Month: September 2011

What’s the difference between Business Continuity (BC) and Disaster Recovery (DR)?

What’s the difference between Business Continuity (BC) and Disaster Recovery (DR)? This is a question I have had to answer multiple times. It is a very good question and the answer is not simple! So, as a good lazy ‘techy’, I tried to find the answer on the web. That way, when I am asked, all I would have to do is send a link.

I have used this approach multiple times for other questions I have received. It is convenient and a great way to avoid re-typing an answer. However, this time, I was not very successful in my quest to find an answer. I searched the web, multiple times, for hours without finding the perfect “pre-written answer” I was looking for. So I decided to stop being lazy and write it myself.

Now, if you are like me, and you’ve been looking for an answer to this question, feel free to use this one.

So, let’s start with a few definitions from the Business Continuity Institute (BCI) Glossary:

Disaster Recovery (DR): “The strategies and plans for recovering and restoring the organizations technological infrastructure and capabilities after a serious interruption. Editor’s Note: DR is now normally only used in reference to an organization’s IT and telecommunications recovery.

Business Continuity (BC): “The strategic and tactical capability of the organization to plan for and respond to incidents and business disruptions in order to continue business operations at an acceptable predefined level.”

First, I’d like to say that I have a slightly different view of DR than BCI. Now, who am I to disagree with what BCI is saying? Well, bear with me a little longer and you will see how my interpretation of DR might help people understand the differences between DR and BC better. So here’s my definition:DR is the strategies and plans for recovering and restoring the organizations (scratch technological) infrastructures and capabilities after an interruption (regardless of the severity).

Unlike the BCI, I don’t make a distinction between the technological infrastructure and the rest of the infrastructures (the buildings for example) and nor I do differentiate between the types of interruptions. In my opinion, either a system is down or a building is burnt or flooded, both should be considered a disaster and therefore both require a disaster recovery plan.

Therefore DR is the action of fixing a failing, degraded or completely damaged infrastructure. For example, the 2nd floor of a building was on fire; the fire is now out so the initial crisis is over. Now the damage caused by fire must be dealt with; there is water and smoke on the 2nd floor, the 3rd floor has damages caused by smoke and the 1st floor has water damage. The cleanup, replacement of furniture, repair of the building and its structure, painting, plastering, etc. are all part of the disaster recovery plan.

What is Business Continuity then? Business Continuity is how you continue to maintain critical business functions during that crisis. Back to the example, when the fire started, the alarm went off and people were evacuated from the building. Let say you had a Call Center on the 2nd floor and this just happens to be a critical area of your business. How would you continue to answer calls while people are being evacuated? How would you answer calls while the building is being inspected, repaired or rebuilt? Keeping the business running during this time is what I call Business Continuity.

The same approach can be taken with a system crash or when the performance of a system has degraded to the point that it has impacted business operations. So fixing the system is DR and the action of keeping the business operations running without the system being available is BC.

In conclusion, BC is all about being proactive and sustaining critical business functions whatever it takes whereas DR is the process of dealing with the aftermath and ensuring the infrastructure (system, building, etc.) is restored to the pre-interruption state.

Content Decision Fatigue

If something of value is in short supply you will tend to conserve it. That turns out to be true of your capacity to deal with alternatives, make decisions and even to sustain your efforts at tasks.These finding have profound implications for enterprise content management (ECM).Psychologists have recently described the phenomenon of Decision Fatigue. A recent New York Times article by John Tierney titled, Do You Suffer From Decision Fatigue? gave an excellent overview which I will quote extensively here.The more you make decisions, the less capacity you have to make additional ones in a given period. And these decisions do not have to be hard to deplete your capacity — in fact they can be quite trivial. Once you have depleted that capacity, you generally respond in one of two ways: you make impulsive decisions or pick the default; or you delay making any decision.The biology behind this process is beginning to be understood. It turns out that making decisions takes energy; in fact regions of your brain actually use glucose to fuel decision making. If the glucose becomes depleted it needs to be restored — typically by taking a break and having a snack. Until that happens, these brain regions, especially those involved in impulse control, have lowered activity.However, overall use of glucose by the brain does not change, because other regions of the brain, including those involved in seeking reward, become more active.An increased tendency to make impulsive decisions is also associated with a reduction in willpower. People become more easily distracted and less likely to complete tasks, including completing a series of decisions required of them. Alternatively, they make take the easy way out by picking a default.What does this have to do with enterprise content management? I think it is very important. Let’s consider two examples:

  1. Consumer behaviour on a business website — a web content management (WCM) example
  2. Staff execution of work — a business process management (BPM) example

