October 4, 2022

What Makes a Great Analytics Enablement Program?

By Johann Carreno

With the abundance of analytics training platforms available in the market, it is easy for buyers to become overwhelmed with choices. When you pair that with how time-consuming these programs can be, it’s extra important to invest in a quality analytics enablement program that’s going to deliver results back to your business.

While there’s no definitive golden rule that separates solid analytics learning platforms from poor ones, we do see a pattern with three components that more often than not lead to successful outcomes.

In this blog, we’ll explore those three key components that make an analytics enablement program great. 

Content is Highly Relevant and Rigorous

The first pillar of a good learning experience is excellent content. While simple and apparent, this is often overlooked. The ideal course content should be:

  • Highly relevant to the learner’s needs
  • Clear with defined learning outcomes
  • Full of opportunities for practicing the topics learned 

Many online platforms have good content but lack relevancy. Have you ever taken a class that wasn’t relatable to your major/job? Or taken a class with concepts that you’d never be able to apply to the real world? We’ve all been there before. 

The key is learning with content that is relevant and applicable to the learner’s job.

For example, the ideal class courses would require learners to apply the concepts presented in the class in a real-world setting with ample opportunities to practice and test their skills. 

In the example below taken from Data Coach, students are required to work with their own data and within their own environment to practice the skills being learned. The course content includes practice exercises, assessments, and capstone projects that require learners to demonstrate the skills they have learned from the course. 

A screenshot taken from Data Coach's course library

Feedback is Incorporated

Another vital component of any learning experience is feedback, more so when working with the ever-changing landscape of analytics

Not all feedback is created equal. The right type and quantity of feedback matters. 

Providing too much information to a learner, to the point where you are giving away the answers, creates dependence and doesn’t equip them to develop problem-solving skills. Provide too little feedback, and you’ll frustrate the learner into giving up and eventually stop trying.

What about the quality of the feedback? All feedback given to a learner needs to be specific and targeted at providing them with growth opportunities. Validation is excellent and should be included, but the best feedback focuses on helping the learner understand how to take their skills to the next level.

The context of the feedback given to a learner is vital. While the chatbots and community pages on learning sites have improved vastly over the years, they only provide generalized answers better suited for procedural steps (how to export a file) and do not help the learner with decision-making. 

Nothing beats the ability to work with an instructor or a coach who can rely on their knowledge and experience to evaluate the problem at hand and provide the learner with specific and relevant feedback. 

You may be looking into live boot camps which give the learner direct access to work with an expert instructor when they need it. But keep in mind that once the boot camp is over, learners will still have questions and need feedback in order to be successful.

Transferable Skills

We recommend you also consider how a learner will be able to transfer the skills learned in the course(s). Skill transfer, which is the ability to take the information learned in one context and apply it in a different context (i.e., classroom to work environment), is one of the most complex challenges that digital learning programs have to overcome. 

By design, digital learning programs address the needs of a very broad audience. 

The best programs present the learner with high-quality course content, practice problems, quizzes, and examples to help the learner make sense of the information being presented. Still, they can’t help the learner experience the nuances and challenges of working with their data and in their own environment. 

So when selecting an enablement program, it is imperative that the projects and demonstrations of learning make the learners use their own data and work within their environment as much as possible.

The Data Coach Approach

If you have read this far, you may have already realized that finding a program that addresses these three considerations is a pretty tall order. Fortunately, the learning landscape has begun to evolve and solutions like Data Coach have been designed to address these and many other components of an effective learning program.

Data Coach combines the flexibility of self-paced learning with the guidance and support of our experienced coaches, who provide technical expertise through 1-1 live coaching to solve problems, get feedback, and remove blockers for learners. 

Data Coach is also focused on providing real ROI and preparing learners to work with their data and within their environment. The capstone projects learners complete within our courses ensure that they gain academic skills while also creating a solution to an existing need within their organization. 

If you’re interested in building a successful data-literate workforce, give Data Coach a try!  

Data Coach is our premium analytics training program with one-on-one coaching from renowned experts.

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