Data Driven

An Introduction to Management Consulting in the 21st Century

verfasst von: Jeremy David Curuksu

Verlag: Springer International Publishing

Buchreihe : Management for Professionals

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book is a “scientific” introduction to management consulting that covers elementary and more advanced concepts, such as strategy and client-relationship. It discusses the emerging role of information technologies in consulting activities and introduces the essential tools in data science, assuming no technical background. Drawing on extensive literature reviews with more than 200 peer reviewed articles, reports, books and surveys referenced, this book has at least four objectives: to be scientific, modern, complete and concise. An interactive version of some sections (industry snapshots, method toolbox) is freely accessible at econsultingdata.com.

Inhaltsverzeichnis

Frontmatter

1. Analysis of the Management Consulting Industry

Abstract

In this introductory chapter, the management consulting value proposition is put into context by looking at general trends and definitions across different segments, key success factors, competitive landscape and operational value chain.

Jeremy David Curuksu

2. Future of Big Data in Management Consulting

Abstract

This chapter discusses the outlooks of management consulting, the interface with data science and the disruptive impact that new information technologies will have on the management consulting industry. The first part of this chapter presents key insights from the literature. The second part engages the reader into a scenario analysis that builds on these insights and starts imagining what the future of management consulting might look like.

Jeremy David Curuksu

3. Toolbox of Consulting Methods

Abstract

This chapter introduces methodological aspects of some consulting activities. The reader is advised to complement insights gathered from this sample of methods with the set of theoretical, overall frameworks introduced in Chap. 5. Indeed, if the current chapter is about what consultants do, Chap. 5 is about how consultants decide which methods to use for a given case, team, client, and circumstance.

Jeremy David Curuksu

4. The Client-Consultant Interaction

Abstract

Before discussing client expectations (Sect. 4.2) and interactions along the different phases of a project (Sects. 4.3, 4.4, 4.5, and 4.6), it may be useful first to clarify what the nature of the relationship is between a consultant and his/her client. Different types of relationships have been articulated in the literature. As you will see, the nature of the relationship depends on the context and most particularly on the client’s perception of what represents success in a consultancy. The consultant should thus beware of these different perceptions and adapt to the situation.

Jeremy David Curuksu

5. The Structure of Consulting Cases

Abstract

A classic dilemma for consulting practitioners is how much to rely on pre-defined frameworks. When does a structure stop qualifying for one size fits all and start reinventing the wheel? How to strike a right balance?

Jeremy David Curuksu

6. Principles of Data Science: Primer

Abstract

Let us face it. Statistics and mathematics deter almost everyone except the ones who choose to specialize in it. If you kept reading and reached this far in the book you are probably now considering skipping the chapters on Data Science and moving on to the next on Strategy because, well, it sounds more exciting. Thus, let us start this chapter on statistics by a simple example that illustrates why it is worth reading and why consultants may increasingly use mathematics.

Jeremy David Curuksu

7. Principles of Data Science: Advanced

Abstract

This chapter covers advanced analytics principles and applications. Let us first back up on our objectives and progress so far. In Chap. 6, we defined the key concepts underlying the mathematical science of data analysis. The discussion was structured in two categories: descriptive and inferential statistics. In the context of a data science project, these two categories may be referred to as unsupervised and supervised modeling respectively. These two categories are ubiquitous because the objective of a data science project is always (bear with me please) to better understand some data or else to predict something. Chapter 7 thus again follows this binary structure, although some topics (e.g. computer simulation, Sect. 7.3) may be used to collect and understand data, forecast events, or both.

Jeremy David Curuksu

8. Principles of Strategy: Primer

Abstract

A competitive strategy augments a corporate organization with inherent capabilities to sustain superior performance on a long-term basis [84]. Many strategy concepts exist and will be described in this chapter, with a special focus placed on practical matters such as key challenges and “programs” that can be used as roadmaps for implementation. Popular strategies include the five forces, the value chain , the product life cycle , disruptive innovation and blue ocean, to name a few. The reader is invited to consider these models as a simple aid to thinking about reality, since none of these theoretical concepts or authors thereof ever claim to describe the reality for any one particular circumstance. They claim to facilitate discussion and creativity over a wide range of concrete business issues. Armed with such tools, the consultant may examine whether his/her client does indeed enjoy a competitive advantage, and develop a winning strategy.

Jeremy David Curuksu

9. Principles of Strategy: Advanced

Abstract

In this final chapter, on the topic of advanced strategies, a selection of topics is discussed through essays across the functional (Sect. 9.1), business (Sect. 9.2) and corporate (Sect. 9.3) strategies. As noted earlier, the merit of defining these three categories is purely pedagogic: developing a strategy should always involve holistic approaches that appreciate the many potential interactions and intricacies within and beyond the proposed set of activities.

Jeremy David Curuksu

Backmatter

Titel: Data Driven
verfasst von: Jeremy David Curuksu
Verlag: Springer International Publishing
Electronic ISBN: 978-3-319-70229-2
Print ISBN: 978-3-319-70228-5
DOI: https://doi.org/10.1007/978-3-319-70229-2