Forecasting and predictions

Forecasting and predictions in a business or innovation context

Forecasting is fundamental for any business and organization involved with risks, opportunities, and security. Experts believe that there are 37 project characteristics that "subjectively combine data on all cues by examining both critical flaws and positive factors to arrive at a forecast." (Åstebro, 2006, para. 1). This peer-reviewed article, entitled "The Effectiveness of Simple Decision Heuristics," investigates the decision leading to "forecasting commercial success for early-stage ventures." (Åstebro, 2006) As the article suggests, predictions and forecasting of the early stages of a business are equal to innovation, and I, as part of a tech company, strongly believe so. Big corporations such as google, apple, Microsoft, and others give up an outstanding award for those who can provide a successful and meaningful prediction of the future for technical and financial prospects. People usually think that predictions are just scientific speech that is supported by facts and other materials, but apparently, it is not just that. Researchers must have historical decision-making datasets, analysis, and test the results' robustness for their predictions. The article claims that "The best heuristic is that which keeps 21 and ignores 16 cues." (Åstebro, 2006, p. 8) of 37 characteristics of the project because "The heuristic has an overall out-of-sample predictive accuracy of 86.0%. Note that the best heuristic, the regression model with all cues," (Åstebro, 2006, p. 8) 

Therefore, there are tools and science that we should use to prove the truth of our claim of prediction and forecasts, and artificial intelligence and machine learning are the best tools for today's forecasting of tomorrow.

For example, a peer-reviewed article predicts future hospitalization with high accuracy using artificial intelligence for urgent patients in the emergency department. (Jung-Ting, 2021) The study used "retrospectively collected data from the ED of a tertiary teaching

hospital between January 1, 2015, and December 31, 2019." to predict the future of hospitalization. They used eleven variables for data analysis and prediction model building, including one response variable, two demographic variables, eight clinical variables, and the response and gender variables. (Jung-Ting, 2021) 

Infamous predictions that came true

The most extraordinary forecast and prediction ever in human life is the long-lost letter from the great Albert Einstein that made an uncanny prediction 70 years ago. The image is attached here.

Nikolas Tesla (a co-worker of Thomas Edison) was one of the most outstanding electrical scientists who predicted wireless systems sometime about 90 years ago.

Note:

Please find this post in my blog. (Nikbin, 2022b)

Reference

 

Åstebro, T., & Elhedhli, S. (2006). The effectiveness of simple decision heuristics: Forecasting commercial success for early-stage ventures. Management Science, 52(3), 395-409. https://coloradotech.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/effectiveness-simple-decision-heuristics/docview/213175064/se-2?accountid=144789

 

 Jung-Ting, L., Chih-Chia, H., Chih-Hao, L., Yu-Jen, L., & Chung-Yao, K. (2021). Prediction of hospitalization using artificial intelligence for urgent patients in the emergency department. Scientific Reports (Nature Publisher Group), 11(1)http://dx.doi.org/10.1038/s41598-021-98961-2

 

Planning and Forecasting I

Scenario planning 

Scenario planning is "a way to assert control over an uncertain world by identifying assumptions about the future and determining how your organization will respond." (Rami, et., 2020) In other words, scenario planning is strategic planning focused on vision, mission, values, goals, and action plans to guide the organization in the long term process. Therefore it is "making assumptions on what the future is going to be and how your business environment will change over time in light of that future." (Mariton, 2016, p. 2)

Why is scenario planning so important? Because this planning method can provide competitive advantages in the middle of the crisis to the organization. Another advantage of scenario planning is that it helps c-suite executives the "effects of various plausible events. Finance, operations and other teams can prepare initial responses." (Rami, et., 2020) 

But the significant disadvantage of scenario planning is the lengthy process to make the critical decision based on the ongoing data in terms of time. Time is always a substantial factor in planning, and time in this method could be a game-changer for finance, security, and any other fundamentals.

Traditional forecasting

Usually, researchers use traditional forecasting to predict the future based on the historical records of datasets of business performance metrics. So, traditional forecasting is the power of using "historical observations to estimate future business metrics like inventory requirements, budgets, revenue or asset performance." (Belotindos, 2020) This method, traditional forecasting, is used when there is a countable dataset and finite numbers of predictive variables are available. So, the more we have known datasets, the more we can take advantage of traditional forecasting. Therefore, we use predefined statistical methods and models such as linear regression in this technique.

The most significant disadvantage of traditional forecasting is when "practices fail because the past does not necessarily represent the future." (Belotindos, 2020, para. 2)

AI and DL vs. scenario planning and traditional forecasting 

In-depth machine learning forecasting is used in traditional forecasting with massive amounts of historical datasets to predict the best performance for the future. On the other hand, AI using machine learning uses a scenario planning mechanism to predict the future of business, science, and anything.

