On A Scale of 1 to 5

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Where would we be without rating and reputation systems these days? Take them away, and we wouldn’t know who to trust on eBay, what movies to pick on Netflix, or what books to buy on Amazon. Reputation systems (essentially a rating system for people) also help guide us through the labyrinth of individuals who make up our social web. Is he or she worthwhile to spend my time on? For pity’s sake, please don’t check out our reputation points before deciding whether to read this article.

Rating and reputation systems have become standard tools in our design toolbox. But sometimes they are not well-understood. A recent post at the IxDA forum showed confusion about how and when to use rating systems. Much of the conversation was about whether to use stars or some other iconography. These can be important questions, but they miss the central point of ratings systems: to manage risk.

So, when we think about rating and reputation systems, the first question to ask is not, “Am I using stars, bananas, or chili peppers?” but, “what risk is being managed?”

 

What Is Risk?

We desire certainty in our transactions. It’s just our nature. We want to know that the person we’re dealing with on eBay won’t cheat us. Or that Blues Brothers 2000 is a bad movie (1 star on Netflix). So risk, most simply (and broadly), arises when a transaction has a number of possible outcomes, some of which are undesirable, but the precise outcome cannot be determined in advance.

 

Where Does Risk Come From?

There are two main sources of risk that are important for rating and reputation systems: asymmetric information and uncertainty.

Asymmetric information arises when one party to a transaction can not completely determine in advance the characteristics of the other party, and this information cannot credibly be communicated. The main question here is: can I, the buyer, trust you, the seller, to honestly complete the transaction we’re going to engage in? That means: will you take my money and run? Did you describe what you’re selling accurately? And so on.

This unequal distribution of information between buyers and sellers is a characteristic of most transactions, even in transactions where fraud is not a concern. Online transactions make asymmetric information problems worse. No longer can we look the seller in the eye and make a judgment about their honesty. Nor can we physically inspect what we’re buying and get a feel of its quality. We need other ways to manage our risk generated by asymmetric information.

The other source of risk is not knowing beforehand whether we’ll like the thing we’re buying. Here honesty and quality are not the issue, but rather our own personal tastes and the nature of the thing we’re buying. Movies, books, and wine are examples of experience goods, which we need to experience before we know their true value. For example, we’re partial to red wine from Italy, but that doesn’t mean we’ll like every bottle of Italian red wine we buy.

 

Managing Risk with Design

Among the ways to manage risk, two methods will be of interest to user experience designers:

  1. Signaling is where participants in a transaction communicate something meaningful about themselves.
  2. Reducing information costs involves reducing the time and effort it takes participants in a transaction to get meaningful information (such as: is this a good price? is this a quality good?).

Reputation systems tend to enable signaling and are best utilized in evaluating people’s historical actions. In contrast, rating systems are a way of leveraging user feedback to reduce information costs and are best utilized in evaluating standard products or services.

 It is important to note that reputation systems are not the only way to signal (branding and media coverage are other means, among others), and rating systems are not the only means of reducing information costs (better search engines and product reviews also help, for example). But these two tools are becoming increasingly important, as they provide quick reference points that capture useful data.

As we review various aspects of rating and reputation systems, the key questions to keep in mind are:

  1. Who is doing the rating?
  2. What, exactly, is being rated?
  3. If people are being rated, what behaviors are we trying to encourage or discourage?

 

Who is doing the Rating?

A random poll of several friends shows about half use the Amazon rating system when buying books and the other half ignore it. Why do they ignore it? Because they don’t know whether the people doing the rating are crackpots or if they have similar tastes to them.

Amazon has tried to counteract some of these issues by using features such as “Real Name” and “helpfulness” ratings of the ratings themselves (see Figure 1).

Figure 1

Figure 1: Amazon uses real names and helpfulness to communicate honesty of the review.

This is good, but requires time to read and evaluate the ratings and reviews. It also doesn’t answer the question, how much is this person like me?

Better is Netflix’s system (Figure 2), which is explicit about finding people like you, be they acknowledged friends or matched by algorithm.

Figure 2

Figure 2: Netflix lets you know what people like you thought of a movie.

Both these systems implicitly recognize that validation of the rating system itself is important. Ideally users should understand three things about the other people who are doing the rating:

  1. Are they honest and authentic?
  2. Are they like you in a way that is meaningful?
  3. Are they qualified to adequately rate the good or service in question?

The last point is important. While less meaningful for rating systems of some experience goods (we’re all movie experts, after all), it is more important for things we understand less well. For example, while we might be able to say whether a doctor is friendly or not, we may be less able to fairly evaluate a doctor’s medical skills.

 

What is being rated?

Many rating systems are binary (thumbs up, thumbs down), or scaled (5 stars, 5 chili peppers, etc.), but this uni-dimensionality is inappropriate for complicated services or products which may have many characteristics.

For example, Figure 3 depicts a rating system from the HP Activity Center and shows how not to do a rating system. Users select a project that interests them (e.g., how to make an Ireland Forever poster) and then complete it using materials they can purchase from HP (e.g., paper). A rating system is included, presumably to help you decide which project you should undertake in your valuable time.

Figure 3

Figure 3: The rating system on the HP Activity Center site: what not to do.

A moment’s reflection raises the following question: what is being rated? The final outcome of the project? The clarity of the instructions? How fun this project is? We honestly don’t know. Someone thoughtlessly included this rating system.

Good rating systems also don’t inappropriately “flatten” the information that they collect into a single number. Products and services can have many characteristics, and not being clear on what characteristics are being rated, or inappropriately lumping all aspects into a single rating, is misleading and makes the rating meaningless.

RateMDs, a physician rating site, uses a smiley face to tell us about how good the doctor is (Figure 4).

Figure 4

Figure 4: RateMDs.com rating system for doctors.

Simple? Yes. Appropriate? Perhaps not.

Better is Vitals, a physician rating site that includes information about doctors’ years of experience, any disciplinary actions they might have, their education, and a patient rating system (Figure 5).

Figure 5

Figure 5: The multi-dimensional rating system on Vitals.com.

