When choosing an RPA technology, it’s important to think about licensing. License models in RPA are tremendously diverse across the vendor landscape, making it impossible to compare on a similar basis.
When we talk about licensing from AssistEdge 18.0 point-of-view, the licensing concepts can be broadly classified under the below categories:
Named User: This type of license is mainly for attended robots (Robots which are triggered by a user on need basis or need a human intervention). It enables him or her to register any number of robots on any machine, as long as the same active directory username is present on all of them. The user is not allowed to use multiple robots simultaneously.
Concurrent User: A type of license that helps users that work in shifts, as licenses are consumed only when you in fact want to use a robot. Multiple robots can work on the same license provided that there is only one bot running at a given instance.
Number of Bots: This type of license is mainly for unattended robots (Robots that run independently based on the schedule, mostly on virtual machines). Primarily, only 1 robot can run on 1 license, and it can run any number of times. For simultaneous execution, multiple licenses would be required based on the number of bots that are running simultaneously.
“Personal bots work on employee’s machine, mostly in attended form and perform tasks for the employee — pulling data from multiple sources to create reports, storing client contact data and even creating regular presentations.
Personal bots can be looked at as a digital concierge for employees in an organization. Through advanced mobile interface and virtual assistants, employees can interact with these personal bots installed on their office machines/systems. The personal bot triggered on-demand or scheduled by the employee, can perform tasks on behalf of the employee, even in his/her absence. Just like a digital concierge, this personal bot on the employee’s machine will be well-equipped to take requests and execute.”
When thinking of licensing models for personal bots, the below models can be considered:
Pay-as-you-go Licensing Model: A Consumption-based pricing model, that is, you pay for what you use can be considered as the most suitable. A mix of named user and concurrent user licensing would be an ideal prospect for personalized bot licensing model i.e. to calculate the runtime hours of a robot and charge on per hour basis. In case more than 1 personal bot is required to run concurrently, then charge on per hour basis for each bot. Since a personal bot is not expected to run unattended or run 24 X 7, it’s only meant to do tasks such as pulling data from multiple sources to create reports, storing client contact data and even creating regular presentations, which require it to work for a specific period of time.
Per bot/per user Licensing Model: In per bot licensing model, charges are based on the number of bots utilized to execute a process i.e. 1 license for 1 personal bot whereas, in per user licensing model, license is allocated based on the number of users, in which a user can use any number of bots provided, multiple robots do not run simultaneously.
Enterprise Licensing Model: An enterprise-wide license for personal bots can be considered as one of the models. For illustration purpose, let’s say a client is interested in implementing personal bots at a large-scale but is not sure about the number of personal bots required. In such an instance, an enterprise-wide license can be purchased by the client, and he can up-scale as per requirement at no extra cost.
Cloud-based Licensing Model – The cloud service offers a quick and convenient way to begin using robotics. Introduction of a pre-built and optimized cloud service is easier and faster than using an on-premise solution. If the client already uses public cloud, the next step is to take the RPA service also to the public cloud, in which case, the cost level will further decrease. This functionality can be extended to personal bots as well. When a client starts using the cloud service, the personal bots will be quickly available at the user’s service with some pre-built functionalities. Also, personal bots can be used even if the person is offline or wants to run it remotely from a mobile device, provided the data is exposed to the cloud.
Also, everyday work may vary each day for a person. Sometimes the workload can be high, which might result in a need for scaling up the number of bots, and other times, there could be a lower workload, which might result in low utilization of the bot. The licensing model should be such that it should cover the above-mentioned aspects as well. The model should provide flexibility to scale up and scale down the bot usability, and the license charges should be such that the person should pay only for the time he has utilized the bot.
Deep thought should be given to the cost of the license for the personal bots. A lot of factors need to considered when calculating the cost, given the fact that it’s a personal bot doing tasks on employees machine and not residing on an application server like the traditional digital worker which is developed under enterprise licensing cost.
We should remember that the personal bot is not to replace the human but to replace the simple repetitive and manually intensive tasks that a human performs in day-to-day life.