First and foremost, I would like to thank you for sticking with me until now. This blog post signifies the end of the MSc Digital Business Models module. Together we explored the fourth industrial revolution. I discussed changing job roles in digital economyand evaluated successful digital business models on various platforms, including colleagues’ blogs, Exeter Learning Environment (ELE) and FutureLearn’s Massive Open Online Course (MOOC). Through collaboration and discussion, I gained insight and new perspective towards current trends and themes surrounding technology, digitisation and transformation. Which brings us here: my reflection.
I found the MOOC, “Building Your Career in Tomorrow’s Workplace”, particularly enjoyable on two counts.Firstly, as a postgraduate, I will be keenly searching for work. Thus, I was aware the significance of this MOOC and its potential for future application. For example, “Building a professional digital profile” provided me with useful guidance regarding social media in a professional capacity. In fact, within this blog I have utilised some of the suggested ‘free tools’, including ‘Canva’ to showcase my comments and ‘Powtoon’ to create my video.
Secondly, I enjoyed the discussion that MOOC elicited. I was particularly surprised to see that most of my colleagues were in support of raising the UK official retirement age, so I decided to include my perspective. I also think that as the MOOC was only available for a limited timeframe, it encouraged my ‘active participation’ and pushed me to complete the course well in advance of the deadline. Ideally, my colleagues would have been able to incorporate my perspectives into their learning as I had done with theirs.
In line with colleagues that commented on my blog posts, I commented on theirs.The first assignment on changing job roles in the digital economy led me to a blog post by Let’s Get Digital, which focused on ‘the digital doctor’. I liked the benefits of AI powered health apps. However, I doubted that the NHS could feasibly afford to invest and train staff in robotic surgery.
I also joined Carrie San’s discussion of ‘retail in the digital age’. I added to the blog by discussing my own example of how technology may be used in the fashion retail industry and suggested potential future uses of big data.
Likewise, I commented on blogs that evaluated successful digital business models. As I had mitigation, I commented on blogs by The Digital Exchange and The Digital Corner in relation to the Covid-19 pandemic. I wondered whether their success would continue.
So, how has BEMM129 impacted my future? Take a look at my short video.
A digital business model leverages digital technologies in pursuit of customer value-creation. Ideally this value-creation creates a competitive advantage over competitors and benefits customers, rendering them likely to purchase the company’s offerings (Innolytics, 2020). Digital business models can help foster disruptive innovation (Altitude Inc., 2020). In the “The Innovator’s Dilemma”, Christensen (1997) describes disruptive innovation as “a specific way smaller companies can outcompete and eventually destroy their bigger rivals”. It occurs when well-established, profitable businesses are challenged by new entrants. New entrants often target ‘overlooked’ segments (e.g. less profitable consumer segments) with offerings of greater affordability or accessibility. Typically, established businesses chase high profitability – thus, extreme competitive responses to new entrants targeting separate segments of the consumer base can be deemed unnecessary. However, as you will later read, this – in the case of Blockbuster – can be a strategic disaster.
Book Video Club (2015)
When thinking of digital disruption in the movie and television industry, Netflix should come to mind. Since Netflix was founded in 1997, its business model has drastically altered. It is no longer a website-based DVD-rental postal service appealing to a select few (e.g. film buffs unconcerned with new releases and early adopters of DVD players (Christensen, Raynor and McDonald, 2015)) – it is an inexpensive, subscription based, on-demand digital streaming platform that serves a loyal customer base of over 167 million subscribers (Statista, 2020).
Netflix vs Blockbuster
Blockbuster – although serving different market segments – was Netflix’s main competitor. Yet Netflix harnessed the availability of new technologies into their business model and were able to offer more content, any-time on demand for a low price. Thus, Netflix became appealing to Blockbuster’s core customers. This and Blockbuster’s strategic blunder/inability to recognise the trajectory Netflix was on, ultimately led to their collapse. Which leads us to question, if Netflix targeted Blockbusters core customer market sooner, would Blockbuster have responded aggressively by counterattacking or even purchasing Netflix? Would the famous phase now be “Blockbuster and Chill?”