While Vitals has an overall rating, more important are the components of the system. Each variable – ease of appointment, promptness, etc. – reflects a point of concern that helps to evaluate physicians.

When rating experiences, what is being rated is relatively clear. Did you enjoy the experience of consuming this good or not? Rating physical goods and products can be more complicated. An ad hoc analysis of Amazon’s rating system (Figure 6) should help explain.

Amazon's rating system

Figure 6: Amazon’s rating system is not always consistent.

In this example the most helpful favorable and unfavorable reviews are highlighted. However, each review is addressing different variables. The favorable review talks about how easy it is to set up this router, while the unfavorable review talks about the lack of new features. These reviews are presented as comparable, but they are not. These raters were thinking about different characteristics of the router.

The point here is that rating systems need to be appropriate for the goods or services that are being rated. A rating system for books cannot easily be applied to a rating system for routers, since the products are so entirely different in how we experience them. What aspects we rate need to be carefully selected, and based on the characteristics of the product or service being rated.

 

What behaviors are we trying to encourage?

Any rating of people is essentially a reputation system. Despite some people’s sensitivity to being rated, reputation systems are extremely valuable. Buyers need to know whom they can trust. Sellers need to be able to communicate – or signal based on their past actions – that they are trustworthy. This is particularly true online, where it’s common to do business with someone you don’t know.

But designing a good reputation system is hard. eBay’s reputation system has had some problems, such as the practice of “defensive rating” (rate me well and I’ll rate you well; rate me bad and I’ll rate you worse). This defeats the purpose of a rating system, since it undermines the honesty of the people doing the rating, and eBay has had to address this flaw in their system. What started out as an open system now needs to permit anonymous ratings in order to save the reputation (as it were) of the reputation system.

While designing a good reputation system is hard, it’s not impossible. There are five key things to keep in mind when designing a reputation system:

 

1. List the behaviors you want to encourage and those that you want to discourage

It’s obvious what eBay wants to encourage (see Figure 7). A look at a detailed ratings page shows they want sellers to describe products accurately, communicate well (and often), ship in a reasonable time, and not charge unreasonably for shipping. (Not incidentally, you could also view these dimensions as source of risk in a transaction.)

Figure 7

Figure 7: eBay encourages good behavior.

 

 

2. Be transparent

Once you know the behaviors you want to encourage, you then need to be transparent about it. Your users need to know how they are being rated and on what basis. Often a reputation is distilled into a single number — say, reputation points — but it is impossible to look at a number and derive the formula that produced it. While Wikinvest (Figure 8) doesn’t show a formula (which would be ideal), they do indicate what actions you took to receive your point total.

Figure 8

Figure 8: Wikinvest’s reputation system

Any clarity that is added to a reputation system will make your users happy, and it will make them more likely to behave in the manner you desire.

 

3. Keep your reputation system flexible

Any scoring system is open to abuse, and chances are that any reputation system you design will be abused in imaginative ways that you can’t predict. Therefore it’s important to keep your system flexible. If people begin behaving in ways that enhance their reputation but don’t enhance the community, the reputation system needs to be adjusted.

Changing the weighting of certain behaviors is one way to adjust your system. Adding ratings (or points) for new behaviors is another. The difficulty here will be in keeping everything fair. People don’t like a shifting playing field, so tweaks are better than wholesale changes. And changes should also be communicated clearly.

 

4. Avoid negative reputations

When possible, reputation systems should also be non-negative towards the individual. While negative reputations are important to protect people, negative reputations should not always be emphasized. This is specifically true in community sites where users generate much of the content, and not much is at stake (except perhaps your prestige).

Looking at our example above (Figure 8), Wikinvest uses the term “Analyst” (a nice, non-offensive term … if you’re not in investment banking), to mean, “this person isn’t really contributing much.”

 

5. Reflect reality

Systems sometimes fail on community sites when people belong to multiple communities and their complete reputations are not contained within any one of them. While there are exceptions, allowing reputations earned elsewhere to be imported can be a smart way to bring your system in line with reality and increase the value of information that it provides.

 

Conclusion

Our discussion of rating systems and reputation systems is certainly incomplete. We do hope that we’ve given a good description of risk in online transactions, and how understanding this can help user experience designers better manage risk via the design of more robust rating and reputation systems.

In addition, we’d like to begin a repository of rating and reputation systems. If you find any that you’d like to share, feel free to submit them at http://101ratings.com/submit.php.

Communicating Complex Ideas

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“Prediction markets are appealing and useful because they can make predictions about future events, but getting people to use them effectively requires a bit of work.”For those who don’t follow the latest popular economics books, the relatively recent publication of The Wisdom of the Crowds by James Surowiecki has generated a burst of activity and interest in the prediction market arena. Prediction markets–markets which explicitly take advantage of the “wisdom of the crowds,” in that the price of a contract can be interpreted as a prediction for a future event–seem very simple and straightforward. People can buy and sell a contract based on a event, much like they would buy and sell a stock, and the resulting price says something about the probability for that event occurring.

Take, for example, a popular prediction market contract: Hillary Clinton will be the next U.S. president. If I think Hillary will be President, I can buy the contract. If I don’t think Hillary will succeed in her bid, I can sell the contract. Straightforward enough, but things can quickly get complicated.

What if you believe that Hillary has a pretty good shot at winning, say a 70% chance, but the contract is priced as if there is a 90% chance that Hillary will be the next president. Would you buy it then, or sell it? Suddenly you need to think about the strength of your belief. And how would you sell it if you don’t own the contract already?

Now imagine the contract is conditional, so that it is priced based on the outcome of whom the Republicans nominate, say John McCain. Would that increase her chances, or decrease them? And what if there is a market, say the Democratic Party Nominee Market, where Hillary is just one of several contracts trading? And furthermore, what if you were only one of 10 traders in the market, so that every time you bought or sold a contract you moved the market by over 10%?

Now add to this the fact that most people don’t know how to trade. For most people investing involves a 401K and maybe an IRA. Shorting stock is an alien concept to most. While day traders rabidly tapping out buy and sell orders into brokerage sites gripped the imagination for a while in 2000, these types of traders are a very small percentage of the U.S. population. Most people, it turns out, aren’t very good at buying and selling stocks at all.

