Is the intelligent management of paper the answer to disaster recovery?
What happens to vital information on your paper documents when disaster strikes? Are you intelligently managing your paper assets?
We have all read or heard the horror stories surrounding disaster recovery. Every time the topic is brought up, we will no doubt hear more discussions about the cloud, alternative forms of storage and talk about data centres. However, one crucial topic that is often left on the back burner is paper.
It might seem like an odd place to start, but let's talk about paper for a moment. There are two things that businesses need to understand in order to have a comprehensive disaster recovery plan in place — the role of paper in their organisation and the intelligent management of this asset.
The role of paper in your organisation
Not every workflow process is covered in most recovery plans. Documents stored in on-site file rooms and sitting on desktops are often overlooked. Few companies consider the possibility that they will not know where their paper documents are, who has them, who might be reading them and who might be using the information gained from them. Most organisations might also overemphasise computer security and neglect the high possibility that paper documents can be purposely or inadvertently misused.
That begs the questions — Does your current disaster plan include a strategy for what happens if you lose all of the paper sitting on all of the desks throughout your office? Is this data secure? Or has this data been secured? How do you ensure business continuity in terms of customer correspondence, the filing of records and other concerns? Do your current processes intelligently capture and manage information on your paper documents frequently?
Understanding the implications of important papers lost during a disaster is just the first step to addressing a loophole that many companies face. The second and more important part is to set up a system that digitally stores the information and using it to manage those heaps of data.
Leveraging document imaging and intelligent paper systems
Managing the massive amount of disparate data from paper documents present in any organisation today can prove to be an uphill struggle. Upon realising the true value of paper assets — and the challenges that come with digitalising, storing and unifying the information in them — a truly discerning leader might consider the following:
- Digitising paper documents - Scan and store paper documents in softcopy form for data recognition and machine readability.
- Data recognition - Ensure that the scanned documents can be read and its key data elements can be recognised with ease. This is in addition to taking steps to automate the recognition process.
- Integration of multiple sources of data - Consider the growth and chaos of unstructured information and use technologies to deal with multi-source input. This is to avoid being buried beneath an avalanche of unstructured information.
- Classification of documents - Weigh the pros and cons of using and integrating the four methods of classification - symbolic; graphics-based document analytics; combined graphics text-based keyword; full, text-based document analytics - to achieve the best results.
- Data extraction - Consider and implement ways to replace manual data entry to reduce potential human errors during data extraction.
- Enabling document collaboration - Consider the importance of "search-ability" and "share-ability" for multi-source documents and optimise the power and value of documents wherever, whenever and on any device.
- Automatic initiation of business transactions - Consider improvements to the company's current content management system so that documents can be automatically assigned to the right departments and have workflows that can check for completeness or accuracy.
- Enhancement of business processes - Consider ways to enhance business processes with advanced insight, such as enabling the content management system with a knowledge management system that has analytics capabilities for big data.
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