Calculating Productivity

Productivity, at its most basic, is merely the ratio of outputs to inputs. Having established the units of output and input, it is a simple mathematical ratio. In a corporate setting, if you believe the accounting numbers, productivity might be rather close to being the same as operating profit. However, the inputs are tough to establish, and for simplicity many measures of productivity therefore focus on ‘labour productivity’, i.e. the ratio of outputs to labour inputs. However, labour input measures can take at least two basic routes, hours or wages.

Even simple corporate comparisons are fraught with difficulty [see W Bruce Chew's “No-Nonsense Guide to Measuring Productivity”], for example moving beyond direct labour to wages, considering unpaid overtime, handling foreign exchange movements, the circularity of cost attributions often being allocated by labour hours, and confusing efficiency (“same with less”) with productivity (“more with same”) leading to volume reduction being equated with increased productivity. And this is well before arguments on financing structures and rent extraction, or existential arguments on output (e.g. “number of patients treated” or “quality of care” or “quality-adjusted life years”) or inputs (e.g. government R&D subsidies).

National productivity calculations and comparisons are largely extrapolated from firm-level methods. The Office for National Statistics (ONS) headline labour productivity measure is output per worker for the whole economy. Other published productivity measures are output per filled job and output per hour worked which are available for the whole economy and selected industry sections and sub-sections.

“Both unit labour costs and unit wage costs are available for the whole economy and measure the labour or wage cost of producing one unit of output. Although not a direct measure of productivity, an inverse relationship between these measures and productivity tends to be observed: the higher the productivity of a worker, the lower the cost of labour per unit of output, and vice versa.”

Problems With The Numbers

ONS International Comparisons of Productivity (ICP) "are based on two productivity measures for all G7 countries (Canada, France, Germany, Italy, Japan, the UK and the US). These two productivity measures are gross domestic product (GDP) per worker and GDP per hour worked. These are calculated using both current and constant purchasing power parities (PPPs).”

Note that both GDP and PPP methodologies are highly criticised, often highly volatile, and often revised, for example Nigeria’s 89% GDP jump in 2014 or Ireland’s problems with aircraft leasing statistics leading to a 2015 revision of GDP growth from 7.8% to 26.3%. The problems with GDP calculations are legion. As Diana Coyle said her 2014 article "A Measure For Error" - "So complicated is the task that the official handbook explaining the construction of GDP and related national accounts figures runs to 722 pages (up from 50 pages in 1953). And the margin of error on the UK’s annual change in GDP has been two percentage points over the past 15 years, which is the same order of magnitude as the headline growth figure itself.”

One of the great areas of discussion surrounds quality and technological advance. For example, search engines have become enormously valuable tools for all businesses since the late 1990s. And search engines have increased markedly in power and usefulness, but how is that captured? Further, the effects of the search business model on other sectors are unknown. Advertising pays for the bulk of the service provision, while the effects are felt on directories, travel agents, or consultants (there was a mini-industry for consultancies marketing their ‘rolodexes’ in the 1990s). Is advertising less productive (more expensive/person in traditional advertising) or more productive (billions of ads served), while directory enquiries is more productive (charge for residual enquiries much higher) or less productive (fewer, more complex enquiries per person), due to search engines?

Another telling point is just that because something is measurable because it’s paid for, doesn’t mean the overall system is working. This is related to Bastiat’s broken window fallacy, that we can increase GDP by encouraging breaking windows and then repairing them. We can install heating systems in tropical countries, or air conditioning systems in temperate countries that don’t need them. We can have a lot of bureaucratic ‘make work’ by government. We can employ a lot of people on artificially low wages and improve our productivity. Productivity and efficiency measures do not naturally focus on the right outcomes, typically more quality-of-life issues.

Government comprises a significant amount of the economy and causes difficulties as well in the calculations. The Atkinson Review: “Measurement of Government Output and Productivity for the National Accounts” (2005) commissioned by the ONS focused on the methodological problems in government output measures. The New Zealand government reviewed many similar issues and have a short critique worth reading. Amongst other methodological problems, they note the tendency for government services to assume inputs are outputs and thus productivity is stable over time, cost of production is often used as a false surrogate for value, output quality can improve markedly while productivity measures are constant, and capital and depreciation numbers may not represent inputs.

“The ONS Productivity Handbook: A Statistical Overview And Guide” (2007), ONS, 191 pages, covers almost all of the theoretical ground and the complexities. Even here though, there is insufficient time and space to cover role of national debt, role of taxation, position of pensions, and other long-term issues. Some traditional areas of market failure highlight some quick areas of critique:

• Externalities – is productivity flattered by running down the environment?
• Agency problems – though agency strength can be a competitive advantage, equally agency issues feature in calculations of pension reasonableness, health care quality, care for the aged, and other awkward topics that can lead to biasing the numbers;
• Information asymmetries – is productivity flattered by living off historic educational quality, or infrastructure?
• Inappropriate or missing competition – for example flattered by exclusive natural resources?

