When to Use Temporal Reasoning

When analyzing potential policy model source material, you should take particular note of rules, data or circumstances that may change over time. The temporal reasoning functionality in Policy Modeling may be the ideal choice for modeling situations that suggest changeability. Policy Modeling includes a large number of functions to reason with the changing values of attributes over time. Using these temporal reasoning functions, even in some situations that could be modeled without them, can considerably reduce the effort needed both to write the rules and to maintain them in the future.

Some example of rules that can be used to calculate time-dependent items are:

Whether a particular condition is true for a given number of days/months/years in a given time period. For instance, 'the employee has been sick for three or more days in the last month'.
The total amount for a currency or number attribute based on complex logic spanning a given time period. For instance, 'the amount of interest earned on the account for the previous financial year' or 'the total amount of a social security benefit over any given time period'.
Whether or not a condition is true, false, uncertain or unknown on, before or after a specified time or time period. For instance, 'the person been continually employed for all of the previous 12 months', or 'the applicant will be eligible on this day next year'.

Temporal reasoning is used to handle three intersecting areas of change:

changes in policy and rules,
changes in rates and other reference data, and
changes in circumstances.

Common scenarios involving these areas of change include:

Calculations of premiums payable by insurance companies
Payment of and eligibility for pensions or other government benefits that are affected by personal circumstances (for example, unemployment, housing situation, income, age)
Calculation of interest rates to debtors and creditors of a financial institution
Calculation of taxes payable
Payment of salaries or wages, which may be affected by varying pay rates, overtime hours worked and so on. Such data can change on a daily or even hourly basis. Temporal reasoning allows you to determine wages due over any desired timeframe (you are not tied to static, predetermined pay periods)

Changes in policy and rules

Policy and legislation are constantly changing. Source rules need to keep pace with that change if they are to be useful and accurate. Temporal reasoning functionality allows you to extend the ability of a policy model to cope with changing rules beyond what can be achieved by hard coded trigger dates alone.

For example, changing social security laws may lead to the introduction of a Government benefit, or a bank may implement a tough new policy for high risk debtors. In these cases, there are likely to be certain 'trigger dates' on which new parts of a policy model need to become active. However, there may be calculations performed over time periods which overlap these dates, or new rules may apply to new clients in a different fashion than existing clients. Thus there is a need to write rules that can handle situations where both old and new rules may have a simultaneous role in reaching the overall conclusion. Temporal reasoning allows you to do this.

Changes in rates and other reference data

It is common for policy models to feature reference data that is periodically changed. This data is generally kept either in the policy model or an external database and is known at runtime (that is, it is not user-entered data). Typically, these pieces of data take the form of rates (for example, pay rates or interest rates) or thresholds (for example, the minimum allowable pension payable, the monthly fee cap for a telephone plan). Policy Modeling allows you to make updates to reference data easily, while keeping deprecated or historical reference data intact. Temporal reasoning functionality then allows you to reuse a rule to calculate outcomes based on any time period, whether that period uses older, newer or a mix of reference data. Explanations for outcomes that encompass changing reference data allow you to easily see the components of that calculation or result attributable to each reference data period.

Changes in circumstances

In policy models that calculate outcomes based on the circumstances surrounding a particular entity or group of entities (for example, people, businesses), difficulties can arise when those circumstances change on a rapid (for example, daily) basis. As an example, the total amount of money a health insurer pays to a customer may be dependent on the severity of the illness or injury, which can vary from day to day. Similarly, a government might pay an allowance that is affected by whether the recipient is co-habiting with someone else. If the recipient concerned is continually moving in and out of co-habitation status, it quickly becomes onerous to calculate the cumulative amount of allowance payable over, say, a year, unless temporal reasoning is used.