The force of Management Visualization changes Business

July 21, 2020

The force of Management Visualization changes Business

Kimiaki Aonuma
Professor, Graduate School of Global Business, Professional Graduate School,
Meiji University
 

The recent progress in digitization using IoT (Internet of Things) and AI (Artificial Intelligent) is largely changing business styles. They make it possible to collect enormous data as never before, and also to analyze that data using various methods, including AI. Because of this, a model-building capability to analyze data to meet companies’ needs and digitize revenue and risks, and the capability to express characteristics intuitively by the sense of sight are required. The skill so called “to visualize management” is required for future businesspeople.
Rapid changes of business models

Now, companies around the world are being forced to change their business models. The progress in digitization, such as through IoT and AI, has made it possible to procure a society in which comparative analysis of quality, price and added value of goods and services can be conducted instantly.

There is a possibility that the transition to teleworking in the process of office-cost reductions and workstyle reforms will accelerate rapidly through the generalization of teleworking due to the coronavirus.

One type of industry that has been affected by these trends is the financial industry.

Recent news of massive reductions in workforce and banking office closures among megabanks arises from the progress of various innovative technologies, which is called FinTech, where financing services and information technology are connected.

FinTech is a coined word that was made by compounding “finance” and “technology” and refers to the efforts of various innovative services where information technology is connected to financial services. One familiar example is money transfers using a smartphone.

In the US, the word FinTech has been used since the early 2000s. Then, after the 2008 bankruptcy of Lehman Brothers and the global financial crisis, new financial start-up companies (venture companies) which provide services utilizing the Internet, smartphones, AI (Artificial Intelligence), and big data have appeared one after another.

For example, there are companies which connect lenders and borrowers of funds directly and provide a settlement service which is connected to e-commerce, and start-up companies also are increasingly entering into financial services such as settlements.

In addition, even in developing countries and newly emerging nations, where financial services have not spread sufficiently, financial services utilizing smartphones are rapidly spreading.

Technology such as distributed ledger technology (technology where management (distributed management) is possible in the way plural participants share the same ledger instead of setting a specific ledger management entity) and blockchain (distributed ledger technology that makes manipulation difficult) have also appeared.

Typical services using FinTech include PFM (Personal Financial Management: integrated management services for information related to personal money), robo-adviser (investment advisory service by utilizing AI), marketplace lending (intermediation service between lenders and borrowers of funds), mobile POS (service where payment with credit cards can be accepted by utilizing smart devices), among others.

These services have a different information provision value from existing traditional financial services and have started to be utilized in many business fields.

The point that must be kept in mind is that changes in users’ values are the background of expanding FinTech, and most of the services are provided with the viewpoint of users.
Good use of data that companies emphasize
The basis for responding to the flow of digitization such as IoT and AI is how management is visualized by data. It is required that objective comparative analysis of the relation between companies or goods and customers, and the balance between risks and returns can be conducted in specific numerical values. And proposal-making capabilities by using data are required not only for an internal strategy but also for customers.

At this time, showing the values of statistics and the results of analysis is just showing collected information as a list of numerical values. The important thing is to visualize them as numerical values analyzed closely according to the in-house and customers’ needs and propose them.

Recently, talented people with this skill are called data scientist, which has become one of the pillars of personnel assessment. As assessment points of skill, actions for AI, risk management, and forward looking are also regarded as important.

Now, let’s try to think about the utilization of AI. AI can analyze the characteristics of data promptly by associating them with an enormous quantity of data that cannot be processed by humans and data whose field is considered to have no relation to humans. However, it is humans that judge the results of the analysis and utilize them.

For example, AI can analyze the characteristics of high-performing salespersons by importing various data related to the persons to AI. However, it is human’s job to judge what is read out from the results of the analysis and what actions should be taken as a company.

Staff in the Personnel Division may consider what themes can be taken in instruction courses to improve salespersons’ performance. If the results are analyzed by AI repeatedly, the instruction courses can be improved more efficiently.

Effective use of AI is actions for AI.

Corporate management has risks at all times. The risks include bankruptcy of business connections, cost fluctuations of foreign exchange and raw materials.

Risk management is to clarify these risks, predict the possibilities and frequencies by risk, the loss and the effect when they happen, and consider what preparation is the most effective, and forward looking is to predict the future business environment and respond to it in advance.

