To adequately describe the explosion of information in our world has required data scientists to adopt new units of measure. From terrabytes to brontobytes, our data universe continues to expand beyond the scope of what our human brains can conceive.
The bigger that universe gets, the faster it seems to expand. Putting that growth into perspective, consider that five years ago, ninety percent of all digital information known to man had been generated just two years prior. At current projected rate of growth, by 2020, the bits in the digital universe will exceed the stars in the physical universe.
All that data promises to deliver access to new knowledge and insights. It also threatens to overwhelm our capacity to manage and all and transform it into anything meaningful or actionable.
When you think about the source and types of data that is fueling this growth, the problem becomes even thornier. Rather than neatly packaged, uniform alphanumeric data like the kind we typically store and manage in enterprise resource planning systems (aka the accounting systems of yore), the new data supernova is being fueled by communications and correspondence, documents, images and video. Much of this unstructured data is information rich—but it is more difficult to parse out the value and capture the underlying actionable information.
To tackle this problem, the tools we use to manage data and transform it into information is advancing and changing to address the challenges of this new world of data. New solutions that leverage intelligent technologies have been designed to relieve the heavy lifted from sorting, sharing and analyzing data of all forms.
This rapid evolution in process intelligence is empowering companies of all sizes to solve some major process pains and allowing them to lift their heads up from their work queues to think in bigger and bolder terms when it comes to innovation, efficiency, customer service and strategic execution.
Narrowing our discussion to tangible, day-to-day business process problems, let’s take a look at the common process of handling customer sales orders within a typical organization. Parsing data and insights out of a complex sales order, while responding efficiently and effectively to the needs of that customer is a challenge that many, if not most, companies can relate to.
Today, it’s more practical and affordable that ever to overcome the challenges that come from a constant deluge of data and documents, by relying on easy-to-deploy systems and solutions that work out of the box and adapt to constantly-evolving business conditions by learning as they go.
Digitizing sales orders and transforming them from documents into data isn’t new, in and of itself. Sorting and routing orders for review and inserting that information into business systems in a way that minimizes manual intervention has been an option for large organizations dealing with high volumes of documents and transactions for decades. But traditional automation solutions, with dependence on custom coding and integration, often have come with a substantial total cost of ownership and some substantial tech support and maintenance overhead.
The key to transforming a constant, often over-whelming flow of customer sales data into actionable information means simplifying the process—and reducing operational and implementation costs and timelines. And that’s where lots of exciting new innovations around self-learning, low code and intelligent integration technologies come into play.
Intelligent data capture platforms can unburden process owners throughout your organization from tasks that threaten to consume all their time and energy; time better spend focused on improving the customer experience by anticipating trends and increasing responsiveness to customer needs.
In the past, however, much of the cost and burden of automation was passed on to IT and shared with process owners who had to intervene to create templates and continually reconfigure templates or definitions, so that the system knew where to find the right information when there were variations to where information might be located within a given document.
That might have been workable in scenarios where twenty percent of a company’s vendors might account for 80% of its payables, but NOT for companies with lots of vendors, lots of invoices and little consistency in terms of how they’re submitted or how they’re formatted.
Today, more flexible way of tackling these challenges are available, designed and packaged to work for a broad range of companies, regardless of size or industry, that can be cost-justified even for lower volumes of transactions. Solutions like Artsyl’s OrderAction can be implemented in as little as 90 days, with ROI achievable within 180 days. Built-in machine learning capabilities allow OrderAction to learn from human process owners, monitoring their mouse clicks whenever they have to intervene and handle exceptions, then updating their algorithm without the need for any coding or manual rule updates. As a result, they can handle 80% of their process flow immediately, then gradually target and eliminate exceptions to get closer to 100% automation—without any coding.
The result? Radically reduced sales outstanding. Quicker access to customer data. More effective and accurate cash management. And more timely insights into customer buying behaviors and seasonal sales/purchasing trends.
Make your New Year’s resolution one that matters: eliminate the work you hate and focus on the things your team does best.
To get started, go to the Artsyl resources page and explore case studies, white papers and more. Our Artsyl solution representatives are available to talk through the details and demonstrate how to get beyond the status quo and transform your business.