Reference

Belotindos, B. (2020, September 25). Live Forecasting vs Traditional Forecasting vs Rolling Forecasting. Performance Canvas. Retrieved 2022, from https://www.performancecanvas.com/live-vs-rolling-vs-traditional-forecasting/

Mariton, J. (2016). What is Scenario Planning and How to Use It. Smestrategy. Retrieved 2022, from https://www.smestrategy.net/blog/what-is-scenario-planning-and-how-to-use-it

Rami, Luther, A. D. (2020). Scenario Planning: Strategy, Steps and Practical Examples. NetSuite. Retrieved 2022, from https://www.netsuite.com/portal/business-benchmark-brainyard/industries/articles/cfo-central/scenario-planning.shtml

Game-changing ideas that came from an error or accident

 

I remember my childhood when I was always looking to make something with my basic tools such as an old broken hummer, a heavy machete that I took from the trash box, nails, woods, and other basic stuff. Most of the time, my work's outcome was different from what I was planning to make. When I chose to continue my academic journey in engineering, software engineering, in particular, I developed some important applications, or modules, randomly and mistakingly again. So, after researching on this topic, I found that there are many essential and game-changing things invented in the past, just come from some errors, mistakes, and misleading research. 

Penicillin by Alexander Fleming

Penicillin (the world's first broadly effective antibiotic substance) was one of the game-changers in humanity's history, which came from a "wonder drug." Alexander Fleming (1988-1955), the discoverer of Penicillin, was a Scottish physician-scientist who found Penicillin in 1928 mistakingly. (NCBI, 2015) "I did not invent Penicillin. Nature did that. I only discovered it by accident," he said. Fleming was not a medical doctor, and even he did not enter medical school after finding Penicillin. Still, he was working in a shipping office for four years because he could not afford to intend to medical school. He could finally start his medical academics when he earned some real estate shares, and he graduated in 1906 with distinction from Mary's Medical School at London University. (NCBI, 2015) 

Fleming was not even a researcher. He was serving as a private marksman (a person with special shooting skills) in the London Scottish Regiment when he accidentally found Penicillin. (Wikipedia contributors, 2021) He was an Army Medical Corps captain during the time when he was witnessing the death of many of soldiers "not always from wounds inflicted in battle, but from the ensuing infection that could not be controlled." (Ncbi.Nlm.Nih.Gov, 2015, para. 4) By that time of war, "The primary means to combat infection was antiseptics, which frequently did more harm than good."  (NCBI, 2015, para. 4) Fleming was searching on a "wonder drug" form to cure the diseases in general, not particularly for infections at the time of war. He wrote an article that discussed the "presence of anaerobic bacteria" in deep wounds was not accepted. Fleming did not give up on his ideas, and ironically he discovered "lysozyme, an enzyme with weak antibacterial properties." in 1922.

Where did the mistake happen? Fleming got infected with a cold, and he "transferred some of his nasopharyngeal mucus onto a Petri dish. Not known for fastidious laboratory organization, he placed the dish among the clutter at his desk and left it there, forgotten, for two weeks." (NCBI, 2015, para. 4) When Fleming came back to the forgotten sample after weeks, he discovered lysozyme. The lysozyme was found in tears, saliva, skin, hair, and fingernails. So, now he could focus on the most game-changing invention in the history of medicine ever, Penicillin, with isolating a larger amount of "lysozyme from egg white, but in subsequent experiments found that this enzyme." (NCBI, 2015, para. 4)

The Pacemaker, a cold Heart Spin-Off by John Hopps

John Alexander Hopps (1919-1998) was an electrical engineer, so-called 'father of bioengineering in Canada', who worked for the National Research Council of Canada. Hopps was working on research on hypothermia by using frequency heating to restore the body temperature when he found that he could bring the heart to life again after it stopped beating due to cooling. Hopps found that stopped beating heart brings back to life with artificial stimulation, which led him to invent the "Pacemaker." (NCBI, 2006)

John accidentally found, "The electrical impulses were transmitted via a bipolar catheter electrode to the atria using a transvenous approach. Atrial pacing was readily achieved and heart rate could be controlled with no uncomfortable chest wall contractions." (NCBI, 2006)

Conclusion

We talked about the scientific and research accident, which led scientists to find some game-changing inventions in human history, but did just the accident make them happen? No! The primary requirement to be someone who accidentally invents something huge is not simple. Those requirements are the ability to believe in yourself, the ability to find a problem worth solving, the ability to build a prototype and test your ideas, and the ability to insist and protect your thoughts.

