I will not summarize the article – that would definitely devaluate it – but in the first part of the article the author starts comparing companies to cities. He mentions at some point that ‘companies that last’ and cities share some characteristics. I’d like to dwell on that for a minute because that metaphor is, as said, the part that triggered me.

According to the author, these are (some of) the characteristics of ‘companies that last’ that they have in common with cities:

Ecosystems: Long-lived companies were decentralized. They tolerated “eccentric activities at the margins.” They were very active in partnerships and joint ventures. The boundaries of the company were less clearly delineated, and local groups had more autonomy over their decisions, than you would expect in the typical global corporation.

Strong identity: Although the organization was loosely controlled, long-lived companies were connected by a strong, shared culture. Everyone in the company understood the company’s values. These companies tended to promote from within in order to keep that culture strong. Cities also share this common identity: think of the difference between a New Yorker and a Los Angelino, or a Parisian, for example.

Active listening: Long-lived companies had their eyes and ears focused on the world around them and were constantly seeking opportunities. Because of their decentralized nature and strong shared culture, it was easier for them to spot opportunities in the changing world and act, proactively and decisively, to capitalize on them.

So these companies were decentralized with ecosystem-like autonomy, had a strong shared culture and were actively focused on spotting opportunities outside of the company. If you add to that the fact that when companies grow (not ‘companies that last’ but companies in general), on average their productivity tends to decrease (per employee) whereas cities have increased productivity per capita when they grow, we now have quite some food for thought. Within these borders, I tried to explain for myself why cities become more productive when they grow. Is the author right in stating that we should organize and manage companies more like cities, supported by the fact that ‘immortal’ companies resemble cities much more than other companies do? Should we indeed try to manage companies rather than control them, similar to cities?

I truly believe the author drew a very truthful metaphor here. From a competitive intelligence point of view, I hardly know where to start summing up all the parallels. When it comes to the ecosystem part, I think the most important factor here is that an ecosystem should stimulate and facilitate initiatives for growth and innovation. By allowing the eccentrics, as the writer calls it, it facilitates creativity and thinking outside the box. There have been many examples of successful companies that display this kind of behavior to stimulate their employees to share their ideas for new products, improvements, et cetera. By stimulating partnerships and joint ventures they make sure the company expands its wisdom and that it is continuously challenged to innovate.

The fact that the organizational structure is decentralized shows that the company puts trust in the people in the field. They are the experts in their particular line of work and they should be made responsible for their turf. If they can operate as a more or less autonomous entity, it becomes their personal interest to perform!

Personally I believe this is an important aspect for every organization. I’m not saying every organization should ultimately be fully decentralized, but to a certain extent I believe people perform best when they are partially (if not wholly) responsible for their own tasks, making it their personal benefit if they do well (profit sharing for instance) and their personal problem when things go south.

And finally, the author states that one of the important shared characteristics is the fact they actively listen to their environment. That is almost the very definition of competitive intelligence (and no I did not pay the author to say this)! The first two characteristics set the starting point for this. If a company is decentralized, the right knowledge is present in the autonomous decentralized units (or at least I believe that’s a fair assumption). But in order to do things in a similar way and prevent overlap in activities, the centralized units need to communicate (either directly or via corporate). And that’s where shared values and culture play a role. Anyone in the organization needs to focus on their own activities, but care about the rest of the company. They should be aware of the rest of the company to help spot opportunities and possible synergy. And they should be willing to share for the benefit of the whole, instead of keeping everything to themselves.

What you have then created is the perfect environment for competitive intelligence activities, or for that matter for ‘actively listening to your environment to spot opportunities in a changing world’. You need to do that to survive. No matter how long a company can exploit their once unique and winning product, it will not last forever. Companies that keep winning are companies that – in a changing environment – change accordingly. No matter how powerful Shell is now, if they would stick to conventional fuel they will at some point lose.

A classic but still painfully clear example is the car industry in the United States in the seventies. Back then dominated by Detroit-based car manufacturers Ford, General Motors and Chrysler with no possible entry for non-American companies. But then the outside world changed drastically. Due to the oil crisis, fuel became much more expensive and ‘miles to the gallon’ became an issue for the first time. Besides that there was a more subtle demographical shift towards smaller families. The latter can arguably be missed but somehow I doubt if anyone back then didn’t see the first. Regardless what they knew, the Big Three refused to act on it and never started producing smaller cars with better mileage. Those changes in the environment did create a market segment and they either didn’t see it, or refused to act accordingly. As a result of this ignorance (or arrogance), opportunities were created for those out there that did watch the outside world (from their perspective). All of a sudden, there was a possible entry to this huge market! This is when Toyota first started selling cars in the US on a serious scale, expanding their market significantly. The rest of this story I believe is history.

So if and when the writer is right that these are the shared characteristics of ‘companies that last’ and cities, I fully agree with him that this increases the chances of survival for these companies dramatically. Cities last thousands of years and become more productive when expanding, both not being typical characteristics for the average company. So companies can learn a lot from cities, increasing their chances of survival by creating the right company structure (ecosystem) and company values (identity). And once they have done that, they can further develop their outside focus and anticipate on opportunities granted by a changing environment. So – with that in mind – is Competitive Intelligence really the elixir of life and will using it grant you immortality? No of course it isn’t, I’m sorry to say, but not drinking it surely diminishes your chances of survival.

