Just a question. I know we have a wide range of people here, with a wide range of jobs.
Just wondering. Is your job or Boss more a proactive or reactive to issues that pop on on the job? Do they wait until things hit the fan before they change or do they see things are changing and alter the way they have the workers do their job?
Mine. Its more of a reactive. They seem to always wait until things hit the fan before they tell us to change how things are done.
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Thread: Proactive or reactive work
07-18-2014, 03:24 AM #1
Proactive or reactive work
07-18-2014, 06:32 AM #2Senior Member
- Join Date
- Jan 2012
- Helsinki, Finland
Depends on the issues. My own supervisors do take in my feedback and react the best way they can, but the higher up the ladder you need to go to get stuff done, more difficult it becomes. Especially so if implementing an idea costs money, such as equipment or security tech issues.
Another story completely is building safety, something which I like to pay a lot of attention to. More often than not it's me or a co-worker spotting some sort of safety risk responsible for the contracted maintenance company to take care of, and they don't do that. Accidents just waiting to happen.
07-18-2014, 08:31 AM #3
O and R.
I leave the pro and react to the guys with the real badges.
Just' say-in.My views, opinions and statements are my own. They are not of my company, affiliates or coworkers.
-If you try to shoot the messenger, this one shoots back
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-The industry needs to do one of two things; stop fiddling with the thin line and go forward or go back to that way it was. A flashlight in one hand and your set of keys in the other
07-18-2014, 11:22 AM #4Senior Member
- Join Date
- Sep 2011
- South Florida
client prefers a proactive approach. stop it before it happens
07-18-2014, 12:27 PM #5Senior Member
- Join Date
- Mar 2013
Security by it's very nature is proactive.
07-18-2014, 01:05 PM #6
We do both. EAS tags, cabling and audits are the proactive things we do. But when they take, that's when the react comes into play.Sergeant Phil Esterhaus: "Hey, let's be careful out there.."
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07-18-2014, 04:21 PM #7Senior Member
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- Join Date
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08-29-2014, 04:28 AM #8Junior Member
- Join Date
- Aug 2014
- Western Canada
We try to be primarily proactive. All of our area security managers conduct regular risk assessments and security audits on all of our clients' sites to ensure that security resources are being used effectively, and that risks are being mitigated appropriately. If there is a more efficient risk-based way to deploy our security resources, we will do that. However, "reactive," or historical, information is also required to make some of these adjustments. We do not, though, tailor an entire security plan around a one time event that had a low risk value to it.
08-29-2014, 09:04 AM #9
As you say, historical data is typically used to help determine both the probability and cost elements of this formulation.
There are a lot of thorny problems with this approach, though, starting with the problem of small numbers. If a client has experienced 2 burglaries during its 10-year existence, can we say there's a 20% likelihood of a burglary during any given year? No, we can't. We simply don't have a sufficient historical sample here to draw that kind of inference.
It gets more interesting when we think about any specific year (as opposed to any given year) - for instance, we're planning security operations for next year. For the sake of discussion, let's say that the 2 burglaries happened during Company Year 3 and Company Year 6. We are now planning for Company Year 11.
The 2 burglaries occurred 3 years apart. We didn't have a burglary in Year 9 or (so far) in Year 10. Even if we ignore the "small number" problem and accept 20% probability per year as historically valid, is our risk in Year 11 really 20%? Or, as we march through time without experiencing burglaries, does the likelihood of a burglary during the NEXT interval period actually INCREASE - perhaps even approaching 100%? The question here is one of the independence of sampling periods - i.e., that probabilities in any period are independent of the experience in preceding periods.
It wouldn't be at all unreasonable to conclude that the longer you go without experiencing an adverse event that has been shown to occur on the property in the past, the likelihood of the next event rises, but the probability model suggests that it diminishes (if we reach Year 12 without a burglary, we might think the likelihood is 17%).
Is an "at-bat" in baseball independent of previous at-bats? If a .325 batter who's gone 0 for 7 in his previous 7 at-bats steps up to the plate, is he "due" for a hit? Statistically, no (each at-bat is independent), but that's not how it actually works out - and we know why. Good batters learn, and they adjust - to the pitcher, and to the situation (e.g., how the defense is positioned). Certain kinds of human threats do exactly the same thing.
It gets thornier when preventive/mitigating measures have been implemented in the past. Suppose that in Year 6, after the second burglary, the Company installed an alarm and improved the exterior lighting, and there hasn't been a burglary since that time. What can we conclude about the interval of time since Year 6 in which there have been no burglaries? Has the risk been eliminated? In other words, are we actually looking at TWO periods of time - Years 1-6 and Years 7-10 - in which the probabilities were actually very different? In years 1-6 we experienced 2 burglaries, for a probability of 33%. In years 7-10 we experienced no burglaries, for a (mathematically impossible, since you can't divide by 0, but we somehow get around this) probability of 0%.
We have three numbers, then: 33% probability (Years 1-6), 0% probability (Years 7-10 after risk reduction - perhaps) and 20% probability (Years 1-10). And of course, we still have the underlying flaw, i.e. that the numbers don't lend themselves to inference in the first place because there simply aren't enough of them to justify doing so. This is actually a fatal flaw in most historically-based risk analysis, but risk managers go whistling past that graveyard all the time, if they even know it's there.
Solve this, though, and there are yet other complicating factors. For instance, physical venues change over time in ways that strongly impact vulnerabilities. If, during Years 1-10, the area around the Company property has changed economically, or if there have been other changes in the occupancy of the immediate area, any of a number of risks to the Company itself can be impacted - for better or worse. The problem here is that our historical information cannot inform us about the impact of these changes at all!!
Company procedures and business activities change with potential risk implications. Employees come and go, and not always on the best of terms. Valuable equipment is acquired, or becomes obsolete or unneeded, and disposed of.
There are even very broad social changes that can directly impact certain kinds of risks - for instance, high unemployment, or shifts in the prices of certain commodities, metals, smaller police forces and less frequent patrols, etc.
Changes in technology or industry practices can impact risk.
When there is a significant shift in the risk environment, the historical data becomes all but useless.
To solve these difficulties, a risk manager might look beyond the immediate client's history and draw inferences from a broader venue (for instance, not this specific chemical plant but chemical plants in general), but that method introduces a different set of problems all its own, and no less challenging.
Even ignoring outliers (catastrophic rare events or frequent low-cost events), "probability x cost" is very problematic, but it provides numbers, and especially in business we worship numbers, even when they masquerade as far more substantial and reliable things than they actually are.
Admittedly, predicting the future can never be an exact science, but it does bother me when I read risk assessments that convey much more of an air of certainty - on which potentially large expenditures might be based - than the underlying inferential jello really justifies.
...and we haven't even spoken about the margin of error yet. If we did, in our example we'd have to say that the likelihood of that burglary for our client isn't 20%, 33% or 0%, but something like "20%, plus or minus X%", which would be a very large number depending on the degree of certainty you assume.
Last edited by SecTrainer; 08-29-2014 at 10:09 AM.A man who will not lie to his wife has no regard for her feelings. - Anon.
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