Keywords: Re-training, Workplace of the future, Social impact design
Self-service technologies and the increasing adoption of robot workers has generated widespread anxiety about job losses in the retail sector, that echoes a concern spanning industries- about the future of the workplace with the increasing adoption of automated systems. Between 6 to 7.5 million retail jobs are at the risk of being replaced due to automation over the next decade (source). Retail cashiers- and women in particular- are at the highest risk of automation.
However if we shift the focus from jobs to tasks, the landscape doesn't seem so bleak anymore. Automating parts of the process, provides an opportunity for workers to transition to customer service roles, where they may engage with individuals and enhance the overall experience (source).
Automation will not eliminate jobs, but it will create the problem of skills gaps. Employers, HR leaders, and individuals themselves will need to invest in continuously upgrading the workers’ skills to address the ever-changing needs of the industry.
To understand the domain better and narrow down aspects of the problem we wanted to tackle we spoke to 4 individuals working in industries like plumbing, food and beverages, and retail.
The workers mostly leveraged their network to find jobs
They were willing to change career paths
3 of the 4 individuals did not apply online, because they felt it would not materialize into any job opportunities
We posted three job listings on Craigslist.com, for a Home health aide (HHA), a customer service representative (CSR), and a front desk assistant (FDA) on 26th October, 2018.
The unknowns we were testing for:
Does our user (middle-skilled retail worker) search, and apply for jobs online?
Is our user willing to move to a different role in the same industry?
Is our user willing to move to a different role in an alternate industry?
We posted the jobs on October 26th, and within 15 days received 316 applications. The breakdown is as follows: HHA- 41, CSR-108, FDA- 168, Unknown- 3
People's perception of an industry matters- The least number of job applications were for the position of a Home Health Aide. Our hypothesis is that generally, these positions require standard certification/ specialized knowledge of a certain software. So, individuals from other industries, may not look for roles/ jobs in such industries- even though entry-level positions do exist.
Individuals apply for jobs in industries other than the ones they have prior experience in- For instance, only 25 of the 108 people who applied for the role of a customer service representative had related work experience. 13 individuals (out of 316) simultaneously applied to two job postings.
A wide variety of resumes and cover letters- There was no standard template/ format that individuals followed in terms of the visual design as well as the content blocks they included. Many individuals had outdated resumes, which had no relevance at all to the job they were applying for.
We created a persona and using the same basic information, drafted three different kinds of resumes. Each resume was used to apply for 10 jobs.
The unknowns we were testing for:
Does the quality of the resume affect the call-back?
Fifteen days after applying, we had not yet received a single call back. Maybe the time frame and the number of jobs we applied to were not sufficient to conclusively make any observations.
We understood the process of applying for a job through Craigslist- A lot of job postings do not specify the requirements in the title. While browsing through long lists of jobs, one clicks on a posting, reads through the description, only to realize that there are very specific skill requirements for the job or that one needs to submit say a cover letter/ photograph/ references to be considered.
After doing the experiments, we narrowed down our user to workers who use the internet to search and apply for jobs. On the basis of our research we drafted a user persona and a user journey map to isolate the pain points in the experience of searching for a job.
Our focus shifted from the mobile to desktop version since job seekers need to upload documents (like resume, cover letter, references, etc) which is tedious and time consuming to do using the phone
Through our research we discovered that the job search process is only partly about the logistics of finding a job. An important, yet overlooked, component is the emotional upheaval one goes through- the anxiety, the frustration, the fear. We decided to use a design language that was friendly, warm and encouraging.
Since it can be quite overwhelming to find a job we broke down complex processes into simple tasks- from finding references in one's network, to breaking the news to one's family and friends
Finally, because the process requires patience, and is often non-linear, it was necessary to integrate a way to visualize progress. This was done through showing the completed modules, and keeping a record of the applications, interviews, and callbacks for each candidate.
A web platform that familiarizes workers (who have been laid off) with the job search and re-training process. With a job matching algorithm at its core, it streamlines the process and breaks down what seems to be an overwhelming process (financially as well as emotionally) into smaller, actionable steps.
T.A.R.A. reduces the number of search results and gives options of alternate roles (within the same industry) as well as alternate industries where one's transferable skills can be utilized
T.A.R.A. acquaints the users to the job requirements- both general (resume, cover letter, references), and those that pertain specifically to a certain job (certifications, years of experience, preferred skills etc), and helps them fulfill it. It has a resume template system- where users can enter the details of jobs they have held and the system provides phrases/ cues they can add to their resume, a cover letter guide, as well as links to local retraining opportunities.
The process taught me the importance of designing with our users instead of for them. At the outset we wanted to build an algorithm linked to a content aggregator that would reduce the staggering number of jobs available- but it was after talking to the users that we understood how severely one's well being is affected- which led us to make major changes to our design.
If we had more time, we would have tested with more individuals and iterated on our current prototype. We would also liked to collaborate with NGOs working in this field to do a test run.