# Software Portfolio Optimization: Access Rejection versus Underutilization
## 1 Introduction
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**User Type** & **Percent** **of Users** & **Type of License** & **Percent of Total** **Licenses** & **Remarks** \\ \hline Heavy users & 25 & NNU & 75 & There are fewer licenses than users because of budget limits, but there is an option to obtain mobile NNU licenses up to four times a year. \\ \hline Light users & 70 & Concurrent & 15 & Counted as all users, including those who make use of the license for only an hour a month and those on vacation or on leave from work. \\ \hline Disconnected networks & 5 & Disconnected network & 10 & Specific licenses for specific users. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Typical distribution of users. licensing options and costs may vary depending on the specific software product and the industry in which it is being used. However, typically, the retail price of a floating license is three-four times higher than that of an NNU license. There are open-source programming languages, such as Python, that do not have licensing options like the network concurrent (floating) license or the network named user license. However, organizations that use Python for commercial purposes (e.g., organizations in the banking industry) may choose to purchase a license from a third-party software company that offers these types of licenses. For example, Anaconda a distributer of Python and R for scientific and analytic computing, offers both floating license and NNU license options for organizations. Therefore, the methodology suggested in this paper can be used for a wide range of software when an optimal choice of various license types is required. Recently, some companies have started offering cloud-based licensing options [3], which allows users to access the software through the Internet and pay for usage on a subscription basis. This can be an attractive option for companies that do not want to invest in expensive hardware and have flexible needs in terms of usage. Licenses and sublicenses can be perpetual or annual. The original software can be perpetually \"owned\" and used indefinitely with no renewal fees (increasingly less common as time passes) or renewed annually. Maintenance and support licenses are mostly annual. For example, the first year of MathWorks' software maintenance service is included in the initial purchase price. Then, after the first 12 months, licensees must pay annual renewal fees for maintenance and updates. Alternatively, with annual software licenses, maintenance and support are often included in the annual license fee. To ensure uninterrupted service, the license owner must renew the license prior to conclusion of the existing term. Otherwise, the license and/or maintenance services expire. In addition to traditional buying and building of software, firms are increasingly using powerful open-source applications [4]. Clearly, in such an environment, selecting the best portfolio of licenses, even for a single application, is not trivial; the number and types of licenses purchased can have a significant impact on a firm's IT costs and operational abilities, with potentially disastrous consequences arising from a lack of access to critically important software when needed [5]. The above notwithstanding, there is an obvious downside to buying an excess number of, often costly, licenses, to avoid denying access to software. Consequently, many firms have begun to monitor utilization of their software applications to make sure they do not purchase more access than needed, and software providers are including monitoring systems with their licenses. Emerset NetSupport DNA and FlexNet, for example, provide license-monitoring applications that firms can use when making procurement and maintenance decisions [6]. Our research takes this recent trend into account by explicitly considering underutilization as a constraint when identifying optimal license portfolios.