The future is bright for organizations committed to Business Process Management and Automation; the intelligent capture of information from unstructured data sources (like most business documents) is the key that can unlock exponential gains in productivity.
In a recent study by Cognizant’s Center for the Future of Work, half of the 50 senior corporate executives surveyed said that they saw intelligent process automation as significantly improving their business processes over the next three to five years. The research also showed that, through automation technologies and analytics, their employees were attaining new levels of process efficiency, such as improved operational cost, speed, accuracy, and throughput volume. A total of 43 percent of respondents cited the use of analytics for better process throughput and quality, and 47 percent said they use analytics to better understand customer requirements.
Often, studies about business process automation talk about concepts like big data, machine learning and artificial intelligence—concepts that sound like science fiction and seem too abstract to be applied to middle market companies seeking to remain competitive in a global marketplace.
Intelligent Data Capture; Beyond “Words Per Minute”
But, for many, there are three key elements to achieving process automation to address MOST of the pain experienced by organizations today. Those elements are:
In plain English, automating the painful process of reading through documents for relevant information; entering that information into business systems and then filing the documents represent three major sources of cost savings and efficiency gains for organizations of all sizes.
Applying business process automation to solving those fundamental problems can easily cost justify ANY BPM initiative, while opening the floodgates for all kinds of additional innovation once you have actionable data, accessible documents and a well-defined business process.
Taking BPM to the Next Level
Businesses that are already embracing these new technologies are capturing more data, improving processes, and generally empowering workers to be more effective at their jobs. Having access to data in near real time, along with a defined process, is the driver for all sorts of automation.
In logistics, for example, real-time dynamic fleet optimization can work wonders for destination and delivery capacity. Pharmaceutical trials can be maximized by collating huge volumes of clinical data. Be it claims management in insurance or reconciliation or mortgage processing in banks, process models can evolve from transactional to interactional once the fundamental issues of data capture and data entry are resolved.