Collective Intelligence And Crowdsourcing

Published Date: 02 Nov 2017

OLATUNJI-DAVID Folagbade J,

OMOLOLU Royal-Praise O.,

OBIGBESAN Olumayowa B.

Abstract

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Keywords: Business Intelligence, Performance Management, BI Technologies, BI 2.0, BI 3.0, Pervasive BI, Mobile BI

Introduction

An organization that cannot effectively identify the important information required at all levels will inevitably be forced out of business by competitors who can (Ackoff, 1967). A vital form of information systems (IS) is the Decision Support System (DSS), which can be defined as "systems that support non‐routine decision making with a focus on unique problems that are rapidly changing, and for which the procedure for arriving at a solution may not be fully defined in advanced" (Laudon, 2012) this literally means they are systems that support better decision making at all levels and this is precisely what Business Intelligence is geared towards.

Business intelligence (BI) is a contemporary term, given to the ability of an organization to collect, maintain, and organize knowledge. This produces large amounts of information that can help develop new opportunities. Identifying these opportunities, and implementing an effective strategy, can provide competitive advantage and long‐term stability. BI technologies provide historical, current and predictive views of business operations (Keen, 1980). Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics (Laudon, 2012).

The eventual expectations that drive the deployment of business intelligence in today’s world is the need to offer better decision making support for businesses. The challenge however is that BI isn't just analyst‐driven anymore; it's pervasive, Innovation is coming from nontraditional and emerging vendors. New technologies are coming for information access, analysis and presentation capabilities (Trevino, 1999). There is therefore a need for Innovation to occur with sourcing options in addition to technology. This paper looks to address emerging technologies that are showing up in the scene of Business Intelligence; trends like pervasive BI, mobile BI and BI 2.0.

Pervasive BI is one of those concepts that is intuitively recognized as positive and having a lot of potential. The benefits of pervasive BI extend the benefits of business intelligence to an entire organization. The pace of business is rapidly accelerating, so being knowledgeable about one’s today business is more important than ever. Keeping everyone in the organization informed is what pervasive BI is all about — and it will impact performance, understanding, and loyalty. For the vast majority of organizations, BI solutions have yet to become fully pervasive — BI still has a ways to go before it is pervasive. Accounting for this knowledge‐gap is the fact that modern business intelligence is only starting to mature and realize its full potential, and this paper will look to discuss much of this referred potential.

In a world that is increasingly going mobile and instantaneous, it would be surprising if the Business arena would not take a cue from it. Recent emerging trends indicate that work‐place analytical capabilities are being deployed via mobile devices to improve job performance, decision making and Just-In-Time (JIT) decisions. This is possible as the frontiers of social networking tools and the ever increasing processing power and miniaturization of mobile devices are being extended to bring about limitless opportunities to be harnessed (Ramakrishna, 2008). Some of the possibilities are due to new technologies that have changed the way BI (Business Intelligence) operates which include (CEP) Complex Events Processing and In‐Memory Analysis. These allow for Predictive Analytics and Real Time Analytics which are going to be instrumental to next‐generation Business Intelligence (Bedell, 2011). Most of all, as expectation time for delivery of results keep shrinking; these mobile BI tools will keep rising to the occasion, by increasing efficiency and best of all, being available on the fly (Hatch, 2008).

This field of research has been chosen over others because of the interests of both student researchers in finding key determinants in identifying the role of proper data and knowledge management in establishing sustainable competitive advantage in business.

1. BI 2.0

BI is an essential utility that enables businesses gain competitive advantage from analyzing data available to the organization. While business intelligence is still regarded as a technology that is not new, its use has increased steadily over time, with an average 4% growth rate in the BI market since the beginning of the recession of 2008 (Trujilo, 2011).

While traditional technologies for supporting BI such as data warehousing, OLAP, data mining, etc. query data from the inside of the organization, novel trends of BI (BI 2.0) that focus on the analysis of external data have emerged. The outcome of having a wider data pool is that the analysis is more comprehensive, and provides better platform and support for decision making. For example, a retail company that would typically focus its BI strategies internally, can now have access to prices of competitors, and can also have information to how the customers receive their products; this will in turn affect their strategy for the release of another product.

