However, in order to maintain and manage a successful RPA solution in your business, you need to measure important post implementation KPIs which can be difficult to identify.
In this article, we identify the 5 most important steps to measures after RPA implementation.
1. Measure the ROI after the initial RPA implementation
Measuring RPA’s impact helps elevate the role of the implementation team, builds an appetite for further productivity improvements and encourages the team to identify areas where they can improve. Though it is complicated to do a thorough A/B test with process automation, looking at output and size of related teams before and after the RPA implementation will give a good idea about the impact achieved with RPA.
2. Keep track of already automated processes
Long-term IT investments can sometimes be planned in isolation of capabilities developed by non-tech teams. And RPA gives non-tech teams a strong tool to automate their tasks. Therefore it is important for tech and non-tech teams to collaborate and ensure that automation completed with RPA are not re-programmed in applications. Scarce technical resources would be better deployed in building changes to applications that can not be completed by RPA tools.
3. Launch an RPA center of excellence
Once you have proved the benefit and viability of RPA projects, you need to consider how you can launch new RPA projects effectively. Most large companies choose to have RPA centers of excellence that help teams launch, audit and improve RPA projects. The crucial thing here is ownership. The business units themselves must be responsible for RPA installations or else center of excellence teams will find themselves responsible for processes they do not completely understand. Center of excellence teams should focus on aggregating best practices and helping teams ramp up quickly.
4. Manage RPA impact on jobs and existing teams
RPA will inevitably lead to predictable redundancies as bots take over more work from humans.
For all/most employees, once most of their responsibilities are automated, new responsibilities can be assigned. The good thing is that you will know in advance which personnel will be redundant which gives managers time to identify new roles for the personnel and train them for the transition. However, this can not be a departmental effort. HR should coordinate the new assignments and managers across the organization should be motivated to take on employees that have become redundant.
As with any industrial revolution, the post-AI world also makes some formerly valuable skills redundant. Workers who are specialized in automatable tasks will inevitably be let go if they fail to improve themselves. Though hopefully, such cases will remain rare, it is critical for management to handle those cases as professionally as possible. People need support from their old managers to continue their professional lives in the best way possible.
5. RPA Training
Since RPA bots need to be programmed, there’s a whole industry of RPA courses and tutors. If you are aspiring to get a job programming RPA software solutions, think twice before you pay for any training. RPA companies are doing their best to make sure that their solution is the most popular among developers so there is a high-quality free training and community support online. I would first take some free courses and then explore paid alternatives after getting familiar with the products.
If you are already working for a partner or customer of these companies, then you can use their training for free to improve your skills. We have an article on RPA training where we collect RPA training resources.
For more on RPA implementation
To explore RPA implementation steps from start to end, read in-depth about:
- Identifying and Prioritizing Processes to Automate with RPA
- 3 Steps to Get Buy-In For RPA
- Top 100+ RPA Use Cases/Projects/Examples in 2024
If you need more answers about RPA, read our comprehensive whitepaper on the topic:
And we can guide you through the process:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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