USE OF SIMULATION IN SERVICE INDUSTRIES

 Simulation software in Service Industry

What is Simulation ?

A simulation imitates the operation of real world processes or systems with the use of models. The model represents the key behaviors and characteristics of the selected process or system while the simulation represents how the model evolves under different conditions over time.

Simulation are usually computer-based, using a software-generated model to provide support for the decisions of managers and engineers as well as for training purposes. Simulation techniques aid understanding and experimentation, as the models are both visual and interactive. Simulation systems include discrete event simulation, process simulation and dynamic simulation. Businesses may use all of these systems across different levels of the organization.

Advantages of Simulation

There are a range of advantages to be gained through the use of simulation, including:

1. Less Financial risk
2. Exact repeated testing
3. Examine long term impacts
4. Gain insights for Process improvement
5. Assess random events
6. Encourage in-dept thinking

Simulation in Service Industry

With the advent of many simulation software, simulation is gaining ever increasing importance in industry to plan & control the processes effectively .Service industries are different than manufacturing industries in the sense that the former works with more flexibility in the processes. Standardized processes may vary from time to time depending the customer’s requirement. Service industries, in general, employ comparatively less automation, which is one of the causes for the variations. 

USE OF SIMULATION IN HEALTHCARE SERVICES

Simulation is a powerful predictive analytics and decision making tool for healthcare organizations.

Hospitals and healthcare systems are complex with a huge range of variables that impact performance and patient care. Managing variability, understanding its impact between departments and organizations, and implementing process improvements can be daunting without the right tools.

Simulation gives you the ability to test ‘what if?’ experiments to safely assess the impact of changes across a unit, hospital or entire health system.

It incorporates the real life randomness that you’ll experience every day. Patients are all individual with conditions developing a different rates, they don’t always arrive to appointments on time, and each appointment may take different amount of time, depending on patient needs.

By including this variability, the simulation reflects reality and behaves in the same way as it would in real life.

What are the benefits of simulation in healthcare ?

1. Identify where problems are happening 

Simulation can utilize your existing data to form an accurate view of operating rooms, emergency department and inpatient resources within a hospital or health system.

As simulation is visual, it allows you to quickly find problem areas down to individual procedural areas, beds, staff utilization, and more.

2.Test improvements in a risk-free environment

Simulation uses predictive modeling to show what will happen as a result of process changes or external factors. It enables you to test changes and measure their impact on issues like waiting times, staff scheduling, ED and patient flow, cost structures or any other KPIs.

Using the data and insight from simulation, you can build stronger business cases and stakeholder buy-in.

3.Confidently plan for the future

Simulation takes the guess work out of strategic planning. With the ability to run scenarios years into the future within seconds, you can assess the impact of strategic and population health changes.

This enables you to make confident decisions that will ensure long-term financial and operational performance.

USE OF SIMULATION IN BANKING SERVICES

1. LIQUIDITY MANAGEMENT

Current correspondent accounts balances form the essential part of the bank liquidity. High balances of the correspondent accounts lead to the yields reduction, but credit organizations tend to maintain high balances due to liquidity risks and ongoing payments support. We need to pay attention to the fact that the behavior of the items which affect the state of liquidity is quite stochastic. The absence of models which can forecast their behavior can lead to unnecessary interest expenses and insufficient yields. A simulation model analyses the current state of correspondent accounts balances, incoming and outgoing payments transactions, clients’ requests and forms a daily balance. This helps to maximize yields and guarantees a rated delay on the current payments.

2. ATM NETWORK OPERATIONS MANAGEMENT

It is inevitable that some stoppages during ATM network operations would appear. Stoppages occur when the ATM cassette is empty and the client receives a denial of the request for cash. The accumulation of the excessive amount of cash in the ATM is another unwanted situation. A simulation model can deal with a complex task: it can define a schedule of the ATM cash loading and proper volume of cash; it can also optimize the route of cash-in-transit guards who renew the ATM cassettes. The location of each ATM stations, the remaining amount of cash and frequency of usage are set at the input of the model. The definite schedule of ATM cassette renewal, the order of renewal and amount of cash for each ATM are formed at the output of the model.