And finally, why would one even care about buying contracts on Hillary’s presidential aspirations?

“These challenges become even harder when one thinks about implementing a prediction market within the corporate environment. Here, the cost of playing can be high (trading instead of working), and the contracts can be relatively arcane–predictions of future sales, for example. Selecting a large enough group of the right traders appears to be a difficult task.”Making prediction markets work
Prediction markets are appealing and useful because they can make predictions about future events, but getting people to use them effectively requires a bit of work. They need to make themselves relevant, attract the right types of traders, and teach people who are new to trading how to trade.

Several websites have taken on this daunting task with mixed success. These public prediction markets offer markets and contracts that cover a range of issues and events. They each have different functionality, and have designed their markets in different ways, but all are trying to solve the same problem: how to engage users to participate in these markets, and produce meaningful predictions.

What follows are some basic and general rules, gleaned from audits of these sites (with selected examples to help explain), about how to improve the communication and simplification of complex ideas about trading, and how to engage users, particularly when developing a prediction market. Some of these rules will be familiar and appropriate to all websites (but with a different emphasis for prediction markets), and some will be unique to prediction markets.

The following is a brief summary of these rules:

  • Liquidity is important to a market, so make people want to play.
  • Brief examples on the homepage will sometimes be the only learning users will have the patience for. Use these examples widely.
  • The stock market is a good metaphor for prediction markets, but don’t take it too far.
  • Simplify. Allow users to focus on the things that really matter.
  • Use tools that indicate and reveal what is happening. Trading is a nerve racking experience and users want to know what is happening.
  • Use contextual help. More so than elsewhere, contextual help guides users through complicated processes.

Make people want to play
Call it the usefulness of a website, or the hook which gets users to stay, the most essential part for any prediction markets website is to have markets and contracts that people are interested in participating in. As one recent book (1) put it, “As the wonkishness of the contract rises, however, volume and liquidity fall rapidly.” John Delaney, the founder/CEO of Tradesports.com, puts it more directly: “there is very little point in listing a contract that no one is interested in.”

The Hollywood Stock Exchange (HSX) is a master at getting people to play. With well over 50,000 users using play money to buy and sell contracts and derivatives based on the revenue of movies and actors, the site is clearly popular. It is also predictive. As academics seek to understand how well these markets perform they have measured the predictive power of HSX against Hollywood experts in how well they can predict who will win Oscars (2). HSX, it turns out, is superior.

As an indication of how passionate some users are about HSX, top portfolios on HSX can sometimes be found on eBay where people are willing to pay real money for fake money accounts.

Protrade is another public prediction market and has extended the concept from movies to baseball, football and basketball. On this site users can “invest” in players who they think are under-valued, and “sell” players who they think are over-valued.

Sports, movies, and actors make good subjects for prediction markets, not only because they are popular, but because accessing relevant information and forming an informed opinion is easy. Sports statistics are readily found on any number of sites, and talking about movies and actors is virtually a global past-time. Who doesn’t know about Tom Cruise? Who doesn’t have an opinion on him? Who doesn’t think they know better?

Making prediction markets work in the corporate world partly depends on overcoming this hurdle. Unless you work for the Boston Red Sox or at Universal Studios there probably aren’t that many compelling issues that workers can get passionate about. Motivating people in the workplace to take part in prediction markets takes imagination.

Use your examples wisely
As we all know users don’t tend to read much online unless they have to, or they have found the specific content they’re interested in. First impressions are also very important, and communicating the content of the prediction market, and how it works at a high level, are usually accomplished on the home page. Therefore most prediction markets have some sort of example or explanatory text on the home page. Unless the users are diligent enough to read the help text, this is often the only chance a site will get in explaining itself.

Different sites choose different tactics, but perhaps the best and simplest approach is that chosen by the Yahoo Tech Buzz Game.


Yahoo’s Tech Buzz Game homepage example

In four simple bullets it explains how the game works, what you will be trading, and importantly, how prices are moved.

On Trendio.com you buy and sell words on the expectation of their frequency of appearance in English speaking newspapers. For example, buy the word Google just before a big announcement by the company and the contract in that word rises once the announcement hits the newsstand. Trendio tries to drive their point home graphically.


Trendio.com homepage example

But they end up only confusing matters more. First, the example refers to ideas and not words. Second, without labeling and a consistent y axis it’s difficult to know what you’re comparing and how to even understand the charts.

When people are learning, examples are their guideposts. Use them wisely.

The stock market is a good metaphor, but don’t get stuck in it
Prediction markets are almost always compared to stock markets, and it makes sense to do so. Despite the fact that most people aren’t traders, most everyone has a passing familiarity with it. And almost everyone knows the most basic trading strategy of all time: Buy low, sell high!

But this model can also work against you. In the stock market there are many ways to enter an order. You can enter a market order, a limit order, an all or none order, and so on. While heavy traders might be happy to see these features imbedded into prediction markets, most people will be confused by them. Despite this some sites make the attempt.

Smarkets, though, a prediction market game that allows you to buy or sell contracts based on Amazon products and what their sales rank is, has simplified the trading interface to a point where it’s almost ridiculously simple.


Smarkets Trading Widget, Step 1 (contract information is to the left on the site)


Smarkets Trading Widget, Step 2 (contract information is to the left on the site)

The Smarkets trading widget dispenses with many of the complicated aspects of trading stock. Of course it can afford to as a play money game, but why make users deal with bid ask spreads and limit orders when they don’t need to. The majority of users will be just happy with a trading widget like the one above. If there are users for your site who want such functionality, then an advanced trading screen can be created for them, such as on Hollywood Stock Exhange (HSX).

Experts may quibble that a bid ask spread is important to price discovery, and so it is, but if you can make do without exposing it to the user, why not?


HSX Trading Widget

The HSX trading widget is even simpler and allows for even greater flexibility. Mouse over the movie you want to buy and the widget pre-populates. Max quantity allows you to purchase the maximum allowed amount. If you already own shares in this movie, to sell all of them just sell max, and you never have to worry about remembering how many shares you already own.

