Happy union: KM and the cloud?
Cloud computing and big data appear to be a new technology marriage made in heaven. For many organizations, the cloud and big data could crack the knowledge management problem.
In 2011, the National Institute for Science & Technology (NIST) published a draft definition of cloud computing. The definition articulated several "essential characteristics," service models and deployment models. The main idea is that most enterprise applications can run in a time-sharing setup with such bells and whistles as collaboration, reports and guaranteed uptime. On-premises systems—despite their security advantages—require specialized staff. To control costs and shift from the hard-to-control expense of on-premise systems, cloud computing offers a managed solution. If the costs are about the same or higher, the efficiencies of outsourcing appear to make sense to many organizations.
Big data is a comparatively new challenge for organizations. The data may be growing, but the fuel igniting the big data booster rocket is management's awareness that information has value. With more digital information available, senior managers are reasoning that digital information must be processed to yield nuggets, information about trends and insights into what prompts customers to buy a company's products. Big data, therefore, is an enterprise information priority. Infrastructure, software license fees, data scientists and capital costs are expensive to deploy in an on-premises model. Cloud computing offers a path forward. Amazon, Hewlett-Packard, IBM, Microsoft and dozens upon dozens of other online service providers are in the cloud game.
The path forward
Amazon, once an online Wal-Mart, has begun to describe its cloud technology, including a presentation by Charles Bell, Amazon's VP involved in cloud technology. A continuing flow of "innovations" range from a virtual desktop service to a streaming data service to technology that permits random input-output operations. According to the Amazon Web Services Blog, Amazon Kinesis allegedly does what other cloud ?services only "say" they do by delivering "real-time processing of streaming big data." (See http://goo.gl/HsutdB.)
For a company that has until recently provided none of the IBM- or Google-style technology briefs, Amazon is ramping up its marketing about its technological breakthroughs. It's making a case for its cloud infrastructure to be a low-cost enterprise application platform. The inclusion of big data and real-time information processing seems to position the company to be the logical choice for cloud-based knowledge management.
I ran a query on Google's search system for "cloud knowledge management" and was greeted with 55.3 million relevant documents. I ran a second query to narrow the result set. I used the query "cloud based knowledge management providers," and Google displayed 55 million hits. So much for narrowing.
The result sets were interesting. Knowledge management combined with cloud is a very popular concept. The results page displayed a full complement of Google advertisements. Advertisers seeking clicks included IBM, a company that offers private and hybrid clouds. Google advertised its cloud management capabilities. An organization can "build and host applications on the same infrastructure used at Google." Consultants, academic institutions and companies with which I was unfamiliar were trying to attract customers.
My excursion into cloud-based knowledge management revealed several characteristics about this particular branch of knowledge management. Front and center is the notion that the cloud is a catchy, versatile buzzword. Almost any information technology feature or function can be enveloped in implied meaning. The benefits embrace ease of use, lower costs and greater operational efficiency, particularly when lashed to some enterprise applications like customer service or sales management. I noticed that "cloud" matches seamlessly with such hard-to-explain services as "enterprise search," "information management" and "knowledge management."
Salesforce.com, once a hosted contact and prospect management service, is expanding its services. The company tried to graft collaboration to its sales prospecting system and failed. The company said in mid-November 2013 that its "social enterprise pitch did not work." (See http://goo.gl/XDG0u0.) The company has pivoted and positioned Salesforce.com as an "integration platform."
According to InfoWorld: "Salesforce1 is meant to allow the rapid creation of apps that can work across Salesforce's sales, service and marketing apps, as well as on top of its Force.com, Heroku and ExactTarget Fuel platforms, all at the same time. Salesforce1 is a free, automatic upgrade for existing Salesforce customers. It is made possible through a new set of APIs and mobile app creation tools, including AppExchange, an app store for Salesforce1-connected apps, where third-party software vendors can sell their creations. Dropbox, Evernote and LinkedIn have signed on to add apps to AppExchange. (See http://goo.gl/PUAWLS.)
The most obvious identifying feature of the services of Amazon, Salesforce.com and other vendors is fuzziness. A developer can build almost anything, but does that new capability solve a knowledge management problem? Perhaps practitioners of knowledge management have created what I call the "fuzziness problem." Will moving knowledge management to the cloud and incorporating big data solve a problem that ties directly to improved efficiency, more revenue or reduced costs? Is a shift to the cloud a way to reduce the costs for a customized enterprise application?
An enterprise application is more than word processing, spreadsheets, presentation software, content management and e-mail marketing. Basic and advanced analytics are available for enterprises wanting to filter meaning from the flows of point of sale systems, Web traffic, Twitter messages about a product or trend and so on. But an application is different from the hope that cloud-based knowledge management will solve a business problem. My suspicion is that the original concept of mainframe timesharing has been reinvented and wrapped in Project Runway fashion.
Also, the companies offering cloud-based knowledge management use a variation on the approach of an allergy specialist. A patient often undergoes dozens or hundreds of exposures to different substances. The physician inspects how the patient reacts to the different samples. When the patient's condition reacts to a particular substance, the physician has a signal to investigate. For a vendor looking for cloud computing knowledge management prospects, the buzzwords replace the allergen.