Why Projects Fail
eBook - ePub

Why Projects Fail

  1. 106 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Why Projects Fail

About this book

Digital disruption is accelerating. Implementing a successful digital transformation strategy requires that senior managers make trade-off decisions to reinvent a business. Equally important all decision makers must learn to ask the right questions, use data and computer support in decision making, and increase their knowledge and skills. Creating a data-centric culture and rewarding data-based decision making leads to successful digital transformation. Join the digital journey. This book is targeted at managers, especially middle-level managers who are trying to come to grips with using data-based decision making in a transforming organization. The authors explore a number of broad questions including: How can managers become data-based decision makers? How can digital transformation become part of an organiĀ­zational strategy? What new skills do managers need to implement digital transformation? How will we know an organization has been successfully transformed?

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Yes, you can access Why Projects Fail by Daniel J. Power, Ciara Heavin in PDF and/or ePUB format, as well as other popular books in Business & Gestione dell'informazione. We have over one million books available in our catalogue for you to explore.

Information

CHAPTER 1
Introduction and Overview
The year 1951 marks the beginning of the first wave of economic and social digital disruption and transformation. The first commercially Ā­available digital computer was the Ferranti Mark I, an English digital computer released in February 1951. A much more famous and commercially successful digital computer, the Universal Automatic Computer (UNIVAC) was released in March 1951.
The vacuum tube computers of 1951 have become solid state, miniaturized devices. Digital computers and specialized software replaced many thousands of bookkeepers and their ledger books. The Sears, Ā­Roebuck, and Montgomery Ward merchandise catalogs are defunct, replaced by online shopping at sites like Amazon.com. Rotary dial phones were replaced by various digital technologies over the years; communication is now dominated by the ubiquitous smart phone. Black and White over the air television displayed using cathode ray tubes (CRT) has been replaced by streaming media provided over the Internet on digital displays. Handwritten, personal letters have been largely replaced by E-mail and social media. These, and many other large-scale changes, have resulted from the initial waves of digital transformation. We have seen incredible data-Ā­enabled changes. Digital disruption is continuing, and the possibilities for change have expanded.
Many organizations must change to survive digital disruption, and managers in those organizations must create and pursue what can be called a digital transformation strategy. Some sources estimate that 90 percent of all the data in the world today has been created in the last few years. According to a number of estimates, 2.5 exabytes, equivalent to 2.5 quintillion bytes,1 of data are generated every day. Research group IDC estimates that 163 zettabytes of data will be created each year by 2025.2 Global society is in the midst of a profound and irreversible change. Data are everywhere, we are dependent on digital devices, and data provide an opportunity for innovative business models, increased efficiencies, and greater effectiveness in meeting customer needs.
Managers must at a fundamental level make better use of data and facts in decision making. Facts should guide digital transformation and digital transformation initiatives should increase the use of data and facts in every activity and process of an organization including decision Ā­making. Analyzing data is now a core decision support task in many Ā­businesses as managers try to derive value from the large volume of diverse data sources. Digitization of business activities and processes has led to an explosive growth in data. The ā€œBig Dataā€ tsunami has hence increased the need for business and data analytics. This major change has heightened the need for managers to understand the possibilities of these technologies and their application in a variety of areas including consumer financial services, insurance, manufacturing, media, retail, pharmaceuticals, health care, and government.3
As senior managers formulate information technology (IT) strategies, formulate a digital transformation vision, and assess investments, it is essential to use data-based decision making and data analytics to investigate and evaluate choices. Managers should ask if the investments will improve organizational decision making, knowledge management, yield valued digital transformation, and ultimately enhance organizational Ā­success? According to Grossman (2016), ā€œOrganizations that foster a culture of making data-based decisions will be in a stronger position to weather the changes ahead.ā€ We agree.
Digital transformation strategy involves making decisions about technology trade-offs and ideally choices are data-informed and fact-based. Data-based decision making is both a process and a culture. Some managers and organizations already value using data and facts to make decisions. Part of successful digital transformation is making systematic use of data in decision making. Data-based decision making, using data and facts to make decisions, is both a prerequisite to digital transformation and the result of a data-informed culture. Improved data-based decision making is and should be a necessary consequence of a digital transformation vision and strategy.
Global business activity is accelerating and decision-making activities and processes must be responsive to changing business needs and a high velocity decision environment. Understanding what is occurring can increase the adaptive response of managers. Awareness is a major goal of the following chapters. In general, it is not sufficient to only understand the need for new technology-supported processes, for Ā­better use of data in decision making and the possibilities for revised and innovative business models to achieve positive change. Managers must understand how to successfully implement digital transformation competitive Ā­opportunities. Managers must think digital and be committed to Ā­building data capture and data use into core activities and processes. AĀ transformation strategy without an implementation plan and action taking is wishful thinking.
