Digital Business Notes, Appunti di Sistemi Digitali

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Digital Business Notes

MANAGEMENT ENGINEERING

INGEGNERIA GESTIONALE

Author: Mattia Longobardo

Professor: Riccardo Mangiaracina

Academic Year: 2023-

Contents

I n t r o d u c t i o n | 1 1 Introduction Can be digital innovation a threat? So, a digital innovation what is the impact of this choice on the company and today is more an opportunity or a threat? The key point is to understand how much complexity digital innovation adds to the Business Environment and how many tools give back to address this complexity generated. Digital Innovation adds complexity on multiple levels the most elementary are the supply-side and demand-side. 1.1 Complexity

1.1.1 Demand Side

Today the demand side focuses not only on the product but also on the experience and feedback. This can be achieved also thanks to digital innovations. Another aspect to consider is that DIGITAL INNOVATIONS(DI) increase customer expectations, and this can be an advantage (because increases the hype for a product or service) but also a downside (if the exceptions are not met) – An example of change in expectations thanks to digital innovation is that today we want everything as quickly as possible. Like Amazon with next-day delivery or the possibility of tracking the delivery guy. Moreover, reduces the asymmetry between the customers and the manufacturers. Nowadays users can search for information about the product and the manufacturing process and based on this fact can choose another product that respects more his/her ideas. Having more information on one hand is bad but from another point of view can achieve a competitive advantage by pushing for customisation thanks to information coming from the customer. Another important aspect to take into consideration is the possibility of reducing the product life cycle and forcing the customer to buy more of the company product. But this must be done with consciousness to see what can happen if the client perceives a too-low product life does not find it worth the buy of that product. (Software-defined life) DI open the possibility to new types of channels to interact with the customers. But must be attention because new channels are not enough to be competitive and must remember base concepts like economy of scale…

1.1.2 Supply Side

DI enable non-local sources; this can be an opportunity thanks to lower prices or better quality but at the same time led to an increase in complexity to manage. Also, the way the company manufacture its products changes, and this improves cost efficiency but brings complexity to the company. Another change brought by the DI is the bill of materials of a product with many varied materials more complex and from various parts of the world this can be a threat that if a major event happens in the supplier location this can stop the company's production. The expansion of supply options also brings a higher level of competition for the same product.

2 | D i g i t a l B u s i n e s s I n n o v a t i o n 1.2 Solution Enablers

1.2.1 Responsiveness

The collection of data from users enables the company to understand better the customer and his feelings and needs. This also evolved in bio-tracking to not only understanding what the customer says and thinks but also how a product impacts the customer at the body and health level. Artificial intelligence enables companies to analyse all the data that have been collected in precise and useful ways. And bring the company to the perfect response to each customer with a customised customer journey and go to an extreme one-to-one personalization.

1.2.2 Visibility

Maturity Model for Control Towers: from visibility to alerting to autonomous response and learning. Massive application of item-level auto-identification to increase the control and visibility of the flows all along the Supply Chain. Like control of inventory level and replenishment time and cost. Another option is to use blockchain to check the route of the object.

1.2.3 Flexibility

A new virtual warehouse that aggregates many physical warehouses enables a faster response time and a wider range. Another advantage of DI is the availability of personnel 24/7.

1.2.4 Risk Management

DI can reduce risk thanks to new digital channels where evaluate their new product. Digital-enabled combination of Supply Chain and Financial Data/Information to assess and mitigate Supply Chain Risks. Also is possible to address old problems with new solutions like the complexity of international exchange. 1.3 Critical Factor for Successful Digital Transformation A critical aspect to consider to be successful is focusing on PEOPLE. People are afraid of change and if people are used to doing things, they do not want change and many times there is the fear of losing power and money on a failed digital transformation. 2 Digital Business Innovation Today there is much confusion on what digital transformation means. Today the word “digital” is used without thinking about the meaning and only to attract people to the project. Digital should be taken from a “strategic point of view.” This view is especially important to understand all the next topics that will be addressed in the course.

4 | D i g i t a l B u s i n e s s I n n o v a t i o n  Value-relevant and transformational. Digital technologies, if properly leveraged, can have a transformational and innovative impact on value propositions. Figure 2-2: Difference between Digital Business and IT strategy 2.3 Digital Strategy Models Figure 2-3: Strategy Palette A strategy palette is a framework that helps firms evaluate three dimensions of the environment where they operate: predictability, malleability, and harshness.  PREDICTABILITY: can you forecast it?  MALLEABILITY: can you, either alone or in collaboration with others, shape it?  HARSHNESS: can you survive it?

