Early in my career, I supported the computers that ran a machine shop factory. The factory was a large, open room filled with machinery of every sort designed to form, cut and polish metal fixtures. I remember things about that factory. One memory is of the smell of machine oil. Another memory was of the cleanliness of the aisles between the production machines. The primary memory, however, was of the sound. When the factory was running (most of the time), there were all kinds of sounds. Drills, cutters, polishers and packaging machines were operating at the same time. Though it was possible to carry on a conversation in the factory, it was not the best place to hear or communicate important messages. Of course, overhearing conversations was just about impossible.

There were ways to get around all of this noise.

• You could take advantage of the times that the factory shut down. That removed all of the background noise. Unfortunately (if your goal was talking instead of production), this happened very infrequently.
• If you knew exactly who to talk to, you could move close to them and speak loudly. If you were the listener, the right strategy was to focus on the speaker’s words while ignoring the barrage of other sounds.
• If you wanted to “overhear” something, then the only recourse was to become involved in the conversation. That, of course, depended on the acquiescence of the other participants. Thus, you were unlikely to hear much of value accidently.

Conversely, some approaches would only make the problem worse.

• You would not want a goal of hearing everything that was being said in the factory. That would simply complicate the problem of separating an important conversation from the background machine noise. Lack of focus was a sure way to hear nothing of value.
• You would never want to amplify the sounds in the factory. Though this might increase the volume of the speaker’s voice, it would also increase the sounds from the machinery.
• You would not want to encourage people to whisper. Obviously, this made it harder to hear since the level of noise would overwhelm the conversation

Both of these lists could go on and on. They illustrate the common problem that we have of separating the important from the unimportant. The difficulty arises because every important communication is surrounded by background (i.e., contextually unimportant) noise. The world (much like the factory) is full of noise. What we want to hear is typically competing with so much that is unimportant (or less important). Furthermore, sometimes we want to “overhear” or discern things not originally meant for us. The background noise makes that task especially hard.

Thus, we get to the fundamental task in competitive intelligence. That is, targeting the signals that we desire to hear, decreasing the “volume” of the background noise and, finally, interpreting the important signals correctly.

Unfortunately, many CI organizations apparently follow a different strategy. That is, there is little strategizing about the right signals, the methods employed are often designed to amplify rather than mute noise and precious little time is spent on excellent interpretation.

Some people say that competitive intelligence is fundamentally about early warning. Seena Sharpe expands this to say it is also about forewarning. My sense is that it is those two things plus supporting effective business strategy decisions. That extension mates the predictive function of warning with the proactive improvement of business approaches and results. After all, what good is competitive intelligence if it does not affect the bottom line?

Okay, here are some thoughts about improving the signal to noise ratio for your competitive intelligence.

1. Check to see if you are intentionally identifying critical signals. A good early warning system process exists for exactly this purpose because its key recurring question is whether you are looking at the right things. Management will be involved in this process with the competitive intelligence team. Their shared question is this, “What is coming that might affect our business prospects or strategies and how can we know, as soon as possible, when it might occur?”
2. Make sure that you are not increasing the noise. In my opinion, there is a seductive risk for many in competitive intelligence. That seduction is the indiscriminate love of data and tools. Our world is awash with data and easy ways to get to it. However, when we disproportionally are attracted to accumulating data, enamored with presentation or convinced that data (alone) causes positive changes in strategies, we are increasing noise at the expense of important signals. Perhaps there should be a limit on data collection activities especially when the cost of collecting more information decreases the time for meaningful interpretations. Thus, the next thought.
3. Rebalance your activities to favor more and better interpretations. Data availability is rarely an issue. History is replete with examples where the information existed, it was known by decision makers and, yet, opponents were able to “spring” surprises. Think of Pearl Harbor when the United States already had broken many of the Japanese diplomatic codes and was reading their classified messages. A retrospective view showed that, due to the sensitivity of the information, no one reviewed the complete sequence and context of the decoded messages. (Avner Barnea recommended an excellent book to me on this subject – “Pearl Harbor – Warning and Decision”.) The Japanese strategy (and possible actions flowing from that strategy) disastrously was missed.  Consider the 1973 Yom Kippur War. Israeli intelligence knew a great deal about the Egyptians and Syrians war plans but did not choose to mobilize in time to repel the initial attacks. Why? In part, there were multiple misinterpretations of the preparations for war. An excellent book on this topic is “The Yom Kippur War: The Epic Encounter That Transformed the Middle East”. This occurs frequently in business too. We accumulate hoards of readily available information using rapidly improving tools but poorly relate that information to strategy decisions. We present abundant data often yet seldom help decision-makers. Not a good combination when it is true.

There is much more to discuss about improving signal identification, decreasing noise and interpreting information better. As Stephen Covey says, begin with the end in mind. If the end is a more successful businesses, then improving strategies by helping strategy decision-makers requires better competitive intelligence signal-to-noise ratios.

The world is noisy. That is not news to anyone. Like the factory that I used to work in, the noise is indicative of activity. However, our challenge is to amplify and interpret the right signals so that others can make good use of the resulting insights.