Role of Electronic Customer Relationship Management in Demand Chain Management: A Predictive Analytic Approach

Role of Electronic Customer Relationship Management in Demand Chain Management: A Predictive Analytic Approach

T. G. K. Vasista (King Saud University, Riyadh, Saudi Arabia) and A. M. AlAbdullatif (King Saud University, Riyadh, Saudi Arabia)
DOI: 10.4018/IJISSCM.2017010104
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Abstract

In 21st century, collaborative business supply chain environments are required to be proactive rather than reactive so that they can better deal with the uncertainty, growing competition, shorter cycle times, more demanding customers and pressure to cut costs. Demand chain management as a new business model requires investing in consumer insights and closer relationships in the supply chain to conduct predictive analysis of retail intelligent solutions. In this regard new kinds of methodologies are required to be discussed. However, at the execution level the limitations in terms of scalability, data integration and knowledge based decision support to providers or suppliers in terms of strategy building and in providing deductive inference capabilities are to be addressed. Therefore, it is required to describe how predictive analytics helps in constructing the knowledge base to conduct verification and validation in terms of semantic predictive analytic for the domain of demand chain management.
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Introduction

Businesses today agree that cost management is important as economy slows and sales decline. Cost management is a broad issue that cuts across all areas of the organization. The characteristics that organizations with effective strategic cost management systems considers customer-facing knowledge as one of the important elements to make the business supply chain more effective (Ellram, 2002). The costs of serving customers have been increasing and companies need to increasingly cater to micro-segments to gain competitive advantage. For this purpose, companies have to take not only the demographic and socio-economic variable into account but also the customer/consumer behavior traits that help segmentation at finer level of granulation. When companies understand customer buying behavior they can avail cost savings and increased customer loyalty (Grover, 2011).

Today’s business environment requires supply chains to be proactive rather than reactive, which demands a new model & approach that incorporates data mining predictive analytics. Today, supply chains are very complex business networks that need to be managed collaboratively and optimized globally. Additionally, global business landscape is constantly and rapidly changing. Uncertainty, growing competition, shorter cycle times, more demanding customers, and pressure to cut costs are just a few characteristics of the 21st century business environment. There is a need of evaluating performance management by relating application of processes, methods, metrics and technologies through ECRM (Electronic Customer Relationship Management) kind of technology enabled relationship between supply chain - strategy, planning, implementation and controls along with adopting business intelligence technique for evaluating performance management, which has been now becoming critical to measure, track and manage the supply chain processes (Stefanvic, 2014). With prescriptive analysis of retail intelligent solutions, it is possible to obtain true demand by which inventory management can be improved in terms of computing demand forecasting at real time (Cata, 2006). Electronic Customer Relationship Management is a technology based integrated strategic approach that seeks to maximize the value of customers by using the proprietary customer’s information efficiently. The knowledge about customers can support companies in two modes: (i) Reactive mode & (ii) Proactive mode. While Reactive mode of ECRM focuses on customer service directly, proactive mode of ECRM focuses on anticipating customers’ needs even prior to the customer contact whether for solving product issues or customer service issues (Cata, 2006).

Demand Chain Management (DCM) is a new business model aimed at value creation and value innovation in today’s market place, and combining the strengths of marketing and supply chain competencies. Demand chain design is based on a thorough market and customer understanding and has to be managed effectively to meet diversified needs of customers (Juttner, Christopher & Baker, 2007). Strategic value creation and value addition through innovation is possible when investing in consumer insights and closer relationships in the demand chain (Ericsson & Sundstrom, 2012). DCM creates strategic assets for the firm in terms of the overall value creation as it enables the firm to implement and integrate marketing and SCM (Supply Chain Management)strategies that can improve its overall financial and operating performance at the same time meet the long term strategic goals and enhance customer value (Madhani, 2013). DCM as a macro level process includes all activities that companies undertake in their quest to create and deliver needs based customer value propositions. From DCM perspective, information systems have to support tasks such as identifying for each order, whether an item is purchased via catalogue, call centre, direct sales force or the web site. In addition, customer information such as sales history and profitability needs to be available along with product availability for their specific requirements (Juttner, Christopher & Baker, 2007).

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