How is artificial intelligence – and its prominent discipline, machine learning – helping deliver better business insights from big data? Let’s examine some ways – and peek at what’s next for AI and big data analysis.
Robotic Process Automation (RPA): 3 use cases to consider
If you're exploring use cases for RPA, sales operations, customer service, and big data offer broad possibilities for pilot tests and early wins. Here's what to ask
Robotic process automation (RPA) is primed to revolutionize the way companies operate, serve customers, and manage data. A 2017 survey by Redwood Software reports that 83 percent of IT decision-makers believe robotic automation is key to their digital transformation strategy, and companies are increasingly investing to automate repetitive tasks, with 59 percent of business processes expected to be automated by 2022. This boom could provide a platform for human creativity: RPA experts highlight the positive effects that automation is likely to have on the labor force and, more generally, the way we work and the skills we use.
Success will arise from communication and coordination between human capabilities and robotic processing power. With RPA primed to play a critical role in digital transformation, it is vital that CIOs carefully consider how to incorporate automation into their strategy.
[ See our related posts: How to explain Robotic Process Automation (RPA) in plain English and Robotic Process Automation (RPA) vs. AI, explained. ]
There is no one right first use case, but several areas can lead to early wins. Here are three crucial areas worth exploring as you develop your RPA journey.
RPA use case 1: Sales operations
Sales operations are a crucial aspect of all businesses, irrespective of size or industry. Today, RPA is capable of transforming a host of sales-related activities, including data replication, invoice preparation and delivery, and consistent updates of customer relationship management (CRM).
CIOs are increasingly being tasked with taking on projects that generate revenue for their organizations. Injecting automation to the sales process can play a role in that. For example, consider CRM and accounting records. Software robots are now capable of handling these operational activities on their own. A virtual agent can make sales invoices available to customers much faster than it could be done manually. They can accurately include purchased items, quantity, discounts received, and total expenditure, all in PDF format, by automating the transfer of data between systems. This change has desirable effects, such as earlier payments and greater clarity for customers. Consequently, cash flow and customer satisfaction improve.
[ Want lessons learned from CIOs applying AI? Get the new HBR Analytic Services report, An Executive’s Guide to Real-World AI. ]
If you’re looking to incorporate RPA into portions of your sales process, be sure to ask:
- Does it integrate with the current CRM systems in place?
- Is it compliant with security systems?
- Which processes, if automated, have the potential to generate the most revenue?
RPA use case 2: Customer service operations
Perhaps the biggest misunderstanding of RPA is the notion that it will replace employees. We’ll blame movies such as “Blade Runner” and “The Terminator” for this. Surprisingly, these films are inaccurate: RPA extends the capabilities of human workers. However, mitigating this fear factor is not easy, and advocating RPA to the workforce is a huge challenge facing CIOs. Assisting customer service operations is a key way of demonstrating the benefits of a human-automation partnership.
[ When you say RPA, some people hear “job loss.” Read also: Robotic Process Automation (RPA): How to persuade skeptics. ]
Customer service is one of the most complex yet pivotal activities in a company, and collaboration between human and robot can greatly improve your customer satisfaction while making work less stressful for your employees. How? Simple, repetitive, high-frequency tasks, such as making and updating customer profiles, can be automated. Virtual agents can take profile data from customers during over-the-phone bill payments, for example, and direct them to the right person to handle their request with automatic triaging. Subsequently, customer waiting time is reduced and employees are free to utilize their emotive communication skills.
Expanding front-end automation can also enhance customer communication. For example, it can trigger a notification when it’s time to follow up with certain customers or if a customer has submitted a complaint, or send automated messages to customers regarding new products.
By automating redundant tasks handled by call center agents, RPA offers these agents a golden opportunity to focus more on building a relationship with customers. When considering implementing RPA, be sure to determine:
- Where it can best improve customer engagement
- How it can collect customer data
- How to get your employees on board
[ Can AI solve that problem? Read also: How to identify an AI opportunity: 5 questions to ask. ]
RPA use case 3: Data manipulation and management
One of the most powerful capabilities of RPA is its ability to organize and harness large compilations of unstructured data.
Data manipulation can be arduous and monotonous for some of your employees. (Know anyone who’s immediately turned off by the mere mention of spreadsheets?) The perfect thing about RPA is that it has no emotions or interests, and therefore won’t distinguish between data manipulation and the latest sporting results. Everybody wins!
In the digital era, the CIO must analyze how to best extract knowledge from the data that companies constantly collect. Consider RPA to analyze which of your products are purchased most often at particular times of the year, and you are onto a winning formula. Using big data analytics through proper RPA installations can pinpoint actionable tasks for improvement and optimization, exposing deficiencies and hidden patterns.
When considering big data challenges and RPA, CIOs must ask themselves:
- How quickly can we begin using RPA to manage big data?
- What are the consumer trends being displayed by structured data?
- How can we use big data analytics to beat our competitors?
Choosing your RPA use case
The functions listed above certainly do not exhaust RPA’s application areas; the software has broad prospects. But whether you are starting your RPA journey or already reaping the rewards of automation, the three areas of sales operations, customer service, and data analysis offer rich opportunities for pilot tests and early efforts.
[ How can automation free up more staff time for innovation? Get the free eBook: Managing IT with Automation. ]