Business and Technology Conditions That Complicate the Application of

Businessand Technology Conditions That Complicate the Application ofAnalytics

Businessand Technology Conditions that Complicate the Application ofAnalytics

Nearlyall businesses have large volumes of data collected over time, butthe usefulness of such data cannot be realized before it is convertedinto meaningful information. This calls for the application ofbusiness intelligence, which refers to the process of converting rawdata into useful and meaningful information for the purposes ofbusiness analysis (Bergeron, 2000). Business intelligence givesbusinesses an opportunity to manipulate the data and generate usefulreports. The process of data extraction and analysis of trends withthe objective of identifying new opportunities and customer segmentsis referred to as the business intelligence (Samild, 2011). Althoughthe concept of business analytics sounds simple, its effectiveapplication in real life situations is complicated by the currenttechnology and business conditions. This paper will address some ofthe key business as well as technological conditions that complicatethe effective application of analytics in businesses and prospectsfor future improvement.

Thereare two major types of technology conditions that hinder theeffective application of business analytics. First, businessanalytics require the use of automated systems whose failure canresult to huge losses on business. According to Samild (2011) it iseasy to keep an automated system running, but the automation of a badalgorithm can result in quick loss of money. This is because a faultyalgorithm leads to wrong forecast, which in turn forces the businessto make the wrong decisions. The fault can be caused by the lack ofadequate security functions, software errors, ad contradictory data(Bergeron, 2000). The installation of an accurate automated systemrequires the use of high quality data, which is difficult to achieveand this presents a major challenge for business.

Secondly,effective application of analytics calls for the employment ofexperienced members of staff. These technology and business expertsshould be able to use the available software to extract data from thedata warehouse and use the data to create useful information (Samild,2011). This implies that the installation of the system is not asufficient measure for effective application of analytics toknowledge management and business intelligence data. This is based onthe notion that the software used to automate the business analyticsystem are simple tools that help businesses extract data from thewarehouse, but does not generate information for them. Lack ofemployees with business analysis skills can hinder the process ofapplying the significant concept of business analytics in businesses.

Apartfrom technology conditions, there are two major business conditionsthat prevent the effective application of analytics in knowledgemanagement and business intelligence. First, unpredictable businessenvironment complicates the process of the use of analytic tools toforecast the future success or failure of the business. For example,the global financial crisis of 2008 was mainly caused by the lack ofcapacity to predict the effect of subprime mortgages on the nationaland the global economies (Samild, 2011). This indicates thatunpredictable business conditions renders economic models andbusiness analysis tools irrelevant and of little use. This alsodiscourages businesses that end up lacking value in the businessanalysis tools.

Thesecond business condition that complicates the process of applicationof business analytics is the problem of change management. Businessanalytics calls for the use of facts-supported decision makingprocess instead of relying on theories and assumptions. However,reliable data and information is obtained through extensive andsophisticated methods compared to theories. This requires significantchanges in ways that a given organization conducts its operations,including the use facts-based decision making processes. Similar toother organizational changes, the decision to use business analyticsalso faces challenges, including the employee resistance (Samild,2011). In addition, system automation leads to a decline inemployees’ motivation, management ambiguities, and reduced employeeloyalty. In essence, the need to address organizational issues (suchas employee resistance to change and potential managementambiguities) complicates the process of the application of analyticsin business.

Thereis s great hope significant improvement in the application ofbusiness analytics in knowledge management and business intelligence.The fact that some companies (such as Wal-Mart) have used businessanalytics in the past to achieve their present competitive advantageis a motivation for more firms to follow the same route (Davenport,2005). Companies will be forced to focus on technological tasks inorder to become analytics competitors. Some of these technologicaltasks include the selection of analytic software, availing data inthe warehouse, production of transition data, and implementation ofanalytic software (Davenport, 2005).

Inconclusion, the application of business analytics in knowledgemanagement and business intelligence has many benefits, but it faceschallenges from technological and business conditions. Some of thekey technology conditions that complicate the process of theapplication of analytics in the contemporary businesses include thepossible failure of automated systems, the need for high qualitydata, and technology experts. Business conditions that complicatethis process include reduced predictability of the businessenvironment and the challenges related to change management. There isa high prospect for improvement of the application of analytics inmany businesses given the fact that some larger companies (such asWal-Mart) have set the precedence.


Bergeron,B. (2000). Regional business intelligence: The view from Canada.Journalof Information Science,26 (3), 153-160.

Davenport,H. (2005). Competingon analysis.Boston, MA: Harvard Business Review.

Samild,S. (2011, September 2). Tom Davenport: Why aren’t mostorganizations competing on analytics? AnalysisFirst.Retrieved August 27, 2014, from