“It didn’t really start as anything fancy,” says Wei Loong Chong, who is now Business Automation Project Leader for IBM Finance. “But it turned out to be kind of our Big Bang moment.” One day in 2019, Chong and some teammates were chatting with members of IBM Finance’s Pricing team in the ASEAN region about ways to improve processes.  

The chat catalyzed the project that automated 4,800 yearly hours of manual data gathering, calculations and data entry. At the time, Chong and his manager, Sue Rynn Tan, were not automation experts; they were finance process experts with the general goal of improving efficiency. Now, they stand as examples of how dedicated people can build automation expertise fast.       

“None of us had coding background in [Robotic Process Automation (RPA)],” says Chong.

Fortunately, around the same time, IBM’s Automation Center of Excellence (CoE) was running a global enablement program to train IBM employees across disciplines to identify and implement automation solutions. Tan, Chong, and team brought their process-improvement ideas to a bot camp led by the CoE. “We created a prototype in two weeks,” says Tan.

The prototype bot was trained to assist transactional pricers, who determine the right pricing for high volumes of IBM software subscriptions, renewals and upgrades quarterly.

IBM has several small teams of transactional pricers around the world to support the company’s global sales force. They process about 100,000 subscription, renewal or upgrade offers per year, touching each one four times on average. These are submitted to pricing by sellers or IBM Business Partners, and the submissions are known as bids.

“The bids volume skews heavily toward the end of the quarter,” explains Kyle Springman, Director of Worldwide Volume Transaction Pricing. “At quarter-end and especially at year-end, our pricing teams could each be handling 2,000 to 3,000+ bids in a week. And we’re not staffed to the peaks.”

Josh Atencio, a pricer in North America, describes the year-end experience firsthand: “We have 15 pricers for North America. During peak times we can have 100+ bids in the queue when we start the day, and throughout the day people are submitting more and more. We can finish 200+ during the day and get the volume down pretty low, but the next morning you're waking up and there can be 100, 120 new bids in the queue waiting for you. It’s a battle.”

And many of the bids are complex, covering integrated, multi-product technology solutions with various factors affecting pricing. Sellers often propose customized bids for their clients, and it’s the pricers’ job to evaluate the bids, adjust them if necessary and approve them so the sellers can present the offers to their clients. “It’s about finding the fairest price for both our client and IBM, and doing that with speed,” says Springman.

“Every seller wants attention on their bid at that moment,” Springman says. “So the more we can do and the faster we can do it, it’s a better outcome for sellers and our clients. It’s a high, high pressure environment.”

And the challenge was compounded by the prevalence of manual tasks. “Before automation, we had a lot of different tools and calculators. Everything was very manual,” says Atencio. For example, pricers had to fill out a parts-check file for each bid, listing every product part number and calculating allowable discounts for each. “It has a ton of information,” says Atencio, “But it’s all basically administrative calculations, it just takes lots of time to do it manually.”

Pricing leadership wanted to save their people for the work that requires a human mind. “Negotiating the price with the seller, or assessing whether different agreement terms would better serve both IBM and the client,” says Springman.

Springman and team explored the possibility of fully replacing legacy bid and pricing tools with an integrated, end-to-end solution, but it was cost and time prohibitive. Springman sums it up: “My pricing team is crushed today. How do we make this easier and smarter without having to spend 18 months and USD 10 million to modernize all the legacy technology?”

The answer began with the automations in ASEAN. Now, Tan, Chong and team needed to help other regional pricing teams in the same way.

Rather than working on separate, custom regulations for each region, Tan and Chong kept the bigger picture in mind. Before developing any automation, they worked collectively with the process owners to reevaluate existing processes and design an optimal flow that could be applied globally. As Springman puts it, “Automation became a standardizing force.”
 
Of course, the discussions with the local teams weren’t always easy. “If you try to introduce or eliminate a process, you will receive pushback,” says Chong. “But we try to understand the rationale before we really suggest changing the process. That’s step zero.”
 
“Automation is always the last step,” adds Tan. “No point automating something that doesn’t make sense.”
 
