How can you learn something new?

August 27, 2013

I’m not asking about how you are learning about competitive intelligence. Hopefully this blog, the books I recommend, and other sources are doing that right now. My question refers to the process of mastering new material when you are starting a competitive intelligence task.

 Of course if you doing this for yourself, the odds are that you know the subject matter already. Or you think you do, anyway. Then ask yourself, “If I know the subject matter, why am I doing more research?” The answer is you don’t really know what you need to know. You just know you have a problem.

 So how to approach learning something new? This focus may be more about your target, details of a mechanical or chemical process that is critical to your research, the regulatory or cultural environment in which your competitor operates, etc. In most cases the process is the same.

 You can just jump in. This is probably what we do most of the time. We look at the topic, and then set off collecting data on it, without really deeply analyzing the data as we collect it. There’s nothing wrong with that, so long as you intend to analyze it, and not merely parrot back what you have (can you say cut and paste?).

 One way to teach yourself is to look for a background resource. By that, I mean a long news feature on the rise of part-time work, or a website explaining the mechanics of the salamander broiler, or even a Wikipedia site on environmental regulations in Canada. But always keep in mind that whatever the source you’re looking at has its own perspective, which a nice way of saying bias.

 Once you have that initial source, look within that source for references to other places where you can get more of this kind of background information. Then go to that site, place or publication. What you are trying to do is to weave your own tapestry of background knowledge so that you can then make sense of the data you’ve collected. To do that you must look to multiple sources, particularly from different perspectives, and weave them together in your mind into your own overall picture. Sometimes, when you are dealing with particularly complicated issue, it is useful to write out or dictate what you think you have learned. You’d be surprised how often you come up with insight about your project by organizing your new background knowledge.

Now with that background established, look at the data you have previously collected. If you find you still do not understand something, go back and add to your background research. Develop a piece of the tapestry for that new issue and then return to your raw data. One additional benefit of this approach is that you are being forced to approach the data differently than you usually do. I believe one key to making sense out of the pile of unconnected facts is to find ways to look at the facts differently. This is yet another tool to help you do that.


Look away

When you try to make sense of your CI data and can’t seem to do so, what do you do? If you’re like most people, you just take a look at your notes and materials again, and you review the most recent draft you made of your report or presentation, and try to puzzle it out. There are better ways to do this when you really are stuck.

The key is to take your mind off what you’re doing, but to have your mind still operate in a similar channel.

Let’s say your problem is dealing with something that has a confusing chronology, such as tracing the launch of a product, or the expansion and modifications of an old factory. You probably have your notes arranged, either physically or in your own mind, in order, from the oldest to the newest. Try reversing that. Start reading your chronology backwards, from the newest to the oldest. You are still trying to analyze the chronology, but by changing the way you are looking at it, you are forcing yourself to read exactly what it is that you have, rather than just to skim over what you already “know” you have.

Sometimes you have to look away even further.  Assume you are working to analyze a very complex situation. The nature of the problem is really not relevant. What is important is that you are trying to look for patterns, keys, or even missing pieces. What you are looking through is a field of unconnected, disparate pieces of data.

You should do something separate from the project that you are working on which forces you, even for a brief period of time, to transfer your pattern analyzing skills to another context. What do I mean by another context? It can be as simple as playing an online game of chess or even Solitaire. Doing that forces you to look for and develop patterns, as well as to fit your activities into pre-existing, predefined patterns.

When you are doing this, you are still working on your project. While you are looking away, your mind is still churning around on your problem. You’ll be surprised how often, when you return to your project, you can now make more sense of it.


Assumptions

August 14, 2013

When analyzing the data you collect to develop CI, sometimes you have to make assumptions. Actually, you have to make a lot of assumptions a lot of times. Some of them a very small and it is usually safe to make them. Others are not so small, and potentially more dangerous.

Usually when dealing with assumptions, you know when you are assuming something. You have a gap between two sets of facts or you have a set of facts and you are trying to determine what they mean. There you understand that you are making assumptions, so you are usually careful.

But there is a special problem dealing with assumptions: serial assumptions. By serial assumptions, I mean assumptions that connect with other assumptions or assumptions are somehow dependent on a former assumption. These can be difficult to manage.

Let me illustrate what I’m talking about by reference to a recent article in Bloomberg BusinessWeek[1]. In an article discussing adjustable-rate mortgages (ARMs), the authors noted that, while it is likely that home prices will probably continue to rise, is difficult to predict that by state or by region. That means potential buyers are usually making that assumption, without qualification, when deciding to buy a home with an ARM.

