Lesson-13-Outline Spring 2020 PDF

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Lesson 13 - Week 15...

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Systems & Information Concepts in Organizations (SICO)

Lesson 13 – April 27, 2020 Hi! Welcome to Class! 1. A few announcements 

Your case study #3 presentations are due by noon on Monday, May 11, 2020. Also, please remember to complete a peer evaluation for your team members and submit the completed evaluation in the assignments tool by Thursday, May 14, 2020.

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Final Exam week is Monday, May 11, 2020 – Friday, May 15, 2020. I will post your final exam a few days earlier, on Saturday, May 9, 2020 at 6:00AM. Your exam will be due by midnight (11:59PM) on Friday, May 15, 2020. The format will be similar to your mid-term exam.

2. Plan for this week’s lesson Context: This week, we will cover Knowledge Management, Business Intelligence and Business Analytics in Chapter 12. Chapter 12 begins with a discussion of how businesses such as Netflix, the Oakland As, Caesars Entertainment and Capital One all make use of analytics to create competitive advantage. Chapter 12 introduces five ways a company can make use of analytics. These are: (1) making information more transparent and usable at a frequency that outpaces the competition; (2) exposing variability and boosting performance by collecting and analyzing more transactional and performance data; (3) more precisely tailoring products and services using better-designed segmentation and large data samples; (4) improving decision making through experiments, forecasting and feedback, and just-in-time analysis; and (5) developing the next generation of products and services more quickly using sensor data to collect after-sales information on product usage, performance, and so on. Knowledge management is considered an emerging discipline, although the management of knowledge has been around for a long time, with the collection and dissemination of knowledge going back to the earliest civilizations. Today, managers still struggle with how to create, collect, integrate, transfer, and secure knowledge. Knowledge management is defined as the collection, organization, and distribution of knowledge assets. Business intelligence is seen as a component of knowledge management. Business intelligence describes the set of technologies and processes used to produce actionable information on business performance. Business analytics refer to the use of quantitative data and predictive models to inform business decisions. Knowledge management is related to information systems. Information technology (IT) provides the infrastructure for capturing and transferring knowledge. While IT helps in the creation of knowledge, it is not necessary in accomplishing knowledge management. IT does not create knowledge nor does IT guarantee the use and sharing of knowledge. Data, information, and knowledge are often used interchangeably, but have significant and discrete meanings within the knowledge management domain. Pearson, Saunders, & Galletta 1

Systems & Information Concepts in Organizations (SICO) nicely summarize these differences on page 261 in your text. Pearlson, Saunders, & Galletta also describe two types of knowledge. Tacit knowledge is personal, context-specific, and hard to formalize while explicit knowledge is easily collected, organized, and transferred through digital means. Most information systems focus on this later type of knowledge, although more current systems are beginning to acknowledge and incorporate facilities to support social interactions and information sharing among individuals as a key component of any information system. There are four main processes involved in knowledge management. First, the knowledge generation process includes all activities that discover new knowledge. Second, the knowledge capture process includes all the activities that scan, organize, and package the knowledge. Third, the knowledge codification process includes the actions to make the knowledge available to those who need to use it. And finally, the knowledge transfer process includes all the activities that allow the knowledge to be distributed for a variety of uses, and for the absorption of the new knowledge. The common elements of business intelligence include reporting, querying, dashboards, and scorecards. Visual representations of the data are often preferred by managers since they are easy to interpret, and they are often aesthetically pleasing. Color-coding the graphs and charts can increase readability. Technological innovations are rapidly incorporating near real-time data analysis, thereby improving decision making on dynamic performance data. Four components are needed to support business analytics. Data sources include the data streams and repositories. Data repositories store the massive amounts of data in data warehouses, or some form of digital collection that is easily indexed and accessed by authorized users. In order to be useful, the data must first be gathered and cleaned (ETL – Extract, Transform, and Load). The software tools are often complex and robust. Techniques include data mining, searching for trends and patterns in the data, and clustering, grouping data on some key dimensions. The four categories include: statistical analysis, forecasting/extrapolation, predictive modeling, and optimization. In order for business intelligence and analytics to be institutionalized successfully, managers must create a data driven environment , one that supports and encourages the use of performance data in decision making. Leaders need to model evidence-based management . Finally, a workforce skilled in quantitative analysis techniques is required. Additionally, continued training on new methods is beneficial. In your optional material this week, I included some videos on data science that you might find interesting. A key point to remember is that an organization’s only sustainable competitive advantage lies with how its employees apply knowledge to business problems. Big data is a term commonly used to refer to techniques and technologies that are capable of manipulating vast amounts of data (in the exabyte 10 18 and zettabyte 1021 ranges). Normal software applications cannot function at that level; specialized tools are required. In Chapter 12, Pearlson, Saunders & Galletta, also introduce Internet of Things, which is highly relevant to big data given the massive quantities of data generated. Pearlson, Saunders, & Galletta also include an overview of social media analytics. This class of data is often unstructured and publicly available from social media outlets. 2

