Automating Skills Assessment

Successful organizations are excellent at leveraging their internal talent. They work to apply the right set of employee skills to tackle every challenge. But to do this effectively, they need a solid understanding of the skills within their workforce.

Keeping track of employee skills is particularly challenging in the information technology space. Ever changing job requirements drive people to constantly adapt their technical skill sets. Software developers need to learn new technologies in big data, machine learning and mobile development, just to name a few. Keeping track of how a large team develops these new capabilities is no easy feat.

Skills data is usually collected through a combination of self reporting and manual assessment. In other words, asking people to tell you what skills they have. These methods are slow, expensive and deliver unreliable results.

Many organizations have a poor sense of their employees' capabilities.

You may ask whether someone has skills in Java development but how do you tell how deep and recent their knowledge is? Resumes tell you some part of the story but they are obviously a biased and rapidly outdated view. What about all the new skills people are learning on the job?

As a result, many organizations have a poor sense of their employees' capabilities.

By analyzing the work people do, we automatically infer the skills they are using.

We think there is a better way to track employee skills. By analyzing the work people do, we automatically infer the skills they are using. Worklytics analyzes software development and collaboration work, completed in common productivity tools, to determine peoples' technical skills.

Key management with Google Cloud KMS

Gathering data on technical work stored in cloud-based productivity tools

Here's how it works

We start by determining the amount of time people spend using different technologies in their work. This includes the use of specific development languages, frameworks and data storage technologies.

Key management with Google Cloud KMS

Worklytics Analyzes the amount of time people spend doing different types of work

This information is then mapped to a skills taxonomy for common technical roles such as software and data engineers. These may be general industry-level skills (Java, C#, Angular.js etc) or skills specific to an organizations internal technologies.

The result is an output of the total number of hours employees have spent using different skills. We perform this analysis retroactively, to look at an aggregate of skills used over the past few years. It can also be run on an ongoing basis, to track new skills being learnt and applied to work.

Key management with Google Cloud KMS

Aggregate of skills used by a single software developer

Resource Planning with Skills Data

We are working with organizations on several uses for this skills data. These include:

  • Resourcing for internal and external customer projects
  • Workforce planning
  • Tracking of learning and development initiatives
  • Tracking of internal knowledge

We work with organizations to build internal skills repositories. Skills data is either delivered through our social interface or directly to customers' existing intranets and skills repositories. As we detect the use of skills, we automatically update internal employee profiles. These updates can be completely automatic or prompt employees for approval, before listing new skills.

Key management with Google Cloud KMS

Internal social interface with profiles for employee skills

Reports aggregate skills by team, department or business unit, to facilitate effective resource planning. These reports can be completely anonymized and shared throughout an organization. We also work with organizations to provide custom analysis of internal skills, including identifying knowledge centers, key influencers and skills gaps.

Key management with Google Cloud KMS

Workforce planning with aggregates of skills used by a team of software developers

Tracking Soft Skills

It may seem that this sort of analysis is only suited to technical skills but that is not necessarily the case. In many cases it is in fact possible to track certain soft skills. The primary limiting factor is whether skills are applied to work performed in cloud-based tools or not.

The fact is that more and more work, such as project management, sales, customer support and collaboration is tracked in cloud tools. For now our focus is on mapping technical skills. But, in future, it will be possible to analyze a continually larger set of employee skills.

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