However many homebuyers, according to the article, applying for ARMs also make another assumption, perhaps unstated, about their income. [Note: unstated assumptions are perhaps the most dangerous of all.] Their assumption is that their income will be higher by the end of the loan’s fixed payment period, some 3 to 5 years out. To them, that means that they would be able to handle bigger mortgage payments, even if they cannot sell the house. So they take the ARM and buy the house.

The article makes very clear the danger of these serial (and unstated) assumptions: “[S]ays Henry Savage, president of PNC mortgage, ‘When you start making those calculations, you’re playing golf in the dark’”.


[1]More Americans are Gambling on ARMs”, Bloomberg BusinessWeek, August 5-11, 2013.


How do you measure success?

August 6, 2013

As you do your own competitive intelligence or utilize CI provided by others, you will eventually run into the question, “So what’s the bottom line here? How much is the CI worth?”

      Commercial aside: I could just refer you to our book, Bottom Line Competitive Intelligence, but I want to talk about it from your point of view, not mine.

There are two ways to look at this problem. The first is to try to measure things in terms of dollars, which is to answer the question “What is the dollar return from the CI?” The second is to look at what was actually done with the CI.

How do we measure the monetary value of competitive intelligence? There really two sides to that. One is to determine how much more money you made that you would not have made without it or, conversely, how much less money you avoided losing that you would’ve lost without it. The problem is that most decisions have many inputs, so crediting one input with a decision’s entire success or failure is just not right. So you try to assign a percentage to it.

Say you were 60% sure your decision would succeed, whatever that decision is.  Your decision, if right, could produce $1 million in new profits. If you could increase the likelihood of success by 10% by using CI, you could assign a value of $100,000 to the CI. The same kind of calculation works in terms of reducing the costs of failure, although most people prefer not to make those calculations. Why? Because they do not like to be “negative”.

The alternative is to see if and how the CI was used and then determine whether or not the decision-making process was improved. Simply put, if the decision-making process was not improved, or if the CI was ignored, then the CI was worth nothing. If it was improved, then the CI was valuable.

For people who believe that you must measure everything, consider the recent observation by the head of Yahoo: “Just because we have a ruler doesn’t mean we have to measure everything[1].”


[1] Brad Stone, “Can Marissa Mayer Save Yahoo?”, Bloomberg BusinessWeek, August 5-11, 2013.


Between, and Behind, the Lines

August 1, 2013

When doing your own competitive intelligence, often you will read materials released by your target. They can be useful, but you have to understand how to read what is there. Let me give you a few rules on reading these kinds of documents.

First, you want to make sure that you can believe that your target is relatively truthful. If your CI target is a publicly traded company, and you are looking at materials that it has officially released, then you may have at least a degree of security that statements are accurate as presented. As we know from cases like Enron, that is still no guarantee of truthfulness. If the organization is a private company, a nonprofit, a university, etc., you do not have that help.

Second, practice reading carefully. In law school, students are taught about the “negative pregnant”: a denial that is pregnant with an admission. For example, again using the law as an example, an individual may be asked in a deposition “Were you in the [named] motel, room 26, on August 1, 2013?” If the individual wants, he or she can just answer no or repeat the question in his or her answer, “I was not in the [named] motel, in room 26, on August 1, 2013.” Technically, that is correct, even if the individual was in room 25, or room 27. So watch for the negative pregnant, and the other form, the positive statement that contains a batch of carefully chosen, specific modifiers. For examples of this, listen to virtually any political press conference or interview.

The third thing to do is to read carefully for what is not in the document. Many corporate documents are drafted by people whose job it is to make them truthful, without making them too complete. Be aware that in many cases you are up against such people. Therefore, read the documents very slowly and take in each word that is in the document. For each word in the document, there may be other words or topics that are specifically excluded from the discussion by implication. Determine what they are and if that is important to you.

Fourth, determine whether or not the document is intended to do more than communicate, specifically whether it is designed to mislead or is even disinformation. Disinformation is created specifically to mislead, in the case of CI, a competitor seeking develop CI. Disinformation is common. It is also extremely dangerous for those who use it. One danger arises from the fact that, for disinformation to work, most of the people working for the enterprise that distributed the disinformation have to actually believe it. You can well imagine what the impact on them when, at a later date, they find they have been misled.