In the business world, where globalization progresses, knowledge of macro-economics and the condition of the world economy to clarify the factors of the risks is essential, and we have to consider that the degree of the risk differs depending on companies even if it is the same factor.

The capability to make an easy-to-understand graph from the data according to a necessary reading method is also an important skill for visualization. This can allow many people to share necessary reading from the data.
Acquire necessary skills as working members of society

The movement to seek talented persons who have skills such as data science, risk management, and AI is spreading throughout companies, so students need to acquire such knowledge regardless of the humanities course or science course.

Meanwhile, it is important for people who are working in society to acquire such skills by utilizing a graduate school for adults, which many universities, including our university, possess.

Mathematics is its foundation.

For example, even if you try to calculate a company’s valuation by its future cash flow, the level is not fixed at this point and various levels are possible.

A variable whose value is not fixed at this point is called a random variable, and in order to evaluate a cash flow whose value is not fixed, it is general to evaluate it with the present value of the expected value.

To do this, it is necessary to calculate the expected value by using the concept of probability distribution and find a discount rate by power calculation of interest rates to turn the expected value into the current value.

In sensitivity analysis to analyze how much an exchange rate fluctuation affects corporate profits, the concept of differential is used.

These events show that a certain degree of mathematical knowledge is required to visualize management as a skill.

Some of you have struggled to solve an equation without understanding how mathematics like differentials and integrals will be useful to you in the future in your student days.

However, the concept of mathematics is becoming increasingly important in the real world.

What is required of you in practical operations is the capability to understand the meaning of the formula and explain practical issues with an intuitive formula (model). You can solve a formula itself or make a complex calculation using Excel if necessary and ask specialists if you need to solve a difficult mathematical formula.

A company analyzed the operational performance of salespersons using data such as academic records, family structure, evaluation values of SPI test when joining the company, and evaluation points after joining the company, which showed that high-performing salespersons had a tendency to have high mathematical skills.

The skills of logical thinking and showing things with objective numbers were supposed as the reason for this.

This shows which salesperson you listen to between a salesperson who makes a sale with warm enthusiasm and a salesperson who logically explains characteristics of goods and the benefit when you buy them by using numbers.

From now on, communication using networks is becoming increasingly important, where proposal-making capabilities and the capability to explain benefits and risks with objective numbers or intuitively are required.



* The information contained herein is current as of July 2020.
* The contents of articles on Meiji.net are based on the personal ideas and opinions of the author and do not indicate the official opinion of Meiji University.
* I work to achieve SDGs related to the educational and research themes that I am currently engaged in.


Profile
 
Kimiaki Aonuma
Professor, Graduate School of Global Business, Professional Graduate School, Meiji University
 
Research fields:
Mathematical finance, risk management, data analysis, corporate valuation

Research themes:
Evaluation model of hybrid finance, credit-risk evaluation model

Main books and papers:
◆“Kigyo Suuri no Kiso” (Basics of Corporate Mathematics) Kinzai Institute for Financial Affairs, Inc., 2014
◆“Excel de Manabu Forward Looking no Kiso” (Basics of Forward Looking Learned with Excel) (Joint author) Kinzai Institute for Financial Affairs, Inc., 2012
◆“Excel de Manabu Kinyu Sugaku no Kiso”(Basics of Financial Mathematics Learned with Excel) (Joint author) Kinzai Institute for Financial Affairs, Inc., 2012
◆“Fading Out Swap no Hyouka Model” (Evaluation Model of Fading Out Swap) Transactions of the Japan Society for Industrial and Applied Mathematics Vol. 14, No. 2, pp. 151 - 164, 2004
◆“Prepayment Risk wo Naiho shita Kinri Swap no Hyouka Model” (Evaluation Model of Interest-rate Swap Involving Prepayment Risk) Transactions of the Japan Society for Industrial and Applied Mathematics Vol. 13, No.4, pp. 471 - 483, 2003
◆“Teiki Yokin Tanpogata Yuushi no Hyouka Model” (Evaluation Model of Loan with Fixed Deposit Mortgage) Transactions of the Japan Society for Industrial and Applied Mathematics Vol. 12, No. 2, pp. 103 - 120, 2002
◆“An Evaluation Model of Down Grade Protection”, Japan Journal of Industrial and Applied Mathematics, pp.627-646, 2001. etc.

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