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Customer Point of View: Highs and Lows of the Intelligent Automation Journey

by Neil Murphy, Chief Sales Officer

It’s not about taking an existing process and automating it, but reimagining what you were trying to do in that old process to begin with.


Anyone embarking on a major change in life would welcome advice from someone who’s already been through it—and that includes digital transformation.

In our final webinar for Intelligent Automation Month, a series of digital events ABBYY sponsored during September to explain the power of intelligent automation, we invited leading innovation experts from global companies to tell us about their journeys: lessons learned, success stories, and what they’d do differently.

Joining us on the panel was Shanx Tripathi from IBM Consulting - financial services sector, and Swaraj Padma, head of automation at international real estate and investment company JLL, along with ABBYY’s own Senior VP of Product Marketing Bruce Orcutt.

With recent research by ABBYY identifying “vague automation goals” as the top reason for automation projects to fail, I was keen to know how IT leaders determine where to start their automation journeys.

Knowing where to start

As one of the biggest commercial real estate companies in the world, JLL had a multitude of forms, documents, and contracts that were being processed manually. The need for automation became clear in their efforts to improve document-centric processes in all aspects of the company—but equally as important was the need for a scalable solution and tech stack that could handle their continuous growth.

The company decided the best place to start would be payments processing, where employees were still receiving invoices by email and manually punching in the data. The success of automating this small part of the finance department helped JLL realize the need to go further and automate the entire AP process end-to-end. This not only resulted in improved efficiencies, said Swaraj, but generated money for JLL through virtual payments and provided greater visibility into their financial operations.

It helped finance to foresee monthly expenses, improved cash flow, and streamlined financial reporting like OpEx calculations. What started as a small use case for invoice data capture just kept growing, eventually expanding into major operational efficiencies providing far greater benefits through end-to-end processing.

As an IBM Consultant, Shanx has delivered change programs with leading companies such as Toyota, Proctor and Gamble, and Intel. He believes automation is not just about use cases but is rather a mindset, starting with basic things like considering how the innovation team will operate, whether to use project management tools, or how to track your own progress and report to leadership. He says you can’t digitize the life out of a client-facing process when your own operating model is pathetic. After all, the ultimate goal of any business is to serve its customers. Therefore, it's crucial to focus first on client-facing experiences and work backwards from there. If your internal operations can’t support the ideal customer outcome, you must address that underlying issue.

Reimagining the process: financial services client onboarding

Shanx recently worked with a leading bank on automating client onboarding; not personal or individual customers, but institutional onboarding where there are many challenges such as KYC compliance and other strict documentation rules.

He discovered the industry average for onboarding was between 60 to 70 days with the bank providing him with nine different process maps of how it works. However, instead of automating the bank’s current system, he decided to implement an entirely new one that enabled onboarding to be completed in a matter of hours rather than months.

It’s not about taking an existing process and automating it, he said, but “reimagining what you were trying to do in that old process to begin with.”

The importance of staying on time

One of the biggest challenges of undergoing digital transformation is staying on target with your timeline and meeting the designated KPIs. Research commissioned by ABBYY showed one-in-five abandoned their automation project completely (22 percent).

We asked our innovation panelists the key to sticking to timelines, and according to Shanx, the simple answer is “procurement.” He believes it’s the mundane tactical thing which often gets short shrift when people are very excited by the whole transformational agenda. His recommendation is to have the procurement lens parallel to the operational and work lens and ensure a strong partnership from the start. He’s also a firm believer in agile methodologies, which are key to meeting deadlines.

For Shanx, meeting deadlines is heavily dependent on diversity in your automation tools, as oftentimes no single platform caters for an end-to-end solution.

He believes that maintaining clarity in documenting your true end-to-end process and having the right kind of tool attached to each fragment of that newly imagined journey will help you stay on target.