Both sites also take another idea from stock trading that people may be familiar with and twist it in a way that’s easy to understand and use. Shorting stock is a difficult concept to understand, and in the stock market it requires that you borrow shares from someone else (your broker figures out whom), sell them on the market, and then repurchase them later, hopefully at a cheaper amount. You pocket (or pay) the difference.

There is some complicated accounting involved and the trader who does this must have a margin account. In other words, you must always have a certain amount of money available in case the market turns against you.

Prediction markets handle the desire for traders to bet against an event or movie by allowing traders to buy shares in the “opposite outcome.” But exposing two contracts for the same event (or movie) to neophyte traders can, perhaps, be a bit confusing (both could potentially be bought and sold), so Smarkets and HSX disguise buying an opposite outcome contract as “selling short.”

In this way they’ve jettisoned the complicated accounting and they’ve removed the “opposite outcome” and, as a result, simplified the user experience. Of course, traders aren’t actually “selling short” but it makes no difference to them. They’ve accomplished what they wanted to accomplished – bet against the movie, or event.

Simplify, simplify, simplify
Yahoo’s Tech Buzz Game does something very interesting and quite logical. They’ve dispensed with allowing the user to enter the amount of shares they want to purchase. Why make the user do the calculation at all? The user only cares about how much money they’re going to invest in a certain contract not in how many shares they’re going to buy.


Yahoo Tech Buzz Game Contract page

By only allowing users to enter an amount of money they’ve actually saved the user time and an extra step. However, they have not carried this innovation over to the selling side of things. When selling, you begin with how many shares you’d like to sell, rather than how much money you’d like to cash out (which would be nice, wouldn’t it?). This is entirely appropriate, since a user may only want to sell half their shares instead of all of them.

Use tools that support the trading process and reveal what’s happening
For those unaccustomed to it, trading can be a nerve racking experience, even when trading with play money. While you bank account may be safe in these games, your ego is not. Nothing is quite so dispiriting as seeing your “assets” dwindle because you were wrong. Therefore, tools that help a user feel “safe” when trading, by explaining what is happening, and exactly what everything means, have value.

Inkling, for example, draws a direct connection between the expected probability of the event and the price. It then sets up three possible trades for you based on how different your expectations for the event happening are from the probability implied in the price. It also allows user to enter their own trades, if they so wish, but neophyte traders can allow themselves to be guided through the process of aligning their expectations for the event occurring and the price and number of contracts they purchase.


Inkling Trade Assistant, Step 1


Inkling Trade Assistant, Step 2

This guidance through the trading process is akin to training wheels on a bicycle. Experienced traders will have no need for this level of hand holding but beginning traders will appreciate it.

HedgeStreet, a real money peer to peer trading site includes a neat tool that helps the trader foresee any potential gains and losses.


HedgeStreet Trading Tool

In this case (Euro-US$ futures contracts) the user can enter in how many shares they would like to purchase. The price is automatically entered for them and their potential gain (upside) and loss (downside) is automatically calculated. It immediately tells you the amount of risk and potential reward you are accepting before making the purchase.

Use contextual help … a lot
And finally, as my father used to say, when all else fails read the instructions. Most prediction market websites have relatively robust Help sections, since there is a lot to learn and get help on. Better, though, are the sites that present their help contextually, and in this way support the user while they are in the middle of a task rather than forcing them to leave the page and go to the Help section.

NewsFutures has the humorously (but appropriately) named “I Need Help!” link which opens up a pop-up window with detailed instructions on how to read what is probably (certainly to most new traders), a difficult to understand bid and ask price list.


NewsFutures “I Need Help” link


NewsFutures “I Need Help” pop-up

While the help diagram is busy, the idea is right.

Smarkets makes it even simpler. With the link placed right under the order type drop down, the user can quickly access an explanation of what they should be doing.


Smarkets contextual help

Contextual help, while not the most sexy recommendation, is just one of the little things that public prediction markets should get right, more so than most sites, in order to create a useable and enjoyable experience for users.

Summary
As prediction markets push beyond being just games and interesting experiments, particularly as they expand into the corporate world, simplifying and communicating complex ideas about trading, contracts, and markets will become crucial. These examples show just some of the ways that these complex tasks and ideas can be communicated.

The most successful sites are those that understand the experience range of their users. Some are veteran traders who know what to do, while others can’t tell a bid from an ask price. Accommodating the novice traders is crucial to the success of these markets, as well as moving them along as they gain experience.

Prediction markets hold great promise. Research has shown a well designed prediction market can predict the future better than experts most (if not all) of the time. This promise encourages us to apply these markets to new areas of knowledge and in new environments. As more people use prediction markets, though, the more usable prediction markets must be.


Notes

Ads Are Here To Stay: Planning For Ad Placement

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“What must be developed… is not a way to make ads go away, but rather a better way to incorporate ads and ad content into our sites.”Ads: IAs dislike ’em; I dislike ’em. And, as an information purist, I believe everyone dislikes ads. They interfere with navigation. They flash annoyingly. They disrupt the flow of content, awkwardly placed, as so many of them are, right in the middle of the content we want to read. Even worse is when they have been somehow blended into the content, as if we wouldn’t notice. Ads, in short, dilute content and diminish the effect of a page.

This interference can be especially frustrating for IAs. We spend time architecting a page that will meet user needs in the best way possible. We’ve done user research. We’ve understood business models. We’ve brainstormed. We may even know that a page has to support ads, but if you’re like me, you try to place them somewhere out of the way, like the bottom of the page. And then the dreaded moment occurs, probably at the final schematic review, when the marketing director or some other important stakeholder looks at the page, searches in vain (ignoring all your fine work), and finally points to the top of the page and says, “We need an ad right there.”

What’s an IA to do?

The bad old days

In the bad old days (the not so distant past, actually), the design team swallowed their pride and agreed to do what our imagined marketing director asked of them. We grumbled, but in the end, whoever was responsible for the profitability of the project soothed our wounded egos and directed us to place the ad in the exact spot we had so astutely avoided placing it.

