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- Herausgeber: Youcanprint
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
- Veröffentlichungsjahr: 2021
Explosion of the economic relevance of data is related to: first, technological progress that has drastically reduced the costs of collecting and storing data; second, the advances in analytic techniques that have allowed for more advanced processing to extract greater value from available data. So, more value is extracted from exhausted data. Information generated for one purpose can and should be reused for another one, which means that data moves from primary to secondary uses . data are more valuable over time. Data's true value is like an iceberg floating in the ocean: only a tiny part is visible, while much of it is hidden. Innovative companies that understand this, can extract that hidden value and reap huge benefits. Data's worth is its unlimited potential for reuse: the option value. What really matter for the value of data is its use and not its possession. Data science can have incredible benefits for your business. With data science and predictive analytics, in particular, you can predict useful metrics and trends for your business. Such an approach can help you improve your ability to serve your customers or otherwise compete in the market.
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1
DATA ANALYTICS AND KNOWLEDGE MANAGEMENT
The hidden potential of Big Data for your Business Success.
Learn Data Science with R and the Blockchain.
By International Management School
Sommario
1. INFORMATION SYSTEM AND KNOWLEDGE MANAGEMENT
1.1 SOCIO TECHNICAL SYSTEM
1.2 CHANGE MANAGEMENT
2. BIG DATA
2.1 CLOUDS, BIG DATA, AND SMART ASSETS: TEN TECH-ENABLED BUSINESS TRENDS TO WATCH
2.2. BIG DATA IMPLICATIONS
3. DATA ANALYSIS AND DATA SCIENCE
3.1 WHAT IS R?
3.2 DATA ANALYSIS AND FORECASTING WITH R
4. HUMAN COMPUTATION
4.1 CROWDSOURCING
5. BLOCKCHAIN AND DATA SCIENCE
5.1 BLOCKCHAIN CRYPTOGRAPHY
5.1 BLOCKCHAIN AND BIG DATA
5.2 BLOCKCHAINS VERSUS TRADITIONAL DATABASES
6. STATISTICS AND DATA SCIENCE
6.1 STATISTICAL ANALYSIS
1. INFORMATION SYSTEM AND KNOWLEDGE MANAGEMENT
Knowledge management (KM) is the process of creating, sharing, using and managing the knowledge and information of an organisation. It refers to a multidisciplinary approach to achieving organisational objectives by making the best use of knowledge.
Knowledge management efforts typically focus on organisational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration and continuous improvement of the organisation. These efforts overlap with organisational learning and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and on encouraging the sharing of knowledge.
KM is an enabler of organisational learning.
Information systems (IS) are formal, sociotechnical, organizational systems designed to collect, process, store, and distribute information. In a sociotechnical perspective, information systems are composed by four components: task, people, structure (or roles), and technology (that fits with the other 3 elements).
Any specific information system aims to support operations, management and decision-making. An information system is the information and communication technology (ICT) that an organization uses, and also the way in which people interact with this technology in support of business processes.
Types of information systems:
The "classic" view of Information systems found in textbooksin the 1980s was a pyramid of systems that reflected the hierarchy of the organization, usually transaction processing systems at the bottom of the pyramid, followed by management information systems, decision support systems, and ending with executive information systems at the top.
The Anthony triangle is a Convenient way to categorize and understand the purpose of different information systems in organization. It is a piramid that represents the strategy translated in simple goal.
information systems can be classified by the nature of activities they support.
Decisions are structured, recurring and can often be automated using IS.
IS used to optimize processes, understand causes of performance problems.
Decisions are semi-structured, moderately complex, time horizon of few days to few months.
These are tactical decisions from management, in which occurs the aggregation of data from different part of the firm is important! They pass info from the operational level to the top management.
they work as “translator”, their tactical is key role to translate between operational and top management, they know both languages and have tools to elaborate data.
IS helps in performance analytics (dashboard), predictive analysis, KPI.
Decisions: unstructured long-term strategic issues, complex and non-routine problems with long-term ramification. Strategic decisions are not shared with all the company. top management utilize the internal info but also the external ones.
IS used to obtain summary of trends and projections, provide KPIs, Internet information extraction.