The internet has been the driving force for data and information dispersion over the last 10 years and will continue to be for a long time. One important thing to note is that the new trend of BI 2.0 is bidirectional: because BI applications receive and process data from the web, BI applications are starting to evolve to become pervasively web driven technologies. (See section <pervasive section>). Some of the BI driven applications today are Social Networks, Cloud Computing, Interactive WebApps, SaaS (Software as a Service), Semantic Web Search, Word Clouds, Wiki’s, Collaborative Networks, e.t.c.

Fig: BI 2.0 Architecture (Source: Trujilo, 2011)

1.2. BI 2.0 Basic Concepts

Like any technology in use today, there are key concepts that essentially define and differentiate BI 2.0 from other data mining and processing activities.

Real-time analysis: BI 2.0 has to focus on data analysis that is on-line and real time. Because of the new found volatile nature of data, BI 2.0 has to be super flexible and super reactive in nature to process and analyze data.

Intuitive and interactive analysis: Unlike traditional data processing that typically involves homogenous data types and 1-directional analysis, BI 2.0 supports interactive analysis that acts based on a user’s preference, and that can be altered and re-analyzed if certain variables are changed.

Collaboration between decision-makers: A key concept in BI 2.0 is the collaboration that should exist between decision-makers in the manipulation of analyzed data.

Linking and enriching data: The concept of Business Intelligence itself is that of the linking of different data to present better information for decision making, and BI 2.0 takes it a notch higher by enriching this data to be more self-explanatory and therefore increases the utility of the information eventually provided.

1.3. APPLICATION OF BI 2.0

Real-Time Information

As a major application of BI 2.0, the importance of up-to-date information is crucial (Thiele et al.). Analyzed information as explained earlier needs to stay fresh so as to stay relevant; for example, an airliner needs to know they availability of seats on a flight at any given time to be able to plan supplements for their passengers, route availability, etc.

Software as a Service

Software as a Service (SaaS) is a model of distributing software where applications are normally hosted by a service provider or vendor and then made available to customers through a network, most common of which is the Internet(McHall, 2011). This means that software is consumed as a remote service (Essaidi et al). BI 2.0 is applied through the use of Service Oriented Architecture (SOA) and Service Oriented Architecture Protocol (SOAP) for platform interoperability.

Because of the mainly internet based dependency of SaaS, and the substantially higher quantity of data available for analysis, it has caused a shift in modus operandum of a lot of BI systems to become BI as a Service.

Cloud Computing

As a concept related to BI 2.0, cloud computing integrates several heterogeneous elements into a network and then makes these elements available through a homogeneous platform for remote users (Armbrust et al., 2009). Cloud computing can in some way be associated as an umbrella which Software as a Service (SaaS) falls under, because typically the services which Cloud Computing offer are made available as SaaS. Cloud Computing also exhibits the real time and responsive characteristics that BI 2.0 applications have, as it supports the addition of new elements at any time, be it data or service.

Collective Intelligence and Crowdsourcing

Collective Intelligence in BI 2.0 is not to be confused with the concept of crowd sourcing, because in collective intelligence, the concept of emerging behaviors is apparent as decentralized individuals are able to take decisions as a group and this promotes initiatives (Gruber et al. 2008). The generic definitions of social networks fall under this category.

Crowd sourcing is the delegation of tasks to a crowd, where every individual contributes a quota to the global goal (Howe et al. 2009). A strong force in this field are wiki’s – with Wikipedia.com being the most popular, where topics on almost anything or anyone popular can be accessed.

Social Networks

The underlining concept in social networks is that groups of people can interact with each other, collaborating and thus achieving faster goals and better outcomes than would have been the case if it were a single user. The key information that determines usefulness of a social network is the data extracted from contributions of participants; this data changes so rapidly and several trends can be identified based on the relationships of the users involved (Berthold et al; Golfarelli et al). Social networks we believe are one of the pivotal elements of BI 2.0 and the foundation to which many more BI 2.0 technologies will evolve.

