SkillSet

Design and delivery of a learning management system

Delivered for WHYTE AND MACKAY

AT A GLANCE

  • Design and delivery of Moodle LMS.
  • Single sign-on.
  • Tailored user training.

THE CLIENT

Whyte & Mackay is an award-winning whisky maker, with five distilleries across Scotland. These distilleries produce exceptional whiskies and premium spirits, which are celebrated around the world.

THE CHALLENGE

Whyte & Mackay sought a professional learning management system provider to design, develop, and deliver of a platform for training line managers.

Key requirements included:

  • Integration with Whyte & Mackay’s authentication system.
  • Face-to-face bookings and tracking.
  • Forced progression through the courses.
  • Bespoke progress visualisation.

OUR APPROACH

SkillSet proposed a Moodle learning management system to satisfy Whyte & Mackay’s needs. It is the world’s most popular learning management system with more than 100,000 installations worldwide. Moodle is an open-source system but supported by a dedicated team of developers based in Australia. SkillSet currently hosts and supports Moodle for over 20 clients.

Moodle is compatible with all common browsers (including Chrome, Firefox, Safari, and Edge), running on all common platforms. Users can access content material on a full range of devices: PCs (including Windows 10), mobile phones, tablets, laptops etc.

SkillSet worked to an ADDIE (Analyse, Design, Develop, Implement, Evaluate) methodology. Each stage was signed off before progressing to the next, to ensure that the project met Whyte & Mackay’s requirements.

Analyse – SkillSet verified the project requirements, defined system roles and permissions, and mapped out the initial course hierarchy.

Design – SkillSet used the Whyte and Mackay branding and style guides to ensure that the learning management system blended seamlessly with its existing websites. Learning report contents and integration requirements were documented.

Develop – The Moodle platform was built using the outputs from the Analyse and Design stages. A staging platform for testing was also set up, replicating the live platform.

Implement – The whole system was tested by a small number of Whyte and Mackay staff, using example courses on the staging system. Once approved, the solution was migrated to the production environment for final testing and sign-off.

Evaluate – SkillSet continue to monitor the system for any potential issues. We also provide help in creating reports and management information.

The system is hosted in an AWS data centre in the UK. Both AWS and SkillSet are ISO27001 certified. The system also complies with GDPR/DPA 2018 and all other relevant data security legislation.

SkillSet utilise the AWS Cloudwatch monitoring tools for all the hosted system components. This alerts us if there are any issues with running services, memory/CPU/disk usage, or errors encountered on the servers.

SkillSet also provided training, tailored to different user groups and covering the following topics:

  • System administration
  • User administration
  • Content creation and upload
  • Reporting

THE RESULTS

Having completed an initial pilot in spring 2021, Whyte and Mackay is now looking to roll-out the LMS to the entire business as part of its digital strategy. This includes a bespoke dashboard. This allows managers to log into the platform and see a “My Staff” overview block on the homepage. This then gives them information such as their direct reports’ last log-in, assigned courses, and progress.

OUR PARTNER’S FEEDBACK

“When searching for the right supplier for this project, I spoke to around five others, who were all non-integrated and did not have single sign-on capabilities. Whereas SkillSet ticked all the boxes for us, particularly for the price. It was clear from the outset that SkillSet could meet our project needs. It felt really easy to work with Jemma, and also the proposed solution suited us in terms of its simplicity and user-friendly system.”

LAURA HENIGHEN, learning and development business partner

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