There are some New laws to classify information systems and knowledge and it’s important to know them because ignoring these postulates bring to misunderstanding and errors in our society and in policies associated.
MOORE’S LAW:
Taken from an empirical observation by the cofounder of Intel.
“The performance of the processors, and the number of transistors available for it, is doubling every 18 months”
The limits of the first law of Moore would be only in reaching the physical limits imposed for the reduction of the size of the transistors, and therefore the scale of integration. This integration capacity and the processing make possible the use of ICT applications increasingly complex, at costs equal with the doubling of computing power.
Moore's Law refers to Moore's perception that the number of transistors on a microchip doubles every two years, though the cost of computers is halved. Moore's Law states that we can expect the speed and capability of our computers to increase every couple of years, and we will pay less for them.
Laws of Sarnoff, MetCalfe and Reed:
laws that define the value of a network respect to the number of participants/connections.
Sarnoff’s law: related to TV and radio.
“The value of a broadcasting network is directly proportional to the number of users.”
Value network increases when more people are connected.
Metcalfe’s law: “The value of a communication system grows with the square of the number of people connected”
Another formulation/ implication: the connection between independent networks creates a higher value than the sum of the values of individual networks. (Law linked to the spread and success of the Internet.)
Reed’s law: “the value of a network, the internet in particular, grows exponentially when combined in groups with common interests, sharing ideas, interest, goals and a sense of belonging”.
The value of a network can be:
HYPE CYCLE DI GARTNER
It’s about Visibility, meaning how many times/how much people talk about it. We have 5 distinct phases:
1)trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven.
2)peak (everyone use it): Early publicity produces a number of success stories—often accompanied by scores of failures. Some companies take action; most don't.
3)disillusionment (not so useful): interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investment continues only if the surviving providers improve their products to the satisfaction of early adopters.
4)enlightenment: more instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious
5)productivity (technology is used in the correct sector where it can fully exploited): mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology's broad market applicability and relevance are clearly paying off. If the technology has more than a niche market then it will continue to grow
LONG TAIL:
The “long tail” concept has found some grounds for application, research and experimentation in for example online business, mass media, micro finance, knowledge management and user-driven innovation.
The overall demand for these less popular goods (represented by this long tail) could rival the demand for mainstream goods.
Mainstream goods: achieve a greater number of customers but initial cost high
Long tail goods: remain in the market for long time, have low distribution and production costs and are available for sale.
Amazon, Apple, Yahoo examples that apply this strategy.
LONG TAIL=consists of small volumes of hard-to-find items to many customers instead of only selling large volumes of a reduced number of popular items.
The total sales of this large number of non-hit items is called the long tail.
LAW OF DISRUPTION
:
Says that “Process by which a product or service takes root initially in simple applications at the bottom of a market, and then moves up market, eventually displacing established competitors.”
Disruption: the time at which a new technology gives rise to a change in a particular activity and completely changes the previous business model.
Disruptive innovation is nowadays helped by the digital technologies, which accelerated this process.
1.1 SOCIO TECHNICAL SYSTEM
Software Systems are essential components of broader systems that have a human, social or organizational purpose.
Sociotechnical systems (STS)in organizational development is an approach to complex organizational work design that recognizes the interaction between people and technology in workplaces. The term also refers to the interaction between society's complex infrastructures and human behaviour. In this sense, society itself, and most of its substructures, are complex sociotechnical systems (Wikipedia).
Following the KEY ELEMENTS of Sociotechnical systems.
A good developer has to take into account:
1. Structure
2. Processes
3. Mind of individuals
There’s the need to check task, people, structure and then to find a technology to implement that fits with all the 3 elements above.
Sociotechnical systems stack is made of:
1.equipment
2.operating system
3.communication and data management
5.business processes
6.organizations=higher level strategic business activities.
7.society=laws, regulations and culture.
The Effects of the introduction of a new Sociotechnical system on organizations are:
A) Process changes
B) Job changes
C) Organizational changes (political power- the ones who have control of the new system have more power)
Many of the problems and failures of Management Information Systems (MIS) have been attributed to organizational behavioural problems, which are the result of inadequate designs .