3. CORPORATE CUSTOMERS’ BALANCES MANAGEMENT

Recently the new service of cash pooling has appeared in Russian banking system. Notional cash pooling has the company combine the balances of several accounts. This service allows holding companies to combine their subsidiaries’ accounts and effectively divide money between them to have a single overdraft limit. The part of money from master account is taken by the bank, which increases the bank’s yield. The simulation modeling task is to define the sum of money which the bank should earmark for the ongoing operations of the holding company. The quantity of current customers’ account balances, prospective incoming and outgoing payments to the subsidiaries’ accounts are set at the input of the model. The structure of the subsidiaries’ reserved money is formed at the output of the model.

4. FINANCIAL RESULTS AND BANK KPI FORECASTING

Every bank tends to forecast the financial result and its fluctuations depending on some managerial decisions, such as the increase of a loan portfolio due to decrease of the loan interest rate. It is often made with the help of MS Excel and the software of statistic modeling. The model developed in AnyLogic simulation software provides much more accurate forecast of the financial result and helps to choose the most effective managerial decision. The model analyses the dynamics of aggregate financial results indicators within a definite period of time for the definite market behavior and the management of the assets and liabilities. The following market behavior scenarios can be used:
Normal state
Local crisis (cash flow)
Market crisis
System crisis

The detailed report on the properties of the Assets & Liabilities Statement for the definite time period (balance amount, average weighted interest rate)is formed at the output of the model.

5. BANK BUDGET PERFORMANCE ESTIMATION

The forecast of the bank financial performance for the quarter or a year and its comparison with the budget assignment for the corresponding period of time is one of the important issues. The following items can be used as financial indicators: Net Interest Margin, ROAE, ROA, Cost / Income, Deposit / Loans, Growth in Net Income. Estimation of the financial indicators can be delivered by simulation of the bank balance management at the required time period. The growth (reduction) scenario of the balance management statements (loans, deposits, current volatile customer accounts, etc.), changes of interest rates and nominal terms of financial instruments can be used as the model input parameters.

6. BANK RISK MANAGEMENT

Risk-taking is the basis of banking sphere. The bank is successful when it adopts reasonable risks which dwell within its financial capacity. In order to implement this approach the integrated solution is needed, which performs data collection, forecasts aggregate risk indicators depending on time for various scenarios of the market behavior and asset-liability management. Simulation modeling and AnyLogic software form a good basis for creating a risk management model. The access to databases helps the modeler to process the detailed data on the level of accounts which give characteristics of the financial products. These characteristics serve as input data to the simulation of individual transactions. The indicators which correspond to the primary objectives of risk management, including the EAR (earning at risk), EVE (economical value of entity), VAR (value at risk), market assessments, indicators of the interest rate gap and a liquidity gap are formed at the output of the model.

7. BANK IT-INFRASTRUCTURE OPTIMIZATION

IT resources management and IT services efficiency increase is a very important issue in the banking sphere. Frequently the IT infrastructure of a company is very discursively formed in response to some major business needs. As the result IT structure is quite a complex system from technical and economic point of view. There is a wide range of problems which should be advisably solved by simulation modeling, e.g.:
determination of the number of service-desk personnel required to ensure the efficient operation of the bank
estimation of the expected profit from investments in IT resources, such as hardware renewal
analysis of the effect of transferring some functions to external third parties (IT-outsourcing)
System crisis

8. NEW PRODUCTS LAUNCHES AND ADVERTISING RESULTS

One of the major simulation areas is the evaluation of the outcome from marketing activities implementation. Evaluation of profitability and risk of the new products launch (for example, a new loan proposal) or the effectiveness of advertising campaigns evaluation are the typical simulation objectives. Agent-based modeling is normally used to solve such problems. The model describes a typical behavior of a client (agent). The effect of the event implementation is evaluated on the basis of interacting agents.

9. ESTIMATION OF THE COST FOR INCREASED RISK PRODUCTS

One of the urgent issues in the banking sphere is the estimation of the cost (interest rate) of bank products with a high level of risk, for example, deposits with an early partial withdrawal or replenishment, credits which provide the possibility of early redemption. Additional features often lead to an increase in interest and liquidity risk, which must be compensated for by decrease of interest rates for deposits and increase of interest rates on loans. The calculation of the deviation of interest rates under different scenarios of market and customers behavior can be carried out using simulation, in particular, using agent-based approach.

CONCLUSION

Simulations are used for a range of applications across industry, saving time and expense while being able to test theories and ideas before implementing them in the real world. Although related techniques such as digital twin may provide added benefits due to the two-way flow of information this allows, simulations still have a great many uses in service industry.