Sunday, August 2, 2015

What are the policy implications of widening productivity diffusion gaps?

When I read the suggestion in the foreword of the OECD’s recent publication The Future of Productivity that governments should be “reviving the diffusion machine” to “promote inclusive growth” my initial reaction was that the OECD would have a difficult task persuading me that markets could not deal with diffusion of new technology without government help. However, it turned out that I had grasped the wrong end of the stick. The OECD researchers have been investigating whether diffusion gaps might be linked to government policy failures. Reviving the diffusion machine involves, among other things, reducing government regulation that prevent markets from functioning efficiently.

The growing diffusion gap in OECD countries is shown in the graphs below. The graphs have been reproduced elsewhere, including by Timothy Taylor, the conversable economist, but they deserve to be widely published.

 The frontier firms are the top 100 firms in terms of productivity levels in each year. These firms are from a range of different countries and many are very much global firms. The data for non-frontier firms is the average of all other firms. Charts for multi-factor productivity show a similar pattern. See the supporting paper by Dan Andrews, Chiara Criscuolo and Peter Gall, Figure A2.

The graphs suggest that productivity growth at the global frontier has remained relatively robust, despite the slowdown in productivity growth in many OECD countries during the 2000s (as previously discussed on this blog). It is interesting that the productivity divergence between top performers and the rest began to widen prior to the financial crisis. That is particularly evident in the case of service sector firms.

The authors acknowledge that the productivity gap is consistent with winner-take-all dynamics or “superstar effects” as well as slower diffusion of new technologies. However, the former explanation is discounted because the divergence is not confined to the ICT sector where winner-take-all dynamics might be expected to be most important. For a discussion of this point by Dan Andrews see the video of the launch of The Future of Productivity at the Petersen Institute (Dan’s response to the relevant question is near the end of the session).

Regression analysis suggests that the ability to learn from the global frontier is stronger in economies that are more open to international trade and more integrated in global value chains (GVCs). The productivity of national frontier firms is negatively influenced by cumbersome product market regulation, and positively influenced by quality of education systems, R&D subsidies, closer R&D collaboration between business and universities, and stronger patent protection. In some economies where national firms have productivity that is close to the global frontier, the impact of those firms on national productivity is muted because they are undersized. The difference between the size of national frontier firms and global frontier firms tends to be smaller in industries with higher job layoff rates, less stringent employment regulation and bankruptcy laws that do not overly penalize failure.

The growth of innovative firms is restricted by high rates of skill mismatch in many countries.  The authors suggest that skill mismatches can be exacerbated by high transactions costs in housing markets (e.g. stamp duties) and bankruptcy legislation that leaves people with valuable skills employed in zombie firms.
The report suggests:
“It is important that young firms either grow rapidly or exit but no longer linger and become small-old firms”.

That set off alarm bells in my mind. What the authors meant to say, presumably, is that governments should reform regulation that assists low-productivity firms to hold resources that could be used more efficiently elsewhere. The idea that young firms should grow rapidly or exit brought to mind memories of the phrase “get big or get out”, coined by an Australian agricultural economist in the early 1970s, and used by industrious bureaucrats and politicians to justify questionable interventions in the normal functioning of credit markets.

A question some of my readers might be asking themselves at the moment is how well Australia scores in relation to the policy variables noted above. The question is not easy to answer because Australian data is not included in some parts of the analysis.
  • Australia’s participation in GVCs is relatively low for a small economy. (GVC participation is measured in terms of imported inputs used in exports and exports used as inputs in other countries’ exports.) This reflects Australia’s remoteness, but it may nevertheless make it more difficult for Australian firms to maintain close linkages with the global frontier.
  • Some OECD data on product market regulation (Koske, I et al,2015, The 2013 update of the OECD’s data base on product market regulation …) suggests that Australia is among the best for OECD countries. Our regulation is apparently more restrictive than that for the Netherlands, UK and Estonia, but less restrictive than for Greece.
  • In 2013 Australia’s score on the OECD’s data base on restrictiveness of labour market regulation – covering ease of dismissal etc. - was 1.94 out of a possible score of 6 (higher scores indicate more restrictions). Australia’s score implies somewhat less restrictions than the OECD average (2.21) and Greece (2.41), but more restrictions than New Zealand (1.01) and the US (1.17).
  • The World Bank’s Doing Business ratings suggest that Australia’s performance in resolving insolvency (rating of 81.6%) is somewhat better than the OECD average (76.9%) although not as good as the US (90.1%) or Canada (89.2%). The average time required to resolve recover debt in Australia is 1 year, considerably lower than for the OECD average (1.7 years) the US (1.5 years) but higher than for Canada (0.8 years).

