We are now at our final instalment of developing a data-driven skills strategy. In Part 2 of this blog series, we discussed the merits and applications of O*NET and the Competency Model Clearinghouse (CMC), as well as how to leverage existing information from sector skills councils, employment and skills boards and other groups.
This final post focuses on identifying, modelling, describing and analysing sectors and occupations to develop clearer skills strategies. Sector challenges, opportunities and further refinement of the required competencies should ultimately be the focus of business engagement. This section is dedicated to establishing the fundamental building blocks of sector skills and occupation specific skills in order to engage employers in dialogue, while engagement with individual companies within a target sector will lead to specified strategies.
Defining Engineering R&D Sector and Skills/Competencies
In Part 2, we used Engineering R&D in Tees Valley as an example of drilling into occupation skills, focussing specifically on laboratory technicians — a very specific tree in a diverse forest. In this section, we will focus on the various attributes of the Engineering R&D “forest” within the Tees Valley economy.
At the highest level, we know that Engineering R&D is growing very rapidly. Since 2007, the sector — composed of engineering activities and technical consultancy (SIC 7112), research and experimental development in biotechnology (SIC 7211) and other research and experimental development in natural sciences and engineering (SIC 7219) — added more than 3,300 new jobs (78% growth). Future growth is expected to exceed 1,100 new jobs by 2016. Hartlepool and Stockton-on-Tees lead the growth, more than doubling their existing employment in the sector, followed by South Teesside (70% growth) and Darlington (4% growth). Within the area, engineering activities and related technical consultancy experienced the largest increase in new jobs — over 2,182.
|County/Unitary Authority||2007 Jobs||2013 Jobs||Change||% Change||2012 Avg. Earnings|
|Source: EMSI Covered Employment - 2013.1|
|Hartlepool and Stockton-on-Tees (UKC11)||2,454||4,923||2,469||101%||£36,610|
|South Teesside (UKC12)||1,253||2,136||883||70%||£33,729|
The engineering sector is continuing to advance technologically. With such rapid growth over the past few years, the need for sector-relevant skills to meet business demands is ever-present. Semta (science, engineering and manufacturing technologies) is the closest representative sector skills council. Semta possesses national and regional information on relevant science sectors and workforce composition. Outlines for specific skills and competencies, however, are not readily available in existing reports and the information is out-of-date.
Furthermore, area specific data on R&D is not available either, and skills-related issues are ambiguously defined. Within CMC, Bioscience is already defined through a collaborative effort from the Bioscience Community of Practice. Advanced Manufacturing and Mechatronics are also well-defined competency models done in collaboration with industry-leading experts and organisations. However, Engineering R&D is not a well-defined competency model, though it is likely a composite of the three aforementioned models.
Therefore, we turn to building a competency and skill description for Engineering R&D, focussing first on foundational, personal effectiveness competencies that apply across the sector. Within the CMC, a committee or task force can build a sector competency profile by moving through the predefined list of competencies, adding other competencies as necessary. Once the initial profile is complete, they can continue through the next tiers of academic, workplace, industry-wide technical and industry-sector technical competencies. These tiers can be pulled into a printable profile that can be used in further discussions with businesses and educators.
For an unofficial example of an Engineering R&D model, see the Engineering R&D Competency Model Sample.
Occupation-Specific Skills Strategy
Once we understand the skills and competencies needed by the sector, we are able to pinpoint learning and training activities that align to those needs. Obviously these activities must be developed in accordance with the needs of critical sector occupations. In typical sector-related workforce reports, “skills demand” describes the number or type of NVQs and degrees needed to support needed occupations within a sector. Our process, however, separates skills demand into two groups:
- Occupation demand
- Competency profile
This allows us to define not only the number of occupation-linked NVQs and degrees required, but also articulate the focus areas of competencies. This information can be used to guide discussions with businesses, as well as link information to curriculum planning and strategic activities.
