Signals #2 – Robotic Process Automation

Challenge

  • People are best suited for collaboration, creative tasks and decision-making. When performing mundane and repetitive tasks we are slow, make mistakes and get bored.

Opportunity

  • Automate the routine digital tasks with Robotic Process Automation (RPA). Free up precious time for doing more work with added value.

Cases

  • Wärtsilägot their first automation running in 3 weeks. They have now 400+ processes automated and over 5,000,000 € saved.
  • Coca-Cola automated 50+ processes across multiple SAP systems. The company found 16 extra hours/day that could be used for productive work by the new digital workers.
  • Posti(the Finnish postal service) used RPA together with machine learning to automatically process 3000 purchase invoices monthly.
  • First Home Bank used bots to help process over6,000 PPP loan applications in a few months. The bots were 30x faster than humans.
  • Lyse automated submitting applications for government approvals. 20,000+ work hours saved annually.

Actions

  • Adapt automation to yourmindset. Start a habitto look for tasks that are repetitive, high-volume, rule-based and prone to human error.
  • Start low-risk, start small. RPA provides this approach. Integrating existing software systems might be expensive or even impossibleRPA fills the gap especially when it comes to legacy system interactions.
  • Apply this 4-step approach:
    • Start to automate micro-tasks first. The simpler, the better.
    • Look for processes where you can gain a lot of value by automating.
    • Map out the processes step-by-step. Then create the automations and test them.
    • Measure results. See if the initial ROI justifies larger investments.
  • Decide whether you want to go the commercial or the open-source route (see Tools-section below).
  • Remember also scriptingmacros and APIs. RPA is just one of the tools in the automation stack.

Tools

Forecast

  • Everyday automation is increasingly making headway. In over half of occupations, 33% of the repetitive tasks have potential to be automated.
  • Software robotswill become commoditized in the future. With increasing competition, prices will be driven lower. As prices go down, RPA will extend its reach from big enterprises towards small-to-midsize companies.
  • Automation departments will emerge in organizations as everyday task automation increases. The need for a Chief Automation Officer (CAO) becomes apparent.
  • As CAOs emerge, so will citizen developers. Done right, they can help scale an automation initiative. Done wrong, they will produce heaps of technical debt to be handled.
  • Existing automations are still highly procedural. Some character reading and computer vision capabilities exist. The future will likely see prebuilt blocksof machine learning, natural language processing and computer visionused inside automations.

Challenges

  • Immediate resistance from your team is likely to occur. Onboard the team and management early on to embrace the change.
  • Typical other pitfalls: automating processes that are too complex, difficulties to scale and selecting processes that have insignificant business value. More lessons learnt can be found from research.
  • Community editions let you get started for free. When scaling further, investments are required. But there’s always the open-source option.