The fact that some of Australia’s policies look relatively good by comparison with OECD averages is hardly grounds for complacency.  OECD averages are heavily influenced by some of the most sclerotic economies in the world which have had woeful productivity performance over several decades.  

Sunday, July 26, 2015

Does capital deepening reduce labour's share of national income?

The share of wages and other labour remuneration in national income has been declining in most high income countries over the last few decades. I have previously argued that if we are concerned with the well-being of the poor, we should be more concerned about trends in real wages than about trends in the distribution of income between labour and capital. That is still my view, but it hasn’t stopped me trying to understand the reasons why labour’s share has been declining.

My interest has been aroused, in particular, by the claims of some researchers that capital deepening (increases in capital per unit of labour) have contributed to the decline in labour’s share of national income. For example, the OECD’s Employment Outlook 2012 provides the following answer to the question: What explains the decline in labour’s share?
Total factor productivity (TFP) growth and capital deepening – the key drivers of economic growth – are estimated to jointly account for as much as 80% of the average within-industry decline of the labour share in OECD countries between 1990 and 2007”.

The message that seems to be giving is that if a country or a region has the institutions, people and natural advantages needed to attract substantial additional investment, don’t expect the associated capital deepening (increase in capital to labour ratio) to have a strong positive impact on demand for labour. 

There are some circumstances where that might be a reasonable proposition. For example, as Dean Parham has shown in work for the Productivity Commission, the growth of the capital-intensive mining sector in Australia during the 2000s was strongly associated with the decline in labour’s share of national income over the same period.

However, the circumstances of Australia’s mining boom are somewhat peculiar. If it is generally true that capital deepening doesn’t have a strong positive impact on demand for labour I might need to make some fundamental revisions to my views about how economic systems work.

Dear reader, the next few paragraphs are somewhat abstruse, but please bear with me because I need your practical wisdom about production technology and the elasticity of substitution between capital and labour.

The elasticity of substitution between capital and labour is the critical factor determining the impact of capital deepening on demand for labour. It can be defined as the percentage change in capital deepening for a 1% change in the ratio of the wage rate to the rental price of capital (making the standard assumption that factors are paid the value of their marginal products). The sensitivity of the impact of 1% capital deepening (a 1% change in the capital to labour ratio) on labour’s share of output and real wages is shown below (assuming labour’s share of national income is 62%, the median for OECD countries).

The graph is drawn under the assumption of zero technological change. The underlying equation for percentage change in labour’s share is Equation 3 of Robert Lawrence’s recent working paper for the Peterson Institute on the decline in labour’s share in the US. The equation for the change in real wage is as derived in the end note below.

The OECD’s assertions about capital deepening reducing labour’s share were backed up by what appears to have been a fairly sophisticated econometric study by Samuel Bentolila and Gilles Saint-Paul (published in 2003) subsequently updated by OECD staff. These analyses suggest that capital and labour are gross substitutes (i.e. the elasticity of substitution between them is greater than 1) and attribute the decline in labour’s share to both capital deepening and capital augmenting technological change (i.e. technological change that has an impact similar to adding more capital).  

However, other econometric studies suggest that the elasticity of substitution between capital and labour is less than 1. For example, Robert Lawrence’s recent analysis of the decline in labour’s share of US income provides econometric evidence that it is attributable to technological change being so strongly labour augmenting (labour saving) that it has more than offset the positive impact of capital deepening. His results suggest that as a result of technological change “effective capital-labour ratios have actually fallen in the sectors and industries that account for the largest portion of the decline in labor share in income since 1980”.

I will leave it to others to attempt to unravel the mysteries of these conflicting econometric findings. It probably makes more sense for me to focus here on considering which set of results seems more plausible in terms of what you and I know (or think we know) about production functions at the level of the individual firm.

Think of any firm in any industry. In order to keep the analysis simple, assume that the firm leases the capital equipment that it uses and that the firm is small enough not to have any impact on either the rental price of capital or the prevailing wage rate. In the hypothetical situation I want you to consider there is no potential to change technology, only the potential to vary the amount of equipment or labour that is hired (and to vary other inputs in proportion to output). Now, consider to what extent the ratio of capital to labour is likely to change if the rental price of capital equipment declines by 10%, thus causing an increase in the ratio of the wage rate to the rental price of capital.