D i g i t a l B u s i n e s s I n n o v a t i o n | 5 Classical: Be big (e.g. Mars): low unpredictability, low malleability: I can predict it, but I cannot change it. To achieve winning positions, classical leaders employ the following thought flow:  they analyse the basis of competitive advantage and the fit between their firm’s capabilities and the market and  They forecast how these will develop over time.  Then, they construct a plan to build and sustain advantaged positions, and, finally, they execute it rigorously and efficiently. Adaptive: Be fast (e.g. Tata Consultancy Services): high unpredictability, low malleability: I cannot predict it, and I cannot change it. To be successful at strategy through experimentation, adaptive firms master three essential thinking steps:  they continuously vary their approach, generating a range of strategic options to test.  They carefully select the most successful ones to scale up and exploit.  And as the environment changes, the firms rapidly iterate on this evolutionary loop to ensure that they continuously renew their advantage. Shaping: Be the orchestrator (e.g. Amazon, Alibaba): High unpredictability, high malleability: I cannot predict it, but I can change it. Firms engage other stakeholders to create a shared vision of the future at the right point in time.  They build a platform through which they can orchestrate collaboration and then evolve that platform and its associated stakeholder ecosystem by scaling it and maintaining its flexibility and diversity.  Shaping strategies are quite different from classical, adaptive, or visionary strategies - they concern ecosystems rather than individual enterprises and rely as much on collaboration as on competition. Renewal: Be viable. External circumstances are so challenging that your current way of doing business cannot be sustained. A company must first recognize and react to the deteriorating environment as early as possible.  Then, it needs to act decisively to restore its viability - economizing by refocusing the business, cutting costs, and preserving capital, while also freeing up resources to fund the next part of the renewal journey.  Finally, the firm must pivot to one of the four other approaches to strategy to ensure that it can grow and thrive again.  The renewal approach differs markedly from the other four approaches to strategy: it is usually initially defensive, it involves two distinct phases, and it is a prelude to adopting one of the other approaches to strategy. 2.4 Digital Multisided Platforms Multi-sided platforms create huge value by:  Reducing search costs  Reducing transaction costs  Reducing product development costs This type of digital strategy takes great advantage of NETWORK EFFECT:  Same-side network effects: Network effects affect the same customer group they originate from.

D i g i t a l B u s i n e s s I n n o v a t i o n | 7 platform going. That subset is called “seed,” and it is chosen wisely, to make revenues soon, and limit the risk for investors. The choice of the seed is crucial; nevertheless, the final aim is the growth of the platform’s value, in terms of customers and functions or applications.

3. Zig-zag strategy: I. In case of positive cross-side network effects, a “zig-zag strategy” could be a good option for the platform. It continuously shifts its focus from one side to the other, trying to attract critical mass in all of them. II. An example of a “zig-zag strategy” is provided by YouTube. The American video- sharing website pushed participation on both sides, fostering several strategies views and videos uploaded in an alternating way. When sides provide themselves with content that enriches the platform’s offering, or they perform interactions and/or transactions, it may be fundamental to build critical mass in more than one of them simultaneously. YouTube needed to get on board viewers and video content providers at the same time, as both groups needed each other to enjoy the company’s offering.
4. Two-step strategy: I. When the platform concentrates its efforts on attracting customers on one side, generating positive cross-side network effects and then, the efforts are focused on the side supported by those network effects, a so-called “two-step strategy” is carried out. II. An example is represented by social networks. The first step is a total focus on user attraction and registrations; consequently, advertising space is sold at high prices in case a large user base is reached. III. Another example is given by cashback-based platforms. To boost a shopping community based on referral and cashback on transactions, the company’s side should be built and made pervasive as well as well-populated. Such an appealing network of offline and online companies will hence attract a wide customer base.
5. Commitment strategy: I. Sometimes customers of one firm’s business model must make a significant investment to receive the company’s offering and to take advantage of positive cross-side network effects. In these cases, the firm should prove to these customers that there will be a large customer base on the business model from which the network effects originate. This commitment strategy is based on the capability of the firm to ensure that promised customer base, for instance by specific partnerships or a favourable pricing structure in that business model. II. An example is provided by Sony Computer Entertainment: it designed the PlayStation 4 a few years ago. When the console was launched, the firm persuaded customers to invest several hundred dollars in buying the PlayStation 4 thanks to a strong marketing campaign about future video games, that Sony would directly develop, and an exclusive partnership with Spotify. 2.6 Digital Business Models Validation: Lean Startup Approaches FALLACY OF THE PERFECT BUSINESS PLAN
6. Business Plans rarely survive first contact with customers.
7. No one besides VC and the late Soviet Union requires 5 years plans to forecast complete unknowns.
8. Start-ups are not smaller versions of large companies.

