It’s never been more vital for businesses utilising a combination of digital and human workers to have a cohesive platform from which all can share ideas, data and workloads.

 

When it comes to building your first digital workforce the key is to start small but think big. Begin with ambition and strategy, by all means, but don’t throw everything against the wall right away and hope that it’ll stick.
 
What you’re building here is not just a team and not just a new toolbox but a multi-purpose enterprise asset that is going to fundamentally change the way your organisation works. So, baby steps are to be expected at first, but that doesn’t mean you can’t make progress quickly and start making serious wins and building confidence right out of the gate.
 
Before we discuss how to build your scale digital workforce, however, it’s vital to understand the individual components (or workers, if you will) that make up an operations-led and IT-enabled digital workforce in 2020.
 
Centre of Excellence (CoE) - Traditionally speaking, a centre of excellence is, essentially, an oversight group that brings together people from different disciplines under a shared banner that prevents siloed working methods and makes sure all teams are sharing their knowledge and skills. In AI, a CoE provides the means to fulfil the mandate for intelligent automation that is set by leadership. It’s essentially the brains of the operations - where the headcount and budget lie and where all skills and methods are built and organised. A survey of US executives found that 37% of firms had already established AI centres of excellence, so this should be your first port of call.
 
The Head - If the CoE is the brain then the head is the mind inside that brain - the thought-leader and the agents that get things done for the Intelligent Automation agenda. The Head helps define what actions the digital workforce will actually take and is responsible for overseeing both their implementation and operations. Other key appointments in the CoE include the Solutions Architect, Technical Architect and Senior IA Analysts.
 
The implementation area - This is the component that designs and deploys automations. The automations may be grouped into projects in order to deploy them for different areas of the business.
 
The control room - This is the operations team that schedules the automations, handles exceptions, reviews the logs and improves the processes. To achieve optimal operational agility, this should be consolidated to optimise performance across all runtime digital worker resources; balancing workload and addressing peaks and troughs.
 
RPA - Robotic Process Automation in this instance refers to the IT department, who host a resilient, secured, virtualised IT infrastructure. Hosting, governance, security, support, scalability and assurance are governed by IT, which requires very close collaboration between the IT and RPA functions, all of which are facilitated by the CoE.


Orchestrating distributed work requires a resourcing platform
 
In a landscape where so much work takes place outside of the traditional office environment, it’s never been more vital for businesses utilising a combination of digital and human workers to have a cohesive platform from which all can share ideas, data and workloads.
 
Work is not only fragmenting but is being resourced virtually: homeworkers, outsourcers, the gig economy (freelancers) and other members of the extended enterprise, including suppliers and customers, are all accessing the same systems and require the same information.
 
A strong resourcing platform will be required in order to orchestrate the actions of both digital and human workers from internal and external sources, to manage service level agreements (SLAs), work queues and adjustments based on planned and unplanned peaks and troughs.
 
The ability to manage the workforce is also something that needs to be considered if the business is going to be able to implement their bold new automated intelligence strategies efficiently and without hampering the customer experience.
 
It’s also worth noting that all external workers will require a different management model to ‘in-house’ workers and will require conscious communication and engagement strategies that help them feel like a part of the team, even when they are not physically in the office. Values, behaviours and policies also need to reflect the purpose and the ‘brand’ of the organisation so that the right ideas are progressed, and the right decisions are made.
 
As a fitting example, a major utility company recently wanted to develop a set of smart energy and smart homes products utilising the latest IoT and Intelligent Automation technology. They set up a separate unit to be the “speedboat outside the super-tanker” that adopted new technologies which were unencumbered by the rest of the organisation.
 
Having successfully prototyped, tested, evolved and deployed the initial products after several years, the unit was subsumed back into the main organisation and embedded within the core products and operating units, evolving business as usual.

 
Continual learning, change and an adaptive culture
 
Building a successful digital workforce is not something that will happen overnight. It’s a constantly evolving process that needs to reflect and adapt to the shifting foundations of an increasingly intelligent and automated workplace. This means it needs to be able to learn and to remain one step ahead.
 
The same is also true of the human workforce. Indeed, people will need to be able to adapt their skills to remain employable for jobs that we may not even have heard of yet. Increasingly, these jobs will be about creating digital solutions or will focus on the human skills that bots don’t or can’t have; empathy, critical thinking, creativity and imagination.
 
As simple tasks are automated, increasingly complex work will be what’s left for the human workforce and this will require a major increase in skills. The resulting work will be much more satisfying, but it will require education and investment.
 
The key is in lifelong learning. We are so used to the paradigm of ‘early learning’ and allowing what we’ve learnt as children and young adults to carry us through life, but that needs to change. It’s all about being able to conceive the workforce of the future and planning the marathon, rather than being disputed by consecutive sprints. So, continual learning is the only way forward if we can hope to build a digital workforce made up of human and robotic employees.

 
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About the author

 

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Chris Tin

Managing Consultant, Hydrogen Group

Chris has 7 years recruitment experience in placing Business Change and IT professionals. He’s currently focusing on Robotics Process Automation (RPA) projects placing RPA Developers, Analysts and Consultants, running RPA training programmes and embedding Digital Workers with various clients.