Digital Intelligence— fueling the growing digital workforce

Original article was published by Ryan M. Raiker, MBA on Artificial Intelligence on Medium


Digital Intelligence— fueling the growing digital workforce

As more businesses go digital, Digital Intelligence is making the transition smoother.

The only constant in business today is changing. Organizations in both the public and private sectors are faced daily with a growing number of challenges, but we as business leaders and managers do not just think about the short-term impact, or changes to our businesses because of COVID-19. We care about perfecting the journey towards a more perfect future of work. We look to motivate our people and work together to plan digital roadmaps, design our processes, and implement digital workers to improve our workflows and make for a more efficient workforce.

Overall, I think we look for opportunities for growth; because growth-minded organizations focus on maximizing their total returns and this doesn’t mean just cost savings.

As businesses and workers adjust to this new way of operating, the thinking on remote and digital work will continue to change. While some have been doing it for years, the current situation, which some have called a “massive work-from-home experiment,” is likely to have a lasting effect on the future of work. But first, organizations need to be set up to thrive in a fully digital enterprise environment.

Photo by Luke Peters on Unsplash

A smarter, more powerful digital enterprise

McKinsey research shows that about 50 percent of tasks are automatable with the technology available today. Most would imagine if we are talking about automation in our management meetings today, we are talking about Robotic Process Automation (RPA). Now when we talk about RPA, we need to also talk about Process Mining and sophisticated Process Intelligence, because if organizations are taking the next steps towards hyper-automation they need to be thinking about the ecosystem of technologies that will be complementing RPA. These initiatives should start with gaining complete Process Intelligence, providing the complete picture of processes and operations as they are. To complement RPA and truly form a hyper-automation ecosystem, businesses need to invest in technology that can provide advanced analytics, including sophisticated process analytics, as well as drive a focus in other Artificial Intelligence (AI) solutions such as ingestion engines (OCR, Computer Vision, etc), and Machine Learning (ML) to create a comprehensive approach to amplify the efficiency and effectiveness of work automation.

Photo by Glenn Carstens-Peters on Unsplash

Maybe organizations should better prioritize automation initiatives

For organizations across a diverse array of industries and geographic markets, the COVID-19 pandemic accelerated the use of automation tools to maintain business continuity. However, business leaders should question automation for its own sake. Intelligent Automation must be done strategically in order to be effective and automating a broken or ineffective process doesn’t fix the process problems.

A digital transformation report from BAI published earlier this year noted that almost anything can be automated or digitized, which makes it imperative for business leaders to sift through digital possibilities and strategically select automation initiatives that deliver the greatest value. The report further stated that while many digital solutions may make work easier and faster, it did not necessarily make these solutions transformative.

Photo by Startaê Team on Unsplash

Digital Intelligence: the key to every RPA strategy

To truly understand the pain points that automation can solve and to identify places where in-person human interaction is critical to successful process completion, businesses must consider the sequence of individual interactions required to complete a task or customer journey end to end.

In fact, a recent survey of senior decision-makers in the U.S. and Western Europe found that 70 percent of decision-makers stated their robotic process automation projects were more successful by using process technologies. Fixing broken processes and enhancing efficiencies before deploying automation helped them ensure the greatest return on investment.

Digital Intelligence technologies use out-of-the-box cognitive skills to easily understand the content that drives operations and then provides insight and control of processes to start automating based on process KPIs, data-supported ROI, automation suitability, and other analytical metrics.

As RPA requires a significant upfront investment in the planning and design phase, Process Intelligence helps guide decision-making about which processes to automate, in all their permutations. Great Process Intelligence technology, which is available today, can deliver 100% process visibility based on actual operational data, making it easy to identify the smartest opportunities for RPA.

Next, Content Intelligence expands the use and value of RPA by enabling digital workers with intelligent skills and understanding to process content, both structured and unstructured.

Photo by JESHOOTS.COM on Unsplash

Knowing, understanding, planning, and continuously improving

Businesses need to utilize a data-driven approach to identify and prioritize the best processes for automation. This means bridging the gap between management, process leaders, and RPA developers to provide advanced insights, so businesses can start automating faster and more effectively. Digital Intelligence is helping perform prompt transactions, decisions, and actions, accelerating processes for any kind of business document — applications, claims, orders, and communications — eliminating costly and time-consuming manual operations and streamlining the modern digital enterprise.

As new working norms take over and RPA adoption continues to skyrocket across industries and geographies, the need to understand more and build an ecosystem of integrated smart technologies solutions is demonstrated clearly for enterprise business leaders.