Advice

How to Make Data-Driven Decisions to Ensure Online Training Growth

One of the most important aspects of business growth is self-awareness. Knowing your own strengths and weaknesses is a valuable trait to have in order to improve. It is also important for leaders to know the strengths and weaknesses of their team to know where improvements need to be made.

In an ever-changing world, learning new skills is needed now more than ever, with thousands of new technologies arising every year. The online training industry is growing and could reach over $300 billion by 2025.

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With everyone interacting over cloud communication platforms, it is harder for leaders to assess employee development.

Challenges in online learning have grown along with online learning itself. Luckily, using data to ensure employees grow from online training can take some of the stress away that comes with going with your gut. But what are data-driven decisions? And how are effective data-driven decisions made?

What are Data-Driven Decisions?

Data-driven decisions are exactly what they say on the tin—using various forms of data to help make business or training-related choices. In business, there are only a few main precursors to decisions being made: Gut instinct, prior experience, or data.

Data has many uses in business, it can help increase profits, save time, and prevent the waste of valuable resources.

Data is everywhere, such as the performance of marketing campaigns, employee salaries, and the latest online sales figures. With technological growth, all of this data can be carried around in your pocket in the latest business phone apps.

Knowing how to utilize the many types of data to make the most out of online training platforms is a key to success.

Types of Data

Knowing what data to collect is one of the first considerations. Collecting every type possible could cause burnout, and time being wasted on collecting data you might not need.

Predictive Data

This shows what is expected to happen. For training, it could tell you, for example, an employee’s predicted customer satisfaction score based on previous performance.

Comparing predictive data to an employee’s actual performance on tasks could provide valuable insights into where to focus training efforts.

Descriptive Data

This tells you what has happened/is happening. This could be the description of events that took place during a phone call with a customer.

Utilizing this type of data in a transcript could help to pinpoint areas that an employee needs to improve on.

Diagnostic Data

This tells you why something happened. For example, if all employees have performed poorly on a certain training module.

It could include key events in the workplace that made an impact on the output. A drop in profits during one month could be explained by increases in server cost – an issue that training can’t fix.

Prescriptive

Prescriptive data explains how the data could be improved if certain solutions are implemented. In a call center, an example could be to increase the advertising of loyalty offers. It could be assessed through crowdtesting and become the main focus of an online training course.

Different types of data may require more complex analysis. However, if executed properly, a more detailed analysis could bring greater value to your business.

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When Making Data-Driven Decisions

Look for Patterns

Any leader needs to understand that the data is only as good as the person analyzing it. Spreadsheets could point out that all employees are failing in a specific aspect of their job, but without someone to realize this pattern, the data is useless.

If the data is telling you that the majority of employees are not confident advising customers on a specific product, this could be the focus of online training modules.

Use up to Date Data

Using statistics from 2016 to guide training efforts in 2021 is a fruitless endeavor. Many employees may have moved on from the company. The employees that are still around may also have learned brand new skills in which they may not need additional training.

Use data, such as contact center analytics, from over the past 12 months to guide training efforts, as it could also include any new products or services on offer.

Check Decisions Against Original Goals

After all the data has been collected, go back and make sure the decisions being made align with the goals you had from the beginning.

One goal could be to train every new employee to deal with one new product. Have you selected enough training material to achieve this? Are you gathering the right types of data to help you fully monitor everyone’s progress?

Utilize Qualitative Data

This usually appears in the form of verbal or written responses, this can be obtained through video calls or group discussion sessions. If one employee has a low customer satisfaction score compared to another, qualitative data could help you fully understand the reasons why.

An interview could show that particular employee getting more angry customers or fewer customers wanting to fill out the customer satisfaction survey.

While numerical statistics (quantitative data) show rates and scores, interviews or a transcript from call quality monitoring can help obtain a much clearer idea of what is going on behind the scenes of statistics. There may be problems that can’t be solved by corporate training, such as mental health issues.

Have Benchmarks and Goals

Setting benchmarks is important to know when decisions need to be made. The online training could include a questionnaire, and if an employee scores lower than the threshold, then appropriate training should be given.

Benchmarks could show how previous employees or management performed as a comparison. Alternatively, they could show how competing businesses performed in the same online training course, which could be used as a comparison to your employees.

Use the Right Tools

Yes, a poor workman blames his tools, but having the right data analysis software could mean the difference between a good and fatal decision.

Being able to use techniques such as dialing out to all employees involved in the same training module means that they can all be contacted at once, instead of having to wait for everyone to individually join the call.

Analyze Properly

Large amounts of data flow in and out of businesses every day. Therefore, it is important to invest enough time and money in analyzing the data properly to ensure the greatest growth.

Using inaccurate analysis to make decisions could lead to wasted efforts and a loss of revenue. Designing an online training course based on incorrect data about your workforce won’t achieve results.

In 2018, using data analysis for decision-making was the highest-ranking priority for marketing strategies. A focus labeled as being this important should be carried out to the highest of standards.

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Utilize Pie Charts & Graphs

It is always easier to read data when it is presented visually instead of as hundreds of rows and columns of numbers on Microsoft Excel. It’s far easier to understand data when presented in a way that anyone can understand with a quick glance.

Having employee performance laid out in a bar chart could help easily show the difference between predicted and actual results. Pie charts could be useful to show the percentage of employees that scored within a certain percentile group.

Don’t be Afraid to Re-Evaluate

It is never a bad idea to take time to go back through the data you have collected to make sure you’re on track. Going in with a fresh mindset from the beginning might make you think of something you missed the first time around. Perhaps the new strategy might turn out better than the first.

Perhaps on a second look, you realize there are better training modules. Maybe you discover that two of the training modules could be replaced by one more effective module.

Note Successes and Failures for Future Growth

Don’t just learn from mistakes, learn from successes. Take notes on what worked throughout the process so you can repeat the right elements for future online training courses. Also, note down what could be improved for next time so the process may not take as much time.

Did all the employees respond well to the online training or feel it was effective? Could you have collected the data any quicker? Did you use the right learning management software to host the online training?

Conclusion

Utilizing data has many advantages. It can speed up the decision-making process as long as the right data is collected and analyzed properly.

Be selective about what types of data you are collecting. Only collect the data that matters most to your online training efforts to achieve maximum efficiency and growth.

 

 

Author bio

Jenna Bunnell is the Senior Manager for Content Marketing at Dialpad, an AI-incorporated cloud-hosted unified communications system that provides phone forwarding services for business owners and sales representatives. She is driven and passionate about communicating a brand’s design sensibility and visualizing how content can be presented in creative and comprehensive ways. Here is her LinkedIn.

Mercy - CBNation

This is a post from a CBNation writer. CBNation is a Business to Business (B2B) Brand focusing on increasing the visibility of and providing resources for CEOs, entrepreneurs and business owners. CBNation consists of blogs(CEOBlogNation.com), podcasts (CEOPodcasts.com) and videos (CBNation.tv). CBNation is proudly powered by Blue 16 Media.

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