Many businesses today seek to transform their operations using digital technology and automation. Yet even after years of encouragement from experts to migrate to the cloud, automate every process, and prepare for waves of imminent technology innovation, the path forward can still seem unclear.
Organizations can get confused about what to automate, and how. Not every business needs, or is prepared for, every new technology or service being pitched by consultants and salespeople. People don’t wake up and say: "I want to automate something.” But there’s a growing need to collect information and serve it to people on different devices, which lends itself very naturally toward automation.
Looking forward in the rapidly evolving realm of digital transformation, we see three trends happening right now that customers can rely on to help them adopt the new technologies and strategies that best fit them: Intelligent Automation, Integration, and React to Anything.
Various forms of automation and assistive capabilities are helping transform businesses today. We can think of “smart automation” as a process with three separate components that can work independently or together:
Digital process automation (DPA) turns manual or paper processes into digital apps that live across an organization, on mobile devices, or with customers. It's human-centric, requiring compelling and informative user interfaces and continuous availability.
Robotic process automation (RPA) uses software to free up people from performing repetitive tasks. This fills gaps that exist in all DPA programs and supports a broader digital transformation strategy. For example, an employee sets a calendar appointment every Monday to pull down an Excel file, process some data, and then push it out in an email. RPA can do that instead.
Artificial intelligence (AI) is a broad term for technology that uses data to “think” more like humans, making sense of massive streams of data. Until recently, AI tools have been difficult to deploy. But advances by Microsoft, Google, and Amazon others now help businesses quickly plug AI into their applications and organizations, delivering much bigger value with much lower investment.
The combined maturation of DPA, RPA, and AI means organizations can now deploy a platform, or a technology suite, using the best available version of these different components to solve complex business processes.
As organizations embrace automation, they sometimes struggle to manage a mixture of IT-owned systems, which are centrally managed and governed, with those owned by business units, which can span a broad range of external components and services. Those apps may reside on-premise or in the cloud, further complicating matters.
An IT department typically develops and owns large mission-critical systems like enterprise resource planning (ERP) or customer relationship management (CRM). But line of business (LOB) owners are increasingly turning to outside providers for apps and automation tools when they can’t wait for IT to build them. Many can be managed by their own team members, but they often lack the technical skills to write code that integrates them with other company systems.
In this environment, companies need a structure that can incorporate all those systems. That structure needs to enable people to build and manage the modern apps they need to drive business results without investing in costly development resources and tools, which might become obsolete when the company updates its ERP system a year from now or moves to another ERP in the future.
Fortunately, it's much easier to integrate systems and programs today than in recent years. Current DPA platforms can efficiently connect systems across the enterprise while respecting those security boundaries and policies already in place.
React to anything
For a business with a mix of on-prem and cloud-based systems, it’s not good enough to simply integrate them. DPA platforms need to be flexible enough to update when business needs change, while also reacting to discrete events.
For example, a customer may fill out a survey in SurveyMonkey, that requires an immediate series of actions in response. The customer input must be stored and managed appropriately, whether on-prem or in a remote location. Data must be analyzed, and customer support engineers notified, prompting a review of the customer feedback. That review might be conducted by AI, which could flag negative feedback that gets routed to the appropriate department for a response. That data and the response need to be routed to the customer relationship management (CRM) system to attempt to identify the customer and whether the poor review was linked to an order. That could prompt an updated order or other response, all of which must be tracked and reported internally.
Through that entire process, with multiple events happening in completely different systems, DPA is the glue that ties it all together, making sure that processes fire correctly, and people are tasked appropriately, and promptly.
DPA platforms also need to adapt and prepare for what’s coming tomorrow. Customers should be confident that any changes in internal systems will be seamlessly integrated into the platform in six months or two years from now. DPA should integrate with anything, including external systems that change over time.
Smart automation means lots of different things to different organizations. No one size fits all customers. Today, organizations can decide what vendor works best with their roadmaps and their plans – or choose multiple vendors.
And as DPA has evolved, it's become more than just task routing or decision-making. By tapping other systems, like RPA and AI, and making them more approachable, DPA can pull in data and provide a more holistic solution that is greater than the sum of any of its parts. That makes it easier than ever to integrate services and get moving toward digital transformation.
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