The answer that some readers may come up with is that the ratio of capital equipment to labour is fixed by existing technology, so that it will not change even if output changes in response to the lower input costs. For example, there is not much point in having more taxis than drivers or more desk-top computers than staff to use them. That corresponds to Wassily Wassilyevich Leontief’s assumption that the elasticity of substitution between capital and labour is zero.

The assumption of zero substitution possibilities is too extreme in my view, but I can’t think of an industry where it would be reasonable to expect a change in the wage rate to rental price of capital ratio to result in a more than proportionate change in capital deepening. Perhaps the time is approaching when firms will be employing both driverless vehicles and human-driven vehicles, so a decline in rental price of driverless vehicles could easily displace humans. But I don’t think that time has yet arrived. (Of course capital equipment can often be substituted for labour by introducing new technology, but the elasticity of substitution relates to unchanged technology.) Perhaps these comments just reflect the limits of my experience. Please enlighten me if that is so.

My bottom line is that unless I am persuaded otherwise I will cling steadfastly to the belief that capital deepening normally tends to raise real wages and labour’s share of national income, and that the decline in labour’s share of national income in high-income countries is attributable to labour augmenting technological change.

Endnote: some of the math behind the graph
Assume CES technology and that labour and capital are paid their marginal products. The rate of growth in the real wage is given by:
(1)     d log W = [(Ϭ – 1)/Ϭ]g + [1/Ϭ][d log (Y/L)]      
where W is the real wage rate, Ϭ is the elasticity of substitution between capital and labour, g is the rate of labour augmenting technological change, Y is output and L is labour input, so Y/L is average labour productivity.
We also know that the rate of growth of output is given by:
(2)    d log Y = SL(d log L + g) + (1-SL)(d log K + h)
where SL is labour’s share of output, K is capital services, h is capital augmenting technological change, if we assume constant returns to scale and Euler’s theorem.
Substituting (2) into (1) and rearranging terms I obtained:
(3)    d log W = g + (1/Ϭ)(1 – SL)[d log (K/N) – (g – h)]      (Both times I tried!)

The graph is drawn assuming no technological change i.e. that g and h are both zero. However, it is apparent from (3) that technological change tends to have a positive impact on real wages (assuming g>0). This impact is diminished when technological change has a labour-augmenting bias (g>h) and amplified when it has a capital-augmenting bias (g

Sunday, July 19, 2015

Where will the future jobs come from?

This question is almost unanswerable, but it is easy to understand why people ask it. A definitive answer is not possible because future jobs will depend on decisions of large numbers of individual businesses, many of which do not yet exist, responding to demands of even larger numbers of consumers around the world. Some guesses are likely to be better than others, but no-one really knows what new products or new technologies will emerge, or how consumer tastes might change.

It is understandable that people ask where future jobs will come from when existing jobs are being threatened by international competition and automation. In the 1970s, when I worked at the IAC (predecessor to the Productivity Commission) many people were asking where the jobs would come from to replace manufacturing jobs then being lost to import competition. People who know about my work career sometimes still ask the same question today for the same reasons (e.g. in the context of the uncertain future of steel production in Wollongong) but these days there is greater concern about the offshoring of services and the impact of technological change.

I was thinking about the way economists answer the question of where the jobs will come from as I read a recently published report by the Committee for Economic Development of Australia (CEDA) with the uninspiring title: “Australia’s future workforce? Fortunately, this is a good example of not being able to judge a book by its title. The report contains many fine contributions by people with expertise in technological change and/or the Australian labour market. Some of the contributors provide information highly relevant to considering the nature and extent of job losses that are likely to occur as a result of technological change and the kinds of jobs that might be in demand in future.