By running a staffing pattern analysis of the sector, we can disaggregate sector employment into constituent occupation employment. In other words, we can estimate the number of draughtpersons, civil engineers, design and development engineers and so forth within the Engineering R&D sector. Combining this staffing pattern with industry (and occupation) projections, we can get a better feel for future occupation needs within the industry. Further to that, we can contextualise the growth across the entire area for any industry that requires these occupations.
This only provides half the story, however. We also want to describe the competencies of “in-demand” occupations to guide our strategic planning activities. To do this, we need to draw upon the UK O*NET system to provide insight on critical competencies within the defined occupations.
The following figure and table describe four key occupations within the Engineering R&D sector: draughtpersons, mechanical engineers, design and development engineers and production and process engineers.
|SIC Code||Occupation||Employed in Industry Group (213)||Employed in Industry Group (2018)||Change||% of Total Jobs (2012)||2013 Total Area Employment||Projected Annual Openings||Median Hourly Earnings||Education Level|
|Source: EMSI Covered Employment - 2013.1|
|2122||Mechanical Engineers||241||282||41||3.1%||905||45||£28.25||Level 4-5|
|2126||Design and development engineers||279||310||31||3.7%||545||23||£16.23||Level 6|
|2127||Production and process engineers||136||148||12||1.8%||417||15||£15.01||Level 6|
The information shown above describes multiple attributes of the sample occupations within Engineering R&D. The LMI data quantifies estimates of current and projected Engineering R&D sector employment as well as area-wide employment. The data also describes education levels, projected annual openings across the area and the percentage of jobs within the R&D — in essence, it gives us a better understanding of the occupation demand and needs within the sector.
Commensurate with the LMI is a competency profile for each of the occupations. The radar chart highlights the top competencies (knowledge and skills) that are typically required to perform job functions. Furthermore, the chart quantifies the levels of the competency attributes, showing how education and training requirements meet business needs. (Note: Any score above 50 indicates an advanced level of knowledge or skill, while any score above 75 indicates an expert level of knowledge or skill.)
Interestingly, we also now have a comparative analysis that can be carried out to determine competency gaps and skills transferability between occupations. For instance, if a draughtsperson wishes to move up in their career to a mechanical engineer, key focus areas of education and training are likely required in mechanical, science and production/processing.
While this last above instalment provides a structured, data-driven research basis for skills strategies, engagement with local area businesses becomes the logical next step. Whether in the form of personalised interviews, focus group or workshops, feedback is necessary to progress the skills agenda. This process is the beginning of a communication framework for more meaningful discussions. Industry and occupation data, coupled with competency descriptions and quantified knowledge and skill levels, enables more accurate articulation of workforce needs and education/training requirements.
We started off the skills strategies series by defining who should be in the driver’s seat of this process, concluding that education is the best fit. However, this process only works if education is capable of collaborating across organisational boundaries (government, business, LEPs, and education/training providers), coordinating cross-organisational resources, developing meaningful relationship with businesses and organisations and proactively engaging senior leadership in strategic discussions.
Within the Tees Valley area, several education institutions offer engineering and design at various levels in their courses, including Teesside University, Middlesbrough College, Redcar and Cleveland College and Darlington College. The questions that typically crop up during this process and next steps are: How well do these courses align to the workforce needs within Engineering R&D? Are the institutions producing enough talented supply to meet those needs? Do the curricula and competencies developed in the course meet business need? And what level of engagement do these institutions have with key businesses such as Darchem Engineering, Dorman Long Technology and The Centre for Process Innovation?
With a clearer process in mind and a structure to build upon, those advancing economic growth in the Tees Valley, whether educational institutions, Government organisations, businesses or LEPs, will gain better direction and strategy as they pursue this agenda. As the strategy develops and the region becomes more adept at changing direction to pursue the best opportunities, the area’s workforce competitiveness will increase dramatically. Ultimately, this approach is at the heart of any data-driven skills strategy.
Hamilton Galloway is an Economist and Senior Consultant at EMSI and is now based in the UK. He specialises in economic development, labour research and education planning, having also taught economics at the college level for three years. Over the past several years, he has worked on dozens of research and strategic planning projects focused on reemployment, course development, skills gaps and target sector strategies.
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