I’ve seen many definitions of the term “data science.” I think it is best summed up as the art of studying data and pulling insights out of it that can practically benefit your business and bottom line.
That’s fine, you might be thinking. But why are you talking about data science in a blog dedicated to business continuity and IT/disaster recovery?
The answer is, because one of the areas where data science can help you is in business continuity and IT/disaster recovery.
Ways Data Science Can Help with BC
How can data science help with business continuity? … Let me count the ways.
Here are a few of them:
- Helping you anticipate organizational risks.
- Assisting you with the plans to address those risks.
- Helping you communicate about business continuity issues, needs, complexities, and plans with staff members and shareholders.
- Contributing to your analysis of disruptions and emergencies.
- Helping you leverage post-disruption insights to strengthen your teams and improve outcomes in the future.
- Helping you promote a culture of resilience throughout the organization.
- Uncovering areas of potential opportunity.
Do you enjoy instant gratification? … Me, too. Here are three areas where data science can help you right away:
- Improving your event response.
- Helping with proactive planning.
- Strengthening your risk mitigation efforts.
Where Does the Data Come From?
Of course, before you can look at data to extract actionable insights, you need some data to look at. Where are you going to get it? You already have it, if you have an even moderately mature business continuity management (BCM) program. Chances are you have already gathered a large volume of data, and all of this can be grist for the data science mill.
Specifically, you can exploit the following types of data and information to arrive at insights which you can convert into beneficial actions:
- Compliance data
- Residual risk data
- Threat and risk data
- Business Impact Analysis (BIA) data
- Recovery plans
- Maps of your sites
- Building information
- Supplier information
- Past event reporting
- Employee population data
Help With Day-to-Day Challenges
How specifically can data science help with the day-to-day challenges of BCM? Here are a few examples:
- Suppose you receive a notification of an impending severe weather event. Data science could help you quickly identify the sites, plans, suppliers, and employees likely to be affected by the event. If could also flag the known gaps in your program which the coming storm is likely to put pressure on.
- Using data science, a Threat & Risk Assessment analysis can help you identify the people, processes, and technology at greatest risk and the residual risks that remain to be mitigated ahead of time.
- A Holiday Business Impact study can reveal the business processes, computer systems, and suppliers most at risk from a disruption due to an unusually large number of transactions that occur during a busy time in your company based on years of transaction history.
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The Importance of Clean Data
In using data science to improve your BCM program, the data is the foundation and the insights you derive from the data are the house. If you want the house to be secure, the foundation must be sound. What does that mean? It means that before you begin a data science initiative, you should make sure your data is:
Your insights are only as valid as your data, so make sure your data is legitimate.
Art and Science
We think of science and art as being opposites, but data science is an art, in a way. It’s the art of extracting actionable insights from data to help a business improve its bottom line and meet its core goals. Potentially among these is making the business continuity management program as strong as possible, to reduce the number of disruptions that take place and to contain the negative impact of those which are unavoidable.
If your organization and BCM team are data-minded and interested in doing everything possible to improve and rationalize your BCM program, you’ll find data science well worth looking into.