Group decision-making methods

 

Summery

Decision-making strategy, in general, needs seven steps: "Investigate the situation in detail, Create a constructive environment, Generate good alternatives, Explore your options, Select the best solution, Evaluate your plan, Communicate your decision, and take action." (Mind Tools, 2022) But, the decision-making techniques are "(1) Brainstorming, (2) The Delphi Method, (3) Weighted Scoring, (4) Nominal Group Technique, (5) Possibility Ranking, (6 The Stepladder Technique, (7) Pros and Cons list, (8) Didactic Interaction." (Dagher, 2022)

The Delphi Method

RAND Corporation developed the Delphi technique primarily to use an iterative multistage consensus process of groups, which hold the individuals' opinions. The Delphi method is a "forecasting process framework based on the results of multiple rounds of questionnaires sent to a panel of experts. After each round of questionnaires, the experts are presented with an aggregated summary of the last round, allowing each expert to adjust their answers according to the group response." (Investopedia, 2021, para. 1) 

Therefore the Delphi method is a process that starts with gathering a group's opinion or decision by surveying a panel of experts. And then, during the surveying, the group's experts reveal their ideas, and finally, the result will be the "true consensus" of the whole group's opinions.

The Weighted Scoring Method

Another method of my focus in this article is the Weighted Scoring method. The Weighted Scoring method of decision making is about getting the ideas of a variety of views of different potential solutions of team. So, still, we are involving teams and groups and opinions of the groups in this method, as the Delphi techniques suggested. Dealing with the Weighted Scoring method in decision making is "you and your team must evaluate each item on your list and assign criteria like Business Value, Costs, and Risks. Each of these criteria must likewise be assigned a score based on the weighting of the item. "(Airfocus, 2022, p. 2). Therefore, we can decide on the Weighted Scoring technique as soon as we "Once you've carried out weighted scoring for each item on your team's list"  (Airfocus, 2022, p. 2) 

Here is a simple Weighted Scoring method of information gathering:

Comparing the Delphi and the Weighted Scoring methods

The main difference between these two methods is the "vastly differing approaches are used to define final consensus, including the use of different aggregation methods and different rating scales." (Lange, 2020)

Reference

Airfocus. (2022). The Ultimate Guide to Group Decision Making - Techniques, Tools and Strategies. Retrieved 2022, from https://airfocus.com/blog/guide-to-group-decision-making-techniques-tools/

Dagher, K. (2022, March 8). 10 of the Most Effective Group Decision Making Techniques. Fellow.App. Retrieved 2022, from https://fellow.app/blog/productivity/group-decision-making-techniques/

Lange, T. (2020, February 10). Comparison of different rating scales for the use in Delphi studies: different scales lead to different consensus and show different test-retest reliability - BMC Medical Research Methodology. BioMed Central. Retrieved 2022, from https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-0912-8

Mind Tools. (2022). How to Make Decisions: A Model for Making the Best Possible Choices. Retrieved 2022, from https://www.mindtools.com/pages/article/newTED_00.htm

Investopedia. (2021, September 4). What Is the Delphi Method?. Retrieved 2022, from https://www.investopedia.com/terms/d/delphi-method.asp

The Futurists II

    Sohiel Nikbin, (born September 14, 1964, Iran, Langroud), Persian computer scientist who was the principal force behind the development of the First Face-to-Face mobile application on Blackberry framework system.

    At age 19, Sohiel began to dabble in computer programming on the latest generation of mainframe. In 1991, while a computer science student at the University of SBU (B.S., 1996), he purchased his first personal computer (P.C.) 386  first-generation computer system with 1 M.B. hard drive and 126MB internal memory. His P.C. used MS-DOS (the disk operating system from Microsoft Corp.), but Sohiel preferred the UNIX operating system he had used on the university’s computers at SBU.

    He decided to create his own PC-based version of the Internet using turbo-C called shared library systems (SLS). The first version of SLS worked inside an intranet with a server (connected to a huge rack of CD drives with numerous numbers of tangible electronic references, from agriculture to technology to medical to anything at all), and 

    Months of determined programming work yielded the beginnings of the semi-remote SLS. In 1997 his SLS was using with big firms and libraries through the dialup modems with lots of users enjoying a huge remote library. Remote Shared Library System (RSLS) retired as early as the first generation of the Internet. Sometimes, Sohiel thinks if he was living in the USA by creating RSLS, by the time, his creations could be the first Internet of all, who knows!

    After years of working on pure application programming development, Sohiel started IT in 2007, and he entered mobile application development in the first platform called the Blackberry around 2011. Sohiel developed the first Face-to-Face call using Blackberry, and soon the application retired because of the first version of FaceTime by iOS.

    Sohiel pursued his journey in computer science, by all means, academics, in the fields of development, in desktop, I.T., mobile, and A.I. at the time, and he released many products, articles, and blogs, and still doing.