Education, skills, international experience and connectivity will boost productivity!

Summary of Key Statistics

Management & the economy
  •  The results from academic studies suggest that just halving the gap in leaders’ management effectiveness between Australia and the world’s best could lift productivity by 4%, which would mean a boost to our economy by around $70 billion a year.
    • Australia’s current productivity gap from the United States is 23%, an estimated 29% of which can be attributed to management quality as measured by a range of factors such as goal and target setting, plan execution, talent management and promotion systems.[1]
    • The productivity boost above would be more significant than that of the internet [2] and could lift the World Bank’s ranking of Australia’s PPP-adjusted-GDP per capita from 19th to 14th in the world.[3] For individuals, this is equivalent to an extra $3,000 per person – approximately what the lowest 40 per cent of households spend on rent every year.[4]
    • This opportunity could be worth around $20 billion to regional and rural Australia, based on its importance to employment and economic activity.
 LinkedIn Data
  • For this study, we analysed LinkedIn’s database of over 280,000 LinkedIn profiles of leaders from over 72,000 Australian businesses.[5] We identified two types of ‘successful’ businesses:
    • Top Attractors – 25 companies that are successful at attracting talent as measured by number of job applications submitted, digital engagement of existing employees, and new hire turnover.
    • Recurring Financial Review fast businesses –businesses that have appeared in at least two out of the last three years of the Financial Review fast list.
  •  We found that there are four key characteristics of effective leaders:
    • Fit for purpose education – overall, leaders are well-educated; in ‘Top Attractor’ established businesses they are 43% more likely to have a higher degree compared with the average business, while leaders in fast-growing companies are 22% less likely;
    • A set of core skills – beyond formal qualifications, leaders need a core set of skills, especially management and strategy skills. What is interesting is that beyond that, business maturity again plays a key role – for established businesses it’s about mastering business process improvement  and change management to make businesses more agile in a fast-moving environment, whereas for successful fast-growing businesses, driving business development is a higher priority;
    • International experience – although clearly not a prerequisite for effective leadership, senior people at Top Attractor businesses and fast-growing businesses were two and three times more likely to have international experience than a leader at an average business;
    • Connectivity – leaders in successful businesses tend be more connected with their staff, suppliers and customers; the opposite of isolated. LinkedIn connections are just one proxy for leaders’ communicative and collaborative behaviours, but telling – on average, leaders in the Top Attractor businesses have 17% more connections than leaders in businesses overall, and leaders in fast growing businesses have 88% more than leaders at average businesses.
  • Introducing new organisational or managerial practices increased the likelihood of achieving above average revenue growth by 3% over not doing so.
  • A business focus on innovation increased the likelihood of achieving above average revenue growth by 7%.
  • These results are from on a simple model using the ABS Business Longitudinal Survey data, which in all is based on 463 questions and 7,033 observations because we observe businesses over a five year period.

[1] Bloom, Nicholas, Benn Eifert, Aprajit Mahajan, David McKenzie, and John Roberts, (2013) Does management matter? Evidence from India (No. w16658). National Bureau of Economic Research.
[2] Productivity of the internet was calculated in Deloitte Access Economics (2015c).
[3] GDP per capita ranking based on World Bank purchasing power parity GDP data.
[4] This calculation is based on weekly household expenditure in Table 3A of the ABS 6530.0 - Household Expenditure Survey
[5] LinkedIn career dataset 2016.