Linked Data

The concept of linked data deals with the relationships of semantically tagged data, which allow for reasoning and inference of knowledge (Berlanga et al.). Knowing what relationship exist between every unique piece of data is key, and this will lead to the automatic obtaining of knowledge for the data (Bizer et al. 2009)

Opinion Mining

This strong application of BI 2.0 leverages on the general feelings a group of people have towards a certain good or service (Balahur et al). Based on several data inputted, the (often) unstructured data is analyzed, and then a conclusion is obtained. This application of BI 2.0 places high relevance to the customer’s perception of a good or service and is important for all customer driven businesses. An example of opinion mining is the user powered ratings systems that most websites now use to rate items or services, based on the feedback gotten from other users. Usually, the harnessed intelligence gotten from the crowd can often be more relevant than relying on the sole opinion of an expert.

Process Oriented BI

This concept deals with the focus on Business Processes and their logic, and tries to compare the documented process expectations to the stored data and the actual process performance. This allows businesses identify and restructure business processes while isolating potential and actual problems (Golfarelli et al. 2004).

1.4. Comparison of Available BI 2.0 Tools

Decided which tool or service to use is never an easy decision, and organizations looking to fully tap into the benefits of BI and BI 2.0 will need to be fully aware of the wide range of tools at their disposal. This section first speaks generally, then presents the comparison in a tabular form after.

A vast majority of BI tools recognize the importance of the cloud and thus support cloud computing by using a SaaS or BI as a service approach.

Some tools also support the use of the cloud for specific tasks; for example, Microsoft supports deploying the data integration and the entire system into Azure Cloud.

Because BI tools are used to aid business strategy and decision making, it is therefore important to keep a clear idea of what this business strategy is, and most tools available today offer this through the use of dashboards. While some of the dashboards available will serve for today, more work can still be done to make dashboards more collaborative, interactive and intuitive.

BI Tool

Advantages

Drawbacks

Pentaho

Open source, platform-independent, rich web interface Dashboards for showing data links

Predictive algorithms

Includes collaborative features when integrated with LifeRay

Designing and integrating dashboards requires too much effort

Interactivity and data enrichment can be improved

Inadequate Integration of business processes

Cognos (IBM)

Interactive Web Interface

Collaborative Support and data enrichment

Support for Mobile BI

Dashboards and Scorecards

Predictive Analysis Support

Does not fully reflect business processes

Microsoft BI

Integration of several tools such as: Excel, PowerPivot, SQL Server, Sharepoint.

Includes:

An interactive web interface

Dashboards and Scorecards are available in mashups

Elements can be linked and can interact with other users

Tags addition to profile in Sharepoint supported

Can include data from the Web

Analysis through Excel and PowerPivot

System not optimally designed, not intuitive enough

The predictive analysis is limited to only Excel functions

Does not possess some collaborative functions

Direct interaction between users not available

SAP

Provides complete support for analyzing the

business strategy combining desktop

applications with web applications

Includes:

Web interface for ad-hoc analysis.

Mobile BI support

Dashboards and scorecards

Complete workbench for data mining tasks

Compatibility with other vendors tools thereby empowering analysis capabilities (Tools like Excel and other enterprise applications)

The collaboration between users is limited

Lacks support for enriching data

Interaction between users not available

Table: Comparison of some available BI 2.0 tools

INTRODUCTION

Being Mobile has become part of our lives. This trend of mobility has also been changing the business world and the way information is handled over the past years.

The idea of mobile BI can be traced back to the invention of the first mobile phones and laptops in the 1990s. It started with exchanging emails and PDFs. Nevertheless the real breakthrough happened years later with the strong market penetration of smartphones and tablet computers.

