estimate the impact of various marketing tactics on sales and then forecast the impact of future sets of tactics. It is often used to optimize advertising mix and promotional tactics with respect to sales revenue or profit.
Price optimization is the use of mathematical analysis by a company to determine how customers will respond to different prices for its products and services through different channels. It is also used to determine the prices that the company determines will best meet its objectives such as maximizing operating profit. The data used in price optimization can include survey data, operating costs, inventories, and historic prices & sales. Price optimization practice has been implemented in industries including retail, banking, airlines, casinos, hotels, car rental, cruise lines and insurance industries.
Mathematical economics is the application of mathematical methods to represent theories and analyze problems in economics. Often, these applied methods are beyond simple geometry, and may include differential and integral calculus, difference and differential equations, matrix algebra, mathematical programming, or other computational methods. Proponents of this approach claim that it allows the formulation of theoretical relationships with rigor, generality, and simplicity.
Pricing science is the application of social and business science methods to the problem of setting prices. Methods include economic modeling, statistics, econometrics, mathematical programming. This discipline had its origins in the development of yield management in the airline industry in the 1980s, and has since spread to many other sectors and pricing contexts, including yield management in other travel industry sectors, media, retail, manufacturing and distribution.
Portfolio optimization is the process of selecting the best portfolio, out of the set of all portfolios being considered, according to some objective. The objective typically maximizes factors such as expected return, and minimizes costs like financial risk. Factors being considered may range from tangible to intangible.
In microeconomics, a monopoly price is set by a monopoly. A monopoly occurs when a firm lacks any viable competition and is the sole producer of the industry's product. Because a monopoly faces no competition, it has absolute market power and can set a price above the firm's marginal cost.