Whether it was a banner ad, skyscraper, pop-up, roll-over, or some other new-fangled advertorial innovation, we accepted our fate and placed the ad. Months later, when the site was launched, we could only cry as we navigated to our beautifully designed, and cruelly despoiled, pages.

I wish we could say that things have changed dramatically since then, but they have not. Advertisers still think up wonderful new ways to draw attention away from a site’s content to their content. And business models are still created which rely on advertising revenue for a site to be “successful.” The truth of the matter is that ads may never go away. If anything, the prevalence of online advertising is growing.

Just consider these facts.

  • The second quarter of 2004 saw record revenue growth for online advertising at $2.37 billion.1
  • Online advertising now accounts for 5.4 percent (or $8.7 billion) of ad spending in America, and 3.6 percent globally.2
  • Twenty-five percent of Ford’s Lincoln Mercury ad spending is going online.3

Add to that the perception among advertisers that online advertising is one of the best ways to reach adults,4 and one is inclined to conclude that online advertising is here to stay. What must be developed then is not a way to make ads go away, but rather a better way to incorporate ads and ad content into our sites.

Strategies for presenting ads

Fortunately we are not alone in our understanding of users’ feelings about ads. Advertisers, while not having our background, do understand that many web users are not all that happy about having ads on the internet, and that too many ads can ruin a page and dilute their own advertisement. Success is often measured by click-through rate, and advertisers now seem to understand that improving the user experience of ads can improve their own success. The success of contextual, text only ads should be noted (40 percent of online ad revenue is generated by search related advertising5).

What follows is a list of some strategies and guidelines for presenting ads on a page. These approaches will undoubtedly become more sophisticated as the possibilities, and variability, of online advertising grows. The Interactive Advertising Bureau (IAB) has put together a list of standards and guidelines for presenting advertising on the web, and is dedicated to educating people on how to advertise online. Instead of addressing these standards in this article, we would like to address their information architecture—how they fit into a larger page-level and site-level system.

Accordingly, the terms “success” and “failure” when used below refer not to the financial success or failure of an ad presentation strategy, but the user experience success or failure of an ad presentation strategy. As to which definition of success or failure is more important, I’ll let others debate.

1. Wrap the ad

Wrapping, or identifying your ad, is really a call-out indicating that what is in the box is an ad. A wrapped ad is really just a nice way of saying to the user, “Look! This content? It’s not our content. It’s someone else’s, and they paid money to have it here. Go ahead, look at it if you want, but know what it is you’re looking at—an ad.”

The visual design of the wrap should be consistent across the site. The design of the wrap generally never competes with the ad or with the design of the site. The text may be grayed, for example, but it is enough to be a consistent indication to the user.

Ad wrapping is appropriate for most types of ads, but most commonly seen with rectangles, buttons, and, skyscrapers.

wrap.jpg

2. Cluster the ads

An alternative to wrapping your ad is clustering several ads together. With this approach you indicate to the user that this area has been set aside for ads. In this example, the right hand side of the page has become an “ad zone,” and the user can see it for what it is, and then concentrate on the content in the center of the page.

In order for this strategy to be “successful” all, or almost all, pages on the site must have the same area set aside for ads. In general, the types of ads clustered together tend to be either skyscrapers or buttons.

A distinct drawback with this approach (and perhaps why one doesn’t see it too much) is the possibility that a line of ads can become like a row of Las Vegas slot machines – lots of blinking and distraction. One way to deal with this is an ad styleguide, addressed later, but advertisers do not always follow the guidelines set out for them.

Another “drawback” to this strategy is that you’ve lost the right-hand column as a space to put content.

cluster.jpg

3. Use leaderboards

“Leaderboard” is an IAB term, and refers to an ad that is placed at the very top of the page. It is larger than a banner (728 x 90 vs. 468 x 60 for a “full banner”), and its use appears to be more and more popular these days. The advantage of the leaderboard is that it gives the advertiser prime space, but also moves the ad out of content’s way.

Of course, the problem with the leaderboard ad is that it pushes the page down, moving more content below the fold.

An additional leaderboard may also be placed at the bottom of the page, but most advertisers may consider this space to be undesirable.

4. Use multiple layouts

Varying the layouts on different pages will help allow for the best accommodation of ads for the type of content that is being presented. The homepage, for example, will demand one layout, while a content page may demand another.

home.jpg
Homepage

content.jpg
Content Page

This can help avoid a certain sameness across a site while giving advertisers the options they crave. However, whatever ad layouts you choose, they should be standardized into a system that advertisers can understand and rely on.

The same template can also have variations that allow for different ad sizes. This allows for the content creator to select a layout that works best for the content, and then ad placement and sizes will conform to that layout. Advertisers also find this option appealing since they can track which ad layouts are the most successful.

5. Place the ad beyond 800 x 600

Another strategy that may be less popular with advertisers but can help the page retain its cohesiveness is placing the ad outside of the 800 x 600 area. This allows the page to retain its cohesiveness, and the content to take center stage, especially for those users who have limited desktop space to begin with.

In my experience advertisers tend not to like this option since the ad may not be seen by all users. However, other IAs have related that they are beginning to see this type of ad more often. It may be that as a greater percentage of users move beyond an 800×600 screen resolution it is becoming less of a worry for advertisers.

multiple.jpg

6. Hold firm on pop-up ads

The pop-up ad is still a no-no, especially if it pops up behind the browser window (a “pop-under”). These types of ads are the most distracting and disrespectful to users and should be avoided at all costs. They also happen to be among the most annoying ads, perhaps because they are not actually near any content that a user might want to read, and are instead off by their lonesome, desperately trying to get your attention.

Although I have no statistics to bear this out other than my own observations, it does appear that pop-up ads are beginning to become a thing of the past. Pop-up blockers are certainly part of the reason for this, but we like to think that advertisers are beginning to realize that extremely annoying is less effective than mildly irritating.

However, if you are forced to use a pop-up, or pop-under, then at the very least follow the guidelines set out by the IAB.

7. Create guidelines: the ad styleguide

An ad styleguide is similar to a styleguide that one might create for a site, except the audience is not content creators, but ad creators. The desire for an ad styleguide stems from the fact that advertisers often have their own interests in mind before that of the content. The result is an ad that competes with your content for the attention of the user, and advertisers do this by making the ad animated, or flashing, or by begging the user to click on it for some special service.