Stratability Academy (2019)Stratability Academy (2019)
Subscription Based models
Subscription-based models, when successful, leverage significant advantages as they are extremely customer-centric. Netflix benefits from a loyal customer base, predictable and continuous revenue streams and a predictable sales pipeline. However, vast infrastructure investments are required to create a smooth user experience (Fourweekmba, 2020) in efforts to retain customers. For instance, Netflix customises viewing suggestions dependent upon unique personal interests and are committed to creating unique content, spending billions annually. To avoid liquidation, it is vital customer acquisition costs are lower than customer lifetime value.
PwC (2019)
AI, Algorithm and Big Data
Customer retention is vital to the success of Netflix; thus usability, ease and access are paramount. This is where the power of AI comes in. In 2006, Netflix offered an impressive $1 million for a group able to produce an algorithm that accurately predicted customer film satisfaction via previous ratings. This algorithm, although changing and updating regularly, saves Netflix approximately $1 billion annually in customer retention (Burstein, 2018). This is understandable when looking at the statistics – Netflix customers are bombarded with viewing options, ciphering through a homepage of approximately 3000 titles. After reviewing around 10 – 20 titles, the average Netflix viewer’s interest diminishes in less than 90 seconds (Burstein, 2018). Therefore, the recommendation system is central to Netflix digital business model, influencing around 75% of streamed content (Bulygo, 2018).
Big data also serves as an important mechanism for success. According to Burstein (2018), Netflix collects and analyses behavioural data to generate a better experience and create more value for the user in the following ways:
Ratings
Title searches
Date of viewing
Device used for viewing
Whether the type of the viewing differ depending on device
When a viewing is paused
Whether sections of viewings are re-watched
Whether the credits get skipped
King (2016) states “Big data is not about the data. It is about the analytics”. These analytics reveal consumer insights and Netflix can act accordingly to improve. For example, Netflix have used big data to create ‘Netflix Originals’ and find “smash-hit series”, such as House of Cards (Burstein, 2018). Analytics also allow for a video similarity algorithm, which suggests videos customers may enjoy based on previous viewings and personalised video rankers which uniquely orders the entire collection of available titles for each member.
Ippolito (2019)
Streaming Service Subscription
We are living in a subscription economy. Globally, streaming services have achieved unparalleled success. In the US alone, subscription service expenditure increased from $215 billion to $420 billion in 15 years (Zuora, 2020). Netflix, who have benefited from first mover advantage for several years, no longer remain unchallenged. A greater number of streaming services have become available. Major studios who initially sold Netflix their content, are progressively withdrawing it as they establish their own streaming service. In 2020, Disney + and Apple TV+ was launched in various countries and is set to be followed by various others including HBO Max and NBCUniversal Peacock. Consequently, consumers will have to spend significantly more than £5.99 monthly to access the same content originally provided on Netflix, and therefore may have to narrow down which services to subscribe to. So, is Netflix’s reign as market leader about to end? Will Netflix, the great innovative disruptor, get disrupted itself?
Book Video Club. (2015, March 13). “The Innovator’s Dilemma” by Clayton Christensen – VIDEO BOOK SUMMARY [Video file]. Retrieved from https://www.youtube.com/watch?v=VPQTeIWugJ4
King, G. (2016, May 21). Gary King: Big data is not actually about the data. The Washington Post. Retrieved from https://www.washingtonpost.com/
PwC. (2019). Video streaming shakeup Survey of consumer attitudes and preferences. Retrieved March 22, 2020 from https://www.pwc.com/us/en/services/consulting/library/consumer-intelligence-series/consumer-video-streaming-behavior.html
Statista. (2020). Number of Netflix paying streaming subscribers worldwide from 3rd quarter 2011 to 4th quarter 2019. Retrieved March 22, 2020, from https://www.statista.com/statistics/250934/quarterly-number-of-netflix-streaming-subscribers-worldwide/
Simply, the digital economy is economic activity that is a product of online hyperconnectivity. That is, the interconnectedness of the internet, internet of things (IoT), mobile technology, machines, organisations and people (Deloitte, 2019). The digital economy is transformational in nature – it has and will continue to undermine conventional conceptions regarding business structure and the way consumers acquire information, goods and services (Deloitte, 2019).
The digital economy and emergence of new technologies affects us all in various circumstances that we tend to keenly adopt and then disregard as the ‘norm’. It is primarily when discussions surrounding how artificial intelligence (AI) will impact us, namely the loss of jobs to robots or the concept of neo-slavery, we begin to have doubts. Although some would assume the loss of jobs to robots is an unprecedented notion, I would argue that we must consider the position society is already in and the direction in which we are moving. Let us consider the way digital disruption can and has influenced the role of a waiter – a job largely considered as menial, requiring little technological skill. A job most people have experience with, either by means of employment or by dining out.
