Assignment 3 - Big Data - Ed.02

Editor's Notes

• #2: This pyramid diagram is a summary review of the presentation. It is intended for internal use only. Therefore, do not provide it to the client.
• #3: Notes are provided in Numerical orders next to every sentence to allow the speaker expanding providing the audience with further information. (1)- i.e. change in customer desire, disruption in supply channel, etc. Although the driving forces are varied, top-performing companies are all agreed on the use of innovation as the only source for creating competitive advantages – to differentiate. (to differentiate) This would be achieved by using new technologies for making accurate decisions. Organisations want to find the ways to extract the most value from the increasing volume of data, thus having more ability to improve their products and services. (2) - Analytic-driven management has profound influence on the performance of organisations no matter if the aim is to gain competitive edge, efficiency or growth. McAfee and Brynjolfsson (2012) argue that “big data” enable companies to make decisions on the basis of evidence rather than rely solely on intuition. (3) – The growth in market for BIG DATA is about six times the growth rate of the overall information and communication technology (ICT) market (ibid). This creates a high priority for many top-performing organizations to improve their capabilities around information and analytics, which is why they use Business analytics five times more than lower performers”. “BIG DATA is forecasted to continuing a strong growth over the next five years”. >4< Cloud infrastructure will have the highest CAGR of 49% through 2017. >5< (4) - The fast-growing multibillion-dollar worldwide opportunity [Big Data] is expanding rapidly as large IT companies and start-ups compete for customers and market share, said Vice President for IDC's Business Analytics and Big Data research, Dan Vesset (ibid). (5) - Traditional storage datacentres are faced with reduction in their revenue size as significant amount of data (Big Data) generated will be stored on the cloud or disposed. (6) – Business analytics is a common tool to exploit new opportunities. BIG DATA also provides a better way of competing in the marketplace. (7)- However, the case is that while companies today generate substantial amount of data, they aren’t sure if or how to get the most out from these sources. (8) - Big Data can be used to find the answer for many questions that the conventional paths would not find it as fast. Finding the answer faster than traditional ways is an advantage of Big Data. SO, while many issues steel involved in analysing data, there is no doubt on the advantages of using Big Data sources (such as Social Media) to generate unique results that can transform the organisations. Social Media, for instance is now providing better opportunities to businesses to make faster and more accurate responses to the needs and wants of their customers. More companies are now connected thanks to growing connectivity and use of technologies among all groups. The better customer’s access to the Internet and connected devices helps to generate more data that goes to organisations.
• #4: Notes are provided in Numerical orders next to every sentence to allow the speaker expanding providing the audience with further information. - That is why, according to Viktor Mayer-Schönberger and Kenneth Cukier’s book, Big Data, “causality won’t be discarded, but it is being knocked off its pedestal as the primary fountain of meaning” (Harford, 2014). The scale and structure of data gathered in Social Media platforms reveals another issue in finding and analysing DIG DATA (Malthouse, 2013). The semi- or unstructured data generated at a rapid scale creates massive issues around analysing and sampling for organisations (ibid) There must always be a question about who and what is missing, especially with a messy pile of found data (Harford, 2014). Moreover, data collected from virtual world contains unstructured data that is reached in customers’ opinion and behavioural information (Hesinchu, et al. 2012). This also creates issues around publicity and share of data (security) due to what is regarded as “puzzling effect” that is important in today’s world (ibid). (2)-The managerial and cultural issues today, have a prefund effect on BIG DATA analysis in organisation (Lavella, et al. 2011). (3)- The online data is now transmitted into system from instrumented and connected sources. To drive value from Big Data, organisations need to have enough capacity to analyse the incoming data generated from Internet based sources. Companies need to develop their capabilities to cope with real-time data analysis thanks to the changing nature of data gathered from social media platforms. Apart from the issues around size, not all the data collected from any Big Data sources necessarily represent the best demographic needed. i.e. represent the whole population, so can still create doubt in its usefulness for businesses. IN looking at 3-5 years, organisations will be more exposed to rapidly developing sources of Big Data gathered in virtual world, which contains unstructured data reached in customers’ opinion and behavioural information (Hesinchu, et al. 2012) It is therefore critical to develop the right skills needed to analyse the social media sources, thus improving the organisational efficiency by having a better insights to deal with issues around marketing, operations, communication and HR, etc.  
• #5: Notes are provided in Numerical orders next to every sentence to allow the speaker expanding providing the audience with further information. (1)- To choice of centralise or de-centralise in turning the data-analytics into action can be described relative to the effectiveness that each strategy does have in helping to trigger the desire for analytics activities, engaging with data analysis and keeping up with these related type of changes. In order to find out how to get the most out from the massive volume of data, it is important to make the improvements in information and analytics by deciding on what strategies should be prioritised. Therefore in the light of Business analytics is necessary to consider the following questions: Who is going to use it? How is going to be used? What kind of analytics you need to have? Do you need solution architect? Or a data analyser can do the job? How to make sure to receive a clean data that is planned to use by data analytics? (2)- The challenge now is to solve new problems and gain new answers – without making the same old statistical mistakes on a grander scale than ever (Harford, 2014). (2)- While holding valuable information, data created in Social Media sources creates a challenging task for the data analytics in organisations. The issues namely are: the lack of control over message diffusion, big and unstructured data sets, privacy, data security, the shortage of qualified manpower, measuring the ROI of social media marketing initiatives, strategies for managing employees, integrating customer touch points, and content marketing (Malthouse, 2013) So the challenge faced by companies is to find out how fast and accurate the can be in analysing the user-generated (online) data, to overcome the challenges identified (scope and structure).
