The Modern Imperative: Managing the Information Overload
by Theresa Lütge-Smith
The tools and connectivity of the digital age give us a way to easily obtain, share and act on information. Standard hardware combines with standard software platforms, creating economies of scale that make powerful computing solutions available to companies of all sizes. However, this new Web work style requires a well organized digital infrastructure that ensures an integrated flow of information to the right part of the organization at the right time; enables a company to perceive and react to its environment; senses competitor challenges and customer needs; and organizes timely responses for maximum and constant learning. Data organization can be as simple as developing the correct categories, or as complex as using innovative software for data mining and Knowledge Management.
How you gather, manage and use information will determine whether you win or lose in the new economy. Forward-looking companies will be those that use digital tools to re-invent the way they work, which includes having to make snap decisions, acting efficiently, and creating innovative ways to explore customer relationships. While the extent of digital data in e-commerce is overwhelming, today's computer networks can retrieve and present data easily and inexpensively. You can probe data to the lowest level of detail and evaluate it in different dimensions, exchange information with other people, integrate ideas, and work to produce a coordinated result.
According to a recent study conducted by the School of Information Management and Systems of the University of California, Berkeley, 1.5-billion gigabytes of content are produced annually. Another source claims that on average individuals spend about 150 hours a year looking for information, and that nearly 50 per cent of people watch TV and use their computer at the same time. The infoglut on the Web has resulted in a new imperative: data organization and management.
While businesses in general focus on a few basic elements, such as customers, products and services, revenues, costs, competitors, delivery, and staff, their most pressing need is to organize data in a manageable way that also allows individuals to extend and combine their analytical abilities.
Data Anxiety
Coping with large amounts of information can cause anxiety for a number of reasons. Not having access to the right information in a data intensive world is the death knell for any business or enterprise. Yet, it's equally vital that the mass of available information is appropriately selected, authenticated and kept up-to-date. The ongoing need to capture the latest data and to organize and select the best information from the infoglut on the Internet, has initiated a new form of cultural stress. This is emphasized by the definition of information as that which "reduces uncertainty" (The Mathematical Theory of Communication, 1949, Claude Shannon and Warren Weaver).
The daily news is so fast and intense that we often do not have time to assimilate it accurately. Too many images and too many words can cause distortion and misconception. There are information theorists who claim that the term Information Age is a misnomer. Rather than information, which implies clarity and understanding, we are in an Age of Mass Data, which is not necessarily cogent, contextual or coherent. Unavoidably, the Data Age is part of the contemporary landscape and the modern imperative of data is to organize and manage it; and to turn it into useful and clear information.
Peter Drucker wrote in Post-Capitalist Society (1993, HarperBusiness): "The basic economic resource is no longer capital, nor natural resources, nor labor. It is and will be knowledge. Value is now created by productivity and innovation, both applications of knowledge at work." With the growth of the Internet and the mountains of information and data, there is a concomitant need for coherent business intelligence methods to cope with the data. This essentially means that the right information should be accessible at the right time and also that this information should be coherent and in a usable form in order to make correct business strategies and analyses.
The Basics Of Data Organization
The process of dealing with infoglut can begin at grassroots level. Data organization should begin at the very point of searching and collecting information. Using advanced search techniques, offered by all major search engines, and simply focusing on precisely what you are looking for, can go a long way toward producing manageable results. Using Boolean expressions is a really worthwhile process that can include and exclude many alternatives that may be applicable to your search. Just as important is carefully choosing your search criteria. Consider the following points to assist you in the initial phases of data organization. Useful resource areas include:
- Search engines and directories
- Statistics resources and databases
- Sites linking to other sites
- Content-based sites
- E-mail newsletters and lists
- URLs from outside sources
- News and news groups
By mining these resources you will learn how to process the information consistently over time. This will also distinguish the context in which the information is provided. Organizing e-mail newsletters and lists is different from managing information directly from Web sites. Understanding how the content of data is related to the specific context in which that information appears, can go a long way to making sense of the infoglut. The secret here is filing and categorization. Once a habitual method of categorization has been set up - for example, URLs from other sources can be filed under certain categories; the information may lose much of its anxiety potential. Some of the more popular freeform and relational databases can be of great assistance in this regard; refer to the sidebar.