Links
The connected company by Dave Gray (Communication Nation)

Sharp teaches us quite some useful lessons in the course of the book. For one, she clearly demonstrates that for a proper CI system the whole competitive landscape should be watched. Not just customers (but she does mention this factor to be the first priority), especially not just competitors. All external factors that influence a company, directly or indirectly, should be considered. Other lessons include the emphasis on the present and (near) future rather than the (distant) past and the fact that if no action is taken as a result of the gathered competitive intelligence, you might as well not bother at all. Sharp offers many pearls of wisdom regarding the value of CI, if and when conducted properly.

At the halfway mark of her book, Sharp shifts the scope from ‘why’ to ‘how’. It is almost like an entirely different book from this stage on, the tone changing from a scientific lecture on the profession – thoroughly substantiated with a large number of cases (clearly displaying Sharp’s wealth of experience) – to an extremely practical how-to guide to CI (in less than a day). The wide variety of practical (but slightly incoherent) tips and tricks will certainly be of help should you be in need of it in that particular area. But it almost seems as if Sharp wants to share everything she found out about the practical side of CI, without forging it into a process structure (or any other type of structure for that matter). The chapters move from a practical questionnaire for the sake of inspiration (questions a company could ask as a starting point for CI) to a chapter about what information sources can be found and where, to yet another chapter about ethics. All very useful, no doubt about that, but in a next issue I think it would be good to structure them by means of for instance the intelligence cycle. And then, amidst the tips and tricks, Sharp suddenly shifts back to a chapter about myths (reasons why CI is not important, profitable, worth the effort, etc.), where she once again creates an opportunity to flee in explaining the ‘why’ part, because that seems to be her comfort zone.

Conclusion

As a relatively seasoned CI professional, I found Seena Sharp’s book, Competitive Intelligence Advantage, to be great reading material. Even if you do not (always) agree with her, it is great to match your thoughts with the broad experience and knowledge Sharp displays in her book. This makes Sharp and her book excellent sparring partners for anyone interested in CI. The first half of the book is not so much a ‘how to’ for CI. Instead, Sharp emphasizes the value of CI, focusing on the ‘why’. The second half on the other hand is a rich collection of practical, more practical and extremely practical tips for anyone practitioning CI. For me personally, the first half of the book benefited me most. Sharp helped sharpen the boundaries of my personal definition of CI. The way Sharp describes the differences between CI and related fields such as market research helped me ‘sell’ the value of CI. But more importantly, her book has been a real eye opener on several occasions. For example when she provokingly states – bluntly against the opinion of many – that competitors are the least important external factor, she triggered me to (re)think this over, and convinced me that in fact she is right about this. For opportunities come from change, not from competitors.

Links
Competitive Intelligence Advantage (Amazon.com)
All reviews for Competitive Intelligence Advantage (Amazon.com)

If you find this review useful, please vote for it on Amazon.com (most recent review).

We all know the typical BI graphs: for instance a pie chart for market shares, a line chart for the sales over time or a bar chart for the amount of orders per week. These graphs are based upon structured data. The total amount of sales can be calculated from order lines for example. In CI tools this kind of data display is only possible when the data you’re collecting is structured data (for instance information from Google Finance or Dow Jones index). However, in the CI process analysts gather and analyze unstructured data much more often than structured data. So the question is: How can you display unstructured data in graphs?

When you’re collecting unstructured data the only measure you can display in a graph is the amount of news items. At first, I was a little sceptic about this. What can you deduce from unstructured data, what can you conclude from the amount of news? This isn’t really a strong measure, is it?

The main reason why I wasn’t very fond of using graphs in CI is the fact they can be confusing. Take a look at the below pie chart. What is your first idea when you see this chart?

This picture does not portray market shares per company, which is probably what you thought. This pie chart shows the amount of news items per company. Because we are used to see these pie charts in relation to market shares, it takes some time to explain what this graph actually tells us. I discovered while working with graphs in CI tools that the value of the measure ‘amount of news’ entirely depends upon the way you use it.

Graphs in CI can be valuable devices. Within a CI tool, categorizing your information is the key to valuable insights. You can compare this with measures in BI (or any other type of structured information). The measure ‘revenue’ in itself doesn’t mean a lot. You need to know in what period the revenue was generated, by selling which products, in which region, et cetera. By assigning this information to the measure you basically categorize it, which is exactly what we need to do with the CI information. You can use different kinds of categories: companies, market segments, strategic areas, regions, or whatever classification is relevant for you. For instance, when you categorize you news items per company, you can portray this in a graph. We’ve done this for HP, Dell and Apple and the result looks like this:

As you can see, there are a lot of peaks in the graph. These occurrences are probably interesting to investigate. This shows us immediately the main value of graphs in CI tools: they function as warning devices. Because CI isn’t exact science, these graphs are mainly about comparisons. As you can see, in September 2010 the results are peaking for both Dell and HP. Closer investigation showed this is due to the fact they were both bidding on 3PAR, a data storage manufacturing company that they targeted to buy. In general, when results are peaking for two companies this may indicate for instance (a rumour about) an upcoming merger, acquisition or joint venture. When all companies in your graph show a peak, it can also be an indication for a market specific development. We can see an example of this in the graph in June 2010. At this moment in time, there were some issues about Foxconn, an assembly company which is contracted by Apple, Dell and HP. There were a series of suicides by employees of this Chinese company, which raised questions about the working conditions. This kind of news influences the whole industry and is likely to be important for your company.

