Challenges on the road to automation
Automation is often pitched as a magic formula for cost reduction. Most automation conversations focus on technology – that’s the easy part. However, we believe that strategies that are only technology-led without people at the centre can create challenges and setbacks. A digital transformation that sets out to automate an enterprise should be backed up by robust strategies for change and communication, and support people as they transition into new roles, learn new skills and adapt to the new digital ecosystem. At Baringa, we work holistically across people, process, and business functions to ensure that automation initiatives are deployed, embraced and scaled effectively. In our experience, here are the biggest pain points that organisations are likely to encounter on their intelligent automation journeys:
Management vision and support
Some key stakeholders may be cautious of new technologies. If unaddressed, their concerns can inhibit the growth and success of the automation programme. To prevent this scenario, key stakeholders must be engaged early on and throughout the project. The team leading the deployment must demonstrate a strong value proposition and clearly articulate the benefits that the automation solution will bring. It’s important to set realistic timescales for benefit realisation, and be aware that some vendors may exaggerate ROI payback times. Moreover, successful IA programmes need strategic leadership and sponsorship from the C-Suite. This ensures that the programme focuses on transforming the overall business and operating model, rather than being a siloed project within a single business unit.
Cost and efficiency
Some IA technologies come with significant upfront costs. To make the most of these solutions, organisations should ensure they have a suitable pipeline of use-cases to justify the investment, otherwise the programmes can lose momentum. In our experience, approximately 70% of RPA projects plateau at fewer than 50 bots.
Business processes and requirements are constantly evolving, so organisations must plan how they will manage changes to their IA solutions. One option that works well is setting up a centre of excellence to maintain IA solutions, capture and govern any changes required, and monitor performance. At a strategic level, an IA CoE can become the centre of enterprise digitisation; and can be used to monitor the organisations’ digital transformation progress.
CIOs should understand and anticipate the impact of IA on their workforce. They should identify the skills their employees will need for the IA transformation, and develop appropriate training and development plans. Existing skills that can be applied differently to best complement IA should be sought out and nurtured. As technologies progress, human skills evolve – job designs should change to reflect this shift.
When choosing a process to automate, it is important to think through how the automation will impact customer experience – whether that is an external customer, or an employee interacting with an application or system. Processes should be redesigned to be customer-centric and outcome-focused.
Vendor and technology selection
A tools-first approach is one of the main reasons why many IA implementations fail. When departments buy IA technologies in isolation, without an overall strategic view of the enterprise, they can end up with disjointed solutions that offer limited potential. Furthermore, the technology selected must integrate with and complement the existing technology stack. Often, there will need to be several technologies working together, so it’s important to define the target state and consider it during the tool selection, to ensure that all the technologies integrate smoothly.