With the advancement of technology we can run various BI solutions on many different mobile devices. This became possible about two years ago with the emergence of mobile broadband and new and powerful hardware platforms such as the iPhone, Android, Windows Mobile/Phone and Blackberry. Over the past several years’ solution providers have placed a lot of effort into developing interactive mobile applications that can be used by decision makers on the road. BI is finally starting to make inroads into the general business intelligence marketplace. Today, people are using mobile phones to track crop prices in Kenya and manage micropayments in the Philippines. They are tapping into these devices to handle healthcare information in Nicaragua and oversee bakery orders in Nigeria. In fact, with an estimated three billion- plus mobile phones in use worldwide and approximately 80% of the world’s population within the reach of a cell tower, almost no corner of the globe remains untouched. (Greengard 2008)

DEVELOPMENT OF MOBILE BI

In 2009 BI vendors started announcing the availability of BI for mobile devices.  First its use was strongly restricted by the low interoperability in between devices and the Screen Real Estate and the supported devices.  End users, in some cases, could change the way they viewed data, but in very few cases were they able to do much more or edit the information they were viewing.  In addition, because of the limited user interface, not much beyond a singular graph or report could be compared or viewed at a time. 

Although the ability to view BI tools via a mobile device added to the value of an organization’s overall applications, the reality was that this type of access to information was limiting.  Despite the advances in technology and the ability to email a new report or analytical insight to a colleague’s mobile device, little value regarding the application of BI through mobile existed.

From 2012 to date the offerings of devices and applications in the field of mobile BI have constantly increased. One big success of the past years was to achieve a higher level of interoperability in between different devices and operating system, like viewing a word document on the iPhone that was send by a Blackberry.

With the Tablet computer a bigger screen made mobile work more convenient. Moreover stronger hardware (also in smartphones) allows more applications.

Since the successful launch of the Apple iPad a year ago, there has been a dramatic rise in the number of companies seeking to deploy business intelligence on mobile devices.

The evolution of offerings

When mobile solutions were first offered, many were focused on providing access to PDFs through blackberries.  The goal was to let end users access reports irrespective of their location.  For business travellers, this made sense as information became easier to access no matter where a person was located. 

As both mobile technology matured and BI usage broadened, the possibility to look at different ways of deploying and interacting with BI became a reality.  Since then Business Intelligence is slowly shifting away from a focus on desktop solutions.

Even though many organizations still use traditional BI applications like date warehousing, OLAP and interactive reporting, the focus starts to shift. Companies realize that BI needs to refocus on providing its users with deeper insights and supporting decision-making.

Within the last year, i.e. 2011, solution providers for example SAP (System, Applications, Products) have announced mobile BI solutions.  These solutions differ from their predecessors in two key ways:

1) Mobile BI includes interaction with BI applications and functionality

2) Attractive user interfaces make the use of BI possible and much easier

OPPORTUNITIES OF MOBILE BI

Not only can users view and share information but they can interact with and analyze data, creating reports and charts as needed. 

The ability to access the right information at the right time is always beneficial.  What mobile BI can offer a company is the ability to provide employees who are on the road with timely and accurate access to analytics. In some cases this might include providing executives with information required to prepare for meetings, or giving sales representatives information they need before visiting clients or suppliers. 

Mobile BI allows accessing and using information without requiring a laptop, having to print and carry papers and being bound to a certain place.

Even though this may have existed in the form of blackberries and the like, the amount of interaction and full-scale functionality was not available previously.

TRENDS OF MOBILE BI (u should adapt the order)

As mobility is increasing in general BI becomes more broadly applied and valued as well. It enables organizations to access, create, distribute and edit required information whenever they need it with everyone needed. 

Several emerging trends have developed in mobile BI:

1) Customization:

Since many employees already have an iPad or other mobile devices, it would be difficult to ask them to carry a second one just for business. Since these are consumer gadgets, it's inevitable that organizations are going to have to accommodate the mobile devices that employees already own. But how do you secure and support personal devices that contain a mix of corporate and personal applications and run on different platforms and versions?

The IT department is used to purchasing, configuring, securing, and maintaining computers for employees. Mobile technology undermines this process and threatens IT administrators, whose job is to maintain a stable, secure, error-free compute environment. How can they do that when they don't own or control the devices?