Another example where comparisons through time can be valuable is when you launch a new marketing campaign or product. With a graph like the one above you can see whether or not your online presence is growing. It is a way to measure the online effects of marketing campaigns. An example of this is the peak in the above graph for Apple in January/February. This is the moment Apple (loudly) introduced the iPad which explains the increase of news items about Apple. Exactly that is something else that this graph clearly shows: the amount of information regarding Apple is significantly higher than Dell and HP. This is not necessarily because they are bigger or better, but because they are louder and make sure people talk about them.

Graphs like the ones we’ve seen don’t show you what the news is about. But… with the right categories, you can refine your data. For instance, you can do this by using subject categories and use these in a matrix as shown below. Here we categorize the news not only by company but also by product type. You can see that Apple is mentioned most in combination with tablets and HP and Dell in relation to laptops. This may tell you something about the market segments these companies focus on, at least in the perception of the press. Because Apple recently released the iPad, it is not surprising that Apple appears a lot in the news in combination with tablets.

Another way of refining your data is to categorize the news based on sentiment. For this, I invite you to take a look at one of our previous posts: ‘Competitive Intelligence functionality: sentiment analysis‘. This way, you are able to display the amount of positive and negative news items. In this situation graphs function again as warning devices, because you can monitor positive and, maybe even more importantly, negative coverage of your company or product.

I hope I’ve shown you that graphs are of great use for CI, if used in the right way. Graphs function mainly as warning devices or for comparisons, and don’t portray an exact measure. CI remains an inexact science and the human factor in the analysis will remain important.

Links
Competitive Intelligence functionality: sentiment analysis by Anne van den Brink
Dell Drops out of bidding war for 3PAR from New York Post
Apple’s Steve Jobs finds Foxconn deaths ‘troubling’ from The Independent

Let’s focus on interviews. Interviews are a common way to get the information needed for an information analysis (as well as workshops for bigger audiences). If you’ve ever read posts or articles about the top <insert random number here> do’s and don’ts during interviews, you might learn a thing or two. If you’re lucky. One of the utter basics you will be taught is most likely this killer tip: “Use open questions”. Doh! Surely if you are interviewing someone who does not want to be in the chair on the other side of the table for whatever reason, it will be a horrible experience if you only use closed questions. You will be the one talking throughout the interview, desperately trying to keep the conversation going, ending up with no useful information because your opponent didn’t say anything other than yes, no, and don’t know. But don’t you think the interview is a total waste of time anyway? Do you think that using open questions will force him into opening up to you, and willingly telling you everything you want to know? One who does not want to be there apparently has other priorities than this interview. So he or she deems this project to be unimportant. That renders this person equally unimportant to the project. Even if you are talking to the CEO here – think about it; if the CEO doesn’t think it’s important what you are doing, he is either not going to be a user of the intelligence solution you are creating, or your project is in deeper trouble than you could possibly imagine before you started. So investing time and effort in asking what this person wants is a waste of time, because he doesn’t want anything (other than being left alone, elsewhere, doing other things).

Another great lesson you just learnt: “Prepare your interview and consider your audience”. Double doh! Isn’t that one of the basic rules for communication in general? Something you do all day, every day (prerequisite for this is that you actually communicate during your day)? Would you tell your 4 year old nephew not to speak so vituperately to his sister (and expect any reaction whatsoever)? At a party, would you say that you recently suffered from the worst acetaldehyde intoxication ever, or would you just call it a hangover (thank you Wikipedia)? Of course you consider your audience. And if you don’t prepare for an interview at all, you are (probably) just (being) arrogant.

It is like writing a book. You are thinking about writing your first novel. Most likely you have been writing tons of stories, poems and other pieces of verbal art but now you want to be well informed to launch your professional career. You seek for advice and hire a very expensive writing consultant (I bet they exist). And this person walks up to you, sizes you up and without kidding this person advises you to rehearse the alphabet…

Don’t get me wrong – I am not stating that these things are not true. I just would consider it a slap in the face if someone gave me these tips because they are so obvious. So seriously, what is important when it comes to interviewing stakeholders? If information analysis is really Art, I am not calling myself an artist, but at least it’s what I do and have been doing for quite a while and I would like to share some experiences regarding what I think is most important.

One of the things I think is important is awareness (this is the superlative of ‘considering your audience’). First, be aware of the reason why you are in the interview and why the other party is. No matter if it’s because you are the subject matter expert, the project sponsor, the project manager or the information analyst – you are there for a reason. Know your position and the position of the person you are facing during the interview. Is this person the enemy who wants to make your life miserable or a consultant with the best intentions (both might be possible). If you are the interviewing party, you want to know what the role is of the interviewee. Not the role that’s on his business card but his role in the project. Is this person a believer of the solution at stake? Is he an influencer? Will he be the most frequent user of the system? If you are unaware of these things, you are bound to ask irrelevant questions. There will be a disconnection between you and the interviewee because he does not feel understood, or worse, taken seriously – and I’ve seen both happen – resulting in unnecessary tension during the interview. This is what I feel is vital preparation for an interview.