Some points that seem to me to be important are summarised below:
  • The jobs that are disappearing involve routine tasks, not just low-skilled tasks. This is resulting in job polarisation, with computerisation or automation of many middle-level jobs in processing and servicing. See the graph in my post: Is average over? (This point is drawn from the chapter by Jeff Borland and Michael Coelli).
  • The jobs that remain are unlikely to be susceptible to automation and will tend to involve perception and manipulation, creative intelligence and/or social intelligence. (Hugh Bradlow).
  • Future skills and jobs will most often be concerned with the creative application of technology to solving problems. Everyone will need to be able, at some level, to architect (e.g. to integrate computing and communication resources) design (e.g. to understand problems of customers and propose solutions) and analyse (e.g. to make sense of performance data). (Hugh Durrant-Whyte).
  • Large job losses are likely to occur over the next 10 to 15 years. The methodology used by Frey & Osborne for the U.S. suggests that about 40% of jobs have a high probability of being susceptible to technological change in Australia. (Hugh Durrant-Whyte et. al).
  • In recent years enough new jobs have been created in Australia at a rate sufficient to replace those that have disappeared. (Phil Ruthven).
  • There have been substantial changes in the pattern of employment in Australia including growth in part-time and casual work. Most workers are happy with the hours they work. Job tenure is not always short in casual work – a quarter of casuals have worked in the same job for 10 years or more. (Phil Lewis).
  • Employment relationships are becoming more adult: workers desire autonomy and employers are unable to guarantee jobs for life. (Lynda Gratton).
  • Digital infrastructure provides potential for greater choice about where work is done, possibly reducing the need for people movement (e.g. commuting) and associated physical infrastructure. (Hugh Bradlow).
  • Self-employed people account for about 18 percent of the Australian workforce. There is a gradual trend toward independent contracting, as in many other countries. The supremacy of the large organisation is fading; technology is creating greater economic freedom for the individual. (Ken Phillips).
  • There is a significant problem of long term unemployment in Australia, particularly for unskilled people. Over half of the long term unemployed have no post-school education (about 9 percent have degrees). There has also been a substantial increase in people on disability support – numbers on disability support now exceed unemployed social security recipients. (Phil Lewis).
  • Education earnings gaps (skill premiums) have been fairly stable in Australia, unlike the U.S. and some countries in Europe. (Michael Coelli).
  • Schools and universities face a double challenge: how to embrace new technology; and how to deliver the skills required. This involves more than just increasing the number of STEM graduates. Education institutions will need to be able to encourage students to become creative and agile in applying technology to solving problems. (Hugh Durrant-Whyte).
  • Technology is challenging traditional methods of delivering education. Individuals may need to treat their careers as a business - taking more responsibility for their own education and investing in skills to adapt to changing demands throughout their working life. (Sue Beitz).
  • MOOCs (massive open online courses) are the iTunes of education. The way MOOCs will change education is likely to be similar to the way iTunes has changed the way people buy music. MOOCs are not likely to replace quality campus-based education. (Jane den Hollander).
  • Australian industry has largely been an exploiter of technology rather than an explorer. (This claim is seems to me to be highly questionable in relation to areas of Australia’s comparative advantage.) In terms of Joseph Schumpeter’s distinction, explorers search out new solutions to problems, while exploiters seek to make use of existing solutions (e.g. by imitating). In the new global economy new ideas will be the commodity in scarce supply, so explorers and likely to forge ahead and exploiters are likely to fall further behind. (Steven Callander).
  • Australia’s comparative advantage in specific industry sectors can be a driver for technological leadership in key areas of technology and computing. The most obvious industry sectors where this applies are mining and agriculture, but it may also apply to financial services, infrastructure and medical devices. (Hugh Durrant-Whyte).
  • Australia is well-placed to benefit from digital disruption because of strength of services industries including education and potential for sale of services to Asian markets. (Sarv Girn; Phil Ruthven).  

My answer to the question posed above is that the future jobs of Australians will be shaped by: 
  1. the pattern of economic growth that evolves in this country in response to the changing opportunities that the world economy will provide to people living on the edge of Asia; and 
  2. the human, technological and physical resources that Australians develop in the years ahead.

It might seem logical to proceed now to consider the policy proposals contained in the CEDA report. However, there are a few other questions I want to consider before I turn to policy.

Sunday, July 12, 2015

Do we face a future of more than ordinary economic disruption?

Change is the most constant element in life. I can remember beginning a report I was drafting with words something like those more than 40 years ago. It was an appropriate thought in the context of the economic changes occurring in Australia during the 1970s and it is just as relevant today. Perhaps it was even relevant when Heraclitus said similar things about 2500 years ago.

During the 1970s I was under the impression that the pace of change was quickening, but in retrospect that was an illusion. The economic disruption occurring in the wake of the first oil price shock and the emergence of stagflation certainly involved a quickening in the rate of change relative to the abnormal stability of the 1950s and 60s. Looking back now, however, economic change over the last 40 years seems to have been less about quickening than about fits and starts. That seems to have also been true to a large extent during the preceding couple of centuries.