An ad can also ruin the effect of a well-designed page. Pages are normally designed to emphasize the most important content elements, but a “well-designed” ad can ruin even the best page designs. Placing limits on what advertisers can create to insert in your site will make for much happier content producers and much happier users.

However, as mentioned above, advertisers will push the boundaries of what is acceptable, and following this strategy means that the ad sales team must enforce the styleguide, otherwise the situation will quickly degenerate.

8. Check the business model

While advertising is certainly a revenue generator, it might please you to know that much of the world, including content producers, would probably be happier with fewer ads, or generating revenue in other ways than selling ad space next to their content. The ad sales department might object, since their year-end bonuses often depend on how many ads they place, but businesses sometimes do consider other ways of generating revenue from content.

As the IA, it is important, and even refreshing, to be a part of this conversation. From a business point of view, ads often have a limited upside. After all, page real estate, while theoretically limitless (a page could scroll forever), is in reality finite, and often advertisers will want a limit to the number of ads on a page so that their ad is not competing for “eyeballs.” This means that the smaller your site is, the less money you can possibly make, and the more likely you are to be motivated to monetize your content in new ways.

While a new business model probably will incorporate ads to some degree, removing ads as the sole source of revenue for a site will make it that much harder for the ad sales team to argue for “top billing ” on your templates.

Strategies involving contextual ads

In the spirit of “if you can’t beat ’em, join ’em,” contextual ads use external inputs to try to blend in better with the content and, it is hoped, with the interests of the user.

9. Take advantage of text-only ads (ala Overture and Google)

Most users should be familiar with the text-only ad. This was popularized by Google AdWords and allowed advertisers a way to capture some of the huge amount of traffic that comes to Google every day, and also allowed Google to monetize their search engine.

Text-only ads, as their name implies, have only text within the ad space, and tend to be generated by a keyword either entered by the user, in the case of search, or a keyword provided by the content, such as a metatag keyword. The resulting links presumably fall in line with not only what you’re interested in, but also the content on the page. The user then, the theory goes, will be less annoyed because the links have a legitimate reason to be on the page.

They are most commonly spotted on search results pages and they are far more effective than your typical banner ad.1 The danger with these ads is that they may be used in place of real content. In this example from abc.com, the abc.com search results don’t appear until far down the page-certainly below the 600 pixel mark-under the sponsored results section.

This suddenly makes search far less useful.

10. Personalize the ad

Similar to text-only ads, responding to a search or metatag keyword, the traditional ad can now be coded to respond to the type of content the user is viewing, and to the type of user who is doing the viewing. If there is profile information available – say the user is registered on the site and demographic or psychographic information has been gathered on them – this information can be used so that the ad presented is in line with certain known information about the user. For example, if the user is from New York City, an ad might be selected promoting a Broadway show.

While these ads may still visually clash with the design and layout of your site, they do have the benefit of having a better reason for being on that page than an ad that contains random content. They also tend to be more popular with advertisers and marketers, and make the ad space more valuable.

How I learned to love the bomb

While ads, by their very nature, will always live in tension with the content they support, new strategies are being developed that can help satisfy the needs of users and advertisers. By thinking of ads not as those annoying flashing animations that distract the user, but rather as another content type with its own peculiar features that must be incorporated into the page, you can change your distaste of ads into an architecture challenge. This may not change how you feel about ads (and if you feel about ads as I feel about ads, you can always purchase Norton Internet Security which has an ad blocking feature), but it can change how you feel about the work you produce.

Successfully incorporating ads into a site is perhaps one of the most difficult challenges, not least because of the nature of the content itself. Ads are revenue generators, and the ad sales department will often make blanket demands about what ads sizes they want and where they should live on the site. Balancing these demands with user needs can be difficult, but using some of the above-mentioned strategies can increase your chance of success.

 For More Information:
 1 IAB Internet Advertising Report Revenue Report
 http://www.iab.net/resources/ad_revenue.asp

2 The Economist December 29, 2004 “Back on the up.”
http://www.economist.com/displaystory.cfm?story_id=3523042

3 IAB Internet Advertising Report Revenue Report
http://www.iab.net/resources/ad_revenue.asp

4 “For advertisers who want to reach employed adults during the day, the Internet offers an unprecedented opportunity, with 50 million people regularly online at work,” says eMarketer CEO Geoff Ramsey. “There’s a virtual elephant in the room — one that astute marketers can no longer choose to ignore.”
http://www.emarketer.com/Report.aspx?atwork_feb03

5 IAB Internet Advertising Report Revenue Report
http://www.iab.net/resources/ad_revenue.asp

6 “Roughly 15 percent of ads displayed adjacent to Google searches (at the company’s own Web site and on Google-powered sites like Yahoo! and AOL) result in clickthroughs – more than 10 times the click rate of the average banner ad.”It’s an Ad, Ad, Ad, Ad World,” Josh McHugh.
http://www.wired.com/wired/archive/12.03/google.html?pg=8

2005 Online Media Outlook
http://www.avenuea-razorfish.com/OnlineMediaOutlook.pdf

Special thanks to Liz Danzico for finding some of these examples of ad displays.

Alex Kirtland is a Senior Information Architect and Experience Lead and is currently working as a freelance consultant. He has worked with a variety of companies and organizations, including Kodak, Verizon, Avaya, Western Union, and the Federal Reserve Bank of New York. He has experience with a diverse set of project types, from executive dashboards to metadata strategies to recipe finders. Most recently he has helped the Rodale Press redesign their online magazines, including MensHealth.com. If you want to learn more about him please visit his website www.alexkirtland.com.

Executive Dashboards

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Contrary to first impression, an “executive dashboard” is not found in a CIO’s car. Rather, an executive dashboard, also known as a manager dashboard, executive cockpit, or digital cockpit, is a child of what in the 1980s was referred to as the Executive Information System (EIS). These systems, and their web-based progeny, all have the same goal: bringing critical information to decision makers and improve the performance of their business.