Second, after the preparation, you should be aware of the interviewee and the way he approaches the interview. You did your due diligence to find out what you can about the interviewee, yet much of what you didn’t find out yet can be learned from the behavior of the interviewee. Is he at ease or stressed, does he seem excited about the project or is ‘annoyed’ best describing your interviewee’s state of mind? Subtle things like showing up on time rather than ten minutes late can be a signal. Be aware of these signals and anticipate immediately, even if it’s the exact obvious of what you expected and prepared. Don’t waste time with the ten-minutes-late-stressed-looking-top-manager. Skip your intro or keep it short. If you cannot beat his Blackberry in the struggle for his attention, you are losing the battle quickly (no matter how rude this is, it happens, so you better be prepared). Come to the point and skip less relevant questions, or move them towards the end (which might be sooner than you think). If he says he has 20 minutes only, make sure you use only 15. It’s commonly known that imitation makes people feel at ease (keywords here being: don’t overdo it). By being to the point rather than being the eloquent poet that you are, you make sure you are on the same level. He has no time to waste, so you better not waste it by beating about the bush. Closed questions (which by the way require a great deal of preparation concerning the interviewee’s role and job) may work extremely well in these interviews.

Quite the opposite would occur if the interviewee seems extremely interested in the project. He shows up 5 minutes early, turns off his cell phone, and wants to know everything there is to know about the project and about your role in it. Of course this interviewee gives you more (and better) options, but still you have to determine the path for your interview. Is this a knowledgeable, pro-active person, eager to share his relevant information? Or does he just talk a lot? And does he try to be in the lead of the interview or will he willingly let you guide him through your questions. All these signals and interactions determine what the best, most effective approach is, and unfortunately none of this you can prepare for. Also note that even though a set of prepared questions might come in handy from time to time, it plays only a minor role in the interview. Merely, if somehow you get stuck during the course of the interview, a list of topics you want to cover can help to get you going again.

There is no way I could even describe headlines of scenarios one can encounter during interview sessions. This is why I do not believe there could be something of a how-to for interviews (to be clear: this is not one!). Be prepared and try to be aware of the situation you are in and the goal you have for this interview. From that point on you have to rely on your communication and interpersonal skills. Focus, listen carefully and observe your interviewee. Their signals, either expressed consciously or not, help you direct the interview towards the desired goal (yours, hopefully). It’s like driving a car; you can get basic instructions to drive a car (your communication skills), and even directions (preparation) but in the end the external signals such as traffic lights and fellow drivers determine when to hit the brakes – it’s all about anticipation.

I think but one question remains: can anyone learn to be a good interviewer? Well – can anyone become a good driver? I believe some people unfortunately will never be one because they miss certain ‘talents’. I think we also agree that someone who just got their drivers license is not a good driver right away. And TomTom doesn’t teach you how to be one either. A good driver is one that is aware of his environment and anticipates well on actions (sometimes mistakes) from fellow drivers and traffic signs. The same goes for interviews: If you don’t have the required skills, such as some degree of empathy, you may never become really good at it. So you need a certain degree of these talents and have to understand the basics of communication. With the proper preparation (set destination in your navigation system) you are good to go but to ever reach your destination you need to find your way in the interview, even if there are unexpected detours. And I bet that this unwilling, rude, Blackberry-browsing top manager wasn’t in your instructions either.

Read this:

[…]
Location-Based Services
To provide location-based services on Apple products, Apple and our partners and licensees may collect, use, and share precise location data, including the real-time geographic location of your Apple computer or device. This location data is collected anonymously in a form that does not personally identify you and is used by Apple and our partners and licensees to provide and improve location-based products and services. For example, we may share geographic location with application providers when you opt in to their location services. Some location-based services offered by Apple, such as the MobileMe “Find My iPhone” feature, require your personal information for the feature to work.
[…]

(emphasis added)

This is a fragment of the privacy policy from Apple. When you want to download something from the iTunes store, you’ll have to agree on these terms (in the iTunes store you can downloads songs, applications, et cetera for your Apple device). The change in the privacy policy is rather drastic, because you agree that Apple knows where you are at any time. Apple doesn’t only gather this information, but also shares it with her partners and licensees.

In our definition, Apple is gathering competitive intelligence, because it is information about external factors (their customers). They use this information to improve their solutions (as they state in the policy) but probably also to manage their marketing campaigns et cetera. Nothing wrong with this, but the way they acquire this information is dubious. Apple doesn’t really give her customers a choice about this. They have to accept or ‘walk away’ (and the apps are what makes a iPhone, right?). Don’t forget, that most people (including me) don’t always read the full policy, because the’re to lazy, don’t understand what it says or simply don’t have the time. So Apple can collect this information sometimes without the customers knowing about it!

How does Competitive Intelligence in general relate to the privacy of those who are ‘under investigation’?

Privacy is one of the most important things in our lives. Privacy is the ability to do things without the public knowing about it. When someone is depriving you from your privacy, you’ll need to consent to this (like Apple asks permission to their customers so they can access personal geographical information). Because the border between private and public is difficult to determine, there is much discussion about it. Companies have also something like privacy. This privacy consists of information that shouldn’t be out in the open, like a secret recipe. It is very likely you’ve signed at least one non-disclosure agreement in your live, and exactly this information (that you shouldn’t disclose to ‘others’), is privacy sensitive.

