Domino's Pizza and Big Data Analytics
Added on 2020-02-03
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International Supply Chain Management UniversityA CRITICAL EVALUATION OF THE ROLE OF BIG DATA ININTERNATIONAL SUPPLY CHAINS AND ITS IMPACT ONSUPPLY CHAIN MANAGEMENT: A CASE STUDY OFDOMINO’S PIZZAStudentIDUnit titleCode numberLecturer’s name1
International Supply Chain Management Executive summaryThis study evaluates the contribution of big data analytics in the management of internationalsupply chains. Evaluation of the data has availed the understanding that the huge amount of datathat supply chains like Domino’s acquire from their stakeholders might be evaluated and utilisedwith the use of big data analytics, for predicting, the market demand and appeal of their productsand services. For this, the business organisation might utilise SCOR model and combine it withthe elements of big data analytics for generation of competitive advantage. 2
International Supply Chain Management Table of contentIntroduction......................................................................................................................................4Findings and analysis.......................................................................................................................4Conclusion.....................................................................................................................................16Reference list.................................................................................................................................17Appendix........................................................................................................................................203
International Supply Chain Management Introduction In the current business environment of global competition, optimisation of the supply chain hasbecome essential for the multinational corporations and big data analytics, due to its capability ofevaluating and comparing homogenous data has immerged as the preferred measure forassuming the company strategies and predicting the market trends (Forbes.com, 2017).Utilisation of big data emerged as an amiable way for generating value in the functional areassuch as product development, perdition of market demand, optimisation of distribution andfeedback acquisition from customers for global supply chains (Russom, 2011). Since a decade,multinational supply chains, such as, UPS, DHL and Maersk have found big data analytics to besuitable for logistics and transportation management. Business experts identified it as capable ofsaving considerable expenses of the company through identifying the shortest and most directpath for the company operations and by predicting the potential determinants of the success ofthe company in market, assisting it to identify the market opportunities. Such in-depthunderstanding of the market trends and varied functional paths helps the business corporation toidentify the most profitable strategic options for conducting the organisational operations ininternational market environment. According to a recent report, Domino’s has already utilised the big data analytics for managingits international supply chain activities which has supposedly improved the organisational salesand increased its revenue in considerable manner (Forbes.com, 2017). Dominos is the largestpizza supplier across the globe, which has accepted that it uses big data analytics for evaluationof the organisational data and predicting its business prospect. The organisation, applying big ataanalytics has recently transformed its marketing and sales strategy in considerable manner andemphasised more on the online transaction and complete virtual sales experience. This hasincreased customer preferences concerning the company’s product, which might be identifiedincrease in company’s sales and reduced sales of its closest competition, Pizza Hut by 2%. In thisparticular research report, the researcher has investigated the role that big data plays inmanagement of international supply chains with examples from Domino’s Pizza. 4
International Supply Chain Management Findings and analysis Concept of Big Data analytics NASA first used big data, as a term in 1997 for explaining the challenging faced in visualisationof the issue or prospects due to the presence of huge sets of data (Hazen et al. 2014). Big datahas the potential of contributing to the enhancement of sales, loyalty of customers and reductionof organisational expenses and risks through optimisation of real-time routes (Waller andFawcett, 2013). From this, it can be deduced that application of big data analytics might becomemandatory for the multinational supply chain companies in future due to the huge amount ofinformation that they are stored in their database for evaluation. Evaluation of the concept of bigdata analytics from the resource-based view might be useful in further evaluating its necessity inmanaging multinational supply chains. Resource-based view (RBV) previewed the physical infrastructure concerning the informationtechnology as the tangible resource of a business organisation, while the competency andknowledge of the employees along with their experience are considered intangible assets (Kwonet al. 2014). These intangible resources of the business organisation are developed through theexternal evaluation and internal investment. Therefore strengthening such tangible and intangibleassets in the RBV is crucial for enhancement of the general IT capability of the company, whichmight be a significant determinant of the competitive advantage of the organisation. Dubey et al.(2016) opined that the richer a company is in terms of such resources, more chances it has forgenerating further value for itself. Incorporation of big data analytics in the data managementand analysis process of the firm ensures heterogeneity of the firm in terms of approach towardsthe market and customer needs, which is crucial for maintaining sustainability of the companywithin the competitive market. Forbes reported that information from 85,000 different sources iscollected and added to the database of the company every day (Forbes.com, 2017). This includesboth structured as well as unstructured data. Therefore, it is essential for the company to utilisebig data analytics to acquire positive IT capability and utilise such data. Apart from RBV, theisomorphism is also capable of explaining the importance of big data in supply chainmanagement.As per the neo-institutional isomorphism,IncomeRevenue5
International Supply Chain Management the basic purpose of abusiness organisationbehind any innovation isnot only enhancement oftheir level of efficiency,but also increasingfunctional and operationalsimilarity with theperformance benchmark(Demirkan and Delen,2013). Often the intentionor willingness of acompany behind theacquisition of IT measuresis triggered by the fact thatsome other market entitieshave already generatedprofit through acquisitionof the measure. Similarly,the acquisition of big dataanalytics has enabledcompanies such as UPSthat operate in the segmentof logistics to acquireconsiderable level ofefficiency (Davenport andDyche, 2013). As perDavenport and Dyche,(2013) application, bigdata analytics in thesupply chain managementprocess of the companyhas enabled it to save 8.5million gallons of fuel andcut its daily route by 85million miles in 2011. Asper the company record,by saving 1 mile a driverper day the organisationsaves $30 million. It hasalso planned to utilise thesystem to optimise thelevel of efficiency of its2000 aircraft flights everyday, which is supposed toreduce substantial amount6
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