Magna Notitia

  The implementation of big data analytics (BDA) in organizations is a costly and complex undertaking, and given there is no recipe that guarantees a successful implementation and execution, a careful and honest assessment of different aspects of the business must be conducted, from the technology, data collection, the human resources involved in the process, and managerial support (Hajiheydari et al., 2021). Hajiheydari et al. state that approximately 60% to 85% of BDA projects fail not because the technology is bad, but because organizations do not have a clear understanding of how to utilize data analytics to construct achievable business goals,  or how to successfully integrate its practice with day-to-day business operations (Sun et al., 2020). BDA offers financial institutions countless benefits, and provides valuable insights to personalize customer service via the analysis of transactional records and other data, including social media information (Flynn, 2020; Sun et ...

  Data science has been used in physics and astronomy, but it is being applied to businesses and finance, manufacturing, and other fields. The demand for data science professionals exploded about two decades ago when businesses began collecting massive amounts of data,  and a shortage of talented individuals, or data scientists, with a specific set of skill sets able to extract the most benefit from the available data (World Data Science, 2022). Data science is a multi-disciplinary field that converges programming, mathematics, statistics, computer science domain expertise, and communication skills, yet seldom organizations are able to find a data scientist that excels at all of them (Bansal, 2021; World Data Science, 2022).  The World Data Science Initiative (2022) reports data science jobs were expected to grow by 364,000 in 2020, but the real number came in at 2,720,000. Data scientists became part of the solution to address the challenges of growing organizational da...

  Netflix services fall under the subscription video-on-demand (SVOD) services category as a so called over-the-top (OTT) provider, which streams content over the web directly to its customers’ devices (Iordache et al., 2021; Pajkovic, 2021). Netflix’s revenue is mainly generated by users’ subscription fees (Kasula, 2020), and to keep customers from cancelling their access, the company relies heavily on the Netflix Recommender System (NRS) which combines big data analytics with powerful machine learning (ML) algorithms (Jackman & Reddy, 2020; Pajkovic, 2021) to keep users engaged and satisfied with the service.  The aim of the NRS is to offer a personalized experience and provide viewing recommendations to each customer (Pajkovic, 2021) based on preferences generated by their rating history (rating the titles they watch), Netflix’s requests for feedback, a “similarity” approach across subscribers, movies, genres, etc. (Kasula, 2020). The NRS is driven by powerful machine l...

  New, innovative, and more efficient technologies have enabled the management of big data for analytics to extract meaningful insights for decision-making (Minelli et al., 2013), emphasize the many differences between big data and conventional data.  Edd Dumbill as cited in Minelli et al. (2013), defines big data as “data that becomes large enough that it cannot be processed using conventional methods,” and Gartner’s definition in 2001 reads “Big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity” (Treehouse, 2022), featuring big data’s three V’s: variety, volume, and velocity (Minelli et al., 2013). Kumar et al. (2021) explains that with big data, it is possible to store large volumes of data, but not in a conventional data setup. Conventional data reflects a centralized database architecture, and big data is found in distributed databases. The data sources are many when dealing with big data, but severely limited with co...

  Introduction  The digital twin (DT) concept can be traced back to the National Aeronautics and Space Administration (NASA) Apollo program in the 1970s, where two identical vehicles built for space efforts, and one was able to mirror the conditions of the other during a mission (Wei, 2021). This “mirroring” concept was called “Mirror Space Model,” and later “Information Mirror Model,” until NASA’s John Vickers introduced the new “digital twin” name in his book. Grievers, a professor at the University of Michigan who put forward the concept of “Virtual Digital Expression Equivalent to Physical Product” in a 2003 product lifecycle management (PLM) course, began using Vickers’ DT name in 2011 (Wei, 2021).  DT has been successfully applied mainly in the fields of manufacturing and PLM to perform simulations, optimization, make predictions and provide suggestions, performance improvement, and others (Wei, 2021). From these applications, the DT concept expanded to “augmented d...

 

  The LEGO Group (LEGO) had been doing everything right since the introduction of injection-molded building blocks in the late 1940s. The company was always on the lookout for new products, inserted themselves in different markets (video games, amusement parks, education centers, jewelry, etc.), they listened to customer feedback, and gave their development engineers free range to innovate and create new products (Oliver, et al., 2007; Wharton, 2012).  LEGO sales plummeted in 1993, and although some of it was attributed to China’s manufacture of similar products at a fraction of the cost, the big-box store (e.g., Wal-Mart) phenomenon, and the merging of such big-box stores (Wharton, 2012), these and other challenges resulted from significant market changes. Production costs were rising in Denmark, Switzerland, and United States, pushing LEGO to outsource plastic production to México and the Czech Republic (Oliver et al., 2007; Wharton, 2012). Another challenge was LEGO’s over-...

  SERENDIPITY The term “serendipity” was first applied by Sir Horace Walpole in 1754, and English writer and historian, after reading a story titled “The Three Princes of Serendip” (Serendip is now called Sri Lanka), where the traveling princes continuously made discoveries of things they did not plan to explore, yet were surprised by them. Walpole created the term “serendipity” to explain the type of discoveries like those in the story he had read (Crampton, 2022).  I understand serendipity as the discovery of unexpected events or innovations, the kind made by chance when in search for something else, as is the case of lysozyme. Alexandre Fleming discovered lysozyme, an antibacterial enzyme, found in human mucus, saliva, and tears. Fleming serendipitously discovered the enzyme after sneezing on a petri dish full of bacteria while working on bacterial research. Some of the bacteria died around the area Fleming contaminated with his sneeze. Lysozyme is able to destroy some of t...

  If I had all of the time, money, and talent in the world, I would do many things. I have added perfect physical and mental health, and provided my list of ideas for 5 different categories as part of this "visioning" exercise.  Education  1. Study medicine (this was my initial field of study when I was young),  2. Learn Python programming language (I only know the basics),  3. Learn French,  4. Learn Japanese,  5. Learn to play the guitar, piano, and violin,  6. Study nutrition,  7. Learn how to pilot a plane,   8. Study religion,  9. Master public speaking, and  10. Learn how to train dogs.  Job or Research  1. Neurosurgeon,  2. Research the brain and brain-related condition (incurable as of today),  3. Philanthropist,  4. Data Scientist,  5. Big data professor,  6. Volunteer to teach others in third-world countries,  7. Write a book,  8. Opera singer,  9. Chef, and...

  Wharton (2012) describes scenario planning as the intersection between strategy and innovation, where proactive strategic thinking aims at uncovering potential futures and changes that may result in opportunities for innovation. Parayre (n.d.) as cited in Wharton (2012) describes it as “Innovation opportunities are the result of changes or shocks in the environment […]. The scenarios become […] ‘platforms for ideation’ […]. They provide a clarity that helps you to anticipate changes and possibilities.”  Athuraliya (2022) states scenario planning segregates knowledge into two areas: (1) Things we know, and (2) Things we are not sure about. The scenarios provide opportunities to look into what could happen in the future, but they do not offer the strategies necessary for effective management of those potential futures. For this reason, outside help from customers, suppliers, journalists, politicians, etc., are key in identifying patterns and uncovering uncertainties with the u...