Within the Competitive Intelligence area most sources are public. About these sources, there is no discussion about privacy. For example, it is not very smart to tell on Twitter that you’re going on vacation and there’s nobody home to look after your cat. When you do, you don’t have any right to complain about your own privacy if a security company is approaching you and asks if you need a security system for your home when you’re on vacation (because the’re not the only ones who know you’re going on a trip). Everything that you (or a company) puts on the internet (via a website or blog etc.) is automatically in the public sphere, so there are no big issues about which concern privacy.

There are privacy related problems when conducting unethical investigation. If you’re tapping phones, intercepting emails or lay in the bushes with a binocular, privacy becomes a big issue. These examples are pretty straightforward, but it’s not always that simple (the Apple case, for instance). How do you decide whether or not the information you find is in the public domain? When can’t you use something because you would deprive someone of their privacy? These questions are answered in a code of conduct, like the one SCIP has for CI professionals. Such a code of conduct describes what acceptable ways are to collect information. It states for instance that you may not ask a former employee of company X to disclose sensitive information about that company. A code of conduct will answer most questions regarding privacy issues. When you can’t resolve privacy issues with a code of conduct, use your own moral consciousness.

The major conclusion of this blogpost is that a CI professional should be aware of privacy-issues, and handle these issues with care. Also, it shows that the security of your CI tool is important. Your database is not only filled with information about your environment. A well-developed and used CI tool will contain a lot of analysis, reports and articles, which is your organization’s ‘privacy’. Although you should respect others privacy and they should respect yours, there’s no harm in protecting your own.

Links
Privacy Change: Apple Knows Where Your Phone Is And Is Telling People by Meg Marco
Code of ethics for CI professionals on SCIP

In order to fully understand the effect of marketing campaigns (and this doesn’t have to be a nationwide TV-commercial during the world cup finals, it goes for any campaign, no matter how small) you need intelligence on both your own company performance and your environment – the latter being Competitive Intelligence whilst the first would be Business Intelligence.

Business Intelligence

BI should be – among other things – the intelligence provider when it comes to your own company. Whether your campaign aimed at improving your sales and market share of your existing product or the launch of a new product, your BI activities will show the impact. In the first situation you should be able to determine the impact of the campaign during a certain period, if in advance you were able – to a certain degree of accuracy – to predict the sales for that period. In case of a product launch, it’s very hard to measure the impact, because you have no ‘normal’ situation. You could compare it to similar launches, or to predictions made by your company, but it’s not very reliable to say the least. So what we have now is a clear view on the effect your campaign had on the sales, based on which we can determine – and in some cases quite accurately – what the financial impact of the campaign has been on your revenue. In some cases this might be enough to justify the investment in marketing, but if you stop here without a clear view on the effect of the campaign on your environment, you may well be counting your chickens before they hatch. And that is where Competitive Intelligence comes into play.

Competitive Intelligence

Many external factors are (potentially) influenced by your marketing campaigns. And that is why you should not draw conclusions based on sales figures only. Let’s discuss some of the external factors that you should consider:

Especially for non-retail companies, it’s important to monitor the sales throughout your channel(s). You could sell a lot of product to your distributors, but they may well be accumulating stock, instead of selling it to retailers. Or the retailers are buying your product, but have difficulties selling it to their customers. The end customer is not the only one acting on your marketing activities. Retailers and distributors may order a lot of product based on your marketing campaigns, anticipating expected increase in demand. For this reason, many companies monitor the sales (and stock) throughout the channel with a Point of Sale system, which could be considered on the divide between BI and CI.

Whereas a successful marketing campaign in the end results in increased sales, a more direct effect on the customer would be the way the campaign makes them feel about your product. The best way to measure this, is to directly look at what they communicate about your product, in the media of their choice. In the previous post about reputation management and other posts about sentiment analysis (see the links below) we’ve discussed this process of measuring sentiment and how this can help you understand the effect of your marketing activities.

Another important aspect that influences effectiveness of your marketing efforts is the way you present yourself and your product. Ideally you should consider this at forehand, but of course it can also help you explain the effects of your campaign. In presenting yourself you should focus on your unique strengths of course, your USP’s, your competitive edge. In order to do so, you need to know the weaknesses of your competitors, which is of course an important aspect of CI. Take Apple for instance. Let’s say you are a competitor to Apple. You could of course aim your campaigns on the coolness and design of your products. Even if you are right, even if your products are better looking, odds are that you lose because of the perception consumers have about Apple products. Apple’s marketing machine did a great job here and created a strong image, which is very hard to break. But Apple also has weak spots of course. In measuring consumer sentiment about Apple (as described in the previous paragraph), I’m sure you’d find a lot of negative sentiment regarding service and support. If you believe in your own service level, you may want to spend your marketing resources on that topic and try to distinguish yourself from Apple.

Conclusion

Hopefully the above shows that measuring (and analyzing) effectiveness of marketing campaigns has a lot to do with Competitive Intelligence. And above examples are not the least bit exhaustive. A lot of external factors influence the effectiveness of campaigns. Shell may want to focus on their care for the environment (I’m not saying they actually do). Volkswagen may now focus on their reliability, now that Toyota’s reputation is steadily decreasing. But also demographic, political or technological factors may influence your campaigns, and these are all important aspects of Competitive Intelligence. So for your next marketing campaign, would you still rely on insights based solely on the sales results of the previous campaign? Or would you prefer to broaden your vision and make a more educated prediction next time? If you put it like this, the answer is not that difficult, is it?

