According to Gartner, a typical, modern organization has implemented five major firm-wide changes in the last three years. And 75% of firms are expected to undertake even more changes in the next three years.
But, per Gartner’s report, half of the change initiatives fail, with only 34% having a chance of “clear success.”
According to Forrester, some possible reasons for unsuccessful change initiatives are the followings:
- Manual documentation of changes,
- Lengthy change-approval processes,
- Redundant meetings with change advisory boards (CAB),
- Inefficient risk assessment processes.
Automation tools, such as RPA, can help automate change management, and by doing so, increase the speed and the efficiency at which they are done. In this article, we aim to explain the top 6 use cases of RPA in change management.
What is change management?
Change management refers to the systems and processes in place to help organizations change the different dimensions of their day-to-day business operations.
Some changes are granular and incremental, while others are more transformational. Some common examples of organizational change include:
- Updating the company website,
- Creating a new department,
- Creating new positions,
- Launching new marketing campaigns,
- Switching suppliers,
- Mission statement changes,
- Digital transformation, and more.
What is change management automation?
Change management automation is software that leverages automation tools, such as RPA, and a host of other cognitive automation technologies – such as NLP, OCR, and other AI/ML models – to automate the manual steps that are within the change management process.
What are the top 6 use cases of RPA in the change management process?
The change management process usually revolves around the following main steps. We will explain the benefits of RPA within each step.
1. Filling out a change request
The employee or department head advocating for a change should first fill out a change request form (see Figure 1). A change request form mainly contains:
- Project name,
- Description of change,
- Reason for change,
- Priority level,
- And various performance KPIs.
Getting these forms and manually filling them out is time-consuming. Companies can leverage RPA-enabled chatbots to transform the document-filling process into a two-way conversation.
So instead of an employee filling each row of information in person, the chatbot will ask questions regarding the details of the change request form to the employee and fill it accordingly.
The benefit of using chatbots is that the process loses its bureaucratic persona and adopts a more engaging and conversational tone.
2. Collection and referral of change request
The requests should be collected periodically in order to be assessed, analyzed, and perhaps implemented, as soon as possible.
For paper-based documents, the person in charge of collecting these forms might forget to do so, or forget to refer them to the person responsible. On the other hand, the employee submitting the request might fill out the form but forget to submit it.
These mishaps invalidate the whole process of change requests.
RPA can be used to:
- First, transform the transcript between the employee and the chatbot into a machine-readable format.
- This structures the change request and makes sure the data format is aligned with the company’s archiving policy.
- In addition, RPA, via OCR, can extract the change request’s recipient email address. It then can automatically draft an email, attach the PDF version of the change request, create a support ticket on the ERP for the request, and forward it along to the email address.
The benefit of automating the collection of change requests is that the RPA will immediately send it to the person of authority’s email address, thus eliminating the possibility of delayed collections and pile-up of change requests all in one queue.
3. Preliminary assessment
Same as with resume screening, where the RPA bot can go through candidates’ resumes for preliminary checks to see if they meet the initial criteria, they can also be leveraged to see which requests make it past the first round of revisions, without human oversight.
The RPA bot will cross-check each row of entries with a series of pre-approved, rules-based metrics to ensure the request is compliant. For instance, the company policy might deny employees with less than 2 months of working with the company to submit change requests. Via API, the software will extract the employee’s information from the database and the RPA will check if the employee making the request passes the 2-months threshold.
Or the company might want to disregard all automation initiatives that might push back the deadlines of projects that currently rely on the old method of doing things. The RPA will use NLP capabilities to read if the answer to “will it impact the project’s deadline?” is “yes.” It will then reject it, or if the employee’s answer is unclear, then will it be forwarded to a human for further assessment.
Thus, RPA ensures the requests sent to the change advisory board (CAB) all meet the basic criteria. And no human effort would be spent in that stage. Furthermore, sacrificing the quantity of the requests for quality also allows managers to spend more time assessing the submitted ones.
Once the request has passed the initial assessment, it can now be fully evaluated by the RPA bot. It could also be partially evaluated, flagged, and sent to the CAB for human intervention.
RPA bot can undertake the evaluation process by leveraging data in a decision table (see Figure 2).
For instance, a salesperson might want to submit a change request for offering one of her/his clients a “Gold discount.” The RPA bot will cross-check the client’s qualifications against predetermined criteria, such as:
- If the client in question has ordered more than 50 units in the last three months,
- And if they have settled their account on delivery.
If the conditions are met on an “if-then” basis, the bot will automatically approve the request and move it onto the second round of assessment. If not, it will reject and disregard it.
The benefit of allowing RPA bot to evaluate requests is that, like a foot soldier, they will always carry out their responsibility with respect to the rules-based orders they are given. Moreover, the number of lengthy CAB meetings will also be reduced. Another benefit of automating evaluation is it eliminates possible human prejudices when assessing change requests.
An international advertising agency wanted to reduce the workload of its IT team by automating the evaluation and assessment of change requests that its department received1.
By leveraging a change management automation solution, they were able to increase their adoption of self-service and self-help features, which allowed employees to autonomously submit their requests and wait for a response, as opposed to getting a human involved. Other benefits included:
- The IT team’s staff dedicated their time to more value-driven tasks,
- The software eliminates ticket backlogs by receiving and assessing requests in a timely manner
A survey has shown that 1 out of every 3 projects in the workplace fails because of miscommunication. That is why it’s paramount for CAB to clearly, and punctually, relay the pending changes to the management, stakeholders, and employees so the workflows can be adjusted preemptively.
RPA can be used to create automated emails to send to registered email addresses of the stakeholders, and all department employees to which the change is going to affect. The timely sending of these emails prior to a full-blown implementation can allow all relevant personnel to assess how they should approach these changes, or whether they want to be a part of it at all.
The email thread can also contain a link to Google Calendar, or internal calendar apps, which the company uses, to allow personnel to automatically schedule virtual meetings with each other, the management, and the CAB to go over the details of changes in person (see Figure 3). Moreover, the ML model can also recommend discussion topics for meetings by leveraging the data that is on the change request form and the submitted feasibility study of this transformation, such as high-risk changes, or changes that are yet to win majority support.
After a certain process has been approved and implemented, process KPIs should be monitored to measure the impact of the actual change. For instance, if the accounting team automated their procure-to-pay (P2P) process, a KPI to monitor is the number of time employees has now saved by letting bots do their jobs for them.
Manually gathering the data from different ERP and DevOps systems can be error-prone and time-consuming. RPA can be used in this stage to gather the reporting data from various ERP applications for data-driven insight.
Another benefit of automated monitoring is that with the advance of ML models, and thanks to the repeated interactions with data, the algorithm can preemptively suggest changes before a request has been formally submitted. For instance, if 4 of the last 5 change requests across all departments were about establishing an infrastructure to allow for remote working, the solution can automatically detect that pattern and inform the C-suite of another possible request.
Such insights that might go unnoticed if requests are all paper-based and swiftly get archived without much attention can allow the company to increase its agility in terms of addressing employees’ requests.
For more on RPA
To learn more about the use cases of RPA automating other business workflows, read:
- Top 7 Business Use Cases of RPA in ERP Applications
- Top 12 Use Cases of SAP Intelligent Robotic Process Automation
- Top 16 RPA Use Cases in IT Services
If you believe your business would benefit from adopting an RPA solution, we have a data-driven list of RPA vendors prepared.
We are here to answer your questions when it comes to choosing a vendor:
- Change request evaluation case study.
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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