In my last blog ‘Outsourcing: Has the pendulum swung too far?’, I suggested some organisations may have risked throwing the baby out with the bathwater by outsourcing and offshoring too many of their capabilities.
However, through the use of emerging technologies to optimise their onshore capabilities, companies can potentially deploy their core resources much more efficiently going forward.
For example, there is a well-established tradition of outsourcing app development to offshore teams. But as a coder friend of mine recently explained, by using a large language model such as ChatGPT to write code, he is able to reduce a 20-hour task to less than an hour. If he then spends, say, four hours optimising the code ChatGPT has produced, he will have realised a net gain of around 15 hours in time that would otherwise be spent on routine coding tasks.
If you compare this to the outsourced model, it is unlikely that an offshore team will be motivated or even able to perform the same process in a quarter of the time. There is however, no reason why offshore teams can’t also use ChatGPT to develop code. So why not gain further savings? In short good practice uses a 'two-in-the-box' model for more effective outsourcing, where the service provider does the heavy lifting of writing code, and the onshore team devotes its time to rigorous code reviews. In this case, the marginal gains from an offshore model using Chat GPT would be more than outweighed by the process costs of a handoff.
Bringing it back onshore
Viewed through this lens, there is a strong case to be made that one of the benefits of using technology to drive business optimisation is the potential to onshore or reshore some core functions back to the business, while still leveraging offshore capabilities to give the in-house team more time to focus on highly skilled work.
Rather than abdicating responsibility and abandoning good governance, in using a tool like ChatGPTentities will be able to do more with the same in-house resources, while still employing an agile methodology.
AI tools are only as ‘intelligent’ as the parameters set for their use. So while ChatGPT can rapidly structure what you might call the ‘known knowledge’ made available to it, it can’t create previously unknown knowledge. That's where human intervention is required, to move things forward through creative thought.
Driving creativity
A good example of how this advanced processing is driving creativity in the wider world, is the use of AI to predict protein structures, which can then be combined to form new pharmaceutical compounds. These processes would ordinarily require many hours of manual work, but the timescale can be dramatically reduced using AI, at which point humans can apply their creative understanding to the output to generate real-world solutions in the form of new drugs.
That’s where the power of AI as part of a business optimisation process lies – giving your team more time to spend being creative. Testing is one function that has been extensively offshored, using outsourced teams to produce the test scripts, which are then reviewed by an onshore test manager.
The ability to carry out automated testing, using AI technology, also gives organisations a fantastic ability to do regression testing that fits with agile, continuous integration and development, the ability to deliver rapid releases of code, and the prospect of automated updating of tests, based on new features and functionality – typically a process that requires substantial investment in time and effort.
Skilling up for AI
Optimising through AI is a challenge, and we need to be on top of the potential downsides – such as the fear that it may replace human jobs - but it also offers an opportunity to do significantly more with the same resources and maybe solve a good chunk of the UK's productivity challenge in the process.
That said, the experience of the banking sector suggests the UK is currently falling behind in terms of the numbers of AI experts being able to drive digital transformation.
Business leaders are going to have to re-think their approach to hiring as they look to optimise their businesses. In order to leverage the power of AI to drive the next generation of processes and practices, everybody from our coders and testers to programme managers and transformation directors needs to be aware of its capabilities.
I believe a sea change is about to occur with AI, but for leaders of change initiatives to be able to bring together specialists with the right skill sets and the capabilities to deliver on transformation they need to be having a conversation, internally and with clients, about what technology-driven business optimisation involves in the age of AI.