Links
Why reputation management is also part of Competitive Intelligence
Sentiment analysis: is it accurate enough?
Competitive intelligence functionality: sentiment analysis

Any company that is not blinded by arrogance cares about its reputation. Reputation has a massive effect on your (potential) customers so it’s paramount to manage it well. To be able to do so, you first need to collect information so you can measure your reputation. After that, you can analyze the information, creating insights or intelligence. And like with any insights, they only add value if you act upon it, and start managing your reputation. Because then you are no longer at the sidelines of the discussion, but you become part of it, being able to control it to a certain extend.

The above process of gathering, analyzing, reporting and distributing resulting in action is very similar to the CI process. And that’s not the only thing they have in common. They both focus on external forces of your company; reputation management is about what external parties (customers, suppliers and even competitors) think and feel about you, your products, your ethics, your care for the environment, et cetera. Both CI and reputation management rely heavily on external, unstructured information as the base for your analysis. Therefore, one could see reputation management as a sub-process of the competitive intelligence process.

Traditional reputation management

In the old days, reputation was primarily measured by means of a customer satisfaction surveys and questionnaires used for market research. You might add information about customer complaints and other feedback your helpdesk may receive and maybe even information about product returns and you get an idea of the level of satisfaction directly from your customers.

But these surveys have some disadvantages: first, you target people. In the case of customer satisfaction survey, you target customers, who evidently bought your product for a reason and therefore might be biased. Even with other questionnaires your pick the target audience and you are the trigger for an opinion, missing out on people that are not questioned and may have an opinion on you. Also, a lot of people do not take the time to fill out long forms about your company, the products you sell, et cetera. People with complaints may take more time to express themselves than happy customers. Bottom line is that these methods may still be valuable, but at the same time they are very limited.

The better approach

Instead of asking people for their opinion via the channels of your choice, the better way would be to listen to them on the channels of their choice. Imagine you just bought a fancy iPad, you discover amazing things and you just want to spread the joy. But unfortunately no one’s around to share the fun, at least not in your living room. What do you do in this situation? Chances are that many of us would twitter something. With misery the effect is even stronger. A product you acquired doesn’t meet the promised functionality and, if that isn’t tragic enough, the helpdesk is unable, perhaps even unwilling, to help you. A lot of people share their frustration on social platforms, either to find someone who listens or in order to take revenge. A lot of people don’t file a complaint, but that doesn’t mean they don’t complain, they just don’t care enough to tell you (or you didn’t listen).

How to start

If you decided you cannot sit back any longer, and don’t want to rely only on traditional methods because they are not sufficient any more, first you need to find your customers. What channels do they use to talk about you and your products? Once you have identified the sources you need to start monitoring them and start measuring the results of your search. Measuring and analysis will lead to insights about your (online) reputation. You can see who the people are that talk about you and can start profiling them. You can also see what they are saying about you. Are they talking about your company or more specifically your product? And how do they feel about you? Once you’ve established the connection to their channels, you need to start acting on it. You can directly communicate with customers that are unhappy. If you can take away their unhappiness, they will stop complaining, maybe even comment you for the personal interest you displayed. Or you can stop rumors that are being spread by means of a press release. You can rectify (partially) erroneous information and take the opportunity to benefit from the attention you get. Engage directly with your customers and they will feel heard and taken seriously. Or will you just wait for the quarterly survey…

It shouldn’t come as a surprise that I strongly believe human analysis is a vital part of CI. The more complex the job is – without a lot of structure, routines and a clear and easy-to-follow process – the less likely it is to be automated at some point in time. Have you ever tried writing a work instruction for a CI analyst? Don’t – you will spend ages writing down exceptions for even the simplest of analyses. So if we agree on the fact the human brain is vital (and therefore irreplaceable), the question is: how important is the role of machines then? Do they have a right to exist in a CI process?

To answer that question, I cannot help but referring to an article about chess computer Deep Blue and its close encounter with Russian chess God Garry Kasparov, back in 1997. The article is called Did Garry Kasparov Stumble Into a New Business Process Model? (by Andrew McAfee, Harvard Business Review) and describes the parallel between the game of chess and business models. I would like to more specifically use it to illustrate the role of men and machines in CI.

Kasparov versus Deep Blue

The story goes as follows: during the eighties, chess computers were hardly a match for Kasparov. In 1985 he beat 32 dedicated chess computers simultaneously, no single draw. In 1996 he beat IBM’s super computer Deep Blue 4-2, but when Deep Blue came back new and improved in 1997, it was the first time a chess computer beat Kasparov (3,5 – 2,5). Hurray for Deep Blue, but what does that tell us? Basically, Deep Blue beat Kasparov because of its ability to process tons of possible moves and their outcomes. In 2003, no super computer was needed for that anymore, and Kasparov had a hard time beating commercially available chess programs running on standard servers. So at that point in time, the processor power of a computer overtook that of a rather brilliant human brain.

Fortunately, the story did not end here. One started experimenting with the combination of human strengths and computer strengths. And according to Kasparov that lead to interesting results: First, the combination of a strong human player with a reasonably weak laptop beat super computer Hydra silly. So the combination of human creativity plus some computer power is much stronger than a very strong computer, that’s good to know. But the most interesting and perhaps surprising result of the experiment – and I have to agree with Kasparov (and author McAfee) on that – is the following conclusion: the strongest combination did not contain either the strongest chess player or the strongest computer. In fact it was the process that lead them to victory. Or as Kasparov put it:

Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.

