An Enterprising Use Case for Named Entity Recognition (NER)
Exploring NER Applied to Mapping the Employment Journey Within The Premise of Enriching Job-Seeking
The primary objective is to explore ways to employ Named Entity Recognition (NER) to “maximise success” in the job-seeking journey.
Conceivably, this follows the Hollywood model, which shows many failures in searching for a hit to balance risk.1 2 We seek to take this experience and reflect on how the knowledge acquired applies in an enterprise setting. For example, entrepreneurship is a possible destination in this journey, and so are learning and education.
A primary motivation for this work is to assess the extent to which access barriers have dropped due to the high availability of low-cost solutions that can run on affordable, high-availability platforms. It seeks to address this question for business practices classified in the UK as small- to medium-sized (SME) micro-organisations.
This study considers the world-view of Small and Medium-sized Enterprises (SMEs) and includes micro-organisations under this banner.
SMEs accounted for 99.9% of the total number. Importantly SMEs employed 61% of the private sector workforce which was 16.3 million employees. They also earned 52% of the turnover of UK plc which is equivalent to £2,300 billion.
Source: “BEIS small and medium enterprises (SMEs) action plan: 2022 to 2025 (accessible webpage)” (2023)
Recap The Project Proposition
NER is far less widely implemented than other technologies. Yet, if an SME has a use case, the risk of failure is not significantly greater than with projects that deploy other technologies. This result is based on McKinsey Survey data (See chart below).
However, this project is based on the high availability3 of low-cost platforms4 that support NER.5
Note that item3 and item4 combined introduce a new issue. The technical analyst team must intervene6 in the business decision7.
This author reflects on a venture to develop a residential childcare database service run in partnership between the [self-acclaimed] great and the good from 11 West Midlands Local Education Authorities (LEAs) and operated by CCETSW (Central Council for Education and Training in Social Work) and the National Institute of Social Work (NISW).
The project driver was regulatory8 and was possible due to the high availability of low-cost, robust database platforms.
Success is nuanced9; the database service outlived the CCETSW/NISW partnership, and subsequently, the LEAs maintained it.
Recent events suggest a crisis point where disruptive technologies emerge—the proliferation of artificial intelligence (AI) embedded in all products and services. We have witnessed a spate of high-tech layoffs and redundancies and many more skilled workers chasing limited jobs.10
At the time of writing, AI is a sufficiently small light at the end of a necessarily dark tunnel. This perspective is unlikely to change, given the vantage of this project. However, AI must be considered from the standpoint of stretch goals11.
References
Footnotes
Citation is Needed↩︎
Also: Consider the↩︎
high availability infers a “paradigm of choice”↩︎
What are the prevailing factors other than cost? (Utility theory)↩︎
Explored here.↩︎
Consider consulting frameworks like 7 Cs (M.Cope)↩︎
Consider frameworks like 4/5/6/7 Ps (marketing mix)↩︎
Within family law, the legislative focus [shifted towards] keeping families together [..] the law now placed new duties on local authorities to provide help to needy children and families in their areas↩︎
Although an optimal outcome from a technical perspective. CCETSW was abolished in 2001 and replaced by the General Social Care Council (GSCC), the Scottish Social Services Council (SSSC), the Care Council for Wales (CCW), and the Northern Ireland Social Care Council (NISCC). This prototype was pre-internet and would not scale.↩︎
Citation is Needed↩︎
Week 4↩︎