• #6: Notes are provided in Numerical orders next to every sentence to allow the speaker expanding providing the audience with further information. (1)- what that means is, while firms themselves collect data from everyday activities such as customer transaction data, supply chain data, operations data, etc., (often known as internal sources of data), using the external sources such as Social Media will help them to find the links to make better prediction of what should be done next to provide competitive advantages for their business. Social Media is also allowing the businesses to make faster and more accurate responses to the needs and wants of their customers. (2)- Cloud computing and Big Data technologies are among the most common tools used to deal with such an issue (O’Driscoll, 2013) Therefore, the key strengths to best analysing Big Data are:   Data analytics tech and tools, which requires to have Right skills, … Right people, … Right process, … Organisational design, … Capabilities The speed in processing the data The accuracy in analysing the data
• #7: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- Transformational changes, {the biggest challenge faced by organisation}, require a great change management leadership in organisation to implement new process in the system. The clear communication of goals and providing the employees with the ultimate result of using Business analytics will guarantee the high participation, thus overcoming the most challenging issue of the organisation. The whole point described above shows how organisation can overcome the managerial and cultural barriers that are amongst the biggest challenges faced by managers in adopting data analytics.
• #8: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #9: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- Making fast responses to drive value from Big Data sources is achievable in organisations with high level efficiency, which only comes through with a standard governing-structure and selective use of advanced technologies. (2)- While new analytic tools is used for finding new solutions to address the identified issues of organisations, it is also important to maintain the use of existing data and technologies and not replacing them. So the idea of focusing on correlation rather than causation means, instead of trying to find out what caused what, which is expensive, time consuming and hard to define, in companies like Google, data analysts try to find the links between the current information and incoming data in order to find the much cheaper and easier way of analysing the Big Data sources.
• #10: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #11: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. Business cases, analytics solutions, optimization, work flows and simulations, will provide the best platform for better understanding and taking relevant actions to achieve intended outcomes. (1)- In reality, organizations don’t have the full capability to use all the data available to them effectively, therefore it is necessary to have a Case study, action plan, or agenda, etc., before starting with the transformational process. (2)- Developing a case study for business accelerates the organization’s ability to share and deliver trusted information across all applications and processes. That raises the importance of the three following points. Having the business case/agenda Continuing repeating business case/agenda Refining the business case/agenda
• #12: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #13: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. The challenge is, while the issue with size exists, not the data collected from any Big Data sources necessarily represent the best demographic needed i.e. represent the whole population, so can still create doubt in its usefulness for businesses. Real-time data fluctuation is now transmitted into system from instrumented and connected sources, which adds on the complexities to extract value from Big Data. (1)- In faced with the growing volume of unstructured data, organisations need to narrow the gaps in finding the relevant sources of information require to find the answer the specific needs of their business. Organisations will be more exposed to rapidly developing sources of Big Data created in virtual world, which contains unstructured data reached in customers’ opinion and behavioural information (Hesinchu, et al. 2012). (2)- Continuing the value creation activities requires an efficient management in time and energy to allow the organisation to have directed efforts on targeted data needs and specific process improvement (Levella, et al. 2011). (3)- A head of starting their data analysis, organisations should identify the insights and questions that would best meet the business objectives they want to achieve. Organisations would need to understand the exact needs (issues) of their business to justify the appropriate piece of data required, thus making fast responses and making accurate decisions in adding value from BIG DATA.
• #14: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- Big Data analysis provides the organisations with abilities to use the available information in testing a situation. Evaluating the impact of competitor’s actions, consumer’s feedback, and other variables, provides a better insights of the likely market environment of businesses (Harford, 2014).
• #15: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- The case shows how companies can bridge the gap between data and knowledge, using the crowdsourcing as a data analysis tool to create competitive advantage by improving their capabilities to foster innovation, solve the problem faster – getting faster to the solution, or predict the future (Martinez and Walton, 2014). A meaningful example would be on how Dunnhumby used KAGGLE model of predictive competition to reach-out the best BIG DATA analytics solution to solve issues around analysing the Social Media data. Another very good example on this would be the success of Tesco Clubcard in better prediction of customers’ behaviour by using BIG DATA.
• #16: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- In other words, the information gathered from Big Data would need to be share at all level of organisation to enable every individual acting upon, thus highlighting the important rule of Social Media platforms in helping businesses to better interact with their surrounding environment for making better decisions. As the result developing such capabilities has become an interesting topic of study for those organisations eager to drive values from Big Data to achieve competitive advantages.
• #17: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #18: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- Among the most common tools used today are trend analysis, forecasting and standardized reporting, however different applications are needed in various cases (Lavalle, et al. 2011).
• #19: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #20: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.
• #21: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- The finding shows that the use information technology is being more useful in improving operations than the business process techniques (Trkman, et al. 2010). Due the broad definition of Supply Chain Management (SCM) to provide an example in which the data analytics is use to improve the operational performance of organisations, the Supply Chain Operations Reference (SCOR) framework is used to define the areas in which the information technology is used to analyse the data to improve the SC of businesses (ibid).
• #22: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information. (1)- The case helps to better understand the impact of such technologies in businesses. Nevertheless, such technologies allowing organisations to develop better products and/or improve their service, which in turn creates more value for their business (Lavella, et al. 2011).
• #23: Notes are provided in Numerical orders next to every sentence by the following >< icon to allow the speaker expanding providing the audience with further information.