Can you learn to analyze? (Part 2)

June 25, 2013

As I mentioned in a prior post on analysis, one of the ways to learn to analyze things is to read mysteries. I recently finished reading a 2002 mystery by Robert Ludlum, The Janson Directive.

In it, Janson, the hero, takes a break from the action and plot complexities that are characteristic of Ludlum’s novels. He is forcing himself to go through a “stack of articles…downloaded from online electronic databases of newspapers and periodicals”, in other words, publicly available materials.

In looking at these articles, Janson is looking for “an incidental bit of data with larger significance.…He was looking for a rhyme – a detail that would be meaningless to most people, yet would resonate with something that his subconscious mind had stowed away. We know more than we know [his mentor] liked to say: our mind stores the impress of facts that we cannot consciously re-create.”


The key here is that he reviews these open source materials with no preconception of what is important and, critically, what is irrelevant. He keeps his mind open and lets his subconscious mind work on what he has read over time. Essentially, he “sleeps on it”.

You know something? It works more than you would realize.

Under the Lamp-Post

June 18, 2013

Let me start with three items:

  1. There is an old joke about a woman who happens upon a man who is on his hands and knees under a lamp-post outside a tunnel. What is he doing? He says he is looking for his keys. She asks if that is where he lost his keys. No, he says he lost them inside the tunnel. Why isn’t he looking there, she asks? His answer: ”It’s dark in there; it’s light under the lamp-post.”
  2. Schumpeter’s column in a recent Economist[1] discussed studies indicating that people become comfortable practicing the skills that have gotten them to rise within an organization, but fail to ask how useful these skills are when working at yet higher levels.
  3. Nate Hentoff, a syndicated columnist, recently observed[2] that the U.S. National Security Agency was increasingly relying on the controversial PRISM program as its “leading source of raw material”, reportedly accounting for nearly one in seven intelligence reports.

What do these three items have to do with each other?

I think, from the point of view competitive intelligence, they are all elements of a syndrome that all of us fall into it one time or another. That is to look at what we are familiar with, or what is easy to access, or what is close at hand, or what worked the last time to satisfy our need for data for our competitive intelligence analysis. When we do that, we are all the man looking around the lamp-post because that is where the light is.

That lamp-post for marketers may be familiar trade journals, for lawyers, recent lawsuits, for financial managers, securities analysts’ reports, etc. I think that one of the problems with the current debate about the NSA is that there is a danger that it is justifying its vast data collection activities because that is what they do for living, and are indicating that these archives are valuable because that is where they looked for help, because what they do for a living. That is the NSA lamp-post.

We all have to avoid that syndrome. Now, whenever you are seeking data for competitive intelligence, make a quick list of the sources that you plan to be using. Did you include interviews with former employees of the target that you identified LinkedIn? What about environmental permits and applications? Are you relying only on media reports? Now, stop and look at your list. Have you included any source that you haven’t looked at in the last five or six searches? The odds are you have not.

So try this little trick: take this list of three categories of data sources:

  • Government & Non-profits
  • Private sector (This includes people and organizations whose business directly involves producing or selling the kinds of data you may be seeking, as well as employees of your competitors, your suppliers, and even your own firm)
  • Media

As you can see they are very broad. Now look at your preliminary list of where you are planning to look. Are you looking for something in all three categories? Probably not. Is there one category you tend to rely on almost all the time? That is probably your lamp-post. Look elsewhere.



Data versus Intelligence

June 13, 2013

Too often, people confuse the presentation of data with the delivery of intelligence. There are major differences, since you should be converting raw data into actionable intelligence. Let me give you a hypothetical example.

You just found out that a competitor of yours, World Wide Widgets, has announced plans to build a new plant, Plant Cee. The announcement contained some general details such as where it will be located, how happy the local development authority is to see a new plant (and jobs), and a general indication of the total capacity of the plant. Now you have some data. But this is not intelligence.

To start your analysis, first put it in context. WWW also has two other plants which it bought from two other companies over a period of years. WWW they both produced three similar products: rock, paper, and scissors. Over the past three or four years, WWW has gradually rationalized production in the two plants, moving rock production in bits and pieces from Plant Bee to Plant Aye, and consolidating production of its most popular product, scissors, in Plant Bee. It has also made continuous small improvements at each to increase production.

The announcement of the new plant indicates it will be dedicated to making more scissors to meet rapidly increasing US demand. That US demand is currently being met by importing more expensive scissors made in its home country, Germany. Now you have more context – and maybe information, not just data.

Now add a little more context. It’s highly likely that, consistent with its past management, that Plant Cee, the new facility, will eventually house all of the production of scissors, and that its production eliminating the need to import more expensive scissors from Germany. This is not certain, but it seems likely. Now you have something approaching intelligence.

However, dig back into your research notes, and read what the local development authority you spoke to said about the new project. You did call, didn’t you? For example, she said that Plant Cee will only be half completed, that is, only 50% of the interior will be occupied with production facilities when it is completed. Why? Because WWW is giving itself the option to expand, cheaply, and produce even more scissors in the future, without having to build another new plant. Now we have something:  indications of a major push to dominate the scissors market.

However, should also have found out that, before announcing the construction of the new plant, Cee, WWW considered expanding Plant Bee to meet this increasing demand for scissors. The local newspapers serving Plant Bee said so a couple of years ago.