It's clear that the IT department is going to have to adapt. They'll need to purchase corporate devices to support development and testing and give devices to employees who don't own them already. But they'll also need install corporate applications on devices which employees already own.

2) Big Data

3) Clouds

The trend of Cloud Computing is a major step towards a higher level of mobility. The more data is stored in clouds the less a user is tied to a location (e.g. desktop) or even to a particular mobile device.

4) Collaborations

Collaboration and social networking have become commonplace in some organizations and people are starting to bridge the gap between the way they interact with technology inside and outside of the office.  As this trend grows, more companies will start to use applications that support collaboration and communication across channels, geographic locations and departments.

End users can communicate with one another in real time through texting, chat or email - to discuss opportunities or concerns based on insights gained through information access and daily interactions no matter the physical location.

5) Improved Customer Service

A new trend is to manage customers irrespective of location by e.g. connecting mobile devices to document management systems. That way data can be accessed and edited in every location while dealing with customers. A good example is Apple. In their physical stores they bring checkout to the customer with the option of a paperless transactions. An iPad replaces a cashier and any need for such furniture in the store. These types of customer initiatives will continue to become more prevalent and provide a good example of how businesses are taking advantage of mobile technologies to expand their reach and enhance customer experience. 

6) FLEXIBILITY AND MOBILITY

Mobile BI will offer more and more flexibility to its employees. The can access the right information at the right time within the right place – whether the right place means on a desktop, laptop or mobile device. People are becoming less attached to physical offices due to the increase in telecommuting, virtual businesses and e-commerce, travel, client engagements, supply chain management, and the like.  Consequently, people are also becoming less tied to traditional means of business management and are adopting more interactive ways of doing business. 

7 ) Better Sales Analysis and Visibility

Sales analysis has always been at the forefront of BI adoption. In traditional or "software as a service" SaaS-based offerings, sales analytics remains a key way by which businesses identify the success or failure of their performance.

(NEW TRENDS, EXAMPLES?)

CHALLENGES

1) Challenge- Screen Size

Even with the benefits of mobile access to information, the reality is that due to the small screen real estate of mobile phones, there will always be limitations in relation to how much can be viewed or interacted with at once. People’s preferences will dictate whether mobile BI actually gains wide adoption or whether the development of these applications simply addresses the needs of internal competition among vendors.

2)

But there are all kinds of thorny issues involved in deploying BI--or any corporate application for that matter--on a mobile platform. The most widely discussed are security, selecting a mobile platform, designing for the mobile form factor, identifying appropriate mobile use cases, and selecting an application architecture (i.e. browser-based versus device-specific). These all represent significant challenges. But one issued that hasn't been discussed much yet is whether an organization should deploy corporate mobile applications on personal or company-issued devices.

Choice of User

The promise of information access in the hands of decision makers without restrictions is appealing.  Organizations using business intelligence effectively within their companies can always choose to move beyond traditional BI use and add mobile BI to their overall usage with relative ease. 

The only real barrier to entry is whether BI users are open to changing and expanding the way they interact with their business applications.

Stolen Devices

But these are small hurdles. The biggest issue is non-technical. What happens when a user loses a personal device with a corporate application installed on it?

If your mobile application is browser based, you only have to worry about data cached on the device, which is there to optimize performance. Ideally, your security software automatically deletes the cache every hour which minimizes (but doesn't eliminate) the risk. If you've deployed a native mobile application in which data resides on the device, you'll not only need to clear the cache, but wipe the hard drive as well, which your security software can perform remotely. (Of course, this only works if the device is turned on and connected to the network. Sophisticated thieves will hijack the data without connecting to a network.) In all likelihood, you'll need to apply all these strategies to secure sensitive corporate information.

3) create a new kind of BI experience – one that is designed more for workers and less for IT.

4) Support Diversity:

Gone are the days when corporate IT can set mobile device standards. Instead, users are increasingly bringing their own devices, forcing IT (and BI vendors) to support a broad swath of smartphones and tablets. The most promising way to support diversity