Ninety percent of the all data in the world today has been created in the past two years. Everything we do online — from our Google searches to our Facebook posts to our online purchases — produces data. This data, in turn, provides insights into the way we think, behave and consume goods and services. It’s no surprise that the world’s most innovative companies are already leveraging this data and the insights it provides to drive engagement and profit. In fact, according to a recent TechCrunch article, organizations that rank the highest for leveraging data have:
- A return of 5 to 6 percent higher output and productivity than less data-driven counterparts.
- Higher asset utilization, return on equity and market value.
- ROI of $13+ for every dollar spent on analytics.
The world’s largest companies are leveraging data not only to make their operations more successful, but also to improve their business predictability. Here are just a few examples of data at work in the operations of category leaders:
- Sales: Major retailers like Target, Amazon and Walmart use big data to target customers with products, pricing and promotions that uniquely appeal to each potential buyer depending on his or her previous purchases, searches and interactions.
- Product development: Netflix analyzes the viewing habits of millions of global consumers to commission original programming and purchase the rights to films and series that data indicates will perform well.
- Manufacturing: Rolls Royce analyzes simulation data and information gathered from its manufacturing systems via the “internet of things” to improve the design process, decrease product development time and improve the quality and performance of its products.
- Sales: T-Mobile combines customer transaction and interaction data to predict customer fluctuations. As a result, T-Mobile USA claims to have cut customer defections by half.
It’s clear that when companies leverage data to make more informed decisions, they win. What’s not so clear is why, even in companies with the strongest data cultures, the application of data has yet to be fully integrated into workforce learning and training.
Learning Data: What’s Available
Since the learning industry began its digital revolution more than a decade ago, the technology that supports workforce training has advanced dramatically. So too has its ability to capture increasingly robust data. The industry has moved from smiley sheets and surveys to full-blown predictive analytics courtesy of AI processes such as machine learning and natural language processing.
As a result, today’s most advanced learning technologies are able to provide some pretty incredible insights. When used properly, this data can have a significant impact on business predictability. For example, learning technologies can help organizations predict:
- Knowledge gaps and where learners need additional remediation — across a class, course and individual levels.
- Whether employees and potential employees will be able to apply the critical job skills taught in training on the job.
- Where employees are likely to make high-risk mistakes and errors.
- What training can be deployed to prevent such errors.
- Which employees will be successful based on integration of data like mastery, engagement and confidence.
- Whether the company’s workforce training is successful in achieving learning and business outcomes.
- Where courses need instructional design improvement.
- Which students will drop out (significant for higher education institutions trying to improve student retention).
- Which job candidates will be MVPs for the company.
The list goes on and on.
Learning Data: What to Look for in a Technology Provider
Companies are often wowed by the amount of data that’s available and want to harness it for use in their organization … in theory. In reality, this level of data is just too overwhelming for many in L&D departments. Even in organizations with strong data cultures, most learning and HR departments don’t have the resources to analyze, interpret and make business predictions from massive amounts of training data.
To leverage the unique business insights and predictions based on workforce training data, L&D departments need learning technology partners that can help make that data insightful and accessible rather than onerous. Here are three things learning departments should look for in a provider:
- Simple delivery: While the data may be complex, its delivery should be simple. At the end of the day, learning professionals want to know how their people are performing, who is at risk and why they are having difficulty. Anything else is extraneous. Look for streamlined dashboards that show all this pertinent information above the fold. Additionally, ask to see samples to evaluate whether the data is easy to interpret, easy to share and easy to act upon. This will empower L&D to better make predictions and deliver change.
- Actionable insights: What good is employee data if you don’t know what to do with it? Training data should be actionable. For example, learning leaders don’t need to know that it took John Doe twice as long as his peers to complete a training. They need to know that he’s struggling to master concepts A, B and C so they can step in. Look for a provider that clearly flags struggling employees or those who predictive analytics demonstrate are unlikely to be able to apply lessons learned in training once back on the job. These insights can help learning professionals predict and mitigate corporate risk.
- Progressive application: Learning departments need and want data to improve their programs and courses. Look for a partner that provides detailed analyses of course performance and is able to identify patterns that indicate poorly written questions, concepts that are incorrectly weighted and areas where additional information/remediation is needed. This data makes courses stronger. It also gives learning professionals confidence that their course is optimized to achieve its desired outcomes and learning objectives.
Learning professionals have a vast amount of data at their fingertips, but they need a learning technology partner that can help them fully embrace the impact that data can have on their employees and programs. The power of the data already exists; it just needs to be better contextualized. Learning data can then deliver its true impact — helping drive business success and predictability.
Patrick Weir is CEO of Fulcrum Labs. Comment below or email editor@CLOmedia.com.Filed under: TechnologyTagged with: analytics, data, knowledge gaps, learning data, learning technologies, TechCrunch, training