The team recognized opportunities to automate much more than the tasks they’d initially automated in ASEAN. By partnering with the CoE, they gained self-service access to IBM® Robotic Process Automation (RPA) software via a centralized platform based on IBM Cloud®, ensuring that the RPA solutions would have the computing resources they’d need. “The CoE provides the automation platform so the teams can thrive,” says Ana Gerin, CoE Lead. “We worry about trainings and certifications and platform maintenance, so they can focus on finding opportunities to automate.”
 
With the platform in place, the team took their automation plans and ran with them. Rather than hiring new developers, they continued what had worked so well in ASEAN: letting the process experts do the automating. “Automation is no rocket science,” says Chong. “You can start to design a bot with two to three months of learning. If process experts learn RPA, they’ll be equipped with process knowledge and automation skills that allow them to zoom right into the pain area to work on it.”  
 
The first pricing automations to go global were the copying of part numbers from the bid into the parts-check file, calculating prices and listing potential discounts. “RPA is doing all these different checks for us, and it’s spinning out one PDF,” says Atencio. “Then we can approve it or recommend changes. That has been huge for us. That’s seven minutes I just got back for one bid. Compile that over a day, now you’re getting half an hour to an hour back. We get that bid done faster and we get to work on more bids. It helps the pricing work itself and our sales reps, and it helps our clients get that quote in front of them a little bit quicker.”

As Tan and Chong’s team continued the cycle of speaking to pricers about their work, helping design optimal processes, and applying automation where it made the most sense, two things happened.

First, the team became more efficient at delivering new automations. “If something took us three months to create before, now we can create something similar in three to six weeks,” says Springman.   
 
Second, the pricers bought into the improvements and became proactive. “When they see the automation benefiting them,” says Tan, “that’s when they’re like, ‘Okay, I think I can do much more with automation.’ Now, instead of us begging for projects, people are like, ‘I have this project for you’ or, ‘Can you quickly do this?’”
 
“It became a crescendo of value, and it unlocks a lot for us,” says Springman.  
 
The crescendo even reached the sellers, who have benefitted from automations that help them create and submit bids to pricing. Cole Moore, an IBM subscription and annuity seller for six years, explains, “We’ve got renewals that come in every quarter. I've got 75 accounts and 50 of them are due on January 1, 12 of them are due on February 1 and the rest are due March 1. And on average, it was probably seven different software tools that we were in to submit each renewal, looking up part numbers, trade-up conversions and calculating prices.” With those tasks automated, Moore says, “Instead of having to do all those different steps, you build one document and it does all of it for you.”

Using IBM RPA, the transactional pricing team automated more than 50 previously manual checklists and enabled 15% of bids to be auto-approved based on predefined rules. They have eliminated about 35,000 hours of manual work per year and reduced the average bid cycle time by 75%.

Beyond the efficiency gains, the solutions helped improve how the recipients feel about their work. “The pricers feel that their responsibility and importance has increased,” says Springman. “They get to focus their time on making the actual decision: is this the fairest price? Is this the right economic decision?”

In Sales, the time savings helped Moore add a new dimension to his job. “I like training folks, so having a little bit of extra time absolutely helps, because I can build better content.” Moore used the extra time in 2022 to build an IBM-internal channel of short training videos to help new and existing sellers fill skills gaps.

“There’s still a lot of manual work around,” says Tan. “We see that as opportunities.”

Tan and her team are part of IBM Finance’s Data Science & Technology group, led by Josephine Schweiloch. Schweiloch explains that the group’s projects are evolving to tackle larger challenges. The CoE automation platform allows access not just to RPA, but also to the rest of the components in the IBM Cloud Pak® for Business Automation suite, which Schweiloch’s team is using to build more sophisticated solutions.

For example, they’ve begun work on transforming complex internal workflows with varied stakeholders. The team has applied the Cloud Pak’s IBM Process Mining software to create a visual map of existing workflows and recommendations for improvement, which allows them to easily identify bottlenecks and other inefficiencies, such as steps that rely on email and manual spreadsheet work. Then the team can transform those steps using RPA along with other IBM Cloud Pak components that automate workflows, rules-based decisions and digital data capture from a variety of sources.

“One of the things that's most exciting for our team is that, with these multiple automation technologies on the Cloud Pak, we’re able to calibrate for different types of projects and problems,” says Schweiloch. “It really gives us a lot of arrows in the quiver, and a lot of power to solve complex, enterprisewide problems and provide analytical insights and huge efficiencies.”

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