Peter Bjorkman - Snow Software

Overall, license metrics have diversified from one-size-fits-all to include metrics that better fit the way modern businesses consume software. Technology developments from a variety of industries have collided, creating a highly-dynamic and flexible working environment, characterized by:

  • Mobility and constant connectivity – through advanced networking technologies
  • More than one device – as software becomes platform-independent and licenses shift to named users
  • Speed – as virtualization technologies shift IT spend from Capex to Opex and provide support for short-term business needs
  • Big data – analysis of vast data lakes that provide insight and facilitate decision making
  • Software everywhere – as all industries rely heavily on IT service and automation becomes more prevalent in white-collar workflows
  • The disruption gap – as spend decisions for technology, especially SaaS products, shift from the IT department out into business units
  • Subscription – as cloud technologies enable businesses to pay-as-they consume rather than investing up front for services they may not need in the long term
  • More with less – enabled by the ever-increasing computational power of machines.

As IoT technology matures, it too will create additional layers of complexity in software licensing. As the IoT evolves and services become chained with the potential to connect billions and potentially trillions of devices, insight and due diligence in licensing agreements is fundamental to avoid potentially catastrophic consequences associated with issues such as indirect usage.

The IoT differs from traditional software as IoT agreements and SLAs include several partners – not just the software vendor and the consumer. IoT solutions tend be multi-stakeholder including, for example, device manufacturers, operating system developers, application builders, third-party solutions, as well as providers of networking, computational, and storage capacity.

In addition, typical IoT applications involve thousands of devices – rendering device-based licensing expensive and difficult to monitor. Finally, as each IoT application is unique, standardized measurements like name-based, or power-based metrics will be useless.

To illustrate the point, let’s dive in to a theoretical use case for fitness monitors. The business model, is based on the service provider as the central negotiating party:

  • The device manufacturer uses open source software for the operating system, and as such there are no licensing cost implications. The manufacturer is free to distribute its fitness monitors as appropriate. For the purposes of this example, the service provider buys them outright from the manufacturer.
  • The service provider enters an agreement with an application builder to create and maintain a user-facing app. The agreement is subscription-based covering maintenance and upgrades. The service provider pays per app download.
  • The service provider enters an agreement with a third-party solution provider to aggregate anonymized user statistics for all instances of the application on a monthly subscription basis. The third-party solution provider also delivers storage, networking, and computational power to manage user data, as well as providing performance insight, which the service provider uses to prioritize feature improvements to the app and to develop marketing strategies.
  • To create additional revenue, the service provider sells the aggregated ‘health’ information to research institutes.
  • The service provider distributes its solution by making the device available through a web portal, including a free version of the app that provides users with access to their private information.
  • In-app purchases are available that provide users with more complex data analysis, which is provided by the third-party solution. The service provider pays the third-party provider a rolling monthly fee based on the amount of data accessed.

In this scenario, the service provider must price and package the fitness monitoring solution in such a way that all the licensing costs are taken into consideration. Advertising can be used as an additional revenue stream.

The third-party solution provider may use middleware that includes an indirect usage clause, which the service provider needs to be aware of. Changes to data protection laws may affect the way data is handled by the third-party provider, and may require app updates and opt-out capabilities. The device manufacturer may make their products available using a Hardware-as-a-Service (HaaS) model. The manufacturer may also be the service provider as well as the developer of the proprietary operating system. Hardware might be sold directly to the consumer at low cost or via a retailer. Revenue can be generated based on the data users consume or create. The possibilities are boundless.

In this use case, the service provider ultimately has control and the insight to ensure that use of software in the solution is compliant. The onus lies with the service provider to ensure that they can sell the service at a level that will cover these costs.

A smart office-climate system might, for example, combine information gathered from the sensors within a building, with outside temperature and forecast information provided by a centralized weather service, and historical performance information from the internal climate system. The hairs stand up on the back of my neck, when I think about the potential risk of indirect usage in scenarios like this one.

So, what’s going to happen? In the same way that named-user and power-based licensing metrics have evolved, a set of working models will eventually emerge for the IoT as it matures. The above scenario, where the service provider is in control, might contain license compliance, but it will limit the capability for multiple actors to share the data they create.

To solve these issues, I believe that new licensing metrics that will evolve are likely to be API-based, but the industry needs to address the issues surrounding indirect usage. According to Gartner:

Source: Gartner, Prepare for Big Changes in Software and SaaS Pricing, Driven by AI and IoT Publshed: April 7, 2017

While the full license model implications of the IoT are not yet clear, one constant will be the need for a Software Asset Management solution that provides complete visibility into all software usage and users across all deployment platforms. As IoT drives a conversion to new metrics arises, a full picture over existing investment will put you in pole position to support business unit initiatives, optimize spend, and ensure compliance.

Book a test drive of Snow License Manager today to see the full picture of all software usage and how it can benefit your organization.

Źródło: SNOW blog

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