Oxford Retail Futures Conference Big Data, Business ntelligence and Real-time Analytics in Retail Said Business School, Oxford University, 9-10 December 2013 Business ntelligence for Building the Competitive Advantage in Retail ndustry Celina M. Olszak
Motivation for the study A contemporary organization competes in a business environment that is characterized by a massive influx of information (Schick, Frolick and Ariyachandra, 2011). A critical component for its success is the ability to take advantage of all available information (Cody, et al, 2002; Jordan and llen, 2009). Business ntelligence (B) - a solution that may help retail industry to make informed, intelligent business decisions and to survive in the business world (Negash and Gray, 2008; (Wixom and Watson, 2010). Although B has been developing for over 20 years, unfortunately, many retail organizations are not able to make from it an effective tool for decision making and creating a competitive advantage (Davenport and Harris, 2007). he analysis of B using shows that practical benefits are often unclear and some organizations fail completely in their B approach (Clavier, Lotriet and Loggerenberg, 2012). he research questions: What possibilities offer B tools for retail industry, what factors allow to achieve high competences in B, and consequently to obtain business success.
Methodology: (1) critical analysis of the literature C O M P V N L L G N C Business ntelligence B 2.0 Web mining, ext mining, opinion mining B 3.0 Mobile mining Alerts Query/drill down Ad hoc reports Standard reports B maturity models (2) interviews with experts from retail sector Optimization Predictive modelling Forecasting/extrapolation Statistical analysis Model of Competition B 1.0 Degree of intelligence Asked questions during interviews (n-15) How do you define B? What do you use B for (reporting, ad-hoc reporting, analyzing, alerting, predictive modeling, operationalizing, optimization, activating, etc.)? Does your organization have a defined B strategy? Does your organization have defined business processes? Does your organization/department have defined metrics? Assess the quality of data used in your organization (complete, correct, consistent; high/medium/poor quality data, etc.) Are you skilled enough in order to take advantage of B systems? Do you use management dashboards? s your B (un)limited to the part/department of organization? Are you motivated to use B (how)? Do you use B for analyzing customers, suppliers, competitors and other business partners? Who is the sponsorship of B in your organization? What kind of B software do you use? Describe some successes/failures from 3 using B ndicate some benefits from using B
Level Human Organization/process ools, technology Benefits ly impaired (n-2) Localized analytics (n-4) Human barriers, poor skills in B he users take the first B initiatives; low support from senior executives Organizations have some desire to become more analytical; processes are not defined, data are not complete and inconsistent raditional approach to management, focused on the performing the basic tasks of departments; identification of basic business processes Lack the hardware and software, simple reporting, using xcel analysis Reporting with pocets of analytical activity,used data bases, OLAP, regional data warehouses Lack the benefit, or poor benefits Low benefits limited to small group of users; better access to data and static reporting Success factors: support from senior management, appropriate B tools, quality of data, defined business processes and metrics aspirations (n-7) B activities gain executive sponsorhip, staff is not enough educated in B Organizations build their first plans of B using.; B is used to perform ad hoc reporting and to answer questions related to department s ongoing operations Management dashboards are used; a centralized data warehouse is built; ad-hoc reporting, query drilldown Benefits limited to departments and business units; improvement of internal business processes and decision making on operational level Success factors: developing corporate culture based on facts, stating clearly B strategy, implementing training system on B companies (n-1) Model of Competition - Results and Discussion Users have high B capabilities, but often not aligned with right role Business process management based on facts, establishing a fact-based culture, clear B strategy, building analytical capabilities High-quality data; have B strategy; using more complex prediction and modeling tools; advanced data mining, CRM, SCM Success factors: support from CO, motivation of users for collecting, analyzing and using information hey do not compete through B; integrated analysis for sale, finance, logistics, improvment of CRM, SCM competitors (n-1) Users have capabilities and time to use B; skill training in B; users are encouraged to collect, process, analyze and share information he common B approach is used in the whole organization; dynamic analytical capabilities, hard to duplicate, unique, adaptable to many situations nterprise-wide B architecture largely implemented; customized reports; web mining, opinion mining, business and B are aligned and cooperative Benefits for the whole environment; competing through B (acquiring new customers, lunching new products, new channels of sale); new ways of 4 doing business
Conclusions and recommendations (1) B may be a key (trigger) for making more effective decisions, improving business processes and business performance, as well as doing new business. (2) he factors that allow retail organizations to achieve business benefits with B, include first of all: management leadership and support, corporate culture, expressed by effective information resources management, clearly stated strategy and objectives, and use of appropriate B technologies. (3)Additionally, the important factors are: clearly defined business processes, business performance measurement, incentive system to encourage collecting, analyzing information and knowledge sharing, appropriate resources (financial, intellectual), training and education on B and knowledge management. (4) Retail industry needs to turn to new generation of B tools (web mining, text mining, opinion mining, search based applications, multiagent technology, etc.). hey enable to better understand the business and the environment. Regardless of the tools used: B and business (retail) must be aligned and cooperative. HANK YOU celina.olszak@ue.katowice.pl QUSONS?