Intelligent Document Processing in Financial Services: Use Cases

Learn more

Examples of measuring value

Apart from the fantastic achievement of reducing customer onboarding times in banking, Shanx spoke of his success with clients in the insurance industry. He was responsible for reducing claims processing times from an average of 16-20 days down to just one day, following the introduction of a digitized system to rapidly resolve identified genuine claims, such as when there is obvious damage.

One of JLL’s biggest success stories was automation of lease processing, which not only improved security but also had a huge impact on employee morale.

The process was previously manual, meaning staff had to print out information and manually upload details to track contracts on their document management system. This posed a huge security risk and the potential for reputational loss.

JLL saw benefits of transformation from the perspective of operational risk and operational efficiency but hadn’t foreseen the huge impact on employee experience. Their staff had been going through 10 different processes manually and felt they weren’t contributing to any kind of worth for the organization in doing this. After automation, employees could focus that time on more important components of their job which led to a huge increase in morale, according to a company survey.

Meet demands for self-service

One area that has been driving automation is the demand for self-service from customers, who’d rather complete their requests online than in person. With machine learning and generative AI now in the mix, the pressure for self-service options is greater than ever.

Clients want a short, sweet answer to their questions straight away. They don’t want to be sent a huge PDF of a contract and told to either find the answer themselves or wait a few days for the team to dig it out. JLL has identified this as a focus area for their business and is prioritizing the resolution of this challenge.

Shanx is also in agreement about meeting demand for self-service options, but believes we need to do better with finding information in unstructured data, where there tends to be less than a 95 percent success rate. However, he feels technologies like generative AI will leapfrog that issue to obtain answers directly and in a very precise manner, which he thinks will be a game changer in banking for services such as equity research.

Mistakes to avoid

There’s always a chance for reflection on any digital transformation journey, and I asked our panelists to put their cards on the table and tell us about their mistakes and what they’d have done differently. Shanx admits he would have started the procurement process earlier, ensured the team thought more deeply about the reimagined process from end-to-end, and better considered which automation partners would be best suited to cater for each particular aspect of change.

Swaraj admits that one of JLL’s biggest mistakes was not using process mining tools to assess their processes before automation and then choosing the wrong process or a broken process to automate. This resulted in creating problems for the business instead of solving them.

He also believes they need to be better at aligning their visions for automation with actual delivery, and in terms of delivery timelines believes it’s important to break down requirements into small achievable parts rather than trying to roll out in one go.

Future use of intelligent automation

Looking to the future, both of our panelists believe that generative AI and large language models will be a key driver in automation.

However, Shanx warns that the shiny new toy must not distract you from doing your groundwork. As a “champion of the mundane,” he advises having your basic wares in order before adding new tech like generative AI and expecting it to create magic. He also pointed to the huge potential for the next generation of process mining tools, which he believes is an extremely important trend in the industry for helping organizations to assess and monitor automation.

At ABBYY, we are honored to have hosted Intelligent Automation Month and share successful outcomes in digital transformation using tools such as process mining and intelligent document processing. It’s also reassuring to hear that intelligent automation is an ongoing project for global organizations such as IBM and JLL who realize the potential for continuous improvement. We wish them luck with their future projects.

You can access the entire customer panel session with JLL and IBM Consulting here.

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Neil Murphy

Vice President, Global Channel Chief at ABBYY

Neil Murphy is Vice President, Global Channel Chief and in his role now responsible for expanding the company's business globally after his role as UK head. Neil's deep experience working with data capture, cognitive understanding and process automation technologies derives from a multitude of strategic roles at leading organisations such as Kodak Alaris and now ABBYY.   While at Kodak Alaris, Neil was responsible for the start-up and development of AI Foundry in EMEA, a technology start-up within Kodak Alaris focused on the AI and RPA markets.

Over the years, Neil has worked with a variety of industry sectors ranging from Finance, Insurance, Healthcare to Government focusing on transforming their legacy approach to back and front office processes such as Accounts Payable, customer onboarding, and consumer loyalty programmes to name a few.

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