Improved data-based decision making skills of middle-level managers and use of analytical tools and innovative computerized decision support can reduce the negative consequences and chaos some organizations are experiencing due to digital technologies and vast, ever-increasing, amounts of data. Data-based decision making can help channel information technology changes in positive directions that are essential to successful digital transformation and improved organization viability. Relying solely on programmed data-driven decision making using algorithms and reducing the number of decision makers in an organization is only a Ā­partial solution for digital transformation and then only in some industries. Replacing decision makers with decision automation, Ā­programmed data-driven decision making, and decision management has a serious downside for society and may actually increase digital disruption and make positive digital transformation in an organization less likely.
To cope with digital disruption, many managers should learn new knowledge and new skills, including the basics of analytics, data-based decision making, and digital transformation technologies. This short book is a starting point, a primer. The following chapters discuss decision making and digital transformation, data-based decision making, high velocity decision making and analytics, and implementing digital transformation. These chapters help managers become data-based decision makers who can assess, choose, and successfully implement digital transformation competitive opportunities. The remaining chapters emphasize the how and what questions of data-based decision making and digital transformation.
Each of the following chapters serves as a guide to help managers actively confront the challenge of implementing and using data-based decision making in a digitally transforming global business ecosystem. Our objectives are both ambitious and modest. We explore a number of broad questions: (1) How can managers become data-based decision makers? (2) How can digital transformation become part of an organizational strategy? (3) What new skills do managers need to implement digital transformation? and (4) How will we know an organization has been successfully transformed?
1http://iflscience.com/technology/how-much-data-does-the-world-generate-every-minute/
2IDC, Data Age at https://seagate.com/files/www-content/our-story/trends/files/Seagate-WP-DataAge2025-March-2017.pdf
3Grossman, R. 2016. ā€œThe industries that are Being Disrupted the most by digital.ā€ Harvard Business Review. https://hbr.org/2016/03/the-industries-that-are-being-disrupted-the-most-by-digital. March 21, 2016.
CHAPTER 2
Decision Making and Digital Transformation
Digital transformation is changing our lives, our jobs, our organizations, and our world. Each of us makes choices that impact how we use digital data and digital technology. Managers and organizations that do not keep up with digital transformation trends and successfully implement key transformation projects will likely suffer negative consequences, including loss of jobs, going out of business, or being acquired by a digital upstart or a more traditional competitor.1
Innovating with data, digital technologies, and data-based Ā­decision making is a major business opportunity that can change business Ā­models, improve customer experiences, reduce costs and increase agility. Such innovation is necessary to prosper in our changing global economic Ā­markets. Sadly, there is no simple formula or training program that can help managers become data-based decision makers. Indeed, most managers are trying to learn ā€œon the jobā€ to understand what digital transformation means for them, their team, and their organization while trying to tackle the great challenge presented by rapidly expanding organizational data. Successful digital organizational transformation requires that managers have Ā­mastered data-based decision-making skills that can help formulate, implement and manage an appropriate digital transformation strategy.
Effective data-based decision making using accurate and timely data is integral to successful digital transformation. Opportunities and obstacles created by digitalization2 and leveraging digital technologies require that managers develop sophisticated data analysis, data interpretation, and decision-making skills. The velocity at which large datasets are processed and reported requires that managers adapt to an increasingly fast paced business environment. A digital world requires decision making and leadership skills that leverage diverse data sources, data analytics know-what and know-how, and decision support capabilities that enable and support the strategic direction of an organization.
Data-based decision making is not a new idea. Decision support research began at the dawn of the digital age and the concepts of decision support and decision support systems (DSS) remain understandable and intuitively descriptive. Related terms such as high velocity decision making, data analytics, business intelligence, and big data analytics are of more recent origin and are interpreted in different ways by managers, software vendors, and consultants. Also, artificial intelligence (AI), data-based applications, and real-time analytics are accelerating the velocity of digital organizational transformation.3
Data-based decision making is a broad concept that prescribes an ongoing process of collecting and analyzing different types of data to aid in making fact-based, routine and nonroutine decisions. The use of new digital information technologies is generating m...

Table of contents

  1. Cover
  2. halftitle
  3. title
  4. copyright
  5. abstract
  6. Dedication
  7. contents
  8. Preface
  9. Ackn
  10. 01_Chapter 1
  11. 02_Chapter 2
  12. 03_Chapter 3
  13. 04_Chapter 4
  14. 05_Chapter 5
  15. 06_Chapter 6
  16. 07_Glossary
  17. 08_Bibliography
  18. 09_Index
  19. 10_Adpage