Job descriptions can reveal gaps between a company’s workforce strategy and its business strategy. If a company says AI is a priority, but few job descriptions mention AI skills, data governance, or related responsibilities, the hiring plan may not support that priority.
Job descriptions record what an organization expects people to do and know. Together, they can show which skills are missing, where responsibilities are unclear, and where the workforce plan has drifted from the business plan.
Job Descriptions as Workforce Data
Most job descriptions get written for one purpose: filling a seat. Once the company hires, the document goes into a folder and stays there until the role opens again.
Each one still contains a small plan, though. It lists the responsibilities the company needs covered, the skills it believes those responsibilities require, and, in better examples, how success will be measured.
Across every role, that adds up to a written version of the operating model. Reviewed as a set, the library shows which capabilities the company hires for most, which functions are changing fastest, and where similar roles carry conflicting expectations.
Finding Skill Gaps Across the Library
Start with a cross-section rather than every role at once: priority functions, critical job families, and positions that have been hard to fill. Put them side by side. What is missing matters as much as what is written.
These patterns usually point to a gap:
- New must-haves: skills that appear as requirements this year and weren’t in the workforce plan last year, such as product analytics or cloud cost management
- Inconsistent priority: the same capability listed as required in one team and “nice to have” in another
- Scope that doesn’t match level: entry-level roles responsible for company-wide strategy
- Concentrated skills: a critical capability held by two or three people, which leaves the company one resignation away from a problem
- Requirements that shrink the pool: degree requirements or legacy tools with no link to job performance
- Vague outcomes: phrases like “support digital transformation” with no measure attached
Two examples show how a pattern becomes a decision. If half of the customer-facing roles mention journey analytics and the training catalog has nothing on it, that is a reskilling need. If data stewardship belongs to two analysts in different time zones, that is a continuity risk.
Growth into new markets shows up in the library early. A men’s health telehealth company launching TRT online in five new states will see new postings for nurse practitioners licensed in those states, care coordinators, and compliance staff. If the onboarding program and the org chart haven’t changed to match, the job descriptions reveal the mismatch before the first patient appointment does.
Check the patterns against outside data
Internal patterns carry more weight when they line up with the wider market. Employers surveyed for the World Economic Forum’s Future of Jobs Report 2023 expect 44% of workers’ skills to be disrupted within five years, with creative thinking, analytical thinking, and technological literacy growing fastest in importance. In a McKinsey global survey of executives and managers, 87% said their organizations either had skill gaps already or expected them within five years.
Then talk to the people doing the work
The data shows that a skill keeps appearing. Managers and employees explain why, and whether the answer is hiring, training, or redesigning the role. A review that skips those conversations tends to produce a hiring plan for a problem that training would have solved in a quarter.
Checking Roles Against Business Goals
A job description should show how the role moves a company goal forward. When it doesn’t, the mismatch is usually small in any single posting and large across the whole library. Common signs:
- A growth plan with no role accountable for running experiments
- A customer-first message with no customer experience skills in frontline jobs
- An AI strategy with no time set aside for model governance
Strategy shifts make this easy to see. Consider a land investing firm that decides to compete on market research and moves its acquisitions team onto a LandInsights alternative with deeper county-level data, filters, and exports. Its acquisitions analyst roles now need market research and data analysis as core responsibilities. If the job descriptions still describe the work as building mailing lists and skip tracing, the firm will keep hiring for the business it had last year.
Fixes for misaligned roles:
- Tie each responsibility to a metric or program the business already tracks.
- Replace generic phrases with outcomes. “Improve onboarding” becomes “reduce onboarding time by 20% within 12 months.”
- Match scope and decision rights to the title and pay band.
- Remove requirements with no link to outcomes, such as a blanket four-year degree.
- Name the teams the role works with when collaboration drives the result.
Two questions catch most remaining problems. If this person did everything listed, would the strategy move forward? Could a candidate tell from the posting how their success will be measured? A “no” to either means the description needs another pass.
What to Look for in a Job Description Platform
Reading a few dozen descriptions by hand is manageable. Reading several hundred every year is not, and that is where software earns its place. A platform worth adopting should offer:
- One central library with version history and approval steps
- Skills tagging and reporting across roles and over time
- Bias detection and readability checks based on published research
- Integration with the ATS, the HRIS, and existing content workflows
- Shared editing for HR business partners, hiring managers, and recruiters
- Governance rules, so changes follow one standard instead of each team’s habits
Run a few real roles through a trial before committing. An afternoon is usually enough to tell whether the tool surfaces anything a careful reader would have missed.
What Changed When Companies Rewrote Their Job Descriptions
The results from job description work often show up within one or two hiring cycles.
Atlassian rewrote its job ads to remove masculine-coded language, alongside changes to how it sourced and interviewed candidates. Over two years, the company reported an 80% increase in women hired into technical roles globally. Peer-reviewed research backs up the wording side of that result. In a series of studies by Gaucher, Friesen, and Kay (2011), women found jobs advertised with more masculine wording less appealing because they expected to fit in less, while their view of their own skills stayed the same.
IBM removed the bachelor’s degree requirement from more than half of its US job openings, one of the cases documented in the Burning Glass Institute’s Emerging Degree Reset report. The same research found that employers who drop degree requirements write more specific skills into their postings. LinkedIn’s 2025 skills-based hiring research puts a size on the effect: hiring on skills instead of prior job titles expands the talent pool for a typical job by a median of 6.1 times globally, and by 15.9 times in the US.
Smaller changes add up too. Teams that standardize titles and remove overlapping responsibilities tend to report faster approvals, fewer rounds of revisions with legal and compensation, and promotion paths employees can actually follow.
Where Job Description Data Is Heading
Job descriptions are turning into skills profiles that change as the business does. Three developments are moving that along.
Shared skills libraries. Companies are linking role content to a common skills taxonomy and to learning paths, so an employee can see which training moves them from one role to the next.
Live market data. Salary benchmarks and emerging-skill trends from external labor data will feed straight into description libraries, flagging requirements before they go out of date.
AI-assisted review. AI will make it faster to spot patterns across hundreds of roles. The decisions about what a role should be will still come from people who understand the work.
Running the First Review
A first review doesn’t need a multi-year program. It needs a defined scope and a regular schedule.
- Collect current job descriptions into one library, starting with critical roles.
- Read across functions for patterns in skills, responsibilities, and outcomes.
- Link each role to one or two business goals with measurable results.
- Standardize levels, required versus preferred skills, and collaboration points.
- Take the findings to managers and employees and confirm what the data suggests.
- Set a review date, quarterly or twice a year, so roles keep pace with the strategy.
Ongig brings job descriptions into one library and flags inconsistencies, biased wording, and readability problems across every role, which makes steps two and four far quicker for a team reviewing hundreds of descriptions at a time.
