Today, employer’s primary interest is to find the best person for the job. They have time constraints to put right effort to hire talent and the educational institutions are not providing them with precise metrics to explore. They lack the advantage of data and depend on the intuition of the decision makers.
The corporate recruitment team asks the decision maker to help them in recruitment and the quality bar of completed student output. The decision maker has time constraints and observes that best accountants and engineers came from a specific institution (brand) and flock to that institution. They know this might not be the best approach. The decision maker recommends the recruitment team to follow minimal risk approach, fire from branded institutions and institutions where they studied.
Following the same approach over years, the power of the alumni increases and the institutions visited by corporates become branded ones. Students wants to get jobs paying higher salaries and do not care for institution’s learning methods and join the institution that has placement. The historical perception of branded institutions has made whole thing a mess. There is clear lack of transparency and that is problem.
An educational institution offers a primary outcome and secondary outcome. The primary outcome is to facilitate learning for student and enable students to understand requirements of career post the learning period and also make them matured for life. The secondary outcome is to research, networking, extracurricular activities, and job placement. Today there are a lot of initiatives to bring a change in the secondary outcome including social networking channels, self-learning on-line programs, MOOC, online career assistance and remote learning.
A good start indeed. The initiatives also needs to focus on the primary outcome of employ-ability and cover both fresh jobs at graduation of a student and help student to increase their ability to chart their careers with evolving industry needs. To solve the problem, learning approaches need to measures learning parameters and provide transparency in measurement to remove the bias and create comfort for the stake holders. Start developing metrics and mature methods to capture metrics is one strategy to solve the problem.
- Focus on what can be measured. Do you want to focus on the skill that can be measured or just soft skills that is not easy to measure?
- Start the process where it is easier to measure and where even minor differences matters to employers. Computers can be enabler in this process.
- Focus on areas where learning outcomes are measurable. Already computer science learning is measured. Identify other entry level jobs that are performed on computers. Here comes finance, accounting, banking and insurance.
- To make the data collection strong, the data set needs to be correlated with the data sets of the corresponding skills required for most entry level jobs in the minds of employers. The stronger the correlation, the importance of students trained in this approach increase.
While alumni brand matters to people, recruitment teams will consider another candidate on being convinced that another candidate is stronger. The another candidate needs an alternative credentials to demonstrate that he could perform the necessary work exceptionally well. When the data driven educational institution comes, the biases will break down. Employers should be able to view the metrics and also trust the metrics and the metrics need to lead the recruiter to think of hiring the applicant from the non-elite brand.
If educational institution is newly started one and lack strong placements, go on-line, take control of the data and get control of your situation.
- Create accurate, real-time data sets around learning outcomes. Make sure the outcomes are inevitable.
- Be transparent with the approach to measure the learning outcome
- Start measuring learning outcomes and record them.
- Make the learning outcome available on-line and create transparency by providing access to corporates.