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Customer Analytics As a Source of Competitive Advantage Master Thesis

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Customer Analytics As a Source of Competitive Advantage Master Thesis TU DELFT Customer analytics as a source of competitive advantage Master thesis Olena Valentynivna Bazylevska • November 2011 6 Delft University of Technology, faculty of Technology Policy & Management Progamm: Management of Technology Graduation section: Technology, Strategy & Entrepreneurship Date: November 2011 Author: O.V. Bazylevska Student number: 4052218 Graduation supervisors: chairperson: Prof. dr. Cees van Beers (TSE) first supervisor: Dr. ir. Fardad Zand (TSE) second supervisor: Dr. Ir. Jan van den Berg (ICT) External supervisor: MSc. Matisse van Meurs ii EXECUTIVE SUMMARY Deregulations, visibility of information over Internet and globalization are widely considered to be positive things, which trigger fast pace of economic development for the modern society. However, in many cases, exactly for the same reason, they destroy competitive advantage and companies start searching for opportunities to gain it. Taking into account increased information processing power and amount of collected data over the last couple of decades, companies are considering if it is worth to invest in customer analytics to gain competitive advantage. Therefore, the business world is questioning an ability of customer analytics to provide competitive advantage. Moreover, a sustainability of such an advantage is also questioned. In this thesis the resource-based view was applied to five cases to analyze how exactly customer analytics contributes to competitive advantage. The system theory was used to analyze the differences in a context where a technology is applied in order to analyze compatibility between organization resources and technology. In addition, a survey on customer analytics was studied to find a relationship between improved performance (across dimensions as: sales growth, time to market and customer retention) and analytical capability. Customer analytics can contribute to competitive advantage across three dimensions: increased bargaining power, improved effectiveness and improved efficiency of marketing capability. However, a sustainability of this advantage with analytics is doubtful. If analytics is complemented with other unique resources of the company such as scale advantage or access to unique data, then it is sustainable. Case studies suggest that each step of maturity requires more and more intangible organizational resources. So that if benefits from analytics were increasing with maturity, then the company which is able to innovate fast with analytics would sustain an advantage. However, this is not the case. The results show that sales improvement diminishes with analytics maturity over time. The decrease of perceived sales expansion might refer to the fact that there is a limit of the ability of the market and the company to grow at some point. Time to market improvement does not correlate significant with maturity (except for public services). This could be explained by a different perception to what it relates to. Profit-making organizations tend to associate time to market with products that bring profits and they tend to exclude extra services (e.g. information availability on their website). In addition, retention is improving with analytics maturity for products, public services and resource industries. The insignificance of financial services could be explained by the nature of the business and the level of regulation. Another interesting finding concerns the relationship between data driven decision making and soft driven decision making (e.g. intuition and experience). There is a significant positive correlation between data driven decision making and soft driven decision making. It rejects an existence of the scientific literature assumption that data driven decision making leads to decrease of soft driven decision making. iii The survey part of this research was limited to only three outcome variables: retention, time to market and sales improvement. The future research should also investigate the impact of maturity on other outcome variables such as cost improvement, process innovation, organization innovation, etc. Moreover, more case studies should be conducted where analytics is applied for pricing such as the airline industry. Also more research should be conducted in industries, where the company has no direct link with a consumer. iv Table of Contents Executive summary ................................................................................................................................. iii Chapter 1. Introduction ....................................................................................................................... 1 1.1 Background ............................................................................................................................... 1 1.2 Rationale behind the research ................................................................................................... 1 1.3 Research question ..................................................................................................................... 2 1.4 Scientific relevance of the research ............................................................................................ 2 1.5 Practical relevance of the research ............................................................................................ 3 1.6 Project timeline ......................................................................................................................... 3 1.7 Report outline ........................................................................................................................... 4 Chapter 2. Literature review ................................................................................................................ 6 2.1 Theoretical lens ......................................................................................................................... 6 2.1.1 Resource-based View of the firm ........................................................................................ 6 2.1.2 Systems Theory .................................................................................................................. 7 2.1.3 Systems Theory and Resource-Based View ......................................................................... 8 2.2 Mechanisms of IT contribution to competitive advantage .......................................................... 9 2.3 Barriers to erosion of competitive advantage ........................................................................... 11 2.4 Complementary resources and capabilities .............................................................................. 13 2.5 Summary ................................................................................................................................. 18 Chapter 3. Domain Overview............................................................................................................. 19 3.1 Analytics overview ................................................................................................................... 19 3.2 Role of analytics in customer relationship management .......................................................... 21 3.3 Potential areas of customer analytics use ................................................................................ 22 3.4 Potential synergy between analytics and customer-facing capabilities ..................................... 23 3.5 Summary ................................................................................................................................. 24 Chapter 4. Conceptual model and methodology ................................................................................ 25 4.1 Conceptual model .................................................................................................................... 25 4.2 Methodology of the research ................................................................................................... 25 v 4.2.1 Motivation for a mixed approach ..................................................................................... 25 4.2.2 Case study ........................................................................................................................ 26 4.3 Quantitative study ................................................................................................................... 28 4.4 Summary ................................................................................................................................. 30 Chapter 5. Case analysis .................................................................................................................... 31 5.1 Operationalization of concepts ................................................................................................ 31 5.1.1 Competitive advantage .................................................................................................... 31 5.1.2 Customer analytics capability ........................................................................................... 32 5.2 Bank A Case analysis ................................................................................................................ 33 5.2.1 Customer analytics capability ........................................................................................... 34 5.2.2 Compatibility ................................................................................................................... 35 5.2.3 Competitive advantage ...................................................................................................
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