There are multiple approaches to pricing of information technology products and services.  Although pricing strategies differ based on whether the software or system is getting sold as a product or getting leased as a service, there are certain basic generic strategies for pricing the same. These strategies are being discussed in this article.

Cost-based pricing of technology is historically the most popular method since it relies on more readily available information from the cost-accounting system. Since often, information technology post deployment is treated with Activity based costing, while developed in-house for many firms, a cost based pricing strategy becomes extremely lucrative to developers for the simplicity of development. Cost of development of a software product is often calculated based on the COCOMO model or from the COCOMO – II model.

The problems of a cost-driven pricing strategy arise from the assumptions that must be made about product costs. But then, one needs to consider the fact that unit costs are volume dependent while fixed cost per unit is allocated such that it varies with projected volume. The allocation procedures, be they direct labour hours, or some other surrogate metric, are not very precise. Therefore, product costs are not too dependable and offer technology developers lower returns on their investments.

Another pricing strategy for software products and services is based on Function Point analysis and Full Function point analysis. Function Point Analysis is one of the most popular techniques for pricing of technology.  Function Point Analysis has been proven as a reliable method for measuring the size of computer software in terms of Kilo Lines of Code (and more recently, Millions of Lines of Code), based on which and its complexity of development the software is priced. Function Point Analysis has been established as being extremely robust in estimating projects, managing change of scope of implemented engagements, measuring productivity, and communicating functional requirements.

A few other pricing techniques are  MIPS-based pricing, tiered pricing, user based pricing, flat pricing and usage based pricing.

In a MIPS-based pricing strategy, software prices are based on the on the theoretical throughput of the system (MIPS) on which the software is running.

In a flat pricing contract, customers pay a fixed price for unlimited use of the software product. This approach enables customers to more easily predict what they will pay for the use of the software. In a tiered pricing strategy, vendors attempt to package software benefits according to user requirements and their willingness to pay. This approach to pricing is an attempt to link software product costs to perceived customer value.

In an user based pricing strategy, the customer is charged based on the number of users that utilize a collection of software features over a given period of time by assigning costs to a particular number of users or workstations and sum up individual cost allocation.

In an usage based pricing strategy, customers is charged by the vendor firm only for what they actually use on a transaction basis, during a contract period, say in months, but more popularly for larger IT firms and engagements, in years.

Today another popular pricing technique is based on the economic value that a client firm may get from a technology product or service level agreement. Such a pricing strategy is called value based pricing. This is slowly becoming the most popular pricing strategies followed in research labs for emergent technologies, like that of IBM Research, Microsoft Research and SAP labs.

However, which pricing strategy to deploy and at what stage is entirely dependent on multiple factors like whether it is a service level agreement or not, whether it is a product or not, whether it is being licensed as a technology platform to another implementer or not, which stage of the product life cycle is it into, what is its competitive scenario, what is the industry structure of the product or the nature of the industry where it will get implemented (say automobile vs telecom), is it entering a new market or an established one, etc etc.

Do let us know if you have any queries.

By Kar

Dr. Kar works in the interface of digital transformation and data science. Professionally a professor in one of the top B-Schools of Asia and an alumni of XLRI, he has extensive experience in teaching, training, consultancy and research in reputed institutes. He is a regular contributor of Business Fundas and a frequent author in research platforms. He is widely cited as a researcher. Note: The articles authored in this blog are his personal views and does not reflect that of his affiliations.