Internationally, the Organisation for Economic Cooperation and Development (OECD) works hard to create valid comparisons. Their Global Forum on Productivity has a wealth of information. But the fact remains that productivity measures are not very reliable.

Comparative UK Productivity

Still, productivity in the UK is puzzlingly low when compared with its peers. Traditional theory indicates that as employment becomes expensive, economic agents are encouraged to find ways to increase productivity. In the UK, despite unemployment being low, productivity remains comparatively low as well:

The UK is interesting in that statistics might imply there is no universal policy for all sectors as some sectors soar in productivity while others plummet:

Andy Haldane and the “Productivity Commission”, chaired by Sir Charlie Mayfield, emphasises in his speech, “a long tail of companies across all sectors in the UK whose productivity performance is falling short. The Commission are developing, among other things, a tool which would enable firms to benchmark themselves relative to others in their sector along several key business dimensions. This could then serve as a prompt for action, enabling firms to boost their productivity performance through targeted action. I think this micro-level assessment of productivity is a useful way to formulate plans which support productivity, and narrow productivity differences, regionally and sectorally. For example, recent work by the OECD has looked at the changing distribution of productivity across firms over time. It suggests a widening– or bifurcation - of this distribution, with a small set of frontier firms whose productivity growth continues apace but a long tail of laggard firms whose productivity has effectively stagnated.” So we have national, sectoral, and long tail productivity problems.

Anything Special About Professional & Business Services (PBS)?

PBS firms are characterised by low levels of physical assets and high levels of rent extraction by principals, the people who run the firm. The traditional profitability calculation looks at profit/principal as a function of rate (the billing rate), utilisation (the percentage of available time working at a rate), margin (the overheads and tooth-to-tail ratio of fee-earners to support staff), and leverage (the number of fee-earners per principal). People who have worked in PBS are well aware that the published billing rate is frequently not the billed billing rate, utilisation algorithms vary and rarely take account of unpaid overtime, and that fee-earners and support staff are not always clearly delineated.

As a result of three factors being strongly influenced by chargeable time, PBS is characterised by a focus on billing for time where possible. Timesheets, time-based comparisons, daily rates, all proliferate. If you can sell on a time-basis, then efficiency can become a contradictory, countervailing factor, a point that has not gone unnoticed by clients. However, one might expect competition, local, national, and international to make a difference.

Ian Stewart, Deloitte’s Chief Economist, feeds in, “As with all aspects of the productivity story there are plenty of explanations - a slower pace of deregulation and globalisation, professional firms hoarding staff as demand fell away in the recession and aggressive cost control on the part of clients… It could be that productivity is not being measured properly and that the true rate of productivity growth is higher. In professional services the official measure compares growth in revenues with growth in wages. This roughly accords with how we measure margins which have, of course, been under pressure for the last decade. In this respect the official productivity numbers and the margin data tell a similar story. The official measure is based on existing, market based data sources which ought to be of decent quality. In the shadowy world of measuring productivity this is pretty good going.”

We are back to observing that “if you believe the accounting numbers, productivity might be close to the same thing as operating profit”. If you believe that there is a ‘natural level’ of profit sufficient to make people aspire to be principals, then productivity might closely approximate a fairly stable operating profit percentage. This might imply that PBS is characterised by firms with little incentive to invest to increase efficiency and facing little change until punctuated by a period of technologically-induced turmoil, potentially with large amounts of culling.

Another area where PBS can sometimes differ is in having mandated services, e.g. audit. In such an environment, i.e. an oligopoly and a coerced client, there is little motivation to reduce time or fees, thus little motivation to improve productivity. Other areas of PBS have similar mandated services, e.g. architecture, legal services, though they might argue there is more competition.

Any Problems With The Policy Responses?

The traditional policy responses to low productivity are:

• Increase skill levels and balance skills with needs – through vocational training and education, in order to get higher-value-added per employee;
• Improve infrastructure – to increase overall economic efficiency;
• Encourage innovation – in order to discover new ways of doing things, typically via increased competition and research.