Website ConsumersOne of the studies cited in the New York Times article compared the degree of decision-making required of online consumers and the consequences:“…Kathleen Vohs, …now at the University of Minnesota, performed an experiment using the self-service Web site of Dell Computers. One group in the experiment carefully studied the advantages and disadvantages of various features available for a computer — the type of screen, the size of the hard drive, etc. — without actually making a final decision on which ones to choose. A second group was given a list of predetermined specifications and told to configure a computer by going through the laborious, step-by-step process of locating the specified features among the arrays of options and then clicking on the right ones. The purpose of this was to duplicate everything that happens in the postdecisional phase, when the choice is implemented. The third group had to figure out for themselves which features they wanted on their computers and go through the process of choosing them; they didn’t simply ponder options (like the first group) or implement others’ choices (like the second group). They had to cast the die, and that turned out to be the most fatiguing task of all. When self-control was measured, they were the one who were most depleted, by far.”Very clearly then the online purchasing process required a series of decisions that online consumers found fatiguing, and which reduced their motivation or self control.The tiresome nature of the process could cause some consumers to abandon the website without purchasing the computer, defeating Dell’s aim of selling a computer.But those consumers who complete the process became more susceptible to impulse purchases. This is illustrated in another study:“Levav… put the experience to use in a pair of experiments conducted with Mark Heitmann, then at Christian-Albrechts University in Germany; Andreas Herrmann, at the University of St. Gallen in Switzerland; and Sheena Iyengar, of Columbia. One involved asking M.B.A. students in Switzerland to choose a bespoke suit; the other was conducted at German car dealerships, where customers ordered options for their new sedans. The car buyers — and these were real customers spending their own money — had to choose, for instance, among 4 styles of gearshift knobs, 13 kinds of wheel rims, 25 configurations of the engine and gearbox and a palette of 56 colors for the interior. As they started picking features, customers would carefully weigh the choices, but as decision fatigue set in, they would start settling for whatever the default option was. And the more tough choices they encountered early in the process — like going through those 56 colors to choose the precise shade of gray or brown — the quicker people became fatigued and settled for the path of least resistance by taking the default option. By manipulating the order of the car buyers’ choices, the researchers found that the customers would end up settling for different kinds of options, and the average difference totaled more than 1,500 euros per car (about $2,000 at the time). Whether the customers paid a little extra for fancy wheel rims or a lot extra for a more powerful engine depended on when the choice was offered and how much willpower was left in the customer.”These findings could be used to improve the effectiveness of a website to help consumers make the best decisions to meet their needs, or to make the most lucrative, near-term decisions to the benefit of the vendor.They also point to the importance of reducing the number of decisions that are being asked, asking the most important ones first, and providing default options that ideally are matched to the specific, expected needs of a given online consumer. Business ProcessesMany business processes are quire automated, but typically depend on staff to provide input. This input usually takes the form of decisions, whether those are to interpret handwriting entries on faxes or to approve a purchase order.A design goal for most automated business processes is to process more items while employing fewer staff. Little consideration is usually given to the decision-making capacities of the staff, or the consequences of decision fatigue that will lead to poorer or delayed decisions.A study of Israeli judges reviewing parole application cited in the NT Times article illustrate this very clearly:“Prisoners who appeared early in the morning received parole about 70 percent of the time, while those who appeared late in the day were paroled less than 10 percent of the time.”Those are astounding numbers. The effects of glucose were clearly illustrated:“In midmorning, usually a little before 10:30, the parole board would take a break, and the judges would be served a sandwich and a piece of fruit. The prisoners who appeared just before the break had only about a 20 percent chance of getting parole, but the ones appearing right after had around a 65 percent chance.”The safest, default decision for a judge is clearly to not grant parole. They take the ‘easy way out’ when decision fatigued. SummaryIn my last post I talked about the ‘disjunction effect’ and how users may fail to correctly use the categorizations you designed in your content management system. In a similar manner, the elucidation of ‘decision fatigue’ has clear implications on the potential for success of a wide range of content management solutions.

Fuzzy Content for Fuzzy People

Suppose you asked someone to classify some objects such as an ashtray, a painting and a sink, as either “furniture” or “home furnishing”. That would seem to be a straightforward task.

If you also asked them whether the same objects belong in a single group comprised of both “furniture and home furnishings,” you would expect that any object that they classified as either one or the other would belong in the combined or parent group. A logical disjunction. Such assignment tasks are very much like those that we require of enterprise content management system (ECM) users to assign metadata about a content (i.e. digital files) they are adding. Such metadata helps subsequent retrieval through searching and browsing, and potentially supporting dependent business processes (e.g. a triggered workflow).

There’s a problem though. Often people will not make the classification you expect. They may place an object in one of the original categories, but not the larger or parent one if it is the only choice they have! There is a tendency for people to delay making a decision if there might be an outcome they don’t know. Apparently this phenomenon has been documented over two decades by psychologists and is referred to as the ‘disjunction effect’.

I learned about this in a New Scientist article posted yesterday (5 September 2011): Quantum minds: Why we think like quarks.  The article describes one of the first observations of the disjunction effect: “In the early 1990s, for example, psychologists Amos Tversky and Eldar Shafir of Princeton University tested the idea in a simple gambling experiment. Players were told they had an even chance of winning $200 or losing $100, and were then asked to choose whether or not to play the same gamble a second time. When told they had won the first gamble (situation A), 69 per cent of the participants chose to play again. If told they had lost (situation B), only 59 per cent wanted to play again. That’s not surprising. But when they were not told the outcome of the first gamble (situation A or B), only 36 per cent wanted to play again.”

Traditionally in ECM we have held that it is difficult to get users to add metadata to describe the content they are adding; in essence that users are lazy. We have not considered that the choices presented to users, and any concurrent information presented, will actually change whether they provide the necessary data, when they provide the data, or indeed the actual values they choose. ECM taxonomies are built on the assumption that users can make logical decisions to correctly describe content. Typically we present mutually exclusive choices, often organized in hierarchical (parent-child) fashion. But as the New Scientist article notes, people employ a kind of quantum logic that allows for something to be a bit of two exclusive alternatives, and for the context of the classification (the measurement in quantum terms) to affect the outcome. As a result their content classifications are fuzzier then we expect or perhaps need.

Content is often described as unstructured information. Metadata schemes are commonly applied to impart a structured framework to manage that unstructured content, but the fuzziness of human logic may make this doomed to failure.