October 24, 2018
Today marks the end of this Blog. I will leave the hundreds of blogs I have written up here for a year or so, and then turn them all over to the Centre for Intelligence and Securities Studies, Mercyhurst College along with all copyright rights.
The reason for this is that I am retiring. I am following my beloved spouse and business partner, Carolyn Vella, who retired from The Helicon Group, which she founded, some time ago for health reasons.
Carolyn is now recuperating in hospital from major kidney problems. I expect her home in a couple of weeks. I am spending full time with her now as she goes through her physical rehabilitation.
September 19, 2018
Over ten years ago, I spoke to a SCIP chapter in Atlanta about some of the major problems I saw in CI, now and in the future
Here are the notes for that discussion.
Current Major Flaws in CI
Most CI staff are forced operate by looking into a rearview mirror. That means that management rarely gets a view of where they are going, but rather of where they and their competitors have been. For example, virtually all of CI’s current processes, including in particular the use of KITs and KIQs, are backwards looking and reactive. Ultimately, they lead to the production of CI with less and less value. And that makes those providing the CI of less and less value.
- Solution: Phase out KITs & KIQs. Let CI staff be freer to anticipate needs, to work directly with key end-users.
Many CI collectors and analysts are being forced to use less and less primary sources by a variety of technological and legal restraints. But, this increased reliance on secondary sources actually tends to support a growing image of CI as akin to library work. And that image may be right!
- Solution: Get clear guidelines/ethical statements affirmatively allowing for primary research; point out where lack of primary research, interviews, attending trade shows, etc. is constraining CI. But don’t whine!
Too many efforts to integrate CI with market research fail. In fact, these efforts are almost always doomed to fail. Why? Because CI is qualitative and MR quantitative. Most MR managers cannot deal with what they see as a lack of precision in CI. And most CI analysts cannot understand the obsession with “numbers”.
- Solution: The very few successes have occurred when the head of the combined unit either (a) comes up through CI or (b) has been a “customer” of CI in the past.
Your client knows more each day, or at least thinks he does. But what he knows might not be right.
- Solution: Read what your client reads and get critical CI to her before she asks for it. If trade sources are wrong, make sure to point that out!
CI as we know it today totally fails to provide any meaningful tools for the next generation of managers who expect, or will be expected to, do their own CI.
- Solution: Wait a few minutes.
Fatal flaw – not all intelligence has to be actionable. Generating real understanding in a clear context can be critical.
- Solution: Increased education of end-users and decreased use of KITs, etc.
Some Failures That Will Emerge Due to Reliance on the “Government Model”
First, a question: According to some, intelligence analysis in government is still not a true profession. Why should we assume it is in the private sector? Just a thought?
The Government Model – the black box after 5 decades. Based on looking at a few targets, most of which generated external “objective” data, coupled with access to secrets, often internal deliberations.
Now being challenged for several reasons:
- Too many end users
- Too rigid in needs determination – Sound familiar?
- Too driven by the reports to be given instead of the intelligence on questions yet unasked out there
- Still believing that secret data is more useful than data in the public domain – essentially dissing analysts!
- Focus on the short term, not the long term
- Focus on what the other side does, not what they think or what they feel
- Too much demand for certainty; drives out dissent in name of unanimity
- Designed to focus on one or a few targets; not a functional model in an era of multiple, changing targets.
- End users also get data, good or bad, from other sources. Intelligence no longer the sole source anymore. Again, sound familiar?
- Buying into the end users definition of needs begins a buy-in process of their biases, their politics, world view, etc.
- Analysts are too far removed from end users of intelligence, with exception of military/tactical, that is battlefield intelligence.
- Lack of experienced analysts to train the next generation of analysts. Current training lacks hands-on “interning” type environment that is most helpful. Also lacks the ability to test analysis of the analysts.
- Inability to deal with “too much” data. Just what do they do with all of that take from the NSA? Welcome to the Internet Age!
These same failings are occurring or will occur in almost every case for the private sector. Why? We have adopted, or at best adapted, a flawed model.
Biggest Future Unmet Needs
Above all of this is a problem not yet recognized by CI. That is the problem of success.
In the past 25 years, the most common model was a formal (or informal) CI unit, charged with collecting data, generating analysis, and communicating the finished intelligence to an end-user. In some case, the unit was one person, serving as both collector and analyst; in others, it was a dozen or more people, dividing among themselves collection and analytical functions.
CI is finally achieving its goals: incorporated in graduate schools, understood by other disciplines, talked about at the AMA [marketing], MRA [market research], SLA [libraries], AIIP [information brokers], LMA [law office managers], PDA [product development], ASIS [security].
In 1986, Carolyn Vella warned that CI could go the way of strategic planning. She meant the over promising, over bureaucracy, etc. that marked SP at that time. At it turned out, strategic planning’s association imploded as planners were replaced by executives telling manager to do their own planning. CI may be close to that position.
