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Knowledge Management (KM) past and present: Five megatrends

 
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Knowledge Management (KM) past and present: Five megatrends
by System Administrator - Wednesday, 31 December 2014, 4:30 PM
Colaboradores y Partners

Knowledge Management (KM) past and present: Five megatrends

by Judith Lamont, Ph.D.

Many issues affect knowledge management but five key ones are big data, cybersecurity, mobility, social analytics and customer engagement. The availability of big data has opened many options for understanding everything from customer preferences to medical outcomes. Amidst all that data, concerns about security have grown, so cybersecurity is taking on new importance. Mobility has become pervasive and affects nearly every element in KM, while social analytics is providing insights at a personal level that were never possible before. Finally, although those four factors feed into many KM objectives, enhancing customer engagement has taken a place at the top of the priority list for virtually every company and is likely to remain there for some time.

Big data

The most dramatic trend impacting knowledge management is harvesting and analyzing big data. An esoteric phenomenon just a few years ago with a new set of technologies and terminology, big data is now wrapped into the strategic plans of many firms, and not just the big ones.

When Slingshot Power, a startup based in Northern California, launched its ambitious plan to create a new business model for solar installations, the challenge of Hadoop and the well-known shortage of data scientists might have discouraged it from using big data as a resource. However, the incentive was compelling—being able to integrate a complex set of weather data, demographics, fuel prices and other information to make decisions that would optimize its marketing efforts.

“We had elaborate Excel spreadsheets that we were using for lead generation and targeting,” says Ravi Chiruvolu, CEO of Slingshot Power, “but there was a plethora of data out there that we were not using. If we could use big data, we could target a much broader range of customers more precisely.” After looking at various approaches, the company selected the ActianAnalytics Platform, a big data analytics solution that is described as accessible and affordable for small businesses, but also scalable to large ones.

 

Slingshot is using Actian to help expand its solar franchise business from Northern California to other regions of the country in which solar power can be successful. “Picking the right customers will be a key ingredient for our growth,” Chiruvolu says. “In addition to using Actian to target them, we also use it to generate an economic case for potential buyers. We can show them the energy that solar will generate, compare it to local electric usage and fine-tune it into a business case, all from a holistic model based on big data.”

Yahoo uses Actian to segment millions of users across 10,000 variables, looking for clues that will help predict customer behavior. Amazon Redshift also tapped Actian to provide the core technology components for its cloud-based data warehouse.

“The digital tap has been turned on and is never going to be turned off,” says Ashish Gupta, CMO and senior VP at Actian. “Our technology pulls together diverse data including clickstream, ERP, CRM or network data in near real time as it flows through the data pipeline, marketing, customer engagement, risk assessment and many other applications.” At both ends of the spectrum, from startups to large-scale users, big data will be a central force in converting large amounts of data to decision-supporting information.

Cybersecurity

With so much information at large, unauthorized access has the potential to be destructive. “Knowledge management is focused on information,” says Karl Volkman, CTO of SRV Network. “What makes KM so important now is that people can get information and analyze it better. In the past, it was hard to find out who was buying products and how they felt about them. Now an enormous amount of information is available, which has benefits. The other side of the coin, however, is that the information can be stolen and used in one way or another for financial gain.”

The cybersecurity market is expected to increase from $95.6 billion in 2014 to $155.7 billion by 2019, resulting in a 10.3 percent per year increase during that time period. That figure includes network, endpoint, application, content and wireless security as well as many other types. Venture capitalists are pouring money into the market, and innovative products are emerging in response to increased threats. The volume of data (including an entire new collection from the Internet of Things), the challenges of mobile devices, greater use of the cloud for data storage and the broad impact of consumer concern are all sparking the growth.

Cybercrime comes in many forms, from stealing credit card numbers out of a merchant’s database to identity theft of consumers. A common strategy is for a cyberthief to obtain some publicly available information about an individual and use it to open an account or figure out a password that provides them access to an account. “Users need to be vigilant about changing their passwords and making them strong,” advises Volkman. “Technological safeguards can be put into place, but security depends a great deal on the human element too.”

Mobile devices add another element of risk. They are much easier to lose or to steal, and often contain sensitive information such as bank passwords. Technological advances such as the ability to remotely disable a phone will continue to emerge to protect users from the impact of cybertheft. However, the result of workers being careless with physical security, such as leaving a laptop in an unlocked car, remains a threat.

Companies can mitigate the impact on their customers by limiting the responsibility of users in the event of fraud or identity theft. Industries are growing up around providing insurance for such scenarios, either to the merchant or the customer. As to whether people will back away from using online methods of purchase and payment, Volkman sees a generational issue. “Those of us who are older may use it more cautiously. The ‘digital natives’ who have grown up with the technology are less likely to be shocked by adverse events such as data leakage. They just move on,” he says.

Mobility

Although mobility brings hazards, it has brought even more advantages, and it will continue to drive the pervasiveness of knowledge management. Increasingly, knowledge management solutions, including content management, process management and analytics, have mobile versions of the solution. No longer a miniaturized version of the desktop browser, mobile apps are delivering usable KM applications.

