What challenges do industrial employers face when developing their own workforce?

Matthew Delaney
May 10, 2019 · 4 min read

Thanks to the “skills gap”, as well as the dynamism of high-stakes manufacturing, an increasing number of employers are taking on more responsibility for training in-house and effectively “growing their own”. While this means more classroom instruction and e-learning videos, it also means more on-the-job training (OJT). Let’s unpack the challenges of running an effective program:

#1 Managing OJT is hard. When we say OJT, we are thinking of all the informal learning that happens on-the-floor and in-the-field — often between an experienced worker and inexperienced worker. In the case of a new hire, this individual is usually onboarded and given mandatory training on safety, quality, ethics, and sexual harassment in the first few days. After that, OJT begins. Here’s a simplified example that we’ve seen across aerospace, automotive, chemical, etc.:

Weeks 1–2 = Level 1: The individual is assigned a station / machine / line, and they shadow a more experienced worker. While shadowing, they are typically trained on a specific set of criteria that makes up standard operating procedure (SOP). The trainee is considered “level 1”.

Weeks 3–5 = Level 2: The more experienced worker will then give a hands-on assessment to validate the trainee’s proficiency against a set of evaluation criteria. If the trainee demonstrates their ability to perform that specific SOP, they no longer require supervision and can be scheduled on their own shifts. The trainee is now considered “level 2”. They may also be audited on an ongoing basis because skills expire and must be recertified.

Week 6+= Level 3: The trainee is evaluated again to determine if they are competent enough to train others and/or repair the machinery. In most instances we’ve seen, management will typically strive to ramp up and cross-train workers on X different skills. So in reality, many workers are going through this workflow multiple times in a short period of time as they rotate around and/or demand for different products increases/decreases. This also stresses the idea that in a peer-to-peer learning environment, workers are trainees on skills A/B/C at the same time they are trainers on skills X/Y/Z.

Everyone’s competencies — from the new trainee to the most senior veteran — are often tracked in Excel-based skills matrices. This skills matrix is the system of record for who has or does not have what competencies. It is effectively an ever-evolving inventory of skills data, which can inform a number of other operational and HR policies. We actually see many instances where each supervisor on each line on each shift manages their own matrix in their own format— and there is no master matrix. More on this in the future.

It is also important to layout the full OJT workflow above because taking on more responsibility for training in-house and effectively “growing your own” requires a ton of time, resources, and know-how. In our brief example above, the employer requires content (training instructions and evaluation criteria), they must know who can train and evaluate, they must assign trainings and trainers, they must coordinate evaluations, they must capture and track data across roles / departments / locations, they must provide remediation, etc. If it is an apprenticeship, they are likely also tracking school registrations, grades, absences, etc. OJT is a significant undertaking and today, it is typically done manually / offline.

#2 New competencies are a wildcard. This is less of an issue for manufacturers that have been producing the same number of the same kind of widgets on the same machines for the last 30 years. But if an employer is investing in automation (e.g., new robots), developing new products, opening new facilities, selling to new customers, facing new regulations, or has any other element of change, they are likely evaluating what skills the business requires. The next challenge is figuring out what skills and capabilities the company currently has and then determining who to upskill/reskill and how. If your competencies are changing, how do you even train the trainers? At this point, there are often more questions than answers.

#3 LMS’s leave a lot left to be desired. Learning management systems (LMSs) are well-designed for classroom management and elearning. However, they are not built to support the day-to-day workflows on-the-floor or in-the-field across multiple stakeholders required in OJT. They may serve as a database for who has what certificates, but they do not track who has what task-specific competencies. The difference here may seem subtle, but a senior engineer at an aerospace manufacturer recently explained it like this: “You may have a internal or external certificate that says you know how to change the oil of automobile, but does that mean you can get the job done if a big rig rolls up, or a motorcycle, or a luxury sports car?” To capture this granular data, you need to embedded in the workflow. It would be unreasonable to require senior production team members to manually log each and every activity.

#4 Limited data to make decisions. Because the OJT workflow happens manually offline and then competencies are tracked in Excel-based matrices, there is very limited visibility into real-time data. This is a particular pain because 1) competency data could help supervisors making daily schedules and managers forecast workforce needs and 2) time-stamped operational data could help training leaders accelerate the time-to-productivity and save costs.

In-house technical training requires time, resources, and know-how — all of which can be in short-supply for many dynamic industrial businesses. Our goal is to continue to shed light on these processes and share innovative practices and solutions we encounter.

Covalent Networks

Equipping people and organizations with in-demand skills

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