Understanding the digital in business (9788245050943) by Fagbokforlaget

the digital in business Understanding

FROM BIG DATA TO SMALL BITS

First Edition 2024 / Printing 1 2024

ISBN: 978-82-450-5094-3

Graphic production: John Grieg, Bergen

Cover design created with Midjourney (prompt used: a book cover for a book about digital business with a retro robot wearing a fedora hat and holding a briefcase)

Typeset by John Grieg, Bergen

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FORORD

Dear reader,

In today’s world, technology is no longer just a tool but the very fabric that drives business innovation, growth, and competitiveness. The digital revolution has transformed industries, reshaped business models, and redefined the way organizations engage with customers, employees, and markets. As businesses navigate this fast-evolving landscape, the need to understand, leverage, and stay ahead of digital trends is paramount.

Understanding The Digital In Business is designed to guide readers through the complexities of the digital transformation. Whether you are a seasoned executive, an entrepreneur, a manager, or someone exploring the intersection of technology and business, this book aims to provide clarity and actionable insights on how to harness digital tools, strategies, and mindsets to drive success in today’s competitive environment.

The digital era isn’t just about adopting new technologies — it’s about creating value, building agility, and fostering innovation across every level of an organization. Throughout this book, you will explore how leading companies have adapted, evolved, and thrived in a world shaped by digital disruption. From e-commerce to artificial intelligence, from data analytics to digital marketing, each chapter delves into key areas where digitalization has redefined the business landscape.

This book not only examines the opportunities and challenges presented by digital transformation but also provides a framework for making informed decisions that will future-proof your business. You will find practical examples, case studies, and expert perspectives to help you align your digital strategy with your business goals.

The future belongs to those who are willing to embrace the digital in business, not just as a means of survival but as a pathway to growth and innovation. I hope that Understanding The Digital In Business serves as both a guide and a source of inspiration as you navigate your own digital journey.

Sincerely yours,

Tarjei Alvær Heggernes

Hi! Did the preface on the previous page seem at little “off”? The author didn’t write the preface, the generative AI service ChatGPT did. In the foreword to the previous (3rd, Norwegian) edition, which was published in 2020, AI was mentioned as the biggest change in the digital landscape since the previous edition (2nd edition). By now, most people are familiar with AI through services like ChatGPT and services like Dall-E and Midjourney, creating text and images based on “prompts”. Even in my rather conservative profession, where we try to physically gather students in an auditorium to share our infinite knowledge, the threat of being replaced by machines now feels real. Students let AI answer exam questions; lecturers use AI to create exam papers and examiner guidance. There are also examples of AI grading and providing grading justification.

Full disclosure: The book has been translated from Norwegian to English with the help of AI-based tools DeepL and Grammarly. I still spent hours checking that everything turned out as accurately, but the AI-tools probably saved me days or even weeks of manual translation.

Since the publication of the third edition, I’ve had the pleasure of spending hundreds of hours with nearly a thousand students on teaching and discussing how to create business value with digital technologies. Undergraduate students often bring a fresh perspective to the material, which I appreciate, and students in continuing education courses have given me a unique insight into how the Norwegian business community handles issues within the rather broad concept of digitalization. My first big thank you goes to this group; they have given me even more insight into the subject. In addition, several professionals at universities and colleges across the country have had the confidence to use the book as a curriculum in courses where they teach. I really appreciate this. Feedback and input from these professionals have been important in the preparation of this fourth edition.

When it comes to the “real world”, I would like to thank Brede Lærum from Equinor, Nicolai Høge from FINN.no, Stein Kjølberg from Jotun Paints Inc., Paul Skeie from Enivy, and Paal Runar Larsen, Joakim Svekum and Tord Søfteland from the Terravera Foundation, who have all contributed information to cases used in the book.

From academia, I have greatly enjoyed conversations and collaboration with Jon Iden and Karen Osmundsen from NHH. From HVL, I would like to thank Carsten Helgesen and Terje Kristensen – who have both contributed to the chapter on artificial intelligence – as well as Ole Jakob Bergfjord and Henry Bjånesø for their motivation. From Vestlandsforskning, I would like to thank Svein Ølnes for both good discussions and for reading through the chapter on blockchains. Among my colleagues at BI, I would like to highlight Cecilie Staude – who has really spread the good word about

the book both internally and externally – Ragnvald Sannes for good cooperation and good professional conversations, ERP legend Bo Hjort Christensen and Odd Rydland, the latter has contributed material on PKI in chapter 12. Finally, I would like to thank Arne Selvik, from whom I have learned a lot through working on the book Den Digitale Styreverden (The Digital World Of The Board Of Directors).

