70% of Jobs Will Be Hybrid by 2029: Are You Prepared?

Recently, the Burning Glass study on the future of the job market has caused a hot discussion among training leaders and executives. The findings revealed the emergence of a new type of job – the so-called ‘hybrid jobs’ that make it difficult for companies to find the right talent for a specific position. The thing is that no industry can avoid hybridization; it’s not a temporary phenomenon. The complexity of jobs dictated by tech advancements and automation calls for similarly complex interdisciplinary skills.

Today, we’ll answer the most burning question about how companies can fill hybrid positions and ensure ongoing performance improvement even if their workforces are not ready-made with hybrid skills.

Do hybrid jobs mean there’s no right talent to bring on board?

We need to understand that hybrid jobs are not something completely new. They’ve been with us for quite a while. Let’s take a look at a salesperson thirty years ago. To be successful, they had to possess strong interpersonal skills. However, nowadays it’s not enough. To provide maximum value to customers and to keep generating new leads, salespeople also have to master their tech and analytical skills. In other words, this position now includes a range of skills that were not taught as a “single package” before. But it’s not only about salespeople. Today, hybridization is a mass phenomenon. The Burning Glass study revealed that one in eight job postings are now highly hybridized, affecting 250+ occupations. According to Forbes, in ten years, up to 70% of jobs will be hybrid, requiring both technical and soft skills for almost any position.

What’s more, Burning Glass forecasts that between 2018 and 2028 the number of jobs with the highest level of hybridization will grow by 21%, compared to 10% for jobs overall.

Matt Sigelman, CEO at Burning Glass Technologies, says that companies are now in search of candidates – purple squirrels – who possess the most unusual combination of skills and are ready to pay them up to 40% more than others. This new type of worker should be able to marry the right and left brain to bring on board a unique mix of skills. Pete McCabe, former Vice President of Global Services at GE Transportation, says he’s ready to “give my left pinky for ten more of those people who know how to plug and where to push.” The challenge is that the talent pool is scarce.

Companies understand that there are not so many readily available candidates who can think across complex systems and who have expertise in different domains. However, this doesn’t mean that hybridized positions will remain vacant. If you can’t find the right talent, you upskill your existing workforce. The Burning Glass study supports this performance improvement strategy: “Since these roles are hard to fill and often are only a few skills away from traditional roles, businesses may find greater efficiency in training up existing workers than in trying to hire afresh.”

This new era calls for a data-driven performance improvement strategy

Filling hybrid positions means finding an effective way to overcome the mismatch between workforces’ current skills and the required ones. The question becomes more complicated when we’re talking about a distributed workforce: assessing their skills and identifying gaps is much harder, as is delivering personalized training.

The answer to overcoming the lack of talent with hybrid skills is wrapped up in the smart performance enablement tool. Rallyware has been driving field performance for more than six years to help companies prepare their distributed workforce for an ever-changing work environment. So today, we want to share with you a smart way to use the data you have to develop an effective performance improvement system for the upcoming surge of hybrid jobs.

• Know the Who

When you choose a performance improvement solution (or decide to build one in-house), make sure it has a robust machine learning system to turn your data into live actionable insights. By collecting and analyzing large data sets, such systems identify each user’s current progress, their existing knowledge and skill gaps as well as potential ones. This, in turn, facilitates the development of the required hybrid skills, since the system aligns the right learning content to the right people. Call it personalized performance improvement paths.

In a nutshell, if Brad, a marketing manager, has some difficulty doing market research to assess the demand for a new product, he might receive a lesson on how to use the available company market analysis tools about which he was not aware. He’s the one who has a specific knowledge gap, so he’s the one who receives training.

• Know the What

Since the system knows each user’s progress and challenges (current or possible ones), it prescribes only the kind of learning which is required to bridge knowledge/skill gaps that stand in the way of completing a certain task or goal.

We now return to our friend Brad. A truly smart system knows that he needs to improve his market research skills. This means that Brad won’t receive learning activities on how to develop advertising campaigns or enhance lead generation. These skills are not the ones that affect market research. His learning activities will focus on helping him use market research tools to manipulate and aggregate data for his research. Brad does not have enough knowledge in using these tools, so the system sends him relevant learning modules on these topics.

• Know the When

Specific tasks for specific people are effective only when they are triggered just in time. Since machine learning algorithms predict challenges that each individual may encounter while performing a certain task, it delivers learning activities the moment they appear.

If Brad is working with a design team to create illustrations for a new campaign, he doesn’t yet need learning activities related to market research skills. Conversely, if Brad has already finished his market research and now needs to work on the budget, it’s too late to send him analysis-related learning modules. The point here is to solve any performance issues at the time of need.

Thanks to data and machine learning capabilities that help track each individual’s behavior and make smart suggestions, your performance improvement solution should be able to deliver just-in-time personalized guidance. This way, your existing workforce will master the desired hybrid skills faster and more efficiently. As a side benefit, your company will also save money on recruiting ready-available “purple squirrels” and their onboarding.

See live how the Rallyware Performance Enablement Platform can help your workforce develop hybrid skills by signing up for a demo!