These policy responses equally make good economic sense at any time. A longer list comes from “The Future of Productivity”, OECD (2015), that summarises well the potential generic policy responses to improve productivity. These include:

• Improvements in public funding and the organisation of basic research, which provide the right incentives for researchers, are crucial for pushing out the global frontier and to compensate for inherent underinvestment in basic research.
• Rising international connectedness and the key role of multi-national enterprises in driving frontier R&D imply a greater need for global mechanisms to co-ordinate investment in basic research and related policies, such as R&D tax incentives, corporate taxation and IPR regimes.
• Productivity growth via the diffusion of innovations at the global frontier to national frontier firms is facilitated by trade openness, participation in global value chains (GVCs) and the international mobility of skilled workers. Rising GVC participation magnifies the benefits from lifting barriers to international trade and from easing services regulation.
• Well-functioning product, labour and risk capital markets as well as policies that do not trap resources in inefficient firms – including efficient judicial systems and bankruptcy laws that do not excessively penalize failure – help firms at the national frontier to achieve a sufficient scale, enter global markets and benefit from innovations at the global frontier.
• A competitive and open business environment that favours the adoption of superior managerial practices and does not give incentives for maintaining inefficient business structures (e.g. via inheritance tax exemptions that may prolong the existence of poorly managed family-owned firms) facilitates within-firm productivity improvements. Stronger competition also enables the diffusion of existing technologies to laggards, which underpins their catch-up to the national frontier.
• Innovation policies, including R&D fiscal incentives, collaboration between firms and universities and IPR protection, should be designed to ensure that they do not excessively favour applied vs basic research and incumbents vs young firms.
• Framework policies that reduce barriers to firm entry and exit and improve the efficiency of matching in labour markets can improve productivity performance by reducing skill mismatch.
• Reforms to policies that restrict worker mobility and amplify skill mismatch – e.g. high transaction costs on buying property and stringent planning regulations – and funding for lifelong learning will become increasingly necessary, to combat slowing growth and rising inequality.

The universal application of the above at any time raises the question of whether productivity measurement at a national level makes any difference.

What Might We Do About Productivity Measures?

Accountability requires measurement, but evaluation also requires judgement. Measurement can displace judgement. Professor Marilyn Strathern’s statement of Goodhart’s Law is "When a measure becomes a target, it ceases to be a good measure." As a former central banker, Charles Goodhart was referring to the fact that measures such as money supply tend to fail to measure well when too much weight is placed upon them. The original form of Goodhart’s Law was, "As soon as the government attempts to regulate any particular set of financial assets, these become unreliable as indicators of economic trends." As he noted, "financial institutions can... easily devise new types of financial assets." Goodhart’s original expression evolved to his preferred formulation: "Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes. "There is an old Groucho Marx joke that Woody Allen recycled to explain the inevitability of amorous relationships:

• Doctor, my brother thinks he’s a chicken. Can you help?
• Why don’t you stop him?
• We need the eggs!

In some ways, productivity measures are equally absurd, and inevitable. We’re going to create them and use them regardless, so what might we do to improve them, or develop alternatives? The French Government tackled this head on with an international "Commission on the Measurement of Economic Performance and Social Progress", appointed by President Sarkozy of France, which issued its report in 2010. Many distinguished economists concluded, basically, that measurement should move "from production to well-being". In November 2010 in the UK, then Prime Minister David Cameron established the Measuring National Well-being programme run by the Office for National Statistics (ONS). Interestingly, from 2012 to date this has shown that "Reported personal well-being has improved every year since financial year ending 2012 when data were first collected, suggesting that an increasing number of people in the UK are feeling positive about their lives".

On alternative measures, there is an argument that productivity at a national level should focus on outcomes, and that these outcomes are not necessarily quantifiable in market terms. For example, perhaps what we should really be exploring is how many people produce what quality of life. This could lead to looking at output (quality of life) to inputs (working population). Some might argue this could encourage near-term unemployment to produce a better ratio, though over the long-term this might be a better approach. Without doubt such measures are harder to make than just relying on economic statistics, but they might be much more meaningful and useful in determining the way ahead.

Another point worth making is that we tend to undervalue lower anxiety, lower volatility, and perhaps security and safety. This is explored in some depth, “Risk, Equality And Opportunity - The Roles For Government Finance”, but the basic point is to recognise the role of government and society in being a "guarantor" for individuals and families.

Some thoughts for discussion:

1. We must first recognise how imperfect productivity measures are. We should urge caution against over-zealous application, particularly in PBS where some of the arguments may be circular;
2. We could encourage more examination of improving productivity measure discussions and methodologies. One suggestion might be that we consider a comparative advantage trade analysis using Monte Carlo simulation to explore the ‘gap’.
3. We could encourage the exploration of alternative measures focused on outcomes. This might mean exploring happiness economics and human development indices in preference to GDP-based measures.

Some Interesting Economist Articles Post-Publication:

• 07 December 2017 — 'Are digital distractions harming labour productivity?'
• 07 December 2017 — 'Family-owned firms hold part of the answer to the productivity puzzle'
• 14 December 2017 — 'Businesses’ investment decisions can have unexpected consequences'
• 11 January 2018 — 'Economists grapple with the future of the labour market'

and an addendum three years later showing how fragile the numbers are, making one wonder why so much emphasis is placed on productivity as a core measure - 11 July 2020 - "Has the ONS solved the 'productivity problem'?"