CI analyst versus CI software

So if we move back from the realms of chess to those of competitive intelligence, we can rest assured: we shouldn’t be looking for the Deep Blue equivalent of competitive intelligence to replace our analysts. Instead, we should look for the level of aiding computers can offer and, most importantly, design the process in such a way that the synergy between the two is optimized.

From what we’ve learnt above, we now know we need to do two things: first, decide which human strengths we should continue using and which tasks a computer is better suited to perform and second, design or alter the processes to make sure both strengths are used most effectively.

Human strengths versus computer strengths

‘Analyst’ in fact is a very good job title. Of the operational phases of the intelligence process, analyzing definitely is the phase where the CI practitioner adds most value. Most activities in this phase require creativity, intuition and a high degree of improvising – typical human strengths. In my humble opinion, the only degree of automation in that phase is a ‘smart Office tool’. For example, a CI tool that can serve as a framework for analysis, one that hands you all the information found in such a way that you can apply it easily to your analysis.

The first phase on the other hand, the collecting of information, is one that is very suitable for partial automation. Computers have the reach, precision and power to search a vast amount of sources, either in the company or online – typical computer strengths. On the other hand, a small minority of information may be best collected by a human being. And that is where the need for a solid process comes in, in uniting both worlds.

The process

When it comes to information gathering, you need processes to make sure the automated gathering is always accurate and up to date. No matter how well it is initially implemented, no system can maintain itself in a changing environment. You need to have a process for periodically checking the effectiveness of the automated tasks. Think of both changes in sources and changes in your environment. New entrants, new products, changing legislation, etc. Apart from that, you also need process steps to make sure you are not manually checking sources that are also automatically processed. When designing these process steps (typically part of the ‘setting direction’ phase) , you think about your complete set of available sources (this can also be knowledge in the heads of your colleagues) and how to use them. Systematically interview those colleagues to tap into their pool of wisdom, whereas you let the computer cover the more straightforward sources (such as internet pages, databases and information available in the systems of your company).

Knowing how to best synthesize these pools of information – even if you would not be the most brilliant CI analyst in the world (which of course you are) with a super computer at your disposal – will make you unbeatable by any super CI tool or CI God. Kasparov’s first law of CI.

Links
Did Garry Kasparov Stumble Into a New Business Process Model? by Andrew McAfee (Harvard Business Review)
The Typical CI Analyst by Anne van den Brink

Who is the typical CI analyst?

For the purpose of this blog, I allow myself to generalize, and talk about a ‘typical’ CI analyst. Due to the nature of the tasks he performs, a CI analyst should at least have the following characteristics.

The typical CI analyst:

• is not afraid to enter the lists against higher management;
• understands and knows how to handle political issues;
• is easygoing;
• knows how to find his way in and outside the organization;
• works systematically and from a rational point of view;
• is analytical and can think outside the box.

So, do you fit the profile? Then you are a typical (or let’s just say perfect) CI analyst! That is, theoretically speaking.

What does the typical CI analyst do?

The profile of the typical CI analyst has everything to do with the tasks the CI analyst has to perform. The analyst should not be afraid to engage in combat with higher management, because his messages aren’t always good news, but he has to make sure he will be heard. Good news isn’t hard to tell, but bad news is. Imagine you have to inform your director about a competitor who brought the same product on the market that your company is still developing. Also, you may need to suggest action that you know higher management truly dislikes and that can maybe even damage their image and/or create awkward situations for them. Informing your superiors is one thing; another is to make sure something is done with the supplied information. Some analysts have a CI manager to do that, and they should consider themselves lucky. Other analysts have to do it on their own, and it is their responsibility to make sure strategic decisions are based upon relevant competitive intelligence. An analyst should understand political issues as well. Politics are important in organizations. When you know who ‘controls’ who, and what implicit rules there are, you are more likely to succeed in transferring your messages. Yes, CI analysts most likely have to play the game of politics too…

The typical CI analyst is easygoing and talks to everybody. Although this is most likely in his nature, it is valuable in his line of work. A CI analyst will obtain a lot of information in informal settings (as opposed to official meetings). The analyst knows where in the organization he has to be/go when he needs something (or wants to know something).

A CI analyst should work systematically and from a rational point of view. He can’t afford to get pulled into one interesting subject, because this causes him to lose track of other subjects. The systematic aspect comes from the definition of Competitive Intelligence: the systematic collecting and analyzing of information about external factors. CI tools are tools that support this systematic approach. The CI analyst shall for instance design and fill out profiles (about products, markets, competitors) which allow him to structure the unstructured information he encounters. Another way of structuring information is the use of analysis frameworks, like SWOT or Porter’s Five Forces. The CI analyst does not only have to know these frameworks, he should have the ability to analyze with the help of these frameworks consequently and precisely. But the analysis should not be limited to the use of frameworks. A CI analyst should be able to think outside the box, because unstructured data can be hard to see through. When the CI analyst is analyzing the same data from another perspective or when he thinks beyond existing frameworks or opinions, it is possible for him to see new trends, topics, et cetera.