8 | D i g i t a l B u s i n e s s I n n o v a t i o n Many times, the business comes from desk research, and this is rarely a good approach so to solve this problem a new approach was developed. Lean Startup is an approach for launching businesses and products, which relies on validated learning, scientific experimentation, and iterative product releases to shorten product development cycles, measure progress, and gain valuable customer feedback. In this way, companies, especially startups, can design their products or services to meet the demands of their customer base without requiring large amounts of initial funding or expensive product launches. All startups, including those that are CVC- backed, benefit from adopting and implementing LSAs. The main principles of the Lean approach are:  ELIMINATE UNCERTAINTY: Using the Lean Startup approach, companies can create order not chaos by providing tools to test a vision continuously.  WORK SMARTER NOT HARDER: By the time that product is ready to be distributed widely, it will already have established customers.  DEVELOP AN MVP: A core component of Lean Startup methodology is the build-measure- learn feedback loop. The first step is figuring out the problem that needs to be solved and then developing a minimum viable product (MVP) to begin the process of learning as quickly as possible. It is not a prototype but a prototype.  VALIDATED LEARNING: Progress in manufacturing is measured by the production of high- quality goods. The unit of progress for Lean Startups is validated learning - a rigorous method for demonstrating progress when one is embedded in the soil of extreme uncertainty. FALSIFIABLE HYPOTHESES A lean startup will approach these assumptions with two things in mind:

1. Make these assumptions testable and tangible, not abstract.
2. Know which of your assumptions are the most uncertain and test these risky assumptions first. Definition - The Startup Way: a management system that contains within it the seeds of its evolution by providing an opportunity for every employee to become an entrepreneur. In doing so, it creates leadership opportunities and keeps the people best suited for leadership in the company, reduces the waste of both time and energy and creates a system for solving challenges with speed and flexibility, all of which lead to better financial outcomes.” (Ries, 2017, p. 539)
3. As a startupper you should follow an «integrated approach» to Business Planning:
4. Start the whole process with a clear Strategy around your business idea.
5. Design a Business Model which implements that strategy.
6. Validate your business model with the Lean Startup Approach (this is when you start operating in the market and maybe collecting pre-seed or seed financing)
7. Write a full Business Plan.

2.6.1 Summary Table

Table 2-1: Digital Business Sum Up Type of digital startup  All startups, including those that are CVC-backed, benefit from adopting and implementing LSAs. Stage of startup development  Startups are to adopt LSAs in their early stages of development, while continuously implementing them following Agile principles whenever the context turns out to be uncertain.

10 | D i g i t a l B u s i n e s s I n n o v a t i o n 2.7 Corporate Entrepreneurship Why is it so difficult to have innovation from a corporation? Figure 2-4: Change time graph The technology change is more rapid than the evolution of organisational change. Definition - Corporate entrepreneurship refers to the strategic process of engaging in entrepreneurial activities within established companies. Two dimensions under the direct control of management that consistently differentiate how companies approach corporate entrepreneurship:

1. organizational ownership. Who, if anyone, within the organization, has primary ownership for the creation of new businesses?
2. resource authority. Is there a dedicated “pot of money” allocated to corporate entrepreneurship, or are new business concepts funded in an ad hoc manner through divisional or corporate budgets or “slush funds?” Create an organisational context in which individual employees are encouraged to think and speak out- of-the-box. This requires acting on the human side of the organisation. The context should stimulate these types of behaviour in individuals:  Initiative  Risk-taking  Entrepreneurship  Brokering  Multitasking A firm should encourage these behaviours by acting on two levers:  Social support, which is concerned with providing people with the security and latitude they need to perform.  Performance management, which is concerned with stimulating people to deliver high-quality results and making them accountable for their actions.

I n t e r n e t o f T h i n g s | 11 In, the end, the organisational level and resource manager. Who decides or gives resources to the other? Figure 2-5: Resource management matrix 3 Internet of Things The base of the IoT is the smart objects, and the main characteristics of these types of objects are:

1. Self-awareness a. Identification b. Localisation c. Diagnostics
2. Interaction a. Metering b. Sensing c. Doing actions
3. Processing
4. Communication Another fundamental part of IoT is the smart networks where smart objects communicate, whose main characteristics are:
5. Open technological standards: All objects from different producers must be able to communicate effectively.
6. Accessibility of single objects: The single objects must be accessible from the network.
7. Multifunctionality

I n t e r n e t o f T h i n g s | 13

3.1.2 From Products to Services

Now from an enhanced product the company can focus on service to improve the experience of the client and can offer package to service for their products. For example, 52% of Italian smart house owners are willing to have additional services. Figure 3-3: Market Research Smart Houses Italy

