Using Business Intelligence to Determine Social Network - Essay Example

?Using Business Intelligence to Determine Social Network Introduction Business intelligence has become a common phenomenon in the modern business environment. Business Intelligence (BI) includes computer based methods to identify, extract and analyze business information like sales revenue by products and/or departments (Negash 2004). Alternatively, information could be analyzed by associated costs and incomes. Business Intelligence provides past, present and future prospects and status of the business and is aimed at making better business decisions. Business intelligence mainly focuses on the processes and applications that happen within the business as opposed to competitive intelligence which focuses on the external environment, competitive activities especially. One main characteristic of business intelligence is its reliance on facts as opposed to rumors and heresy. Business Intelligence can be used to analyze people’s social networks to an extent that it may impact on organizations’ performances. This paper focuses on the application of business intelligence in analyzing social networks and its potential effects at the organizational level. Business Intelligence and Data Businesses depend on information form the field, which is translated into data, to make strategic business decisions. In many cases, businesses generate data which they store in databases, flat files or spreadsheets. The data that is stored by any business is extremely important to the organization especially if it is properly analysed and utilized (Inmon and Nesavich 2008). In other words, the data stored by a business should not simply be perceived as information recorded in the past. It should be used for example to monitor sales trends for the purposes of planning market campaigns or to establish the kind of resources that ought to be allocated to certain sales teams. Such information could also be analysed to establish market trends and products that enjoy viability in the current and future marketplace. Yet again, information stored by the business may be used to analyse customer behavior (Negash 2004). Better stated, information can be analysed by organizations to increase profits and maximize revenues through the application of business intelligence. Social Networks A social network is basically a structure that is constituted by a set of actors who are engaged somehow in their interactions, connections or relationships (Liebowitz 2007). In other words, social networks are commonly associated with social groups. The actors or players in a social network may be individuals, businesses or organizations acting at a local, communal or even global level. What this means is that a social network is a group of individuals or organizations that interact with shared goals. While social networking can be done in person, most of the activity is done online. This is the case considering that the Internet is accessed by millions of people with common interests. Websites are commonly used for social networking as online community members who have common interests, or share related views in politics, religion, or hobbies meet and share views and ideas (Liebowitz 2007). Some of the most common and visible social networks in the current business environment include Facebook, Twiter, LinkedIn, MySpace, Google Plus+, Orkut, Tagged, Badoo, and myYearbook, just a few mentioned. While social networks have a great share of advantages, their limitations cannot be undermined. Data theft, frauds and viruses may be part of the social networking experience. Business Intelligence and Social Networks Any organization that applies business intelligence cannot underestimate the potentiality of the application. Business intelligence can measure and report a vast amount of data real time (Respicio, Adam, and IOS Press 2010). Business intelligence may be used to harness trends, and create business to business and business to customer relationships on social networks such as Twitter and Facebook. The data retrieved from social networks can effectively be tracked and measured by establishing the metrics to be used, combining these with relational values and then extracting the data to form measurements that are sensible to the organization. Some of the information that BI can track from social networks include demographics; competitor services, activities and user relationships, trends, topics and keywords; and measurer-able outcomes such as from campaigns. Some of the common trends witnessed in the BI market include data warehouse appliance market, agile BI and self service. The objectives behind these trends commonly include the development of more interactive and efficient business intelligence (Rodriguez, Florian, Casati, and Cappiello, 2010). Coupled with social media, organizations and even individuals can apply BI to communicate more effectively with various stakeholders. Business Intelligence can be applied in monitoring conversations in social network sites to establish such factors as preferred brands, complaints and personal sentiments as noted by Watsonand Wixom (2007). Such information can be vital in establishing certain facts relating to people and markets. When an organization, for example, digs deep into people’s conversations as posted on social media with the application of business intelligence, it can gain an insight into directors’ driving strategies, inform the development and research of products, improve business culture, and establish a competitive edge with respect to other businesses. The importance of incorporating social networking functionality within business intelligence is beyond measure. This addition of business intelligence in the work place ensures that social networking of directors is constantly monitored. Hence it makes it easy to use business intelligence and support the need for self service business intelligence. It will also make communication and information sharing among people a natural analytical extension. Higher levels of social networking on regular basis accompanied by real time raises the overall value intention of business intelligence in an organization. Once organizations choose to incorporate social networking within their business intelligence environments, it embraces various options and this may affect its directors and other workers (Rodriguez, Florian, Casati, and Cappiello, 2010). For example, organizations can add mutual technologies into their general business intelligence platforms. Some of these constitute searching for more interactive solutions that incorporate social networking functionality. For instance, Lyzasoft provides a social networking policy with business intelligence features. Other vendors look for wide deployment opportunities and the capacity to share information via blogs, alerts and emails. The impact of using BI applications such as SPSS Clementine to analyse data from social networks may be positive or negative depending on how the information or data that is gathered is used. When information such as brand preferences of managers or workers is used positively, an organization can achieve great success in terms of sales of the particular brand. Based on the information drawn from the social network, the views or attitudes of employees regarding certain brands, directors, or duties can be established and necessary actions taken to improve the company’s situation. On the other hand, a competitor may use certain notions negatively to impact negatively on the performance of a brand in the market. If for example, a company director posts a thread that he/she does not like red wine for health reasons, a company that makes white whine can take advantage of this to convince its audience that a brand of red wine is unhealthy. Innovation is one of the main the main activities that drive a company towards business intelligence activities. Through collective intelligence as established by BI with data drawn from social networks, an organization increases its capacity to produce new and innovative products. Furthermore, the organization may use social media to express its ideals as established through business intelligence. A company like proctor and Gamble has used business intelligence to establish customers’ tastes. The company has in turn taken measures to provide customers with what they demand following information drawn from their conversations in social sites. How Business Intelligence can be applied to Impact on an Organization. One way of using BI to positively impact the company’s performance is by mapping the company’s or brand’s graph based on information drawn from a social network. Once this is done, the company should establish the graph’s nodes and their influencers. Attention should be drawn to what various groups within each node find important and where they air their views. Competitor’s activities and people’s views about them should also be considered in identifying opportunities and threats. The data gotten from the intelligence should then be shared with other members of the organization and brainstorming done to establish ways of implementing new ideas in support of the company’s goals. Ideas drawn from such an exercise may lead to greater innovation in the company. Conclusion Business intelligence is growing in use ever since it was introduced in the 1960s. BI involves the retrieval and analysis of business information with the aim of making better business decisions. Business intelligence when used together with social network sites can have great impacts on the performance of an organization. Data mining using business intelligence applications can lead to the discovery of vital facts regarding the organization and its performance. Performance trends, success factors, personal preferences of managers and effective management styles can be established through the use of data retrieved from workers’ social networks. Based on the factual information, the company’s performance can be positively impacted as necessary measures are taken to correct or improve the current situation. References Inmon, B. & A. Nesavich, "Unstructured Textual Data in the Organization" from "Managing Unstructured data in the organization", Prentice Hall 2008, pp. 1–13 Liebowitz J. (2007) Social networking: the essence of innovation, Scarecrow Press. Negash, S. (2004) "Business Intelligence", Communications of the Association of Information Systems 13: 177–195. Respicio A., Adam, F. and IOS Press (2010) Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade, IOS Press. Rodriguez, C. Florian, D., Casati, F. and Cappiello, C. (2010) "Toward Uncertain Business Intelligence: The Case of Key Indicators", IEEE Internet Computing 14 (4): 32. Watson, H. and Wixom, H. (2007), "The Current State of Business Intelligence". Computer 40 (9): 96. Read More