Now, as CI becomes integrated into other business processes, a new model is emerging – not easily. That is one where the collector, the analyst, and the end-user are all the same person. CI’s present models and processes do not fit that new archetype, whether it is in the areas of ethical conduct, needs determination, communication, data collection, or utilization.
The CI cycle and all of the literature surrounding it no longer applies – Needs, Collection, Analysis, Dissemination, Utilization.
What about ethics – where is the check on unethical means of collection?
- Revise ethical policies to acknowledge the incorporation of CI into general management. And really train everyone on them. Yearly, if needed.
Where is the pushback in defining needs more sharply when you do it yourself?
- Stop before you start collecting, even though you have already been doing it. Recall your time as a student. Realize that collection and analysis are now not merely linked – they are merged!
Where is the need to write up a separate analysis when you just synthesize it into what you are doing?
- It is good practice to separate what you know, suspect, and yes, guess, in a report or presentation. You are not God. Don’t deliver a message on stone tablets!
Where is the review of what you did before you present it to be used?
- Get someone else to at least read it – critically, really critically. If you cannot deal with that thought, your work product probably could not stand up to it anyway.
Where is the completion of analysis when the data is just absorbed as it comes in?
- It is not a bad thing that the analysis is continuing – changes in the competitive environment don’t stop for your Monday briefing, do they?
Where is the feedback in terms of success of the intelligence work?
- You had better learn to evaluate what you do poorly – you know what you do well.
Where is the ability (or is there a need) to justify the costs of getting the intelligence?
- If you cannot use what you collect, why are you bothering? Develop new targets, new data sources, new tools!
Where is the application of a variety of analytical tools? To a man with a hammer, everything looks like a nail!
- This is a problem now for analysts. In most cases, you only have to decide if you are assembling a puzzle or proving/disproving a working hypothesis. Remember, if you think it is only working with a puzzle, how do you know the pieces you have are even from the same puzzle!
What is the relationship with the library/information center process?
- They can and should become your first stop in collecting data. Even if they do not have the data you need, they can help identify where/from whom you can get it. They should become more valuable, not less.
What kinds of skills are needed? The current CI research indicates that there are a variety of skills needed to be a CI analyst. The odds of having them in one person are nil. In fact, a parsing of these skills divides them into the Nero Wolfe-Archie Goodwin divide. If they are hard to get in one person now, how do you add them to a batch of OTHER skills/training a manager must have?
- Here, you will have to just make do. No one has all of the skills that they need. Just work at acquiring new ones and polishing old ones.
What this all means is that without a new CI process aimed at the end user as analyst and/or collector, they will misuse CI, produce poor CI, or none at all. At best they will be subject to what one critic of US intelligence has recently called, and I paraphrase, the spectacle of the collection of factoids driving out real thinking.
Note: Oddly enough, this disconnect does not apply to the outside source of CI. There, the current CI model would seem to work perfectly well there, with the exceptions noted earlier. And, based on our experience, as well as the facilitated sessions at SCIP06, company restrictions, such as above, may actually drive work towards outside consultants.
What are the overall solutions for CI to avoid imploding as it achieves success?
In no particular order:
- Admit that CI is not a profession. Lawyers still refer to their practice, a “guild” term.
- Redirect training at SCIP and by private consultants to training non-CI professionals in CI. Already those in security are looking at CI (defensive) as a new tool. Others will too, and soon.
- Train all managers who might conduct or use CI on what CI really is. Stress the concept not the process. CI is a tool for sales, marketing, crises management, and strategy. It is also a tool for human resources and many other functions. Recognize that and deal with it. The Baldrige Awards already have – for years!
Looking back, I do not see much progress on any of these, do you?
August 6, 2018
This blog will not publish again until the week of September 4, 2018. Our office was flooded out in the heavy rains of August 3-5. We will reopen on September 4.
June 8, 2018
The other evening, I attended a chapter meeting of SCIP. To tell the truth, I was there to plug our new book, Competitive intelligence Rescue: Getting It Right. We had a very fluid discussion among those attending, all very experienced in competitive intelligence.
One of the topics that emerged was Millennials. For the sake of privacy, I will not attribute specific comments to anyone. Besides, some of this contains my interpretation of the impact and meaning of these personal observations.
Here are some of the observations and my comments on them:
- Millennials seem to believe that they can easily evaluate the veritable sea of data because they swim in it every day. That often means that they are not interested in a formal analysis of what that data means, i.e., intelligence, but rely on their interpretations, made on the fly. That, in turn, means that they are relatively self-centered in their assessments.
- Millennials are cautious about or even suspicious of what they see and hear, being raised in a world surrounded by data that is very often unverified and sometimes inherently questionable. That data ranges from advertising to news sources. Oddly, they are not so cautioous about what they receive from personal sources, which has its own downside.
