Abstract Science Construction’s business is in planning, developing and building road projects. The major of its clients are municipalities, city governments, and other public sector entities. While the bankruptcy rates for these clients is very low, when economic downturns happen, their ability to pay in a timely fashion also suffers. This leads to businesses such as Science Construction needing to take on additional debt and to find creative methods in order to stay afloat during times of recession. Methods such as selling accounts receivables at discounted rates and taking larger lines of credit through banks and other lending institutions are some of the ways organizations can remain viable when their cash inflows have turned into a trickle. Science Construction is asking the Turkish Courts to postpone their bankruptcy proceedings for a year while they attempt to restructure. Through this, suggestions such as forcing shareholders to pay their debt to the organization, gaining credi...
Since information is processed, interpreted, organized, structured or presented data that gives meaning to facts and figures so as to make them meaningful or useful, the terms information explosion and data explosion are interchangeable when discussed as being rapid increases in the amount of published information or data and the effects of that abundance (Wikipedia, n.d.). This information or unprocessed data has become so plentiful and abundant that the management of it becomes more difficult which leads to an overload.
The term was first used in April 1961 in article at a biological conference, then again during the same month in a publication by the New York Times. Since the initial use of the phrase, a lot has transpired since the 1960s later experts making the following predictions (Frew, 2018):
a 4300 % increase in annual data production by 2020,
7 billion people and businesses will be connected to the internet by 2020,
30 billion devices will be connected to the internet by 2020.
Quality and quantity go hand-in-hand with respect to information. For it to be useful, data must be managed by describing what information is to be extracted and a clear way to collect and analyze that extracted information.
A plethora of businesses recognize the value of data and information. Businesses like healthcare, supermarkets, vital statistics, journalism and more are affected, by this explosion. The issue arises when there is so much information that these businesses cannot use it as fast as it’s produced which creates a surplus. This surplus of information creates other problems (Frew, 2018):
Data collects dust on servers when not used creating a storage issue and eventually collapse
Data lifespan is not infinite therefore loses will lose its accuracy and relevancy
Data costs money to store whether in use or not
For those who can make it work them, the data explosion can be harnessed to create new revenue streams, and growth by committing to digital transformation in the next three years. Specifically, digital transformation is the reimagining of how technology works to empower people with data and processes that creates value and maintains a competitive advantage in the digital-first world (Bell, n.d.).
Discuss Thomas Davenport’s assertion that analytics are source of sustainable competitive advantage.
Now, about Tom Davenport. He “is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative for the Digital Economy, and a Senior Advisor to Deloitte Analytics. He has written or edited twenty books and over 250 print or digital articles for Harvard Business Review (HBR), Sloan Management Review, the Financial Times, and many other publications. He earned his Ph.D from Harvard University and has taught at the Harvard Business School, the University of Chicago, the Tuck School of Business, Boston University, and the University of Texas at Austin” (Davenport, 2019). His expertise and credentials are above reproach and he’s probably forgotten more than most remember about analytics. When he speaks, the world listens, especially about his views on sustainable competitive advantage. In an interview posted on HBR, Davenport defined analytics as the systematic use of data and facts and typically, quantitative, but can be qualitative as well, analysis to make decisions (HBR, 2010). Davenport proposed the use of analytics as a basis for companies securing a competitive advantage.
Using analytics as a basis for decision making births a different type of visionary, the analytical leader. By actions alone, this leader creates an company environment where there is a competitive advantage by insisting company decisions be based on facts. They are indifferent to having information brought to them using phrases like, “I think we should or we should.” The only way to capture these leaders’ attention is to bring them data to support a particular theory. Davenport further reveals analytical decision making must be a thorough and complete assimilation in order for it to become foundational within a company. Analytical leaders wouldn’t make gut decisions but have others bring him data to support theirs. It must be established as a company culture for effectiveness.
Another aspect of grounding a company is hiring analytical talent. Though the talent pool is limited, companies should hire those who are both analytical and good communicators. Trying to do this as early as possible in the life of an organization makes them a true strategic resource.
In further discussion during the interview, Davenport does reveal there are instances where you don’t find analytical data at the epicenter of the decision making process. When organizations ready themselves for mergers, acquisitions or new product lines, companies tend to use analytics,though there are exceptions.
Futuristically, Davenport sees the need for closer ties between analytics and decision making from a management standpoint. Technology will evolve with a new class of data and information. With sensors or smart dust (Dictionary, 2019) placed anywhere and everywhere conceivable, a new data explosion will incur because there won’t be enough people to analyze it for value. Even now we have security cameras and videos without people to analyze the footage. Davenport also sees social media as a needed area of attention for relative analytics and decision making.
In the Davenport interview (HBR, 2010), he’s asked to speak on his research where he discovered companies and organizations who deployed better decision making through analytics and had great results. Progressive Insurance, Google and 1-800-flowers are three of the companies researched and detailed in either of his books, "Analytics at Work" and "Analytics at Work: Smarter Decisions, Better Results." Carnival Cruises and Amazon are two others. Kroger who used analytics to capture a competitive edge with promotions is another. JC Penney who used the process for merchandising and Best Buy used it for segmentation are two others mentioned in his books.
On the other hand, an example of an organization that has faltered and not made the transition to using analytical decision making very well would be Macy’s. Even though they hired the same company Kroger used, they’ve had some lack of success.
As far as an industry goes, healthcare is probably the least productive with analytics by not having adequate information. This inadequacy could be in part because the sharing of Personal Health Information or PHI is protected by the Health Insurance Portability Accountability Act or HIPAA (Rouse, 2018). This act limits covered entities from the type of PHI they can share, collect and use in marketing. Now being mindful of the time this interview took place, some things have improved with EMR or Electronic Medical Record stimulus provided to health care entities to improve the collection of information within the HIPAA guidelines, of course.
The biggest underachieving industry of analytical decision making is the retail industry. This is probably due to profit margins not supporting employment of qualified analysts to do the job. Over the years, retail companies such as Walmart and Target have gotten better.
If there were a third hand, companies such as Chevron would be placed there as a bit of a hybrid. As mentioned before, some companies don’t use analytics as a basis for major decisions. At Chevron, if actions require the use of $100 million dollars, certain quantitative information must be considered, but not as the basis for the decision. This model of decision making seems to do the company justice with "big ticket" decisions.
References
Bell, Jason. (n.d.). Digital Transformation is Here. Are You Leading the Way? Retrieved from https://www.abelsolutions.com/digital-transformation-leading-way/
Davenport, Tom. (2019). About Tom Davenport. Retrieved from https://www.tomdavenport.com/about/
Frew, Scott. (April 2018). The Data Explosion, Part 1: How to Manage All That Data. Retrieved from https://blog.iasset.com/data-explosion-part-1-how-manage-all-data
Harvard Business Review (HBR). (2010). Better Decisions Through Analytics. Interview. Retrieved from https://hbr.org/ideacast/2010/01/better-decisions-through-analy.html
Rouse, Margaret. (2018). Protected Health Information (PHI) or Personal Health Information. Retrieved from https://searchhealthit.techtarget.com/definition/personal-health-information
Wikipedia. (n.d.). Information Explosion. Retrieved from https://en.wikipedia.org/wiki/Information_explosion
Comments