The tsunami of data is here. And it just keeps growing. In fact, it’s predicted global data creation and replication will see a compound annual growth rate (CAGR) of 23% over the five-year period of 2020 to 2025. Organizations need to capture, process and analyze this data quickly to run efficient operations and make informed business decisions. But how can companies keep pace with the ever-increasing speed of data generation?
Automation has long been viewed as the answer, but the traditional point solution approach is too slow and disjointed. An intelligent automation platform, however, integrates various technologies, making end-to-end, scalable automation a reality and creating the optimal mix of people, processes and technologies.
But the work doesn’t stop there. Truly intelligent automation goes beyond the technology platform itself and requires organizations to take a hard look at their business processes and workflows. Which ones are the prime candidates for automation? How can companies ensure all the necessary stakeholders are on board and committed to the initiative?
These are tough questions, but, when done right, organizations can use intelligent automation to re-engineer business processes and become the digital enterprise of the future — no matter how massive the wave of data is.
The Data Challenge: A Blueprint for Automation at Scale
How can organizations tackle the data challenge and obtain maximum value from the tidal wave of structured and unstructured data? A leading financial institution took the plunge from point solutions and moved to a comprehensive intelligent automation platform. Their success story can serve as a blueprint for the types of automation technologies required for scalable automation, making it possible to move further down the digital transformation path.
The financial institution had already made investments in automation technologies like robotic process automation (RPA), but RPA alone isn’t enough for end-to-end automation. They needed to modernize their approach with an intelligent automation platform that would cover all existing and new use cases within the company, such as wholesale lending, home mortgages, trade finance and auto and consumer lending.
The company chose an intelligent automation platform that was able to integrate with existing technologies and vendors, as well as solutions the institution may invest in down the road. A hybrid cloud solution enabled the company to outsource their IT infrastructure, saving them an estimated $2+ million a year in infrastructure costs alone.
A low-code platform provides an intuitive interface with drag-and-drop features, empowering citizen developers to contribute to the automation and digitization process. It also gives the organization the speed and agility needed to keep up with the vast amounts of data coming into the enterprise. In addition, a low-code solution makes it easy to scale automation initiatives across departments and use cases.
The intelligent automation platform also addresses the complex ecosystems within the organization through digital workflows. Specifically, the system is being used to govern other automation solutions, creating a hyper-connected enterprise where data is ingested and automatically passed from one application or system to another.
Some of the specific automation technologies leveraged in the platform include:
- Cognitive capture, which leverages AI for automated document identification, document processing and data mining
- Smart integration to connect critical systems without coding
- RPA to automate tasks such as onboarding and assist the human workforce
- Advanced analytics and reporting capabilities to help business leaders make faster, more informed decisions
- Authentication and authorization through role-based permissions for optimal security
As a result of the implementation, the company is benefitting from:
- Consistent document and data processing across all channels
- Reduced compliance risk through document security protocols
- Strong integration with existing workflows to layer on analytics across the organization
- The transformation of 100 million pages annually across functional use cases, saving multiple lines of business time and costs
The solution supports the financial institution’s new digital infrastructure strategy to drive technological speed, agility and scalability for its customers and employees. The cloud deployment initially transformed one million pages annually across cross-functional use cases and has been positioned to provide workflows for additional use cases that process more than one billion pages per year. The move to an integrated automation platform and the creation of digital workflows has turned the choppy waters of data into a smooth, ridable wave.
Where to Start: A Federated Model for Long-term Success
As with many transformation processes, the first step on the path to becoming a truly digital enterprise is the most important. True re-engineering of business processes demands collaboration between the CIO, IT leaders and line of business leaders. How can this be accomplished efficiently and effectively?
It all begins with a Center of Excellence (COE). This team is comprised of representatives from each stakeholder group within the company. The COE is responsible for six core functions critical to establishing the infrastructure needed for a successful automation program which meets current and future needs.
Program leadership and vision: Responsible for overseeing the Center of Excellence and ensuring all impacted groups within the organization are consulted and informed as new automation initiatives begin.
Vendor and IT relations: Manages the relationship with the intelligent automation platform vendor. This includes external issues such as software updates and licensing, as well as internal items like the server used to host the platform. Technology disruptions can bring initiatives to a screeching halt, so this function is essential to ensure smooth sailing.
Platform enablement: Creates assets to promote the adoption and spread of automation initiatives within the organization. This may include training for citizen developers or information to help employees identify uses cases ripe for automation.
Human capital and transition planning: Many employees may fear automation, thinking it will put them out of a job. This group is tasked with fostering a positive attitude towards automation and ensuring workers impacted by automation continue to feel empowered. New roles may need to be created, and this group will also work to fill any skills gaps created by automation initiatives.
Program reporting: Monitors the impact of automation and reports findings to a designated program champion. Success metrics should be defined early on, and they should have a direct tie to larger strategic priorities in the company.
Knowledge management and continual improvement: Automation technology is constantly improving. This group is responsible for testing new releases and software updates from the vendor and making sure they’re adopted and rolled out without interrupting the current automated operations and processes.
Through these six competencies, the COE supports operations and scalability, ensuring the long-term benefits of automation are realized.
What’s Next: Identifying the Best Process Candidates
Once the COE program is operational, the next step is to determine where to start automating.
An Operating Model Assessment is a three-step process that helps organizations identify the best process candidates fit for automation. This ensures companies gain the biggest value from day one.
1. Identify processes that can be automated
- Conduct an initial analysis to determine if a process is fit or unfit for automation.
- Base the analysis on criteria such as the manual work involved, the likelihood for errors to occur and transaction volume.
- Create a prioritized list of processes ripe for automation.
2. Assess process complexity
- Determine the level of effort needed to develop digital workers for each automatable process.
- Items to evaluate during this step include the type and number of applications involved, the type of input data (structured, unstructured, digital) and systems integration requirements.
- Assign a level of complexity to each process, such as “low,” “medium” or “high.”
3. Document the initial business case
Don’t drown in a sea of data. Leverage an intelligent automation platform to unlock the true value of data and re-engineer business processes. With the power to make faster, smarter decisions, intelligent automation helps organizations ride the data wave into the digital enterprise of the future. Surf’s up!
- Evaluate the key metrics associated with each fit process, such as labor costs, to calculate the initial ROI of automation.
- Create a business case based on four key areas:
- Strategic alignment: Does the investment align with the larger organizational strategic priorities?
- Financial impact: What’s the estimated cost savings, payback period and the ROI?
- Business operational value: What are the projected efficiencies in processing time and daily throughput? How will data analytics improve?
- Workforce impact: How many labor hours will be saved annually? How many employees can be reallocated to higher-value work?