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Procurement is, by nature, in the business of relationships. Whether it’s managing suppliers or stakeholders, the success of any procurement organization relies heavily on building relationships between people.
Despite this, many procurement professionals do not have the time to focus on the human side of their job. Data collection, reporting, transactional activities, urgencies, etc. are all tasks that eat up their precious time and prevent them from focusing on relationships that could generate more value and better outcomes. This problem isn’t new and is the main driver behind the constant, growing interest in procurement technologies that automate processes and increase efficiencies.
What is new, though, is the pace of innovation and the hype around some of the latest technologies.
Emerging technologies have begun to dominate discussions in the procurement space, and it has become impossible to avoid debates, articles, publications, etc. on artificial intelligence (AI) or blockchain. The new “hot” technology that has been generating a lot of hype in 2019 is Robotic Process Automation (RPA).
Before jumping on the RPA bandwagon, it is critical to look beyond the features to understand the bigger picture. In the case of the latest RPA technology that has integrated AI, it is about making procurement jobs more human by offloading even more mundane, robotic tasks to… robots!
The goal is to augment, not replace, people by combining the best qualities and capabilities of both human and machine to achieve better outcomes.
RPA: Copy/paste on steroïds…
“[RPA is] a pre-configured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management.”
Source: IEEE Guide for Terms and Concepts in Intelligent Process Automation (whose purpose is to provide standard definitions of concepts, capabilities, terms, technology, types, etc. for emerging process technologies)
This technical definition of what RPA is and how it works can be summed up with a simple analogy. Imagine that you have to repeatedly copy data from one Excel file to another to produce a monthly report. One way to eliminate these mundane, low-value, tedious tasks would be to create a macro that would do all the copy/paste for you.
In addition to saving hours of your precious time over the course of the year, it would also reduce the risk of errors. This is, essentially, a simplified definition of what RPA is about. It’s a way to automate repetitive and scripted actions that are usually performed manually by users (not just copy/paste!). It is a form of business process automation.
The typical benefits of RPA are:
- efficiencies to free-up resources usually spent on manual tasks and re-focus them on core business (efficiency fuels effectiveness)
- better consistency and compliance in data entries by reducing errors
- from a system/IT perspective, RPA is a valuable workaround to break data silos. It avoids the costs (investment, change mgmt.) and risks associated with replacing an existing system or creating interfaces. RPA solutions sit on top of the existing infrastructure and simply simulate user actions to take data from system ‘A’ and put it in system ‘B’.
RPA has limitations and it is i0mportant to be aware of them and consider if the trade-offs are worth it. Some of them are:
- RPA can do one thing and only one thing. If there are changes in the source or in the destination systems, then it will stop to work correctly
- It requires extensive programming to ensure that the RPA solution takes all cases into account. If not, it will not work or, even worse, it will create even more issues as it is very consistent in executing rules. If something is off, the same error(s) will be consistently repeated
- For the same reason, it is vital to ensure that processes are running well before implementing RPA
If RPA only Had a Brain…
There’s no getting around it: RPA is a very dumb technology. It does exactly what it’s told, blindly executing whatever set of rules it’s given. Such technology has been in use for years but on a limited scale. However, with the advancement of other, smarter technologies opening up new opportunities to make RPA more useful and less “dumb,” it is experiencing a revival. AI is one of the emerging technologies revitalizing RPA, and stirring up hype. These days, it’s rare to see RPA without an AI component, which has also lead to a lot of confusion between RPA and AI.
“[AI is] the combination of cognitive automation, machine learning (ML), reasoning, hypothesis generation and analysis, natural language processing and intentional algorithm mutation producing insights and analytics at or above human capability.”
By nature, RPA and AI are very different technologies:
Because most business processes require a combination of “DO” and “THINK,” newer generations of RPA solutions integrate AI components to:
- Understand input via natural language processing, data extracting and mining, etc.
- Learn from mistakes and exceptions
- Develop/enrich rules based on experience
It is this new, smarter generation of “RPA+AI” solutions that has broader applications as a valuable tool for Procurement.
RPA Applications for Procurement
“It is not the type of business process that makes for a good candidate for RPA, but rather the characteristics of the process, such as the need for data extraction, enrichment and validation.”
The Hackett Group
RPA is particularly well-suited for operational and transactional Procurement because these areas are characterised by countless manual activities. Here are some examples:
Automation & elimination of mundane tasks;
- Invoice processing: It is possible to drastically reduce efforts and cycle times to extract essential information from an invoice and perform an m-way match by using a combination of RPA and AI (Optical Character Recognition + Natural Language Processing)
- RFx preparation: Tasks related to data collection (quantities from ERPs, specifications from PLMs or other file sharing systems, etc.) and even the drafting of RFXs can be streamlined by using RPA.
Data compliance and quality:
- Supplier onboarding: RPA can automatically get more supplier data or data needed to verify registrations or certifications by crawling the web or other data sources.
- Data mappings and deduplication: RPA can be a great support in Master data Management (MDM) by normalizing data (typos, formatting, etc.) and by ensuring that naming/typing conventions are respected.
Support to gain better insights:
- Supplier scorecarding: This is an activity that requires thorough data collection. RPA can be leveraged to collect data from various sources and integrate the information into one system either for internal purposes and/or for the preparation of a negotiation or business review
- Contract analysis: RPA can crawl file sharing systems, network disks, and even emails to collect and gather contracts in one central location. Then, it can extract key terms and store them as metadata in a contract management solution.
RPA, in combination with other technologies, is an efficient way to connect silos (from a data perspective) to win back valuable time and remove the “robot” work from the desk of procurement teams so they can focus on the human side of their job.
On top of that, procurement organizations can gain tremendous insights from implementing RPA because it can make new data digitally accessible and more visible.
However, it is important to keep in mind that RPA is only a workaround; it does not break silos like an end-to-end procurement platform would do.
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