Where does that leave us? If you think about it, and you should, you can see a pattern here: rationalize and expand. So this announcement of a new plant to produce more scissors foreshadows two different things:

  1. A coming, long-range, massive increase in WWW’s capacity to produce more and more scissors, and to sell therm either more cheaply or with a greater profit margin.
  2. A high likelihood that after the completion of stage 1 at plant Cee, that the remaining production for scissors will be moved to Plant Cee from Plant Bee. That in turn, consistent with WWW’s “rationalize and specialize” pattern over the years, would allow WWW to increase the production of paper at Plant Bee.

That is the difference between just recording facts and applying analysis, simply by putting the facts in a deeper and broader context.

Trade Shows and Business Conferences (Part 4)

June 7, 2013

The trade show, for many businesses, particularly those in the business-to-business niche, represents a major investment and tremendous opportunity to retain existing customers and to development customers. It also represents an important competitive intelligence opportunity.

The first thing you want to do at a trade show is look around. Where are your competitors’ tables and displays located? How big are they? That should help you write ups tonight how much their spending.

Who was not present? It might be useful to ask around to find out why particular competitor is not present. Maybe they are having financial issues or maybe that they moved on no longer represent a direct competitor to you.

If you have a chance, and by that I mean make a chance, visit your competitor tours’ booths and tables. Do not attempt to hide who you are, but then again do not announce your presence either. Look around – in what section do they display? How big is the display? Are there any materials or samples that you can obtain? If so get them

Always ask yourself “What is it that I expect to see here, but no longer see?” You have time after the session to determine what the answer means.

When people come to your display area, if they mention anything about your competitor, such as comparisons of products, service, terms, etc., take the time to engage them in a conversation to understand what they have been told about your competitor. This is a golden opportunity for you. You have perhaps only a few seconds with people who have been approached as potential customers or even are existing customers of a competitor. Feel free to ask them about what they were told. The worst they can do is to tell you “no”.

Make time to walk around the hall. First, visit the booths and displays of your competitors. Second, take time to visit the booths of your suppliers, if they are present, and your own distributors or customers, if they are present. This is a very good opportunity to open a general conversation and see what they have been told, and what they have learned about your competitors.

Do not try to be a spy. By that I mean do not cover up your registration badge so that people cannot see for whom you work, or substitute a badge that looks like that of the different company for your own. Unethical behavior does not pay. You are unlikely to gain anything of real value that you could not otherwise get, and you basically have contaminated yourself. Bad idea.

If you have several people who are at the show, either have one person detailed to work the show from a competitive intelligence point of view, or assign people on a rotating basis the same task.

One suggestion: if a competitor comes into your exhibit area, welcome her/him. First that will throw her/him off base. Second, use it as an opportunity to find out what he or she is looking for. If you know what they’re looking for, you may learn something about what they plan.

 Before the end of the trade show, if at all possible, gather everyone together for an onsite debriefing. While it is busy and many things are going on, this is best done at the trade show or at least after the trade show is over, but before you return to your office or your plant. People’s minds are still focused on what they’ve been doing, they are still fresh from dealing with customers, competitors, suppliers and the like, and they can play off each other in terms of what they heard or did not hear, saw or did not see.

While a trade show is a golden opportunity to do business, is also a golden opportunity to do your own competitive intelligence.

Where is intelligence going?

June 4, 2013

Two interesting pieces raising this question in my mind again. The first was an essay by Ben Gilad, in a SCIP publication, asking whether or not competitive intelligence had become “Googlized”, that is, evolving into a situation where, because of the access to information through the Internet, the practice of competitive intelligence will be in the hands of line managers and not competitive intelligence specialists within large corporations. One key trend underlying this is that many end-users of the competitive intelligence seem to view it as being basically the collection and organization of raw data, and not the critical analysis of that data.

From another point, the recent issue of Bloomberg BusinessWeek featured the article “How the U.S. Government Hacks the World”. There it was reported

“When President Obama receives his daily intelligence briefing, most of the information comes from government cyberspies, says Mike McConnell, director of national intelligence under President George W. Bush. “It’s at least 75 percent, and going up,” he says.”

Let me dissect why I was taken by the quote. First, it described the president’s intelligence briefing as containing “information”, not intelligence. Second, it indicated that at least 75% of the contents of the daily intelligence briefing came from government cyber spies. In other words, they do not come from open source materials or communications with government employees and diplomats, but rather from hacking into the computers of other nations.

Hacking provides data, sometimes information, and only rarely intelligence. Yet it seems that raw data is now what passes for some intelligence at the governmental level. I doubt that is the universal case, and sincerely hope that is not true. For if it is, then the craft of intelligence, at least at the government’s highest levels is becoming more a matter of repackaging data into information than it is providing truly insightful and actionable analysis.

What do these two pieces have in common? In government we see a possible pattern that is similar to Ben’s observations in business about competitive intelligence managers being replaced by data gatherers, not analysts.

What we need for business to function effectively is not more data, whether from open sources or from government cyber spies, but rather insightful and actionable analysis. That is not provided by overwhelming the end-user with data. In the end, doing that only chokes off decision-making by minimizing or even eliminating analysis. It creates the erroneous impression that one knows what is going on, when all that one has is a mass, or mess, of raw or somewhat digested data.

To draw from another discipline, cooking, there is a huge difference between the meat, vegetables, and other ingredients, the raw data if you will, and the intermediate products as delivered by the prep chef, the trimmed meat, the sliced vegetables, ready for cooking. That is the information. Then the chef converts the intermediate products into Beef Wellington, the meal. Preparing the meal is the equivalent of using analysis to generate intelligence. Right now it seems as if, both in the public and private sector, we are in danger of people confusing raw meat and vegetables, or prepared meat and vegetables, with a gourmet meal. If that is the situation, that is worse than unfortunate.