Mobility is also forging new paths. “Consumers have grown acclimated to the use of their mobile devices to access data,” says Penny Gillespie, research director at Gartner, “and are now moving beyond that to see the devices as sources of value. For example, Apple Pay allows use of the smartphone as a wallet.”

However, the payment model has not kept up with the technology. “Today, merchants have to pay a ‘card not present’ fee when the purchaser is using Apple Pay for an online payment,” Gillespie says. “This is the same fee that applies to purchases made by phone or over the Internet when the card data is typed into the application and cannot be validated. However, this charge does not make sense for an Apple Pay transaction because the card is present (i.e., embedded in the iPhone) with additional authentication of the cardholder through a fingerprint.”

One mistake merchants make in designing mobile apps is to try to duplicate a physical purchase experience on a mobile device. “Merchants should not necessarily automate an existing process, but instead should look at the experience holistically,” adds Gillespie. “Mobile experiences have to be simpler and as good as, if not better than, the non-mobile experience in order to gain loyalty from the customer.”

Barriers remain in the use of mobile devices for enterprise applications, but the barriers also represent opportunities. In a study of U.S. and U.K. information technology decision makers conducted by Vanson Bourne, respondents reported that although more than 400 enterprise applications were typically deployed in each organization, only 22 percent of them could be easily accessed on mobile devices.

One reason for that is the diversity of enterprise applications. Some are custom, some are SaaS and some are off-the-shelf, and the technology for accessing each one is different. Therefore, development of mobile apps for such applications is needed, but organizations are hampered by the high cost. More efficient development techniques would be a big benefit.

The proliferation of mobile devices has also spawned a number of other supporting sectors beside mobile application management (MAM), including mobile content management (MCM) and mobile device management (MDM). Each of them has a touchpoint to knowledge management and should be viewed in conjunction with an overall KM strategy.

Social analytics

Social analytics is a booming market, expected to triple over the next five years to nearly $9 billion and showing a growth rate of nearly 25 percent per year. Initially based on simple counts of the number of times a brand was mentioned in social media, analytics has evolved to the point where it is using sophisticated algorithms that support the use of social data for targeted marketing and for initiating customer service.

“Over the last five years, social media analytics tools have come a long way,” says Wilson Raj, global director of customer intelligence at SAS. “They have also moved from hindsight to insight and now to foresight, with predictive capabilities.” SAS social media solutions include integration and storage of social data, general text analytics and analysis of comments for sentiment, and a social conversation module that can work directly or integrate with third-party engagement solutions.

 

Real-time analyses allow marketing or brand campaigns to be synchronized with the topic threads that are emerging. “Decision trees allow ‘what-if’ scenarios such as the impact of increasing the frequency of an ad, or combining customer segments,” adds Raj. “These analyses allow the user to determine the relationships among various factors and to present visualizations of the relationships for better marketing decisions.”

The value of social media analytics is also increased by meshing it with data such as purchasing information from the data warehouse, to compare customers’ stated intentions with actual behavior. “We see tremendous growth in analyzing social media information along with data from the Internet of Things, such as the Nike FuelBand—which measures physical activity—or other wearables,” Raj says, “to build a profile not just of transactions but of tone and behavior along the customer journey.”

Customer engagement

The driving force for all of the above is customer engagement—collecting and managing big data, keeping information secure, enabling mobility and analyzing social media inputs. The ultimate goal is to engage the customer, whether for marketing, customer support, participation in loyalty programs or some other outcome.

Key right now for customer engagement is “omni-channel.” Whether the interaction is initiated by the customer or the organization, customers want options in the delivery channels. “When customers get to the engagement stage, companies need to think about how best to engage them,” says Sid Banerjee, CEO and co-founder of Clarabridge, which provides customer experience and customer care solutions.

Clarabridge solutions collect and analyze information from social media, surveys and recorded conversations. The software can incorporate data from customer relationship management (CRM) systems to develop a complete profile, and can export data into third-party systems used by their clients. “Social media analytics should not be an island,” Banerjee says. “The information should be tightly connected to upstream data so different departments can use it to drive the customer experience.”

Customer engagement is not a static business area; witness the evolution of “call centers” to “contact centers” and then to “customer engagement centers.” The feedback obtained through social analytics and traditional business intelligence can now be merged to explain both what customers are doing and why. That information can guide the delivery of marketing materials and help provide better customer service—two functions that have historically been separate.

“Neighborhood retail stores used to know what a customer wanted because they knew the customer,” Banerjee says. “Mass merchandising shifted that power to the manufacturer and distributor, who knew what the customers wanted in aggregate form because they tracked inventories. But now, the emphasis is coming back to the individual. What recommendation is a customer reading in a review, written by another individual? Is the company sending an appropriate recommendation or offer to the customer? In a different way, customer support has become personal again.

Link: http://www.kmworld.com

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