“Companies are finding it’s much better to allow a manager to make an immediate decision in response to a market opportunity than to force him to wait for the CFO…“Who uses them and why?
An executive dashboard (referred to as “dashboard” for the rest of this article) is an intranet for a select group of users. These users tend to be executives—VPs and above, the people who are the main decision-makers in the company.

However, not all new dashboards are for executives and their ilk. As organizations push to become more nimble (and hence more competitive), dashboards are now being developed for managers of all stripes. When developing a dashboard, don’t be surprised if you hear phrases such as: “Every employee a CFO.” These reflect a realization by companies that faster decision-making helps them succeed. This means giving managers the ability to make decisions on their own. Companies are finding it’s much better to allow a manager to make an immediate decision in response to a market opportunity than to force him to wait for the CFO, or some other executive, to be alerted to the opportunity and then make a decision.

A dashboard supports a manager or executive by doing three things:

  1. It answers fundamental questions about the business or business unit.
    The dashboard should answer basic business questions: fundamental questions about the health of the business that can be financial, operational, or comparative in nature, such as:
    • Did I reach my sales numbers this month?
    • How many widgets did we sell in China last year?
    • How many widgets are we producing per month at the Chicago factory?
    • How often do employees call in sick at our Miami store? On what days are they most likely to call in sick?
    • Is revenue growing on a month-to-month or week-to-week basis?
    • How am I doing in comparison to my competitors?

    These sorts of questions can often take a full-time administrator and several spreadsheets to answer. Currency of information is important, but not as important as having the right information.

    Each particular executive or manager will have their own statistics (called Key Performance Indicators, or KPIs) that are important to them, but often companies will also have a standard set of measures that has been applied across the organization. This eases comparison of managers and executives to one another. Basic KPIs can be combined to form a scorecard, and organizations that have a scorecard likely will want it to be a part of their dashboards.

  2. It alerts the user to issues or problems in such areas as production, sales, and revenue.
    Closely related to the first point, a dashboard should alert the executive or manager when something goes wrong. How an “alert” is defined is based on the needs of the business. Some example alerts would be:
    • A product defect rate is going above an acceptable level.
    • Absenteeism is becoming a problem at a particular store or factory.
    • Average delivery time is falling below normal.
    • Sales targets are not being met.
    • Operational expenses are growing beyond an acceptable rate.

    Every dashboard needs to have an alert system that communicates when a critical figure has been passed or is about to be passed. In this case, currency of information is extremely important.

  3. It helps make decisions that impact the business.
    Finally, the executive or manager will use the information from a dashboard to make decisions. Sometimes these decisions can be very straightforward and can be answered by a single KPI, but more often business decisions will be complex and require a variety of inputs. Examples of these decisions are:
    • Do I increase or decrease production?
    • Do I need to change my product mix to be more competitive?
    • Should I close shop in Des Moines?
    • Do I need to hire more salespeople?
    • Why is the business not growing as fast as planned?

These types of questions require the ability to explore a series of KPIs. Also, they require drilling down into figures based on time or region, or selecting and comparing variables. In this case, it is important that the information is presented in a way that helps the executive or manager come to a conclusion about the issue they’re confronting, and construct a rationale to support the decision they make.

The backbone of the dashboard
The heart of any dashboard is the KPI. KPIs can measure all sorts of things, such as:

  • Inventory levels
  • Monthly gross profit
  • Sales revenue by business unit, by product, by region
  • Revenue forecasts
  • Top customers
  • Number of consultants engaged
  • Accounts receivable
  • Employee attendance rates

These measures can be financial or operational, but at the very least they should say something important to the user about the business. KPIs are most often presented in tables, charts, and graphs. Different executives and managers will need different KPIs to support their views of the business.

Data sources
For any project, understanding the technology is important. For a dashboard project this is doubly so. My advice is: become good friends with your technologists and understand as much as you can about what they’re doing.

The data for each KPI has to come from somewhere. For each KPI it is important to know:

  • Which system or database will provide the data?
  • What is the format of the data?
  • How the data will be abstracted from that system?
  • Will it be moved to a data warehouse or some other environment where it will be cleaned up and analyzed?
  • Will a person need to review the data before it can be disseminated?
  • How will the data be pulled into tables and graphs?

The source data will often be kept in a variety of places. Some of these will be operational systems, such as SAP or PeopleSoft, and some will be data warehouses. It is important for information architects to understand where the data is coming from, and how it is getting into the dashboard. Data accessibility will have an impact on how the dashboard is designed.

It can help reassure the street
As a side note, companies have also used dashboards in recent years as a way to tell Wall Street that their CEO and executive staff are aware of the financial state of the company.

CEOs are now expected to be responsible for the financial integrity of their company, and dashboards have been touted as a way to ensure that the CEO is aware of all financial aspects of the company.

Personalization/Customization
During the requirements-gathering phase of the project, executives and managers will voice the need for different KPIs. Also, based on their level within the organization, some information may have to be protected from some users. Information architects should have a clear understanding of these limitations to ensure that the right data is delivered to the right people.

Users will also want to customize the dashboard. The dashboard’s interface should also allow users to pick which KPIs they see first, as well as set their own alert levels. Users’ interests may change over time, and alert levels can change depending on the business environment. Pre-set alert levels should be programmed into the dashboard, if these are known, but unless the business requirements state otherwise, users should be allowed to change these to suit their situations.

Finally, the more robust portal servers will allow integration of other business systems into the dashboard, such as email, news feeds, and so on. These should be included, if possible, since they will only increase the value of the dashboard and the likelihood that the user will, in fact, use it.

Since not everyone is interested in the same set of KPIs, and since the structure of the company may require that some information is screened from particular users, a good portal server will be required, or a server platform that can provide similar functionality. If the company already has portal software, then it would be wise to take advantage of this.

Gathering requirements
Dashboard projects can sometimes move a bit slower than other projects because the target audience—executives, mostly—are harder to schedule time with. If the dashboard is for senior executives (the CEO, for example), then it will be very unlikely you will be able to interview your users (with the likelihood decreasing as the size of the company increases). Usually, at this point, the client will appoint someone to identify the needs of the senior executives, and he or she should be able to provide you with most of the information you need.

