The information goods market has experienced a substantial change during the past decade. A lot of new platforms and products have emerged that differ in terms of user interface, cost structure and content. Among the information goods with growing importance are data analysis software programs – platforms that are able to perform complex operations and process tremendous amount of data. The most widely used data analytics tools are SAS and R. The subsequent paragraphs examine and compare differences between the two programs, followed by a prediction for the two products’ prospects.
R Programming Language
R is an open-source programming language used for developing statistical software and data analysis. Since its establishment, it has gathered an entire community of professionals and academics that contribute to its development. Consequentially, the platform is also used by a growing number of data analysts who are part of corporations or academia. One of the greatest advantages of R is that it is open to innovations. Due to its open source nature, the program offers few barriers to entry for new techniques. An individual who develops a new technique can quickly incorporate it, even if the updated version has only niche appeal. This is a great example of the long tail effect in action.
SAS Analytical Tools
The main competitor of R is SAS, a proprietary software suite developed by SAS Institute. By using SAS, users are able to perform a number of different tasks such as report writing, data visualization, operations research, project management and more. This sophisticated data analysis software empowers enterprises by helping them gain valuable insights into their businesses. Another crucial benefit of SAS is that support is provided by experienced master’s- and doctorate-level statisticians who deliver a level of service and knowledge not often found with other software vendors.
SAS vs. R – Pricing Strategies
Besides the above-mentioned dissimilarities, the two programs also differ in their pricing strategies. There is no business model behind R as it was developed for academic purposes, while SAS is a product of a for-profit organization. The incremental total cost of ownership to download, install and use R is zero. It’s completely free which provides a great opportunity for start-ups and companies looking for cost efficiency.
On the contrary, SAS is price discriminating and targeting mostly large companies. SAS achieves higher profits through bundling and generates high marginal revenue from any additional feature a customer buys. SAS Institute has high costs to develop and update the platform but its reproduction costs are modest. For example, the SAS basic package starts from several thousand dollars, a lump sum that customers pay for the first year and every additional year they pay a subscription fee of only 30% of the initial cost. The longer the customers keep the software, the higher amount of the sunk costs they will recover. Most of the products can be divided into countless modules, once the customers configure their bundle, they can request a personal quote on SAS website or negotiate the price with one of the SAS representatives. This approach would not have been possible in the past when customers had to go to a physical store and buy a CD with the software for a fixed price.
Prediction for the Future
Taking into consideration the above-mentioned differences of both programs, it seems that R has the potential to outpace SAS in the future. The open-source platform is more agile to innovation and “cutting-edge” techniques. It keeps gaining more recognition among
academics that directly translates into more graduate students with R programming skills. Due to the fact that SAS Institute offers too many different interfaces, SAS tools tend to be more difficult to integrate. On the other hand, R poses a risk of delivering inconsistent and unverified packages as there is no governing body to assure content quality. Moreover, R is vulnerable to the discretion of the community to contribute. At some point, the community may lose interest and the platform could vanish. This scenario provides an opportunity for SAS, however, SAS needs to keep up with the speed of technology advancement to preserve its market leader position.
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