I would also like to pay tribute to my former editor, Knut Ebeltoft, for starting this book adventure with me, and its current editor, Andreas Nybø, for taking the work forward with the last two editions.

The biggest thank you goes to my patient and inspiring family: Trym, Aurora and Christina.

Bergen, September 2024

Tarjei Alvær Heggernes

ta BLE OF CON t EN t S

PaRt IV BUSINESS SYStEMS

t HE DIGI ta L t R a NSFORM at ION

In this first part of the book, we will look at how IT and digitalization have fought their way from being a field of study for those with a special interest, via a necessary evil with a tarnished reputation, to being on the agenda in the boardroom. We’re going to look at the skills needed to deal with this development, a skill we call understanding the digital in business. The rest of the book will provide you with this understanding.

But how did it come about that we now need digital business understanding? Below is an overview of events over the past 30+ years to illustrate the interplay between business and digital.

The 1980s: Big machines, mobile phones and Commodore1

Computers slowly but surely became part of some companies’ business operations during the ‘60s, ‘70s and ‘80s (in 1985, the author had a workweek internship at the IT department of an insurance company, NKP). But, in 1987, Solow warned us that productivity in American businesses had not increased at the same rate as investment in IT, which became known as the productivity paradox (Solow, 1987).

1 Image created by Midjourney with the following prompt: illustration for boring textbook of mainframe computers, cell phones and commodore computer, black and white.

The 1990s: PCs, the World Wide Web and pagers2

In 1993, Henderson and Venkatraman proposed a solution to the productivity paradox: They argued that the strategy for using IT was not aligned with the business strategy and that a better alignment would help companies realize the benefits of their IT investments (Henderson & Venkatraman, 1993). In 1997, Markus and Benjamin warned that IT is not a magical solution to a company’s business problems in itself but rather a tool that the company had to actively use to solve the problems (Markus & Benjamin, 1997). At the end of the 1990s, the internet became ubiquitous and there were high hopes of enormous value creation for companies that invested in online business operations. However, success failed to materialize, and bankruptcies lined up, leading to distrust of IT as a business tool.

Image created by Midjourney with the following prompt: illustration for boring textbook of personal computers, pagers and the world wide web, black and white.

The 00s: The dot.com crash, smartphones and data analytics.3

“IT doesn’t matter” claimed Carr in his article from 2003. He believed that IT could only add value to businesses in special cases and should be treated as an infrastructure on a par with electricity. He advised companies to buy standard IT services and software from the cheapest supplier (Carr, 2003).

At the same time, a revolution in consumers’ use and understanding of technology and the Internet began: the first social network, Facebook, saw the light of day in 2004. It wasn’t just the interface with the outside world that IT was changing at this time; the same year researchers at Google described how to organize large amounts of data in the Hadoop file system and access them with MapReduce to better analyse them. This was an important part of data analysis as we know it today, and this new understanding also laid the foundation for later breakthroughs in AI (Dean & Ghemawat, 2004).

Around 2008, the importance of social networks became apparent. Clay Shirky highlighted social networks as a glue that created cohesion between people around the world with enormous potential (Shirky, 2008). And when the iPhone was launched in 2007, the world would never be the same.

3 Image created by Midjourney with the following prompt: illustration for boring textbook of smartphones, the dotcom crash and data analytics, black and white.

Most businesses in the world woke up to the social media revolution in a hurry, and Li and Bernoff advised businesses on how to ride the wave of data generated by social media users (Li & Bernoff, 2011). This wave is still being ridden well by some of the largest businesses in the world.

Behind the scenes, work continued finding new uses for data. In 2012 we saw deep learning used in voice recognition – Hinton et al. deep learning for voice recognition (Hinton et al., 2012). This was a breakthrough for machine learning, a form of AI that we will spend some time discussing later in the book.

