Insights from the Girard School of Business and the School of Science and Engineering
When most people think of data in relation to business continuity planning, they focus on the need to protect data in the case of an interruption in business. However, data also can play a role in making those critical plans.
Data can identify vulnerable areas of a business in the case of disaster, predict incidents, analyze how effective the current recovery process works, and develop ways to restore systems faster.
It’s another area of opportunity for professionals who earn a master’s degree in data science or business analytics. While both concentrations are primarily associated with making businesses more efficient and effective, they can play a critical role in planning to get a business quickly back on its feet if disaster strikes.
What Is Business Continuity?
A business continuity plan helps to ensure that an organization can continue operations during emergencies or disasters or get back on its feet as quickly as possible.
Disasters can take many different forms. Common challenges include a fire in the place of business or at a warehouse, a malware attack that shuts down information systems, server failure for an eCommerce business, and natural disasters such as a hurricane or flooding.
Business continuity is not merely data backup, although that is part of the plan. It involves maintaining or quickly resuming operations in every phase of the business. Ideally, a business can maintain “continuous uptime” while damage is repaired.
That’s valuable when every hour lost can cost a business thousands of dollars.
Data and Continuity
Large data sets give business leaders a more complete picture of their entire operation. That includes how employees operate within the business, how customers interact with its services and products, and how the company’s systems operate on a regular basis.
This type of information is especially useful when it comes to continuity.
Data scientists can help anticipate what might happen during a business interruption by doing analysis based on different types of disasters. They can identify an organization’s vulnerable areas and propose solutions.
These processes include:
- Predicting potential, critical incidents
- Analyzing risks and testing the best methods for handling them
- Analyzing the current recovery processes for effectiveness
- Developing methods to restore systems quickly
- Identifying the best methods for systems backup, and when they should be done
Data can also help answer questions around business continuity. Is there remote access to important data in the event of an incident? Are there proper communication channels in place? These issues are all part of the analysis of a current continuity plan before changes are made. Merrimack College’s graduate degrees in Data Science and Business Analytics prepare students to address these areas.
Using data to analyze potential threats and the best practices in the event of business interruption can include a variety of issues. Following are two of the most important.
With the risks identified, data can also determine key personnel that needs to be involved and at what point. Continuity plans ensure that all the key employees understand their roles and responsibilities in relation to data management – both during regular operations and during an emergency.
Good Data Hygiene
Like a trip to the doctor after years of neglecting your health, an incident that interrupts business can expose issues that companies did not know about if they have not properly managed data. A better move is to have an accurate map of where data is stored, who can access it, how it is accessed and how the data is used. Having detailed knowledge of these issues can lead to better business continuity plans.
Business continuity is a critical issue. While data won’t cure all the ills of a poorly conceived business continuity plan, it can support the creation of a better one. It’s another way data can make a business more efficient and effective, and an area where those with expertise in data are valuable employees.