These bad designs are due to the way MIS system designers view organizations, their members and the function of MIS within them. (system designers’ frames of reference);
These frames of reference cause faulty design choices and failures to perceive better design alternative;
There are 7 conditions which are the major causes of inadequate designs and unsuccessful change strategies, and which collectively reflect the existing frames of reference / system designers’ point of view. The goal is to reframe MIS design adopting a STS design approach.
The technical system is concerned with the processes, tasks, and technology needed to transform inputs to outputs. Aims to improve task accomplishment.
The social system is concerned with the attributes of people (e.g., attitudes, skills, values), the relationships among people, reward systems, and authority structure. Aims to improve quality of working life (QWL).
MIS is viewed as an intervention strategy: to enter in an on-going work system for improving.
STS approach to MIS argues that any intervention must deal with both technical and social goals, simultaneously.
The CONDITIONS responsible for inadequate design are listed as follows:
1- Systems Designer's Implicit Theories:
Systems designers clearly make assumptions aboutpeople, organizations and change process. These assumptions affect which design alternatives are considered and chosen.
2- Systems Designer's Concept of Responsibility:
The critical question is "Who is responsible for the change effort?"
Currently, systems designers are the ones taking responsibility for the system development process. But MIS change effort can be successful only if the client assumes the responsibility for its success.
More attention needs to be given to the strategic design phase and the appropriate sharing of models, assumptions, and goals between users and designers in order to develop meaningful collaboration.
MIS designs can have a high probability of failure if the users do not assume responsibility for them.
3- Limited Frameworks - Non-systemic View , meaning a limited conceptualization of work systems/user systems used by systems designers in the design process;Systems designer should view a work system as a set of complementary or interdependent information systems.MIS practitioners systemic do not understand the relationship between the variables we manipulate and other variables within the work system.
4- Limited Goal Orientation - Optimizing the Technical System:
System designers tend to focus only on technical system (and not consider social system);
So their goal is technical system optimization (lack of concern for improvement in quality of working life).
Research have found that there were a lot of unexplored, possible alternative designs for existing MIS designs that would have improved not only task accomplishment, but also quality of working life. These results support the opinion that both goals can increase together for an MIS intervention.
social system improvement needs to be considered jointly with the technical system improvement in MIS design.
5-Limited Design Referent Group - Who is the User?
Systems designers must take a "total system" referent group orientation in order to improve their designs. Total system orientation implies that consideration be given to all people affected by the design.
6- Rational/Static View of the Systems Development Process:
The traditional approach to the development process of an MIS treats design and implementation as a rational, systematic process that proceeds in a static environment. BUT this rational/static view does not accurately reflect the MIS development process in real life.
Need to replace with a realistic view of the political/dynamic dimensions of MIS development.
7- Limited Change Technologies
Systems designers use a limited set of change technologies; BUT an integration between the MIS technology and other technologies is needed to produce a more effective intervention.
Use of techniques that tend to facilitate the improvement of both social and technical systems. These techniques coupled with an MIS intervention would allow us to pursue the goal of joint optimization.
1.2 CHANGE MANAGEMENT
We are going to talk about Change Management, starting from some literature and then presenting the Nokia case study from an organisational management point of view.
Charles Darwin was the first to say that “the species who survives is the one that is the most adaptable to change” (Origin of Species - 1859) So he was the first to understand that the ability to adapt to external conditions is essential not to die. If we transfer his point of view to the organizations field...
The era of rapid innovation, technology and competition has forced organizations to embrace change, in order to remain alive and competitive in their respective sectors.
According to the existing literature, change is defined as an “ever-present feature of organisational life, both at an operational and strategic level”(Moran and Brightman, 2001: 111). Therefore, ability to identify and forecast where the organization should be in the future and how to get there it’s crucial to any business. So we can state that, due to the importance of organisational change, its management is becoming a highly required managerial skill.
Change management has been defined as ‘the process of continually renewing an
organization’s direction, structure, and capabilities to serve the ever-changing
needs of external and internal customers’ (Moran and Brightman, 2001).
In the change management literature there is considerable disagreement regarding the most appropriate approach to operate change within organisations, depending how change comes about. We will present the 2 main approaches to it: planned and emergent.
Planned change is based principally on the work of Kurt Lewin (1946) and it has been a pillar in change management theory for the past 50 years.
