Every individual business process has stages, each of which has inputs, business rules, and outcomes. Each of these stages can be linked to a microservice – and improvements made to any such microservices will benefit the overall process.
However, the boundaries of these microservices must be determined beforehand, and alternatives need to be considered where appropriate. It may be, for instance, that a function is best conducted not solely by a tech sub-routine, but by a person whose performance can instead be augmented by technology. An example might be where invoices are validated against purchase orders: the routine could support people in this activity; or it could perform it by itself, alerting team members for human input only where there is a mismatch; or it could be set to flag anomalies such as false positives, or only those discrepancies that are above a certain level.
One of the advantages of this segmented approach is that it enables organizations to focus on areas in which improvements will deliver the greatest overall benefits. Such areas will probably include high-frequency activities, with fairly high exception levels. Once they have been identified and their boundaries have been determined, they can be simplified, robotized, and – if circumstances allow – perhaps even fully automated.
It’s not only the organization and its employees who benefit from these improvements. They can be good for customers, too.
For example, air travelers can be asked to enter their details just once, on the online booking system, so that when they reach check-in, their passport information can be recognized automatically.
Supply chain partners can also benefit. Processes can be simplified, and they can at the same time incorporate artificial intelligence – so that when, for instance, a supplier tells a chatbot that one of its own invoices has been lost, the bot will not only understand, but will be able to retrieve a copy of the submitted invoice from the system and return it to the supplier’s accounts team.
The potential of the microservice concept is considerable. It enables us to put a new way of thinking into action – an approach in which organizations are driven not by monolithic processes, but by an invisible infrastructure of discrete elements that come together as needed.
Processes on the fly
What’s more, these elements can be tweaked individually to improve both specific and general performance. For example, a business may undertake to revisit given process areas every few months, to see how the most recent changes have affected not only outputs but also performance. Have those improvements changed working practices in this part of the business, or further up or down the line? If so, what further changes can be made to other, related microservices, to maintain the momentum of success?
The business may be able to go further still, and make tweaks as frequently as daily, changing processes on the fly in response to demand, but while remaining realistic in terms of metrics such as production capacity, financial targets, and sales projections. If you’ve seen the quiet majesty of a flock of starlings in flight, you’ll get the picture: individual elements, hundreds of them, changing places and forming new combinations, but always as part of a macro organism, with its own shape and its own purpose.
In a forthcoming post, I’ll take a look at how different processes and technologies can come together to build a new, frictionless enterprise. In the meantime, you might like to visit the page I’ve contributed to Capgemini’s TechnoVision 2020, which helps to set the scene on this subject.
Want to know the simplest ways to create a digital transformation in 2020? Download the TechnoVision 2020 report to help you through the process.
Read other blogs in this series :
- Introducing AI – Simplifying the starting point
- Robots – that was then, this is now
Manuel Sevilla advises customers on moving to a new world with radically faster time-to-market, new business models, new ecosystems, and new customer expectations, through adopt domains such as cloud, cloud-native, AI, blockchain, and DevOps.