Time + Place Predictable

One of the main factors to reduce the likelihood of being a victim of a targeted attack is to not be time and place predictable.  This is especially true for “at-risk” personnel who are more likely to be specifically targeted.  What do I mean by at-risk personnel?  These are people that because of their profile, actions, behavior, etc. are likely to be targets of violent crime for economic, political, personal or other reasons.  Some examples might be:

  • Expatriates or long term business travelers living/working in a high crime or poitically unstable area.
  • Politicians, activists, journalists or others that take a political position that may be at odds with people or groups prone to violence.
  • Stalking victims and victims of domestic violence.
  • People working in cash businesses or people working in business where they have access to unusually large amounts or money or valuables.
  • Celebrities and others that have a high public profile such as broadcast journalists.
  • Business people involved in disputes with partners, customers, suppliers, etc.  This is particularly true in the developing world.
  • Witnesses in criminal cases.
  • Judges and lawyers depending on the type of cases they handle.
  • Government personnel such as diplomats or military personnel stationed abroad.
  • High net worth individuals

People who are at-risk or more prone to be the victim of a targeted crime should consider the role that time and place predictability plays in these types of incidents and take steps to reduce their vulnerability and mitigate the risk.

As was discussed in the posts on surveillance detection most criminals, terrorists and other violent actors will conduct some type of surveillance to determine locations where there victim is both vulnerable to attack and predictable.  The greater your predictability the easier you make it for this type of assailant.

For most people two locations are place predictable: home and work.  For many people there may be others like the gym, a favorite restaurant or a favorite place to get coffee.  For most people there are defined routes between home and work that are taken everyday or almost everyday and there are points on these routes – typically chokepoints – where they are particularly vulnerable to attack and where there are points of concealment and ready escape routes for the attacker or attackers.

By varying routes and departure and arrival times at-risk personnel can at least make it more difficult to attack them.  We will discuss route analysis in greater depth in a future post.

Historically a large number of kidnappings and assassinations have occurred in the morning as the victim left their home.  A classic example is the 1992 kidnapping of Exxon executive Sidney Reso which is often used as a case study.  Reso was kidnapped by a former Exxon employee as he left his New Jersey home one morning.

Arguably most people are most predictable when leaving home in the morning.  For most too there is little opportunity for variance of route at this point as they can usually turn right or left and that’s it.  For this reason — and because of these constraints one thing you can do is recognize this vulnerability and heighten your awareness when leaving your home as we discussed in an earlier post.

People are creatures of habit.  Often in the workplace even if an employee doesn’t have an assigned parking space they generally park in the same area each day.  Understanding these vulnerabilities and making a conscious effort to change them or at least heightening awareness at these key times is a critical element of a good personal security plan.

Does everyone need to focus on varying routes and times to not be predictable?  I don’t think they do.  I think this is more important for people at risk like the examples mentioned above.  I do think everyone benefits from recognize these vulnerable points and times and raising their alertness level accordingly.  Circumstances change and the person who may not need these measures today may be at risk tomorrow.

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