When the first edition of this book was published in 2013, it was largely based on the idea of aligning IT strategy with business strategy. In the same year, Management Information Systems Quarterly published a special issue on Digital Business Strategy, which emphasized technology as a driver of business transformation, as opposed to the previously ascribed role of aligning with business strategy (Bharadwaj, El Sawy, Pavlou and Venkatraman, 2013). Hopefully, at some point, digitalization will become so integrated into business strategy that a digital strategy will become redundant. We’re not quite there yet.

10s: Social media, platforms and a new boom for AI4

Image created by Midjourney with the following prompt: illustration for boring textbook of social media, digital platforms and artificial intelligence, black and white.

In 2014, the book The Second Machine Age was published (Brynjolfsson & McAfee, 2014). It looked at which tasks are now ripe for machines to take over and which are best performed by humans. This is a fast-moving picture, where machines can take over increasingly advanced cognitive tasks.

We see that many technologies and trends that have emerged in recent years are now coming together and putting us in the midst of the fourth, and even into the fifth industrial revolution, where digitalization is the key to survival and development. In 2017, the sequel to The Second Machine Age: Machine, Platform, Crowd (McAfee & Brynjolfsson, 2017), discussed the potential of the interaction between people, artificial intelligence and digital platforms. In 2018, the book Prediction Machines (Agrawal et al., 2018) stated that artificial intelligence has made predictions of all kinds, both cheaper and more accessible and that it is a driver for exploring new business opportunities and streamlining existing processes.

But it’s not all joy in technological development. Many are critical, including the author of The Age of Surveillance Capitalism (Zuboff, 2019), who believes that the collection and commercial exploitation of personal data, especially by Google and Facebook, is a major threat to humanity.

The roaring twenties, or Rise of the Machines?5

Artificial intelligence came close to most people when ChatGPT 3.5 was launched in November 2022. Many believe it’s a big step forward for AI, but is it a step back for humans? It remains to be seen whether all jobs (and the world?) will be taken over by machines this time. However, the fear of losing jobs to machines has long been present. In 1589, Queen Elizabeth the First of England denied William Lee a patent for a knitting machine he developed on these grounds:

Thou aimest high, Master Lee. Consider what the invention could do to my poor subjects. It would assuredly bring them ruin by depriving them of employment, thus making them beggars. (Robinson & Acemoglu, 2012)

Technologies have always created new jobs. Your job will not be replaced by AI, but by someone who knows how to use AI. In a way, this book is designed to make you able to keep your job by being able to see how it can be improved by using digital technology.

5 Image created by Midjourney with the following prompt: illustration for boring textbook of the roaring twenties and artificial intelligence takeover, black and white.

SPRE a DING INFORM at ION – FROM RHYME tO R a M

A few thousand years ago, in northern India, there lived a sage called Valmiki. He was highly respected and had settled on a riverbank with several disciples. One day, Valmiki went to the river to take a bath. The water was clear and fresh, and two cranes were mating in a tree above the river. Valmiki thought this was a beautiful sight. The idyll was suddenly broken by a hunter shooting one of the birds with a bow and arrow. The other bird screamed out in pain and died of grief. Valmiki was so upset by the hunter’s action that he exclaimed in Sanskrit:

mā niṣāda pratiṣṭhāṁ tvamagamaḥ śāśvatīḥ samāḥ yat krauñcamithunādekam avadhīḥ kāmamohitam

Translated into English:

You will find no rest for the long years of Eternity

For you killed a bird in love and unsuspecting

For a long time, he thought about this verse, or śloka, as it is called in Sanskrit. With the blessing of the Hindu god Brahma, he wrote the epic poem “Ramayana” of 24,000 verses in the same format as the śloka. He is considered by many to be the first poet.

This epic poem revolutionized the spreading of information. At the time it was written, it was not common for everyone to be able to read and write, nor was there any technology that could reproduce the poem. The śloka structure made it easier to

memorize and retell, much easier than a regular story. The poem spread from Valmiki to his disciples, between friends and through generations.

In addition to making information easier to transfer information between people, the verses had another element to in common with modern information management: categorization. Many ślokas were created to preserve and share information on various topics, ranging from astrology, mathematics, agriculture, botany, etc., to spiritualism and religion. A collection of ślokas dealing with the same topic is called a sutra. Just like hashtags, sutras were used on related ślokas: #kamasutra.

