Decisions, decisions…we all want to make the right ones. So, in an era of artificial intelligence, how can technology help employees make challenging choices that can delight customers while improving efficiency and ultimately the bottom line?
According to Gartner research, poor operational decision-making by mid-level finance managers costs upwards of 3% of profits annually – running into billions of dollars a year for some organizations. And worryingly, a survey by McKinsey revealed that 60% of executives thought that bad decisions were as frequent as good ones. Often it was attributed to cognitive biases.
There’s no end of examples of the financial impact. You only have to look at mistakes made during the recent pandemic when the rush to digitize processes and assist remote teams led to bad decisions on introducing automation. According to a recent survey 1 in 5 projects were abandoned altogether, while 1 in 3 companies discovered the technology they implemented didn’t work as intended – all money down the drain!
And it seems employees weren’t thrilled about the new technology either with 74 percent experiencing challenges, and an incredible 1 in 4 becoming so frustrated with it that they wanted to quit their job!
As you can see there’s much to be gained from helping both employees and managers become more efficient in their judgements.
In the past, while weighing up options, we would often focus by putting all our “cards on the table” to help us make a decision. Let’s look at technology in a similar way, by examining four key points.
Efficiency in Data Analytics
Data analytics has been around for a long time, but it’s the efficiency of it that’s key. Take Amazon, Google and Facebook, which have been ramping up their use of analytics to spot trends, gain more valuable insights and evolve strategies.
According to Accenture, the traditional view of data is that of a cost that must be managed – an overhead. Now it’s an essential source for a competitive advantage, with the COVID-19 pandemic demonstrating the need for companies to be on top of their data as customer behaviors change beyond recognition.
However, 1.7MB of data is created every second by every person in the world and most of it is not fit for machine consumption. Data is messy, unlabeled, and from multiple disparate sources.
Gaining meaning from data is not made efficient simply by allowing someone access to hundreds of documents, or by simply digitizing data when all computers can see are pages of numbers and letters. When you read a document, you are not simply identifying data, you are understanding the document. Analytic and document process automation platforms need AI applied to documents to provide the context from data that helps drive decision-making and enhance the business process and customer experience.
Mining complex content
It’s estimated that 80% of key decision-making is based on complex information found within documents, so it’s no surprise that uncovering essential content is now the number one priority for business leaders. It’s important to note that the definition of documents has expanded from Word files; they also encompass images, PDFs, paper and web forms, faxes, mobile photos, emails, chatbots and other free-form text used to engage and serve clients. As such, content cannot be effectively automated without first using technologies such as intelligent document processing to transform data that can be understood by enterprise applications.
However, many companies are limiting content’s power because they do not have the proper approaches to unlocking and utilizing it. Most solutions and processes are data-centric, which reduces content to a manual data-entry problem, rather than a rich source of insightful, contextual information needed to make decisions.
Automation platforms powered by AI in the form of cognitive capabilities (such as reading, learning and reasoning) to unlock content empowers employees to make better decisions faster. This form of AI is important for understanding and using information when faced with complex scenarios, which takes us to our third card.
Using Artificial intelligence and machine learning
With the use of AI and ML technology, employees can find essential information from content to better understand, evaluate, and make important decisions at the point in the process where it is needed. Should an early payment discount be extended to a vendor? Does a potential borrower qualify for a loan? Do contracts meet compliance standards? Should a claim be paid?
Pertinent information to make these decisions are tucked away inside attachments, forms, text messages, contracts, and emails. Modern AI and ML can understand the richness of content and still perform the data extraction and validation where needed and augment the knowledge worker’s daily tasks. Putting this technology into the hands of every worker will be key for organizations being more customer centric, which takes us to our final card.
Leveraging the democratization of artificial intelligence
Between the advancements in making complex technologies simpler and the need by enterprises to digitally transform within weeks, more low-code/no-code platforms are entering the market that make it easy to deploy and be managed by business analysts or citizen developers.
Historically, intelligent document processing platforms were complex and required users to be certified in ML technology. Now, it’s as easy as finding another discoverable application on a desktop and adding AI powered cognitive skills from a digital marketplace for specific document types – invoices, receipts, purchase orders, bills of lading, shipping documents, mortgage applications and forms of any type.
Adding cognitive capabilities to document processing yields a huge benefit to all employees. They will be able to make decisions more effectively and efficiently by recognizing, tracking, and alerting patterns of communication, while using their process automation solutions to organize data and manage workflow and chains of events. When bringing in content intelligence to aid decision-making, organizations can scale up their decision-making power and effectiveness without adding headcount. AI is doing more than facilitating a process; it is helping knowledge workers become more effective at how they organize and interpret them and changing how processes work.
It’s important for organizations to remember one thing – every decision is a financial one – make sure your employees are armed with the tools to make the right choice.
About the Author
Bill Galusha is Senior Director at ABBYY, a Digital Intelligence company.