Systems & Information Concepts in Organizations (SICO) Intellectual capital and intellectual property are important topics covered in chapter 12. Individuals expect to be compensated for their knowledge work, and their products should be legally protected. However, it is difficult to enforce these rules and laws when the product is easily replicated and distributed. Chapter 12 concludes with a discussion of “caveats” for managers to consider. First, knowledge management and business intelligence continue to be emerging disciplines. Managers must continuously scan for new technologies. Second, making knowledge more visible is not always the objective. Managers should be cognizant of competitors seeking information on business performance. Third, knowledge can be used to develop predictive models and develop future directions. Lastly, it is all about the people – the analysts with technical skills, the managers making better business decisions, and the employees collecting accurate data at the source. Knowledge sharing is critical to realizing value from these processes. 

Reading: - Textbook (Pearlson, Saunders, Galletta, 6th Ed), Chapter 12 (pp. 258-274) - Lesson 13 Lecture Notes - Hagiu, A., Wright, J. (2020). When Data Creates Competitive Advantage. Retrieved April 25, 2020, from https://hbr.org/2020/01/when-data-creates-competitive-advantage - Herring, L., Mayhew, H., Midha, A., Puri, A. (2019). How to Train Someone to Translate Business Problems into ... Retrieved April 25, 2020, from https://hbr.org/2019/02/howto-train-someone-to-translate-business-problems-into-analytics-questions - Davenport, T. H., & Harris, J. G. (2007, September 17). Competing on Analytics. Retrieved from https://www.computerworld.com/article/2553007/competing-onanalytics.html.

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Additional Reading and Videos: (optional): - Nielsen, C. (2014, November 12). Collect Your Employees' Data Without Invading Their Privacy. Retrieved from https://hbr.org/2014/09/collect-your-employees-data-withoutinvading-their-privacy. - Knowledge Management Portal at Brint.com, The BizTech Network https://www.kmnetwork.com/ This portal is a virtual library on KM. The library has links to forums, articles, events, white papers, recent news, resources, job postings, and more. - What is Data Science? [Data Science 101] (video) - A day in the life of a data scientist [Data Science 101] video - Applications of Data Science [Data Science 101] video 3

Systems & Information Concepts in Organizations (SICO)

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Discussion Topics: (no new discussion topic this week) Read the material I posted to participate in the discussion thread, then: i. Answer the question I posted. ii. Contribute one question iii. Submit answers/comments to at least one of your peers’ questions/ Topic: Reflection Due Monday, May 4, 2020 at Noon

For this week’s discussion forum, I ask you to think about the topics we have covered in this class and what you have learned. Choose at least two topics that were either interesting and/or relevant to you and share your thoughts. How will the information you learned in this class apply to your career, work, or personal life? There is no right or wrong answer. I am looking for your participation, thoughtfulness, and reflection.

3. Closing Remarks 

Stay healthy and safe, everyone! I will see you in the forum!

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