The Division of Labour

In the 18th Century, Adam Smith, the father of economics, coined the phrase the ‘Division of Labour’. It means, simply, “that ten people each concentrating on one task will do a better job than ten people dividing their time between ten different tasks”[1]. More interestingly, Smith noted that this was likely to drive innovation as each person understands their task thoroughly and are best placed to invent more efficient methods of production.

The Challenge for the Financial Services Sector

Though the ‘Division of Labour’ was observed in manufacturing firms during the Industrial Revolution, modern Financial Services firms, with their functional design, are organised in a similar way (i.e. they have separate teams specialising in MI, Finance, Operations, HR etc.).

Interestingly, whilst these functional areas may be innovative in terms of improving their own efficiency, this specialisation appears to have knocked the wind out of their sails with respect to delivering game-changing innovation that transcends functional boundaries and meets specific business goals. This is due to the narrow focus of these specialised functions.

The challenge, therefore, is to develop business structures that maintain current functional efficiencies whilst also delivering game-changing innovations. One interesting means of doing this is through Innovation Labs.

Introducing Innovation Labs

Innovation Labs are generally:

  • Set-up to meet an aspirational business goal (e.g. making better use of existing data).
  • Separate parts of the business with their own profit and loss, resource and physical location.
  • Using agile rapid prototyping methodologies to test and learn with ideas that add the greatest value.

They can take many forms, examples include:

  • Customer Engagement/User Experience Labs
  • Data Labs
  • Finance & Risk Labs
  • FinTech Labs
  • Marketing Labs
  • Product Labs

An Innovation Labs Perspective

It was during my time in one of our Data Labs that I noticed the stark difference in approach and outputs between the Data Lab and the regular MI/Data Function – they were worlds apart and rightly so.

The MI team, as specialists in producing standard MI, were relatively efficient and focused on gaining marginal efficiencies relating to MI outputs. However, they were missing the opportunity to innovate using their data, to experiment and try new analytical and machine learning techniques to add value beyond their day-to-day tasks.

As a result, the business decided to create a Data Lab whose sole focus was to test new ideas and techniques with data. This approach has already delivered game-changing innovations, accruing large business benefits in the process - the wind appears to be back in the sails and pushing them towards their business goal.

Why are Innovation Labs Successful?

There are 4 key reasons why Innovation Labs can add significant value to businesses:

  • Cultural Change – the Lab approach encourages employees, even those outside of the Lab, to think outside of the box and collaborate across functions.
  • Unafraid to Fail – they are at ease with failing which encourages Lab participants to experiment with radical ideas.
  • Test and Learn - rapid prototyping encourages quick delivery of new ideas.
  • Innovation focused – they do not involve themselves with business-as-usual deliveries, they can focus on game-changing innovations.

So, was Adam Smith Wrong?

In short, no. Innovation Labs are a form of ‘Division of Labour’. The key point is that they operate across functional frontiers and are working to achieve an aspirational business goal. The result is that they are more likely to deliver radical innovation than functional structures, which are better at achieving incremental efficiency gains.

Indeed, Adam Smith himself was aware of the limitations to innovation from intense specialisation, which applies neatly to our modern functional model:

The man whose whole life is spent in performing a few simple operations, of which the effects are perhaps always the same, or very nearly the same, has no occasion to exert his understanding or to exercise his invention. [2]


[1] Rory Sutherland (2015) 

[2] Adam Smith (1776)