Today, much of the information we use is digitized, and represented by data that can be found everywhere. Much of a working day is spent with a computer as the main work tool. You receive notifications of new emails, updated stock prices, shipments, etc. You assess customers, partners, competitors, and potential employees and search the Internet for trends affecting operations. You look for information to support decisions.

All transactions and interactions a company makes are documented in digital form and stored in large databases, and analyses are performed by retrieving the digital information from the databases. The analyses should lead to decisions that generate revenue or save costs for the company and should often also give the company a competitive advantage, which means that customers will choose products from our company instead of products from our competitors.

In recent years, software and data communication has become deeply integrated into business operations: Many people buy and sell their goods online, and through social media, we can listen to what customers think of us, build relationships with customers, solve problems for them and try to create loyalty, so we can gain an edge here too.

To compete in a competitive arena, knowledge is important. For example, a rally driver needs to know much more about how a car works than a normal driver. A top athlete needs to know much more about how their body works than an exerciser. The business world is a competitive arena, and it is therefore important to be familiar with the machinery that is our own business.

A computer in itself is worthless to a business. It is only valuable if it can support and improve the processes that create value for the company and ultimately create value for its customers and owners. If a computer program such as a chatbot can provide a quick response to a customer enquiry, this is of value to the customer; if the customer can find an answer quickly on the Internet, this may be of even greater value to the customer, while saving the company time and money on customer care. In the latter case, we depend on the company’s ability to provide the answer the customer is looking for based on data stored in the company’s systems and that

this answer can be made available to the customer online. In addition, it is also a prerequisite that the customer is connected to the Internet with a device that can read this information.

Large parts of business operations have been digitized. To do business today, you need to understand and be able to utilize this. This requires what we can call digital business understanding.

The purpose of this book can be summarized as follows:

• It will provide insight into the digital business world.

• It aims to help you understand that data is created everywhere, inside and outside the company’s walls, and that much of this data can be business relevant. The book is based on businesses, but most of the discussions are relevant to non-commercial organizations.

• It will explain how an organization creates value and how digital technologies can support these value-creating activities.

• It will present various digital technologies representing both an opportunity and a threat for existing and potential new businesses.

• It will familiarize students with business systems and link them to business functions.

• It will explain how the company’s business system collects transaction data.

• It will illustrate the challenges of extracting data from operations and present different data analysis methods.

• It is designed to address the company’s security challenges in connection with the use of IT-based business systems.

• It also addresses the negative effects that digital can have on businesses, society, and individuals.

Digital business understanding

We might as well start here with the book’s definition of the term:

Digital business understanding is understanding and assessing the role of ICT in creating value, developing, and utilizing the potential, and innovating within company, and making it possible for the company to function in the market and in society.

Let’s briefly examine the different elements included in the concept. Business acumen is the ability to focus on what creates value for an organization, including helping to develop the business and translating knowledge into new ideas and opportunities. (Undervisningsministeriet, 2012).

A strategy is usually put in place to ensure value creation in an organization. Digital technologies have become central to organizations’ strategy work, so we discuss strategy at the beginning of this book.

For the company to create value, it must deliver products/services that have a higher value for the customer, measured in money, than the resources it uses to deliver the product/service. The strategy is broken down into more concrete goals, and the goals are broken down into concrete measures. In this book, we focus on measures that make use of digital technologies: digitalization measures.

In this book, digital refers to a specific type of technology. Technology is the study of techniques and the associated material products within a specific area (SNL).6 This book focuses on ICT (information and communication technology), and within this area, we will talk about both software and hardware. This book uses digital technologies as a collective term for this type of software and hardware.

Just as we have business and business understanding, we have technology and technology understanding. In English, the term “technical literacy” is often used. The OECD and Statistics Canada (OECD, 2000) define “literacy” as using written and printed information to function in society, to achieve one’s goals, and to develop one’s knowledge and potential. Another definition (ITEA, 2000) states that technological literacy is the ability to use, manage, evaluate, and understand technology.

This book aims to give readers some of this understanding: a bit about how an application is built, how a database can be structured to either record or analyze data, conceptual clarifications for big data and social media, what types of business systems exist in a company and for what these are used. If you don’t acquire the same expertise that professional IT people have, you will at least be better positioned to communicate professionally with them.

