Welcome to part 5 of an ongoing series of blog posts demystifying “process intelligence” - the terms, the technologies, and how and why process intelligence can help improve your business. In our previous blog post, we discussed building process transparency. For this week’s blog post, we will be looking at scaling process automation. Process Intelligence helps automation leaders build a data-driven approach to their automation strategy, including when deciding what to automate as well as building a quantifiable business case.
As always, you can learn more about this and related topics by reading the Skan Process Intelligence Playbook here.
Adoption of RPA is growing fast, but one question remains: will it scale?
Tools that enable the automation of digital tasks and processes, such as robotic process automation (RPA), have surged to the forefront of transformation and IT budgets over the past several years. Below are just a few of the impressive data points which highlight the technology's incredible growth in recent years:
Despite this impressive market growth, RPA has not been without its share of challenges, particularly in growing from pilot projects to scaled, organization-wide implementations. For every RPA success story, there is an example of underwhelming results, unclear ROI, or failed implementation. In fact, Deloitte found that only 3% of the survey’s 400 respondents reported that their organizations have been able to scale their digital workforces.
Challenges with scaling RPA
So with all of the success and excitement surrounding the technology, why have so many companies struggled to scale RPA throughout their organization?
We have found that there are often four common challenges which impact the success of RPA efforts (this was also the topic of my recent keynote presentation at Reuters Insurance AI and Innovative Tech conference)
Without a detailed, data-driven foundation and understanding of the end-to-end process, overcoming these challenges becomes difficult if not impossible. Building this data-driven view is where process intelligence can help.
How using Process Intelligence can help overcome these challenges
Process Intelligence overcomes many of these critical challenges mentioned above by enabling organizations and automation leaders to use data to guide, measure, and validate their first automation efforts. Below are just a few of the ways Process Intelligence can help build a data-driven approach to automation:
Ready to learn more? Read the Process Intelligence Playbook
Modern process optimization requires a data-driven approach. That means considering all the technologies that can help you do that.
Wondering where to get started?
Skan’s actionable Process Intelligence Playbook explains approaches to process discovery, how to get started with process intelligence, and illustrates process transparency in action through real-world applications.
Ready to learn more? Download Skan’s Process Intelligence Playbook today.
“One of the things you don’t ever want to do is to automate a bad process. You are just going to make bad things happen faster, and that is not what anyone wants.”