Integration of new information sources  

With modern technology continuously expanding, there are numerous ways to receive information – both structured and unstructured. Today, paper documents and mail are becoming outdated as sources such as social media, mobile apps, and Web sites take over in volume and significance.

These new information sources are known as “big data,” and they are explosively increasing.  Big data gives businesses more data that is available to be analyzed, which in return makes for better decision making.

However, many businesses find these sources to be “chaotic or difficult to manage,” according to AIIM’s report titled “State of the ECM Industry 2011.”  Paper documents are easy for businesses and organizations to manage because they are easily organized through a capture system.  But how does one organize a Tweet, e-mail, Web document, and a phone call all about the same thing?

For example, say you get in a car accident. You would take a picture on your Smartphone of the damage, call your insurance agency to explain what happened, e-mail the photos from your Smartphone, and depending on how you feel about your insurance company’s service, you might Tweet about your experience.


ImageThe insurance agency must then manually enter all of that data you provided to them into a unique customer claim case folder – which can be very tedious and time consuming.  Ultimately, this work will provide the insurance agency with instant photos of the case, instant communication with the customer, and overall details about the claim straight from the scene.

Businesses that are able to expand (and manage) their information sources with the proper solution will find that big data does not have to be time consuming and frustrating, but overall very rewarding.


Do you have any questions about multi-source integration?  Read more about this topic in our whitepaper.



How data recognition drives intelligent document understanding

How does scanning a QR code with your phone, make the device present the right Web page? This is possible due to a form of data recognition, which is an important factor of intelligent document understanding.


Intelligent document understanding first happens when information from a paper form has been scanned and converted into an image. Once a document has been converted, then key relevant data elements of that document can be recognized. There are different ways to do this and recognizing key elements ranges from very fast and accurate, to time-consuming and not as accurate.

To expand further, there are five main techniques for reading the data needed off of documents.


The first two techniques are fast and accurate, but only extract key information from the forms of data; they do not read the entire document.

  • Barcode- For instance, when you pick out items at the grocery store they all have individual barcodes that allow the cash register to recognize what item it is and charge the appropriate amount. This method is very fast and accurate but has a limited range of document types because you must complete printing at the source.


  • Object Mark Recognition (OMR)- This type of data recognition is found on items such as surveys, school tests and applications. OMR can only understand yes/no type questions, it then takes the written marks and converts them to data on a device. This is in the process of being replaced by online capture of information.


  • Optical Character Recognition (OCR)- OCR can recognize printed text, such as shipping labels, unlike OMR which could only recognize marks. This technique is very accurate with Latin-based characters and is still under development with Asian languages. Although it is accurate, it is very intense so it can be a slow form of data recognition on PCs.


  • Intelligent Character Recognition (ICR)/ Handprint recognition- The final two techniques are grouped together because they are the least developed and least accurate forms of data recognition. These techniques understand handwritten data but only accurate when using a limited vocabulary or information that can be matched to a database.


Any questions on how data recognition works for intelligent document understanding?  Read more about this topic in our whitepaper.



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Five Recommendations for Increasing Mailroom Efficiency

In mid-size and large enterprise businesses, the costs associated with maintaining an effective and efficient mailroom can be substantial. Using a combination of cutting edge technology and process improvements, these costs can become more manageable and overall efficiency can improve.

Here are five recommendations for improving the cost efficiency of your organization’s mailroom:

  1. Create a centralized knowledge base across all contact channels. As you know, input today comes from a variety of different communication channels. Being able to manage all of these channels and process documents or digital communications under one roof is key to mailroom cost efficiency. Using adaptive, dynamic Artificial Intelligence to merge your conventional mailroom with your more efficiently managed digital mailroom can cut down on individual input process time and improve accuracy in the overall process. This centralized knowledge base becomes the foundation of your input management.
  1. Create one workflow platform for processing all input sources. Managing structured and unstructured content documents in one workflow can be tricky. Throw in the multitude of input types (email, letter, online form submissions, social media inquiries, etc.) and the potential for process breakdown or inefficiency is great. Creating a system workflow that allows for streamlined processing of all content types and structures can save your organization huge headaches and costs.
  1. Optimize OCR results with virtual optimization methods. Optical Character Recognition performance is key to smooth input processing. If mistakes are made when capturing input (at the beginning of the process), significant costs and loss of quality can result. Effective AI technology can ensure OCR is accurate and the input management process gets off to an effective start.
  1. Implement extraction approaches to enrich input management. Capturing all applicable customer data from input documents is crucial to your organization’s ECM. The more data an agent has at his or her disposal when handling customer communications, the better they can serve that customer. Leading technologies are even capable of learning extraction behavior from agents and can process free-form text documents automatically, making the process more cost-efficient from start to finish.
  1. Set the stage for customer-value-oriented processing. Implementing processes and technologies that assist in time savings and accuracy will lead to improved customer value—both immediately and over time. These improvements will set the stage for processing techniques such as customer prioritization and improve overall CRM results for your organization.

To learn more, download the full Input and Response Management ECM white paper.