It is also a goal that you should recognize the opportunities technology represents for business operations. Finally, we can add a definition of computer literacy: If you can tell a computer how to perform tasks you want it to perform, you are computer literate (Luhrmann, 1982, cited in McMillan, 1996).

We summarize this section by combining the above concepts into our definition of digital business understanding:

Business

Value creation

Development

Inno vation

Strategy

Goala

Processes

Gains

Figure 1.1: Digital business understanding.

Technology

Devices for capturing, process and present data (hardware)

Business systems (so ware)

Application architecture

User interface

Business logic

Databases

Business understanding and data understanding: CRISP-DM

A recurring theme in this book is utilizing the value of data. A major application area is data as the basis for machine learning and artificial intelligence, which we will return to in Chapter 7, and data mining, which we will discuss in Chapter 19. In such processes, combining an understanding of technology with an understanding of business is important. In 1997, a consortium of data mining users and suppliers proposed an industry and supplier-independent model to ensure the link between business objectives and data mining. The CRISP-DM model (Cross Industry Standard Process for Data Mining) was published in 2000 (Shearer, 2000) and illustrated in the figure below.

Figure 1.2: CRISP-DM model.

The different phases of the model are briefly described below:

• Business understanding: One goal of using technology is to solve actual problems for a business. In this phase, the focus is on the business problems to be solved and on turning the solution of the business problems into a data mining task. If we look at the lending process in a bank as a starting point, the problem may be knowing which customers to grant loans to, and which customers should not be granted loans, based on their loan applications. If customers are assessed too strictly, the bank may lose customers that could have represented income. If the assessment is not strict enough, loan defaults can represent costs.

• Data understanding: In this phase, you familiarize yourself with data, look for problems with the data quality, and hypothesize what hidden information exists in the data. Using the example of loans, you would start by getting an overview of

all loan contracts and look for factors that customers who default on their loans have in common. This phase is – or should be – close to business understanding. In this phase, the business works closely with the technology to suggest what data to use. In the case study in Chapter 15, this phase is called the data discovery phase

• Prepare data: In this phase, the relevant data from the data base is, among other things, sorted, corrected for errors, and converted into a common format. In this way, the data is prepared for modelling. This phase is more of a technology job, but the business can also contribute in an advisory capacity in this phase.

• Modelling: The models that will solve the business problem are created in this phase. Algorithms and methods are used to create models based on data. In this case, it may be a model that can assess the probability of repaying a loan. A business user will not normally be part of the modelling process but may know about the different methods used for different problems. The modelling will also reveal whether the data needs to be better prepared.

• Evaluation: The model is tested and evaluated against the business objectives. In this example, you could, for example, test the application on loans that have defaulted to see if the model can predict the default. In this phase, it is also decided whether the model should be used, or if further work needs to be done.

• Implementation: The model is now ready for use. In this case, it contributes to, for example, automatic or manual assessment of loan applications. After implementation, the model’s value will also be assessed about whether the loan volume goes up, the default rate goes down, or both. In addition, the model is often adjusted periodically to adapt to changes in the customer base or other working conditions.

How to use the book

The model below shows the main topics covered in this book. There is no specific order to the topics, however, knowledge of all the topics is needed, in the author’s opinion, in order to achieve digital business understanding.

Data

In the hub of the model, we find data, the lifeblood of value creation and the enabler of all digital technologies. Chapter 2 looks at all kinds of data, from how it is stored in bits and bytes to big data and has examples of how big data is utilized in both digital twins and smart cities.

Understanding The Digital In Business provides the reader with a basic understanding of how digitalization interferes with business operations. Since the first edition was published in Norwegian in 2013, the book has been read by many thousands of students and other readers.

This first English edition of the book corresponds with the fourth Norwegian edition. It has been significantly revised and updated over the years, both to incorporate recent technological developments and to make it work even better as a textbook.

A basic premise of the book is the realization that everything starts with data. An early chapter on understanding data lays the foundation for the rest of the book and there is extensive coverage of generative artificial intelligence (AI). New concepts, such as low/no code, NFT, proof-of-stake, etc., are explained and discussed.

The book is suitable for economics and social science studies, engineering and technology studies and for practitioners who want a better understanding of how digitalization intervenes in everyday work and how it supports a company’s value creation.

ISBN 978-82-450-5094-3