The pandemic is demonstrating the importance of acting with agility, speed and resilience in response to major global disruption. What’s also crystal clear is those organisations that haven’t already adopted intelligent automation technologies with success have been left struggling to respond effectively.
At its best, intelligent automation enables work to be performed across the front, middle and back offices much smarter, faster and more efficiently. However, one of the biggest problems for organisations when they start automating their business processes is how to sustain and scale up these activities. The reality is that not enough business automation projects are really progressing past the pilot stage, and having good intentions and good intelligent automation technologies just isn’t enough.
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It’s actually the people, talent and structure behind intelligent automation that are as important as the technology itself. The key here is having the right delivery methodology – while retaining a team, with the right skills to action this – right from the start. It’s these critical factors that determine success and failure. I’ll discuss the following steps that ensure intelligent automation consistently generates value across enterprise operations.
Start with a purposeful vision
For an intelligent automation programme to really deliver, a strategy and purpose is needed. This could be improving data quality, operational efficiency, process quality and employee empowerment, or enhancing stakeholder experiences by providing quicker, more accurate responses. Whatever the rationale, an intelligent automation strategy must be aligned to the wider needs of the business.
Ideally, key stakeholders should be involved in creating the vision; if they haven’t, engage them now. If they see intelligent automation as a strategic business project, they’ll support it and provide the necessary financial and human resources too. Although intelligent automation is usually managed by a business team, it will still be governed by the IT team using existing practices, so they must also be involved at the beginning. IT will support intelligent automation on many critical fronts, such as compliance with IT security, auditability, the supporting infrastructure, its configuration and scalability.
So intelligent automation can scale as demand increases, plan where it sits within the business. A centralised approach encompasses the entire organisation, so it may be beneficial to embed this into a ‘centre of excellence’ (CoE) or start moving towards creating this operating environment. A ‘federated’ model is also effective where intelligent automation capability sits within a particular function but is scaled across the business, with the central automation team controlling standards and best practice. This is achieved by creating delivery pods throughout the organisation, responsible for identification and delivery of their own automated processes – governed by the CoE.
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Identify the best processes
Always select process automation opportunities that will generate the fastest benefits, and be very clear about what makes a truly good process. For example, best options are those processes suffering from human errors, involving a high volume of manual and repetitive tasks, or require customer experience improvements – such as faster response times.
Also, before automating a process, consider if it really needs streamlining or improving as this requires additional time, cost and effort and usually results in only minor improvements. Any decision should always depend on the overall strategic business objectives for automation. If the requirement is for ultra smooth process delivery, go ahead and improve it, but if cost cutting is the core aim, just automate an ‘as is’ process.
At this stage, liase with the IT department to ensure that there isn’t any maintenance planned for the target application, or the process automation will have to be stalled. To guarantee the traceability of the automation program and before any activities take place, a set of indicators should also be agreed – including; financial, process, quality and performance related KPIs.
To actually start automating processes, capture the correct information in the define phase to avoid problems, so involve knowledgeable subject matter experts in this activity. It’s also worth holding a process walk-through for the right audience. Each chosen automated process must be documented and an understanding gained of how it will differ from the same human process.
Once this has all been agreed with the business, and the process design authority has approved the proposed blueprint and conducted the necessary peer reviews – development can begin. Only when the business is satisfied, can sign-off testing begin. Once the robots are fully working, ensure that they are handing back business referrals, or exceptions, to the operational team for manual intervention, and that a technical capability is readily available in case they don’t act as expected. Ultimately, to ensure continuity and availability of automation resources, there must be a robust, supporting IT infrastructure.
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Build a multi-skilled team
Appointing a high-quality lead developer is essential to deal with any intelligent automation pain points but these people can be extremely difficult to find in the current market. Developers will need to be trained to the highest standard in development and process analysis. As a development team continues to grow, appoint a Design Authority to ensure standards are maintained, and a Control Room Monitor to manage the production robots.
Having the best talent in intelligent automation is the life blood of any successful initiative, and with these skills being increasingly more sought after has led to demand outweighing supply. Therefore, it’s worth considering a partner that provides the human resources, governance, management and methodologies to support global learning programmes and integrate training into rapidly expanding intelligent automation implementations.
Ultimately, to gain the best results with intelligent automation, the complete journey must be defined upfront, rather than waiting for mistakes and then correcting after. Once company-wide support is gained and a vision of desired results created, starting small is recommended, then start delivering – while learning fast – to allow the programme to really thrive as it scales across the business.