I am going to begin with a much-loved example – JD Wetherspoons. Although not a typical restaurant experience in which customers receive full table service, JD Wetherspoons have been at the forefront of innovative service. In 2017, the “Order & Pay” mobile app was launched for customers. An extremely accessible customer-based digital adaptation to JD Wetherspoons business model helped optimise the ordering process. The app allows customers to order what they like, whenever they like – no queues necessary! This is particularly useful as long queues deter around 79% of consumers from ordering food or drink (Mintel, 2017). Hence speed of service remains a prominent issue. As we experience technological and digital developments in our everyday life, we have grown accustomed to certain standard and speed of our online ventures. Perhaps this means our patience is wearing thin, but JD Wetherspoons’ attempt to combat slow service digitally should be considered highly successful. As well as increasing waiter productivity, the app has also managed to increase sales non-conventionally. A trend emerged in which JD Wetherspoons patrons use social media to promote which restaurant branch they are in, as well as their table number in attempt to receive free drinks from others (Borland, 2019). Other than free drinks, people are commonly gifted with ‘comedic’ items they would not normally purchase, like peas, yet this all adds to the increased sales and revenue. Which as we all know, is the ultimate aim of business.
Image 1
Future directions restaurants may take is the possibility of pre-ordering your meal via an app. Incorporating IoT further into restaurant business models may become an economical ‘perishable inventory’ strategy. Restaurant managers may be able to predict stock requirements more accurately, reducing the amount of waste and obsolete inventory, whilst boosting net income. Meanwhile, waiters will be less likely to disappoint customers by advising that a specific meal is out of stock, whilst delivering speedier service.
From a business perspective, use of this technology can greatly enhance human performance. But does this mean that those working in the hospitality industry are safe from technological advancement or AI replacement? I would argue that, with a more efficient waiting service in place, restaurant owners are likely to consider employing less staff. Clearly, this would result in greater net profit. But is this a catch 22? Would this result in slower, poorer service? Or would service quality remain stagnant, getting no better or no worse than it is today?
I will leave you with this – robot waiters. In 2018 a pop-up café in Tokyo trialled a team of remote-controlled OriHime-D robots as waiting staff (Fleming, 2018). These robots were controlled through tablets by disabled people who received video and audio of the café. The project was created in effort to use technology to combat social isolation. But importantly, it gave disabled people a chance to work. Use of robot waiters could also be targeted towards the ageing population. If ‘retirement age’ legislation continues to increase, and the ONS is correct in assuming that those born in 2020 will be economically active into their 80s, then any job role undertaken would have to be suitable from a health and safety context. Unfortunately, as we age our body declines physiologically, thus will our efficiency at being “economically active”. Therefore, technology such as robot waiters could provide an alternative, but efficient style of working for the elderly.
Job loss by AI is usually polarised negatively: it will hit unskilled workers and the poor the hardest; jobs are hard enough to acquire as it is. But could job loss to robots actually provide an opportunity to help the disadvantaged? Could AI create job positions for people usually not given the chance? Could this become the norm? Or will our desire for “the human touch” prevail. Creating an inviting atmosphere is fundamental for restaurant success and is largely down to the waiters as they try to connect with their customers. Having soft skills, such as the ability to show empathy, adaptability and understanding to all customers is something that may need a human face.
Welcome to my blog. I’ll be focusing on all things digital – well in a business context!
I’m Hannah, and I’m currently studying for an MSc in Marketing at the University of Exeter. As part of this degree, I’ll be documenting my educational journey through the world of digital business. Here’s hoping that my journey will inspire yours – or at least help you gain further insight into the digital developments, challenges and opportunities businesses face in the digital age.
But first, here’s a little bit about myself: I was born and raised in the South East of England. I first came to Exeter in 2016 to embark upon a BSc in Exercise and Sport Sciences. After completing my undergraduate degree, I decided to alter my academic pathway and let me tell you – I have not looked back. Marketing is a fascinating subject that is comprised of a broad range of disciplines. As a hopeful future Marketer, the need to understand the ever-changing digital and technological landscape is paramount. As such, I was keen to study BEMM129 – Digital Business Models.
The Digital Hunt 