IA in 2021 & Beyond: 10 Key Factors

Over the past half a dozen years, SSOs have come to – initially, cautiously, experiment with and then enthusiastically embrace process automation technology.

In the early days, this took the form of robotic process automation (RPA), which served to knit together disparate tasks, acting as a band-aid to connect different systems or applications. Today, this trend has morphed into a sophisticated movement, embracing the concept of the “digital enterprise” as it drives smart automated solutions through “platform” thinking.

Automation’s importance is further amplified (and adoption accelerated) as SSOs developed new ways of working due to the pandemic. SSON’s Top 20 Most Admired SSOs of 2020 cited automation as a key enabler to help adapt their service delivery model to the current business climate.

According to SSON Analytics’ data, Intelligent Automation (IA) is predominantly seen as a means to achieve a) process efficiency, b) optimize workflow productivity and c) improve customer experience. SSOs can also expect to achieve an average cost savings of $50,000 -<$100,000 a year for their highest performing automated process – the median benchmark for North America (Metric Intelligence Hub).


While majority of SSOs have embarked on their automation journey, only a third of global shared services have reached advanced automation maturity i.e. adopting cognitive solutions and scaling them successfully. There are many factors to take into consideration, and challenges to overcome for a successful IA program. The two most cited challenges limiting IA implementation are the lack of understanding (knowledge) and siloed enterprise structures that do not support integration.

Some key factors to take into consideration include:

  1. Who will own the IA agenda in your enterprise?
  2. Process selection and functional priority
  3. What automation solutions should you adopt? Attended or unattended automation?
  4. Which technologies are necessary for IA integration?
  5. How are you filling the IA skills gap?
  6. Integrating additional solutions (Machine Learning, Cognitive, Computer Vision, NLP, AI) with RPA. Which should you prioritize?
  7. What are the barriers to scaling?
  8. How do you get to enterprise-wide implementation?
  9. Impact of IA on the workforce
  10. How do you measure the performance of the digital workforce?


The possibility and growth of Intelligent Automation is endless. 43% of shared services expects IA to evolve via a best-of-breed combination of different technology stacks, while just under a third expect to leverage cloud-based platforms that enable access to different vendor solutions.

To gain clarity over where and how shared services are riding the IA wave, look to SSON Analytics interactive workbook: Global Market Review – Intelligent Automation in Shared Services. For regional automation benchmarks, visit SSON’s go-to benchmarking platform: the Metric Benchmarker.

Follow SSON Analytics on LinkedIn and Twitter for data updates. Subscribe now, to access more than 100 key benchmarks and metrics, as well as to compare your initiatives and achievements to the Top 20 Most Admired SSOs – all available via subscription here

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