There's a lot of talk these days about the move from centralized to distributed scanning. The idea is to capture documents at the earliest point where they enter an organization, streamlining document workflows and eliminating so-called "information float." Across organizations, departments receive multitudes of documents every month, including correspondence, service requests, legal documents, invoices, statements, cancellation notices and more. For this reason, distributed scanning already is changing the way that end-users and their vendors look at document imaging solutions.
But that doesn't mean distributed scanning is right for every organization.
Before moving to a distributed scanning environment, organizations need to think hard about the potential impact such an approach would have on staff productivity, task specialization, quality assurance and the potential number of redundant, underutilized scanners across the enterprise.
Enter: Distributed Scanning
The North American document scanning market continues to be dynamic, with new opportunities driven by increased penetration of document management solutions and the use of distributed capture in organizations, according to data from InfoTrends. The demand for document scanners is growing in response to evolving business requirements for managing paper documents, the research firm notes. Once scanned, documents are routed and managed much more easily and are integrated into the electronic flow of information that is common in most companies, InfoTrends explains. This is designed to drive business process improvements from the point of capture, including:
- Accelerating business processes
- Streamlining workflows
- Feeding enterprise applications more quickly
- Enabling employee collaboration
- Eliminating paper handoffs
- Reducing opportunities for lost document
- Providing faster access to document images to fulfill customer service inquiries
For certain applications, such as retail, distributed scanning can make sense.
A Flawed Approach
But it is not for every company. Many organizations that evaluate distributed scanning conclude that centralized scanning still delivers better performance and reliability and greater return on investment.
Here are some real-world examples:
- A large insurer decided against deploying desktop scanners in its agent offices because it feared the agents didn't have the technology savvy to operate the system; it also wanted to keep its agents focused on customer service. Instead, the insurer's three regional capture centers feed information on claims and policies to its customer service department.
- In lieu of deploying distributed scanning across its enterprise, another insurer installed high-speed devices at its five regional scanning locations and implemented small scanners only where they provided significant improvements in the collection of customer information.
- A large brokerage company consolidated several regional operations sites into one location to gain economies of scale; the company never considered deploying distributed scanning.
- Another investment company determined that distributed scanning wouldn't work for them because it would have to provide scanners to the licensed brokers through which it sells.
Despite all the market hype, these companies, and many others like them, concluded that distributed scanning didn't offer the payback trumpeted by its proponents. There are several reasons for this:
Redundant, underutilized scanners: Distributed scanning implementations require users to install devices across an enterprise. Using multiple slow-speed scanners across an enterprise inevitably leads to labor-intensive, inefficient processes based on redundant, underutilized hardware. In traditional desktop environments, it's also not uncommon to see frequent hardware downtime. The bottom line: Desktop scanners are too slow, unreliable and inflexible to support the mission-critical applications that they are driving.
Lost productivity: Counting on desktop scanners to image a company's large volume of paper documents (albeit in small chunks) can create processing bottlenecks and a litany of manual steps (removing staples, repairing tears, sorting documents, inserting separator pages, photocopying small items on sheets of paper the scanner supports) that keeps staff from other tasks and creates processing delays that impacts downstream applications waiting on critical information. Downstream users such as accounts payable, claims processing and customer service rely on captured data. In an environment such as insurance, where extracting timely vital data from documents is key, this is unacceptable.
Poor quality controls: Most distributed scanning implementations lack the standardized platforms necessary to ensure uniform operation, high quality and adequate performance tracking. This creates downstream errors that impact operations and customer service and ultimately inhibits return on investment.
Since scanning is the first step in converting paper documents to more usable digital information, it can have a profound impact on productivity, operations efficiency and data accuracy. It is a task that should never be taken lightly. For this reason, companies should think twice before relying on redundant, underutilized scanners - which often lack the standardized platforms required for peak operation - to manage one of their organization's most value assets: its business information.
Companies should avoid falling into the trap of thinking that they have to put scanners on every desktop in order to drive new capture efficiencies. Enhancing centralizing operations and/or strategically placing scanning in a decentralized fashion will actually deliver better ROI.
Using this approach, rather than distributed scanning, provides significant benefits:
- Resource consolidation
- Lower operating costs
- Better service for internal and external clients
- Faster response and turnaround
- Improvements in data capture
- Greater workflow
Regardless of the deployment approach, organizations should look for a flexible and reliable scanning infrastructure that will drive process improvements from the point of capture, whether it's the back office or strategic, decentralized locations. Distributed scanning isn't always up to the task.
Jim Bunn [firstname.lastname@example.org] is a business development manager for ibml.