- Millennials tend to gravitate to secondary data when making decisions, since they have the Internet at hand (literally), a magical source of secondary data. But they shy away from accessing primary research data, that is data developed from interviews of relative strangers. That is because they are reluctant to talk with others, particularly those who are not already a part of their own social or work environments. Many strongly prefer to use email or texts to telephone or face-to-face communications. That, of course, means the immediate loss of the context provided by listening for inflections, pauses, as well as watching body language.
All of this bodes poorly for the creation, use, and impact of CI in their day-to-day business activities.
May 3, 2018
Recently, I read about a new factory in a trade publication. I will not name the magazine or company because it is not relevant.
The article touted the new technology and safety of the plant, indicating that it was to replace a factory owned by the same firm that had been in the area for about 50 years. The company’s representative quoted in the article praised the firm’s long ties to the area.
At the very end, the piece noted approximately as follows:
“The company plans to fill all of the positions at the plant with employees from the closed facility.”
Sounds nice, doesn’t it? The workers from the old plant will migrate to the new one, right? Think of reading this very closely. How? Try moving the modifier, “all of the”. It now reads:
“The company plans to fill the positions at the plant with all of the employees from the closed facility.”
But the actual quote does not mean this. Now you understand that the sentence actually means some employees at the closed plant will NOT be working in the new one. What was not said was telling you more about what is actually going on.
“Yesterday, upon the stair, I met a man who wasn’t there.” Hugo Mearns
March 5, 2018
“Got a revolution, got to revolution.” Jefferson Airplane, Revolution (1969)
in our new book, Competitive Intelligence Rescue: Getting It Right (Praeger 2017), Carolyn Vella and I relate a case dealing with DIY CI (chapter 8). . Let me give you a couple of my thoughts on DIY CI.
Remember that the CI universe today has three basic research and analysis epicenters:
- CI professionals within an enterprise (including adjuncts such as researchers sited in libraries/information centers)
- Independent CI professionals who consult for/research for that and other enterprises
- Internal DIYers.
My own perception is that the first group is static or growing slowly, the second is stable or slightly declining, and that the third is growing steadily. Compared with 10 or 20 years ago, the existence of DIY CI marks an important evolution, if not revolution, in CI. Those growth trends, if they continue, may fundamentally change the CI “business”.
One plus from this is that it shows an increasing use of CI in enterprises, coupled with better access to end-users, particularly since the end-user in DIY CI is the person who generates the CI. It should also mean that the time between a perceiving a need for CI and its creation could fall.
However, there are also some minuses:
- Those producing the CI will necessarily have narrower experiences in producing it, since they deal only with one client. That could result in a loss of professional perspective or even the failure to develop it.
- The use of elicitation interviews will necessarily fall, thus diminishing use of a proven, valuable primary research resource.
What does this mean? One consequence could be that CI degenerate into several subspecialties where experience and developments are not easily transferable, such as IT CI, pharma CI, B2C CI, etc. Another consequence could be that CI could morph into a discipline that will not be able to look forward as easily as is it can look back and look at the present. Why? Because data on future actions and intentions lies with people to a significantly greater degree than in published sources. A third could be the separation of early warning processes from everyday CI, in part due to the lack of necessary broad perspectives among internal personnel.
What to do to keep these trends from “damaging” CI? (Sorry, I know that is a loaded question, but that is how I see it):
- Institute regular awareness sessions and focused training both on producing CI and on using it. To avoid inbreeding, vary the sources for that training. That is use insiders, then external resources, and vary the outside providers over time.
Establish a stable of outside CI professionals pre-approved for future assignments. Rotation among them avoids having them buying into your firm’s blinders. Also, use one or more of them to regularly review your CI processes and work products to enrich your program with their broader perspectives. Interestingly, this is a flip on the CI audit that was used in the early days of CI before initiating a new CI program. Now the audit would be of the system as it operates and not of the potential need for CI and existing internal resources
February 21, 2018
Fortune magazine recently did a piece on Shell, one of the pioneers in developing and using early warning systems. At Shell, the outputs are called “scenarios”.
The article indicated that the Shell early warning team “concluded that global demand for oil might peak in as little as a decade – essentially tomorrow in an industry that plans in quarter-century increments.” The piece goes on to detail what Shell is doing: “making some big strategic bets.”
What is of interest is that the rest of the oil industry now knows what She’ll is and will be doing. That raises an interesting issue: by acting and revealing what actions Shell, a dominant force in the oil industry, will take, Shell is giving its competitors, suppliers, and customers insights into its own contributions to making the oil industry look different from today. And that is also changing the future Shell has projected. That means that, if Shell is right about its scenario, by acting and broadcasting those actions, it may, nay will, cause the future to be different from what it would be absent it’s actions.
Of course, this means that, in a decade, when Shell measures it’s accuracy in predicting the future, it may find it was wrong. But, this is because it did\could not factor in the direct and indirect consequences of its response to what was then still in the future as well as the responses of others in this business ecosystem to its responses, etc. Yet, the scenario could still be extremely invaluable, even if they cannot prove it.
Is your brain still on straight? Welcome to a brave new world.