When people look back in 40 years are they likely to perceive that the first half of the 21st century was extraordinarily disruptive?  Or will they perceive this to have been a period of fairly normal disruption, with the pace of change being similar to that occurring on average since the beginning of the industrial revolution?
Richard Dobbs, James Manyika and Jonathan Woetzel, the authors of "No Ordinary Disruption: The Four Global Forces Breaking All the Trends” (published this year by McKinsey and Company, the famous management consultancy firm) argue that many of the long standing trends of the 25 year “Great Moderation” prior to the 2008 financial crisis “have broken decisively” and “a radically different world is forming”. The authors give the impression that they think the current bout of creative destruction is by no means ordinary.

According to the authors we need an “intuition reset” because our intuitions have been formed in a world in which changes were incremental and somewhat predictable. We have to re-think our assumptions rather than making decisions on the basis of intuitions built on our experiences.

The authors argue that the world is in the middle of a dramatic transition resulting from four fundamental disruptive forces:
  • First, there is the shifting locus of economic activity and dynamism to emerging markets like China and to cities within those markets.
  • Second, there is an acceleration in the scope, scale and economic impact of technology.
  • Third, the average age of the human population is becoming older as a result of declining fertility and increasing longevity.
  • Fourth, there is globalization - the world has become much more connected through trade, movement of people and capital, and information flows.

As discussed in a recent article on this blog it is not clear whether there has actually been an acceleration in technological change. The other three factors are well-known features of the economic environment in which we have been living for the last decade or so.

Some of the implications of those forces are less well known. For example, new classes of consumers are emerging, for example from relatively unknown, middle weight, cities in China. Another example is the extent to which new technologies may enable small nimble firms to compete with large established companies.

The authors argue that the era of low interest rates is coming to an end. Their reasoning seems plausible. Monetary policies are likely to tighten somewhat as America and Europe recover from the great recession and inflation resumes. Population aging is likely to result in lower savings rates, since retired people normally have lower incomes and less capacity to save. And the rebalancing of growth in China is likely to favour consumption rather than saving.

Some of the authors’ proposed “intuition resets” are more controversial. For example, they suggest that a prolonged period of falling and steady prices for natural resources is coming to an end. It already seems as though they have underestimated the supply response brought about by high resource prices. I wonder whether Andrew Mackenzie, the CEO of BHP Billiton, read the section of the book containing that particular intuition reset before providing his glowing endorsement.

My main reason for buying this book was not the endorsement by Andrew Mackenzie (or even the one by Lawrence Summers, former U.S. Treasury Secretary). I was particularly interested to learn what a book that draws upon McKinsey’s extensive work with companies and organisations around the world might have to say on the question of how technological change is likely to affect the job market.

The authors suggest that specialization, globalization and technology are making ‘interaction work’ – the searching, coordinating and monitoring required to exchange ideas, goods and services – a critical element of success in developed economies. Interaction jobs range from low skilled to high skilled and many of them involve services that are not internationally tradable, particularly in health care, education and government services industries. The number of these interaction jobs seem to growing rapidly:
“In the same period when nearly three million production and transaction jobs disappeared, nearly five million new interaction jobs were created in the United States”.
The numbers don’t quite match, but it looks as though this statement might relate to the period 2001-09 and be based on data from the U.S. Bureau of Labor Statistics.

The authors note that technology is increasingly allowing employers to redesign and disaggregate work, with routine tasks being assigned to lower-skill employees. In some instances cross-training is enabling workers to perform a variety of tasks and reduce idle time. Workplaces are also being disaggregated as many interaction jobs can be conducted remotely. New technology is connecting purchasers of services to service providers in new and disruptive ways e.g. Uber and Airbnb.

While some parts of the book are full of examples, I was disappointed that the authors’ comments on the changing nature of work seem to be based mainly on abstract reasoning and aggregate statistics. I had hoped that the book based on McKinsey’s real world experience would harvest insights superior to those of academic economists on a range of questions that are highly relevant in considering the disruption associated with technological change. For example, after reading the book I am still wondering whether any evidence is emerging of a limit to the economic benefits that can be obtained by unbundling jobs into routine and non-routine tasks?  Is there evidence of decline in quality of service when unbundling is extended too far? Is there evidence of ongoing movement in the opposite direction as happened in the 1980s and 90s when PCs replaced typists and many professionals had to learn how to do their own typing?