What makes the CI analyst valuable?

The value of the information about the competitive environment depends on the work the CI analyst does. If the CI analyst does a lousy job in structuring information, the reports he produces will reflect his way of work. When this happens, supervisors don’t see the surplus value of CI. When a CI analyst works systematically, from a rational point of view and when he feels like a fish in the water in the organization, most likely his services are greatly appreciated. This analyst will produce good reports, and is able to advise his supervisors based upon grounded information. When he also thinks outside the box and offers new insights, the value of the CI analyst will increase more and more. In the hands of a capable analyst, CI does what it should do: provide strategic decision makers with useful information about the external factors from the organization which make it possible for them to make informed decisions.

The puzzle […] graphically and deliberately demonstrates that competitor intelligence is merely one element in the business environment. Competitive intelligence is more expansive in that it considers all the elements that impact the company’s success – customers, suppliers, distributors, substitutes, regulations, technology, the economy, other industries, demographics, culture/societal issues – and competitors.

Though competitors may be the best known part of that environment, CI definitely is not solely about that. In fact, some – and obviously Seena Sharp is one of them – believe focus should not even be primarily on competition but on customers. Be that as it may, in this blogpost I’d like to discuss the above statement – about the necessity for CI in governments – considering both competition and other external factors. For every organization has a competitive environment that influences it. Regardless the industry you are a part of and regardless whether or not you are on the government pay-roll.

For the sake of example, let’s focus on any city council. To influence their competitive position – which I will discuss later on – they have similar tools compared to companies. Where companies can directly influence their product/service in terms of quality, pricing structure and promotion, governments can do the same, although somewhat more indirectly: by means of infrastructure (product), taxes/subsidies (pricing structure) and lobbying (promotion).

And there are more similarities. Like companies, governments have a vision on where and what they want to be. And they have a plan to get there – strategy. This vision can be that they want to be economic leader of the country, the number one tourist attraction or the knowledge centre. The strategy to achieve those goals will be a mix of the above instruments. If you want to be economic leader, you might want to invest heavily in infrastructure, but you can also create a friendly tax/subsidies climate to attract companies to settle in your city.

So far, I hope you agree that governments don’t differ all that much from companies. And completely similar to companies, government organizations need to know their (internal) strengths and weaknesses compared to competition, in relation to the (external) environment factors, to be able to determine opportunities and threats. After this analysis, they can determine which tools are most effective to achieve their goals and improve their competitive position.

This competitive position can be related to the strategic goals the city council has determined. Different strategic goals may require a different scope of external factors that influence these goals. For example, a company with an expansion strategy in upcoming markets can also thrive on market share in its existing markets. For both strategic goals the company needs to watch different competitors (possibly), customers (most definitely) and legislation, demographic factors, et cetera. So back to our city council – the one that is willing to become economic leader of the country – and its competitive position. Who are the competitors? Who are the customers? What other external influences do they have to take into account?

In random order, let’s start with competitors. If you want to be economic leader, then your (relevant) competitors are the alternatives that companies have to run their business in. Any city that is also anxious to become economic leader, but that is not an option for the companies you’d like to attract, is at this point not a relevant competitor (for this particular strategic goal anyway). In order to attract the desired companies, you have to create a more beneficial economic climate than your opponents. And you have to know them to know how you can outsmart them.

Whilst discussing the competition we’ve already seen the (potential) customers. You need to know what drives your customers to choose a specific location. You need to understand their business to know which tools to apply. A transportation company for example will need an outstanding transportation infrastructure. For consultancy firms, your city (or region) should contain potential customers for them and if you are a dairy company, the availability of grass for your livestock is a key requisite. So in order to efficiently apply your tools to attract companies, you need to know what their requirements are.

I will not discuss all the external factors in this post, but I think the point is clear. If a city council wants to be the country’s knowledge centre, it needs to have (or create) the necessary demographic conditions for it. A university will not prosper without enough potential students with the required level of education. Providers of this education may be considered suppliers in this situation. Legislation (on a higher level than the city council) may influence how successful you are in achieving your goals. All of this is completely comparable to non-government organizations.

So with all these similarities, is the business case for CI in government organizations the same as for companies? Well – no, not quite. Mainly the difference is caused by culture and nature of the organization in question. In companies, not meeting strategic goals may lead to dramatic financial results and lay-off of staff. Ultimately, not achieving your goals challenges the existence of the company. A healthy company may be able to survive this once or twice, but even the most successful companies cannot handle consequent underperformance and strategic failure.

In government organizations we see a totally different mechanism. City councils do not cease to exist. There is no culture of harsh measures when targets are not met. And the other way around, no huge bonuses are rewarded when they do a good job. So where a company leader has plenty of incentive to make sure he makes the right decisions based on the proper intelligence, in government organizations this is a bit different. So how can we convince government leaders to invest in decision supporting intelligence regarding their environment? One of their main incentives in this would be re-election. If a government organization malfunctions, the public has a chance every once in a while to either keep supporting the city council, or not. It’s like the annual review for the public sector. That’s when they are held accountable for the results. So for all you CI people out there, whenever you want to approach a government organization, make sure you do it just before election time!

References
Sharp, S. (2009), Competitive Intelligence Advantage. How to minimize risk, avoid surprises, and grow your business in a changing world, John Wiley & Sons, Inc., Hoboken (NJ)