Megan Amdahl

If you work in sales, you understand this scenario all too well: When a prospective client requests a quote and makes a purchase, a long and resource-intensive chain of events is triggered. After calculating an expected cost, teammates spend valuable time swiveling about from computer to computer manually entering purchase orders into a system to create an invoice and placing the order with a partner.

It’s common to see businesses of all sizes relying on people-power to complete tasks that today can and should be automated. To address this challenge, companies should consider deploying robotic process automation, or RPA.

RPA uses bots to reduce manual workloads, freeing up teammates to work on more value-added tasks that ultimately enhance the customer experience and create greater job satisfaction. With further implementation of cognitive learning software, which adds reading functionality and features a light level of artificial intelligence, the automated process gets smarter over time. For instance, by reading one purchase order, as you give it more purchase orders, it starts to understand how the fields from one company to the next might be in a different location or spot, allowing the tool to learn, evolve and become more intelligent.

While RPA offers advantages, it can also present difficulties to deal with. Here is a look at the successes, challenges and best practices that other organizations may find helpful in their automation journey.

Improving CX through RPA

Among other functionalities, RPA can be used to fully or partially automate an organization’s manual workloads. For example, it can automate workloads in the areas of deal registration, special orders and backlog management, driving faster and more accurate transactions.

Without automation, sales teams might spend significant time manually entering client purchase orders into systems to create an invoice and place the order with a partner. RPA and cognitive learning can be used to automatically enter purchase orders that come in over email, which triggers the placement of the order with a partner—all without requiring human touch.

By automating aspects of deal registration, businesses can achieve more competitive cost, which can result in revenue growth and margin expansion. RPA capabilities can considerably decrease lead time for a new sale, registering deals more rapidly.

In areas where an organization experiences too many human mistakes or miscalculations, RPA also can be implemented to help avoid the errors that can become costly for a company.

Refocusing employee efforts for added value

Bots work 24 hours a day, seven days a week, which can liberate teammates from working challenging hours overnight and on weekends. With more people-power available, teammates can spend more time on meaningful, fulfilling work.

Procurement teams can use RPA to refocus their efforts from performing backlog management tasks to working to reduce costs, thereby improving margins. Rather than time spent swivel-chairing on backlog management, manually entering one client purchase order after another into the system or repetitively requesting shipping status information from partners, they can spend that time engaging clients in real conversations about what they need – cross-selling, upselling and, most importantly, providing the human touch that bots lack the capability to do.

Being able to offer employees the ability to do more gratifying work and add greater value to the organization should be one of the leading drivers for launching automation initiatives.

Overcoming challenges to automation

While potentially game-changing, RPA isn’t perfect. Environments where RPA can be used, like websites that feature pricing data, aren’t static. Frequent site updates can necessitate the reconfiguration of bots, which requires ongoing maintenance.

To cope with these challenges, organizations might consider dedicating teammates to keep bots on track, as well as address which company operations would benefit most from automation.

Good candidates for getting a good return on investment from automatic processing tend to be areas with high rates of manual touch, with multiple people and systems involved.

Making changes to an organization’s core system can prove challenging, especially if the organization is particularly large or has been around for a long time. The more complex a system is, the more demanding the move to automation will be. To solve for this, organizations can set up their own automation centers of excellence to develop a thoughtful methodology to identify the processes that are best suited for automation. Additionally, instituting a methodology helps ensure that companies are better positioned to get the return on investment they are looking for in terms of improved SLA, accuracy and freeing up teammate capacity in a meaningful way.

Automation efforts should be closely tied to other internal departments, which can ensure consistent quality of RPA bots. Automated processes should go through development and testing to ensure protection in environments as part of a thorough quality review testing process.

Looking ahead: advancements in AI

While automating select services with RPA is the first step that organizations should take, it’s just the beginning. Cognitive learning software can enable the processing of more and more tasks without requiring additional teammate interaction.

Recent advancements in cognitive learning software and RPA have created the ability to scan email inboxes, determine which emails have a client purchase order attached, extract the relevant information and create the sales order, all with no human touch.

Ultimately, RPA isn’t a play on headcount reduction. Rather than spending valuable time processing rote information, RPA is a real opportunity to produce better, timelier results for clients, improve the employee experience, and bring an organization to the cutting edge of operational proficiency.

Megan Amdahl is senior vice president of operations, North America, for Insight Enterprises, a global IT solutions provider. Megan has more than 10 years of experience in financial planning and analysis, cost reduction, process improvement and technical accounting. She’s responsible for Insight’s global logistics, supply chain, business transformation and profitable growth, and she’s led Insight’s implementation of RPA to make client connections more meaningful.