In the previous article, we discussed embedded and platform analytics solutions, and how to choose the right type of system for your needs. For most organizations, embedded solutions are a good choice for getting started, but over time, platform solutions become a must due to their greater power and flexibility.
If your organization is ready to move on to a robust analytics platform, the next step is to determine how best to implement it.
Three Different Implementation Options
There are three main ways to implement your learning analytics platform.
You can build your own solution from scratch, designing it to meet your specific needs. You can implement an existing solution from a learning analytics vendor, obtaining a complete package that includes official support. Or you can modify an existing open-source system, gaining some control over the final solution without having to create the entire platform yourself.
Let’s take a look at the advantages and drawbacks of each method:
Build Your Own SoftwarePros
- Fully customized to your needs
- Complete control over code base
- Large investment of time and resources
- Maintenance and updates will be required
- May not be designed for extensibility or scalability
- Higher chance of security vulnerabilities
The first option is to build your own learning analytics platform from the ground up.
The main advantage of this route is that it gives you a fully customized solution specific to your needs. Since the L&D department will play a prominent role in the design process, you can decide exactly which features to include in the software, and users can be certain about exactly how the system will operate. In addition, you also have complete control of the code base, allowing you to make future tweaks and changes as needed.
On the other hand, creating your own solution can be very expensive and time-consuming. Once deployed, the system will continue to demand in-house resources for regular maintenance and updates. You should be sure this increased cost is worth it for the benefits gained.
Another concern is that software built in-house can often be of lower design quality than systems purchased from a software vendor, since it is not your organization’s core competency. This may result in a system that is not easily extensible or scalable over time. Or it may mean less secure software, since vulnerabilities are harder to spot without testing the system over a more diversified user base.
And if any of these problems do occur, you will have to solve them internally, without the benefit of official vendor support.
Implement an Existing SolutionPros
- Lower total cost of ownership
- Faster deployment
- Official vendor support
- Designed for ease of use
- High reliability & security
- May not be suitable for highly specific needs
- Less customizability over time
The second option is to implement an existing solution from an established software vendor.
This path has the benefit of a much lower total cost of ownership, in both time and resources. Since there’s no need to build a solution from scratch, the setup and deployment process is much faster and smoother. Once the system is up and running, official vendor support is typically available, so you do not have to devote in-house resources to ongoing maintenance.
The design quality of an established learning analytics platform is also likely to be much higher, due to significant R&D investment by the vendor. These platforms have been designed to be as easy to use as possible. They also tend to be engineered for reliability and security across a wide range of applications, and have usually undergone extensive field-testing.
The downside of this option is that your chosen platform may not provide the specific functionality you need. There is also less customizability over time, since the vendor controls the code base. So if you pick a solution that does not properly meet your requirements, there is little you can do to change the software. To avoid this problem, be sure to select an analytics solution that has been designed specifically for L&D, and that is based on a learning-specific analytics standard like xAPI.
Modify an Open-Source SystemPros
- No need to develop from scratch
- Complete control over code base
- Designed to be extensible over time
- Bugs typically fixed quickly
- Often not very user-friendly
- May not be designed for learning-specific analytics
- Lack of official vendor support
- Still requires some in-house expertise
The third option is to modify a freely available open-source analytics system.
In a sense, this is a hybrid of the first two options, since it gives you full control over the code base, without requiring you to develop the entire software from scratch. This can be an appealing choice as open-source solutions are designed to be extensible over time, giving you a strong foundation to build on. The more popular open-source platforms also tend to be quite secure and reliable, with bugs getting fixed quickly by the large developer community.
However, open-source solutions are often not very user-friendly “out of the box”, which may increase user training requirements. They also tend to be designed for general use, and may not perfectly fit your specific learning analytics needs. This could make the user learning curve even steeper, and in some cases, might make certain applications impossible without extensive customization.
Many open-source solutions also lack official vendor support, and will require in-house expertise for deployment and ongoing maintenance. As a result, the open-source route might end up costing more than an established vendor solution in the long run.
Making the Right Choice
Deciding how to implement your learning analytics platform is a major decision, with long-term effects on customizability, operational costs and usability. In addition, implementation paths vary in the time and expertise required to deploy and maintain them.
This article has given you a general understanding of each option, and should help you in making an informed decision. Remember to include your IT staff in the decision-making process, so that you know if a given option is feasible with your in-house resources.
For more information about Zoola Analytics, Lambda’s xAPI-based learning analytics and reporting solution, click here.