Recent technological developments in data research have focused on making searches more relevant. Relevancy of data, rather than quantity, is one of the guiding principles in searching and collating information. The search engine enhancer Outride for example, which was subsequently acquired by Google, functions to refine and expand searches based on user history. In simple terms the software reads, summarizes and categorizes text documents, which may include Web pages, news feeds and e-mails. More importantly, after the software has been through the analyzing process it provides the most significant and relevant documents to the user. Inxight is another data management application that adds a visual element in its Hyperbolic Tree software - which turns text into maps thereby making the information more accessible. Another popular product is ClearForest. This software also emphasizes the visual side of things, and reconfigures information into visual fields with color-coded arrows that guide the user. This type of software was used by the Eastman Kodak Company to search through mountains of patent documents in search of technical experts.
Filters
The use of filters to eradiate the unnecessary, and select only important information, has become part of the way we work online. It is also a very valuable tool for basic data organization. This is especially true when it comes to the Internet killer application, e-mail. All the best e-mail clients incorporate filtering tools; Microsoft's Outlook, and particularly Qualcomm's Eudora Pro, have extensive filtering options. These serve not only to partially eradicate spam mail, but can also be used to filter and select e-mail from clients, e-mails lists and other categories, which all serves to make the information overload more manageable.
Smart Agents
To Facilitate Process
Smart Agents are software components; interactive database elements are scripts that are able to perform tasks such as filtering and sorting incoming information. They can also summarize and analyze data according to specific criteria as well as perform various other tasks.
An example is an agent that can make travel arrangements. The user can tell the agent where and when they need to travel and add criteria like prices on prices. The agent then searches various sources for airline tickets, hotels, rental cars, etc., and creates a custom travel package. The agent could even make the purchase for the user. Of course agents, while immensely helpful, have not yet reached a state of science fiction perfection. While they can perform many tasks, yet true artificial intelligence (AI) has not yet been perfected. Many agents do not have the ability to fully understand Web sites and complex data, especially across differing interfaces and environments. Agents are best used when they collaborate on or assist the user in organizing data. In other words, in combination with manual organization, agents can be used to simply manage tasks, and thereby make the organization of data speedier and more effective.
There are very sophisticated tools and methods for categorizing and organizing data. However, you do not necessarily need the latest artificial intelligence (AI) tools to set up basic category systems to organize data. To reduce the number of categories you might need a manageable series of concepts to help manage that infoglut. A possible example is to divide information into about five main or top-level categories. This should never be more than eight as the mind struggles to keep a large number of central concepts comfortably in view at one time. The next-level categories that link to the main categories should not exceed a dozen.
Another simple method of reducing data overload is to distinguish between sites that provide professional and trustworthy data and those that don't. This can be simply achieved by paying attention to a number of aspects. Misinformation is as much a part of the Internet as is good useful information. Learning to distinguish between the good and the bad can also save time in the collection and processing of data. Some signs to look for include the following:
- Sites that do not openly display their contact information are often less trustworthy in terms of the information that they provide than those that make themselves available to questioning and scrutiny;
- Older Web sites that are continually updated indicate a more consistent and professional source of information;
- The essentials of data organization therefore depend largely on understanding the nature and value of information. This involves three steps. Firstly, one has to search and capture the information. This in itself reduces extraneous and irrelevant information and is an important step in the process of organizing data. Secondly, isolating the relevant data through a process of selection, categorization and filing is an important part of the process. The third stage is more complex; this involves the creation of new information from the mass of information that has been isolated and selected. Information theory emphasizes that information alone is meaningless without interpretation. This means that the information has to be processed for a certain purpose and employed to create new business ideas, models, and paradigms.
PART TWO: Using Databases
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