The authors’ discussion of skill gaps is interesting. They project that around the world by 2020 a shortage of about 40 million high-skilled workers and 45 million medium skilled workers may emerge, alongside a surplus of 95 million low-skilled workers. It is easier to grasp what those big numbers might mean for employment and wages when they are disaggregated. The numbers come from a McKinsey report published in 2012. That report suggests that there might be around 3 percent too few tertiary educated workers in the U.S. and somewhat higher percentages in Europe. They project a surplus of medium and low-skilled workers of around 10 percent for advanced economies in 2020.

Without looking closely at the methodology, those projections do seem to provide grounds for concern that current skill gaps will widen. The authors recognize that the skills gap cannot be met by just increasing the numbers of people with tertiary qualifications. In some fields of study many graduates receive multiple job offers, while in others many end up in unskilled work. Even in the STEM fields (science, technology, engineering and mathematics) a “quick churn in job requirements” is apparently common with workers having to master a new set of tools every few years. The solution proposed by the authors is fairly predictable: governments, companies and individuals need to “reset the way they think about labor markets, where to find workers, and the relationship between technology and work”.

My conclusion: I am not persuaded that current economic disruptions are out of the ordinary when compared with other major disruptions that have occurred in patterns of employment and skill requirements during the last couple of centuries. Nevertheless, there are grounds for concern in many parts of the world about the capacity of educational organisations funded by governments to adjust effectively to help meet changing labour market requirements.


1.     Historical perspective

Jim Belshaw has provided a comment below which adds useful historical perspective. I quote:

“Just dealing with the scale of change, and if you work in 40 year increments from 1800s and look at the scale of change and major events in each period, you quickly get the feel that stability is unusual. Then if you look at major technological advances during the period, you can also see that the scale, timing and effects were arguably as fast and significant than anything we have seen in the last forty years. So I would argue that your intuitive feel is correct.

The twenty five year "Great Moderation" is a little unusual, but not excessively so. In the newly formed Australian colonies we had quite a long run of economic advance up the 1848 depression, then another long run into the 1880s. After that economic activity was far more choppy. It was not until the end of the Second World War that we had another long growth period, if one broken by various economic crises, that ended in the 1970s.”

2.      Interaction work in provision of professional services

Noric Dilanchian, a lawyer whose areas of specialisation include protecting, documenting, managing and commercialising intellectual property, has provided some comments on Facebook. Edited excerpts are below:
  “The transaction vs interaction work distinction helps frame some technology developments. Transaction technologies, e.g. for ecommerce, are now maturing after 20 years or more of development. In contrast interaction technologies are less advanced and there are very interesting blips on the horizon.

I'm tracking these developments for professional purposes. They affect the future of the content industries that have been my career's focus. More critical for me, they hold out some promise for reducing the time taken in early stage contract drafting when one is business modelling before one tries to locate suitable resources to cut and paste together templates. This work involves interaction between professions and their clients/patients/public/audiences. Technologies that improve interaction are important at this time when the old form of interaction (meetings in rooms with lawyers) for various reasons (including cost) has declined.

Over the last year or two I've been observing progress in the way interaction work is affecting what computer scientists term ‘deep learning’, ‘machine learning’ and ‘neural networks’. There is also greater use now of visualisation software or visualisation in software. These software technologies are raising excitement as they appear to be producing promising results for product about to be released. In the history of computing artificial intelligence has gone through fits and starts. Right now it’s going through a fit as is being reported regarding augmented reality devices such as the Microsoft HoloLens (less easily in virtual reality devices, e.g. Oculus Rift), Google Photos, and next version of Microsoft's Skype." 

3.     The changing relationship between professional firms and their clients

Some comments that Jim Belshaw and Noric Dilanchian provided on an earlier post are relevant to considering problems that arise in attempting to unbundle services to enable the more routine aspects to be computerised. Jim has experience in conducting economic/commercial analysis from an informed legal perspective, while Noric has skills in provision of specific legal skills (described above). The comments are summarised below:

Jim: Two things became apparent. On the client side, there had been a decline in the in-house knowledge that would once have informed the request for legal advice. There was also an increase in impatience: “Just get us that contract”. On the legal side, there was greater reliance on and availability of templates and precedents. Use of templates can be efficient, but not if poorly informed clients are given boiler plate solutions that results in a reduction in the quality of legal advice and large legal bills.

Noric: There are now new ways of working. The platform used to be face to face meetings and work bees, but it is now electronic. Perhaps more important than the change in the platform, however, is the productivity impediment at the client-firm transactions level arising because the world has changed, but perceptions about roles and requirements have barely changed.