Many of the clients I’ve spoken with over the last year have been seeking methods to improve their processes by making them smarter, more adaptive, and resilient. Many firms, according to our latest research, regard a mix of AI and automation, or intelligent automation, as critical to accomplishing these objectives.
Despite the promise of improved operational performance through intelligent automation, one typical concern is where to start: with the process itself or with the data that will power the process. The key is to figure out what you want to accomplish. Making a mistake with the sequence could work against you.
The right starting point
When it comes to intelligent automation, here are two examples of when a process-led vs. data-led strategy makes the most sense:
What can we do to increase the efficiency of our operations?
Many firms have prioritized enhancing operational efficiency as a result of supply chain interruptions and social distancing requirements. In this situation, the goal is to increase speed and accuracy throughout the value chain, allowing for faster results without sacrificing quality.
By using data intelligence, you may drastically minimize errors, eliminate process bottlenecks, and identify areas where improvements are needed. However, to influence when and how the data is applied, you’ll need a strong process automation backbone. As a result, a process-driven strategy is an ideal option in this circumstance.
For example, we’re collaborating with a large insurance company to better manage customer lifecycles. Long decision periods, a lack of transparency into decision making, and repetitive or disconnected requests for information submission are all common complaints among insurance consumers who file a claim.
When it comes to handling claims, insurers may set themselves apart by being quick, easy, and responsive. However, in a highly regulated business with overt risks of claims fraud, speed must never be sacrificed in favour of accuracy and compliance.
The insurer’s reliance on third-party systems and various data sources to make choices was one element leading to the insurer’s process difficulties. We assisted the organization in implementing an automated and completely integrated claims handling process, which was subsequently supplemented with artificial intelligence and data modelling to segment client profiles and customize services.
The technology has helped reduce claim capture turnaround times by up to 80% and claims processing times from 14 to two days, all while maintaining the required high levels of accuracy and regulatory compliance. Customer feedback on the efficiency and quality of the insurer’s services has also been excellent.
How can we make our product and service offerings more flexible?
Leading retailers excel at recommending relevant products and anticipating customers’ future moves. Whether customers are looking for a specific item, browsing relevant websites, or interacting with brands across several channels, digitally savvy businesses can connect the dots in real-time and generate highly accurate recommendations.
Companies require an agile approach to satisfy customer expectations because there are so many aspects and variables at play in dynamic online customer environments.
To provide this level of personalization, we’re working with an online fashion retailer. The corporation is well aware of how quickly consumer tastes and patterns change, and it knew that it needed to act quickly to capture and retain customers’ attention.
We used a data-driven strategy since it was critical to acquiring insights into consumer preferences. We assisted the business in gaining a better knowledge of its customers by utilizing existing data. We then created a strategy that categorized the brand’s client base and ensured that all interactions and product recommendations across channels such as chatbots, email, and social media were relevant, timely, and valuable.
A digital thread was woven through all phases of the customer lifecycle, including product design and development, sales, and after-sales, thanks to a mix of process improvements and data insights. As a result, the shop can now provide more relevant customer interactions and next-best offers, improving consumer mindshare, loyalty, and revenue.
Accelerating the path to Intelligent Automation
Process and data must be in sync to get the most out of intelligent automation. Data allows for better decision-making, while automated processes allow for increased efficiency.
Businesses can add intelligence to how and where they automate operations by harmonizing these attributes and having a defined result in mind, allowing them to speed up business outcomes while also improving the service quality.
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