Digitisation of Services and Automation of Labour

Digitisation of services is all around us. Where we used to call for food, taxi, hotels and flights we now have apps. This ‘app’ based economy has resulted in a large number of highly specialised jobs (e.g. app developers, web designers). It also impacts unskilled or lower skilled jobs as gaps in the digitisation are filled in with human labour (e.g. physical delivery of food, someone to drive the taxi).

The other side of digitisation is automation. Where manual steps are digitised, the data processing steps can involve human labour (e.g. you fill a form online, a human processes it, a response letter is generated and a human puts it in an envelope for posting it). 

In case of a fully automated and digitised service, processing your data would involve ’machine labour’ (with different levels of automation [see http://fisheyefocus.com/fisheyeview/?p=863]) and any communication would also be electronic (e.g. email, SMS). One very good example of this is motor insurance, where you enter your details via a website or app, risk models calculate the premium on the fly and once payment is made all insurance documents are emailed to you. Only involvement of human labour is in the processing of claims and physical validation of documents. This is called an ‘e-insurer’.

Machine Labour

Automation involves replacing or augmenting human labour with machine labour. Machines can work 24×7 and are not paid salaries – thus the cost savings. However, machines need electricity and infrastructure to work and they cannot self-assemble, self-program or self-maintain (so called Judgement Day scenario from the Terminator series). Human labour is still required to develop and maintain an increasingly large number of (complex) automated systems. Human labour is also required to develop and maintain the infrastructure (e.g. power grids, telecom networks, logistic supply chains) that works alongside the automated systems.

So humans earn indirectly from machine labour but in the end automation and digitisation help save large amounts of money for companies by reducing operational costs (in terms of salaries, office space rentals etc.). Another side-effect is that certain types of  jobs are no longer required as automation and digitisation pick up pace.

Impact on Consumption

Now we know from basic economics that all consumption results in someone earning an income. 

For a company, the income is the difference between the value of what they sell and their total costs (fixed + variable) in making and selling it.

A company will increase digitisation and automation with a view to increase their total income. This can happen by targeting automating processes that increase sales or decrease costs. A company will also automate to keep levels of service so as not to lose customers to competition but there will always be some element of income increase involved here as well.

If costs are reduced by digitisation (e.g. less requirement for a physical ‘front office’) and/or automation (e.g. less number of people for the same level of service), it can lead to loss or reduction of income as people are downsized or move to suboptimal roles (e.g. a bank teller working in a supermarket). This also contributes to the ‘gig’ economy where apps provide more ‘on-demand’ access to labour (e.g. Uber).

People consume either from what they earn (income) or from borrowing (e.g. credit cards and loans). If the incomes go down then it can either impact consumption or in the short term lead to increased borrowing. This decrease in consumption can impact the same companies that sought an increase in income by automation and digitisation.

To Summarise:

  1. Automation and Digitisation leads to cost savings by introducing electronic systems in place of a manual process. 
  2. If less people are required to do the same job/maintain a given level of output then employers are likely to hire fewer new workers and/or reduce the size of the workforce over time. 
  3. This will reduce the income of people who are impacted by redundancies and change of job roles. 
  4. This in turn will reduce the consumption of those people which may hit the very same companies that are introducing automation and digitisation
  5. This in turn will further push the margins and thereby force further reduction in costs or increase in consumption from some quarter…. 
  6. And we seem to be trapped in a vicious circle!

This Sounds Like Bad News!

So looking at the circular nature of flows in an economy, as described in the previous section, we can predict some sort of impact on consumption when large scale digitisation and automation takes place. 

As an aside, this is a major reason why ‘basic income’ or universal income is a very popular topic around the world (read more: https://en.wikipedia.org/wiki/Basic_income). With basic income we can guarantee everyone a minimum lifestyle and thereby promise a minimum level of consumption.

The actual manifestation of this issue is not as straightforward as our circular reasoning, from the previous section, would indicate. This is because the income of a company depends upon several factors:

  1. External Consumption (exports)
  2. Amount consumed by those whose income increases due to automation and digitisation
  3. Amount consumed by those whose income decreases due to automation and digitisation
  4. Labour costs attributed to those who implement and support automation and digitisation
  5. Labour costs attributed to those who are at risk of being made redundant due to automation and digitisation (a reducing value)
  6. Variable costs (e.g. resource costs)
  7. Fixed costs

Exports can help provide a net boost to income – this external consumption may not be directly impacted by automation and digitisation (A&D). It may be indirectly boosted if the A&D activities lead to imports from the same countries.

The two critical factors are (2) and (3): namely how much of the output (or service) is sold to people who benefit from A&D and how much is sold to those who do not benefit from A&D. 

If a company employs a large number of people who can be made redundant via A&D activities and a large portion of their consumers are those whose incomes will be impacted by A&D then we have a very tight feedback loop – which can lead to serious loss of income for the employer, especially if it ties in with an external shock (e.g. increase of a variable cost like petroleum).

On the other hand if a company caters to people whose incomes increase with A&D (e.g. software developers) then the impact to its income will be a lot less pronounced and it may even increase significantly.

What works best is when a company can sell to both and has enough space for both A&D activities and manual labour. This means they can make money from both sides of the market. A good example of this are companies like Amazon, McDonalds and Uber who have human components integrated with A&D which then acts as a force multiplier. 

Using this framework we can analyse any given company and figure out how automation will impact them. We can also understand that in the short term A&D can have a positive effect as it acts as a force multiplier, opening new avenues of work and creating demand for different skills.

Breaking Point

Real issues can arise if automation is stretched further to complex tasks such as driving, parcel delivery and cooking food. Or digitisation is taken to an extreme (e.g. e-banks where you have no physical branches). This will have a large scale impact on incomes leading to a direct reduction in demand.

One way to force a minimum level of consumption is for the government to levy special taxes and transfer that income as it is to those who need it. This will make sure those who are unskilled or have basic skills are not left behind. This is a ‘means tested’ version of basic income similar to a benefits system.

The next step will be to re-skill people to allow them to re-enter the job market or start their own business.

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