3.1.3 Value from IoT Data

Data acquired from the smart objects can then be used to produce value in, the following 5 possible ways: A. Process Optimisation Exploiting IoT data to improve the internal processes of the companies. B. Next Generation product/service Using data regarding the usage of IoT objects to develop product/service improved versions. C. Customised product/service Grasp the needs of the individual, at the heart of the strategy. D. Reselling data Sale of the collected data to interested third parties, generating a new source of revenue. E. Advertising & commerce Innovative promotions and selling. But,72% of consumers are worried about the security of their data, and this is a problem. Cyber Resilience Act First UE regulation for cyber security of digital devices and products during the entire lifecycle  Cybersecurity by design  Vulnerability management  Market surveillance  Transparency of security properties of products 3.2 Industrial IoT

1. PRODUCTION: a. Machinery preparation. b. Support to operators. c. Production progress monitoring. d. Better planning/production scheduling.

14 | I n t e r n e t o f T h i n g s

2. MAINTENANCE a. Preventive/predictive
3. QUALITY CONTROL a. Better control of production/assembly activities. b. Higher support to human operators, with a reduction in errors
4. MATERIAL HANDLING a. Product movements monitoring b. Management and monitoring of handling systems (e.g. AGV)
5. JOB SAFETY a. Monitoring of the worker's position and movements within the factory b. Identification of environmental hazards and conditions
6. ENERGY MANAGEMENT a. Consumption monitoring b. Integration with other use cases (cf. Smart buildings)

3.2.1 New supply chain(s)

 NOTIFICATIONS/ SERVICES BASED ON CONDITIONS

 PAY PER USE / PAY PER PERFORMANCE

 MANUFACTURING AS A SERVICE / PLATFORM ECONOMY

Moreover, there’s also the possibility to add smart logistics with AVG, quality control and time cycle, lead time and so on. On this topic there are so many examples present on the slides such as SMART RETAILER these two can be interesting to see but they are also very similar to what we have now. !! We haven’t done the example of smart cities so there will be no questions on it in the exam. 3.3 The Strategic Value of IoT Applications Figure 3-4: Strategic Value of IoT

16 | A r t i f i c i a l I n t e l l i g e n c e 4.1 Different types of machine learning Figure 4-2: Machine Learning Sum Up Machine learning can be divided into 3 categories:

• Unsupervised learning
• Supervised learning
• Reinforcement Learning The paradigm changes from inputting the program and the data and getting the output to inputting the data and the output and getting the program. 4.2 Application fields Figure 4-3: AI Application fields

A r t i f i c i a l I n t e l l i g e n c e | 17

1. Autonomous Robots o Types: Collaborative robots, in-store assistants, humanoid robots. o Capabilities: Environmental perception, voice/text data handling, structured data processing, habits learning, and interpretation. o Applications: Driving action/reaction, manipulation, answering queries.
2. Autonomous Vehicles o Types: Delivery drones, self-driving boats, self-driving cars. o Capabilities: Environmental perception, identification, and interpretation. o Applications: Driving action/reaction.
3. Intelligent Objects o Types: Smart thermostats, intelligent cameras, smart glasses. o Capabilities: Environmental perception, voice/text data handling, structured data processing, habits learning, and interpretation. o Applications: Automated actions based on environmental data.
4. Virtual Assistants / Chatbots o Capabilities: Handling voice/text requests, comprehension, and learning. o Applications: Customer service, recruiting, internal helpdesks.
5. Recommendation Systems o Capabilities: Cross-selling, content recommendation, customized promotions. o Applications: Behavioural data analysis, habits/preferences learning, generating recommendations.
6. Language Processing o Capabilities: Handling vocal/textual data, and comprehension. o Applications: Information retrieval, document search engines, text generation, translation.
7. Image Processing o Capabilities: Surveillance, object detection, face recognition. o Applications: Video/image analysis, identification, and interpretation, generating actionable information.
8. Intelligent Data Processing o Capabilities: Predictive analysis, anomaly detection, pattern discovery. o Applications: Processing structured and unstructured data, elaboration, learning, and generating actionable insights. 4.3 Generative AI WHAT IS GENERATIVE AI? Generative Artificial Intelligence is a type of artificial intelligence that uses machine learning algorithms to generate new content. This content can be for example text, audio, images, video and computer code. WHAT’S BASED ON? Generative Artificial Intelligence is typically based on foundation models, AI models trained on huge amounts of data. These models can learn the probability distribution underlying the training data and use that distribution to generate new content that is similar in style and structure to the training data.