How to improve job search
With 87% of the workforce disengaged at work (up from 70% previously) and 63% of CEOs calling availability of skills a serious concern (up from 58% previously), it is easy to argue that today’s methods for connecting talent with work leave significant room for improvement.
With 87% of the workforce disengaged at work (up from 70% previously) and 63% of CEOs calling availability of skills a serious concern (up from 58% previously), it is easy to argue that today’s methods for connecting talent with work leave significant room for improvement. Furthermore, as these trends evolve, but job discovery models do not, the gap between what we have and what we need is widening.
We believe the most impactful way to solve this problem is by bringing more data into the process. Today’s methods for matching talent with work are weak because they are based on so little data.
The prevailing model for hiring a role today is the employer creates a 1 page text document with a job title; 3-4 structured attributes such as location, contract type, salary range; then 2-3 sections of text for job responsibilities, candidate requirements, and sometimes a paragraph about the employer.
The listing is published to the company’s jobs page and appears on job boards and aggregators.
Candidates search for “what” (job title) and “where” (location) and receive thousands of results. In London, a search for Sales Analyst on top job aggregator Indeed today returns 3,250 results, Agile Project Manager returns 3,961 and Operations Manager returns 21,035.
At this point, the candidate has to decide which listings to explore further, and which to apply to. But on what data are they basing this hugely impactful decision? The results say “sorted by relevance” but the job board doesn’t know anything about the candidate and the only input was 2-3 words of a job title and location, so how is relevance determined?
Job boards use the same search model as Google: a word search string produces results ranked by relevance. But with Google, this works because of the vast network of outbound/inbound links and billions of clicks per day that help them determine PageRank. On a job board there is no such intelligence engine in the background, yet the site is trying to do the same. The result is that the list the candidate sees is almost random.
If we look for what is actually important in creating a successful match, a recent Intelligence Group survey on Millennial workers gives some useful guidance:
- 64% say it’s a priority for them to make the world a better place,
- 79% want a boss who serves as a coach or mentor,
- 88% prefer a collaborative work-culture rather than a competitive one,
- 74% want flexible work schedules,
- 88% want “work-life integration”.
These are high percentages. So where are these parameters and attributes in an average job requisition? And how are they factoring into job boards’ algorithms for “relevance”? The answer is they are not. And to get people into the right jobs, these and a slew of other parameters must become visible, searchable, sortable and rankable by candidates in their search process. The good news is that the best companies all want to share this information. They’ve worked hard to make their culture compelling, and they want to tell you about it.
Craft’s approach is fundamentally different because we are an index of companies not an index of jobs. On Craft you can search for companies that solve a particular problem, are of a particular size, stage, financial profile, offer remote work opportunities, and many more contextual parameters.
Once we have narrowed a search to a target group of interesting companies, then we start looking at individual jobs there, which may already appear as a job listing (which our job aggregator pulls directly from the company’s jobs page), or it may be an emerging (not yet published) opportunity, such as a news announcement that the company is opening a new office in New York and will be hiring 15 sales and marketing roles. Then, we work to figure out who is the boss for this position, finding their professional bio, their twitter stream, perhaps a video of them speaking at a conference - all data to help answer: is this someone you’d want to work for?
As the Intelligence Group’s survey said:
Millennials are … not looking to fill a slot in a faceless company … They’re looking strategically at opportunities to invest in a place where they can make a difference, preferably a place that itself makes a difference.
That is the right way to go about a search - focused on the company, not a job title. Enabling that type of search and uncovering those strategic opportunities is what Craft is here to do.
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Craft is a free, open information platform mapping the Innovation Economy. We provide data on dynamic sectors, companies, teams, people and open positions.
Our goal is to provide Context in a rapidly changing landscape and help professionals discover and evaluate different opportunities. Our data can also be used for market research, lead generation and competitive analysis.