Tackling the UKs productivity gap IED ANNUAL CONFERENCE 2016 BROWN , - - PowerPoint PPT Presentation

Tackling the UK’s productivity gap

IED ANNUAL CONFERENCE 2016 DUNCAN BROWN, ECONOMIST & SENIOR CONSULTANT

Productivity

The value of the stuff we make What it takes to make it

What have we learned about productivity?

• 1. Not manna from heaven – 2 per cent, reliably, every year
• 2. Happens from real innovations in real workplaces
• 3. Distribution matters – averages can obscure as well as inform
• 4. Spillovers matter – a little success can go a long way

Every place has its own story

65 70 75 80 15,000 20,000 25,000 30,000 35,000 40,000 GVA per head, £2014, 2004 to 2014 Employment rate, %, 2004 to 2014

Source: ONS GVA for LEPs: 1997 to 2014 (deflated by GDP deflator) and Nomis/ONS APS employment rates for 16-64s by LEP , Q4 in each year.

And averages really can mislead; just one LEP area contains these areas

Source: Nomis/ONS APS and ASHE analysis.

65 70 75 80 85 15,000 20,000 25,000 30,000 35,000 40,000 Average earnings (mean), £2014, 2004 to 2014 Employment rate, %, 2004 to 2014

Productivity differences reflect job differences

2003 2016 Place A Place B Place A Place B 0% 25% 50% 75% 100% Employment share of occupational group

High Middle Service Labour

Source: Emsi 2016.1 occupations.

Projected job specialisations will magnify those differences

10,000 20,000 30,000 40,000 Market research interviewers Window cleaners Footwear and leather working trades Food, drink and tobacco process

• peratives

Refuse and salvage

• ccupations

Textiles, garments and related trades n.e.c. Road construction

• peratives

Biological scientists and biochemists Chemical scientists Natural and social science professionals n.e.c. Median earnings, £ 2015 Area

Place A Place B

Source: Emsi 2016.1 occupations, top 5 specified by shift in Location Quotient from 2016 to 2022.

Beware the cliché!

Different skills matter in different places. STEM skills and creative skills are always good, but their value will vary locally. Getting the right mix of skills matters – and that needs detailed local intelligence.

Breaking through the limits of today’s data for economic development

§ Play to your strengths … but not always so clear to understand where those strengths lie – how to look beyond SIC codes? § Make the right comparisons ... but neighbouring local authorities aren’t always peers, so where to look? § Attract a talented workforce ... but what’s the right mix between a ‘place to live’ and a ’place to work’? § Getting more granular … what beyond ’technical skills’ are employers looking for? What can your workforce offer?

Thank You

Duncan Brown duncan.brown@economicmodelling.co.uk economicmodelling.co.uk