However, there are some other things you can do to help make the dashboard as useful as possible:

  • Interview administrative assistants and technical support staff.
    These people respond to the needs (and whims and desires) of executives on a daily basis. They will be able to inform you of how the executives like to get their information (print vs. screen vs. PDA, etc.) as well as what other sources of information the executive uses. Keep note of any failed information systems (there are usually a few) that were supposed to make the executive’s life better, but were accessed only once or twice for demonstration purposes and are no longer used.
  • Understand the business.
    While this should be true for any corporate web project, it is extremely important for a dashboard project. You’ll want to know more than just what products and services the company sells, but things like:

    • What are their lines of business?
    • How do they report revenue?
    • Is the company is growth mode or managing for profitability?
    • What is the company’s overall business strategy?

    If the company is public, read the annual report, or go to Yahoo! Finance and review the company information. Since executives are usually striving to please shareholders (and increase the stock price), it’s important to understand how investors look at the company, and what the major issues are, such as problems with debt or flagging product sales. This will help give context to the KPIs executives will ask for.

  • Be aware of similar but different KPIs.
    You should be aware that, especially in large organizations that are the result of several mergers, a KPI may have been created in one group that is similar to, but not exactly like, a KPI generated in another group. For each KPI it will be important to know how it was generated, how long it has been around, and the exact formula used to generate the KPI. If you are merging two KPIs into one, understand how the KPIs are similar or different, and what the effect of losing one of these will have on an executive or manager.

    Balancing these needs can be politically tricky, but should be manageable.

  • Consider access issues.
    Access issues are important to consider especially when creating a site for users who are almost always pressed for time, as executives and senior managers generally are. To ensure your dashboard gets used, spend some time during the requirements-gathering phase to understand how executives currently get the information that will be newly presented in the dashboard. Understand what they like and dislike about how they get the information.
  • Choose an effective delivery system.
    A dashboard can have amazing information design, a smoothly functioning back end, and can satisfy every whim and desire of the executive, but it still may not be used because the executive or manager travels so much they only use their wireless handheld, or because they’re used to reading everything on paper, or because their administrative assistant doesn’t know how to find it and therefore doesn’t open it up for them.

    Also, don’t underestimate the power of having reports hand-delivered. For people who have an enormous amount of information to look at, printed reports is one way of controlling that flow. When interviewing an executive’s administrative assistant, ask them about the best way to deliver the dashboard to ensure it gets used by the executive.

  • Plan for security.
    Given the type of information that is being displayed, security will play a big role in the development and design of the site. There will be two aspects of security you will need to confront: who gets to see what; and how is the site protected. Personalization will allow you to control who sees what (see above), but controlling access to the site also needs to be considered.

    The best is to take advantage of a current Single Sign On (SSO) solution, if one has been developed, or use the network login, if that is possible. Otherwise, one is faced with having to generate a new set of user names and passwords for users to memorize. Given that most of these users are pressed for time and already overwhelmed with systems that are supposed to help them, a new set of user names and passwords can severely hamper the success of a new dashboard.

    Balancing security concerns and ease of access concerns may confront you with some tough decisions. Try and resolve these issues as soon as possible in the project.

  • Understanding the technology
    A large part of ensuring the success of a dashboard project will be getting the technology right. As an IA, you will probably not be expected to manage this part of the project, but it will be critical that you understand the possibilities and limitations of technology. The following are some things to keep in mind.

    Business intelligence
    Business Intelligence (BI) is an area of technology that is concerned with gathering and analyzing financial and operational information. Most likely, the systems from which data will need to be extracted are BI systems. It is also likely that there will be other BI projects with which the project team will have to coordinate. These projects are normally managed through the technology department.

    There are many companies that provide systems and software for the BI space, and they all offer a variety of features. Some of the players currently develop systems to manage business information, such as SAP, PeopleSoft, and Siebel. Others develop data warehouses and analytic tools such as data-mining tools. Some of the players here are Oracle, Hyperion, Cognos, and Business Objects. This is by no means a complete list, and each vendor offers a different set of capabilities. Most have some sort of dashboard offering that is tied into their own system.

    However, the information needed to create an effective dashboard rarely lives in just one system or database. Most organizations use a variety of these systems and may even have a few home-grown solutions as well, including Excel spreadsheets. On a recent project, the client captured much of their financial information in Hyperion Essbase, operational information in SAP, and sales information in Siebel.

    Moreover, many of these systems are not known for their ease of use. Often they present too much—or too little—data, and sometimes they are not customizable by the user. The graphs themselves may be confusing.

    Real-time data
    At some point you will have to define what you mean by real-time data. Very rarely will this mean instantaneous data. Often, data is exported out of one system and into another on a daily or weekly basis. Financial figures are revised often, and sometimes only reported on a weekly basis. Sometimes there is data manipulation that needs to occur to bring the data into the right format. Almost always, companies are tinkering with their data systems in an attempt to improve or consolidate them. All of this will have an effect on the accessibility of data, and how current it will be when it is abstracted.

    Understanding exactly what information the executive or manager needs, and why they need it, will help you make a decision on how current the data needs to be on the dashboard. Sometimes data that is a little older may even be better, since the executive or manager will have more faith in its reliability.

    Reporting software
    Before designing functionality for the dashboard, it is best to understand which charting software will be used and how it will impact chart and graph design. Many BI systems will export tables and graphs that can be pulled into a dashboard. Crystal Reports is a popular charting option, but there are many other providers of charting software such as JFreeCharts, Big Charts, and Object Planet’s Easy Charts. All of these charting programs have benefits and drawbacks, and all of them will place some limitations on chart and graph design.

    Once charting software is chosen, you might perform a test to help clarify its limitations. Design one chart or graph, and then try to generate that using the charting software. You may find that you can’t make the font as small as you would like, or that other design elements cannot be represented as you intend. It’s better to find this out sooner rather than later.

    Another thing to keep in mind is that not all reporting software generates charts on the fly. Especially if charting is a part of a BI system, be sure you understand how often charts are generated, as some BI charting applications generate charts on a daily basis, rather than on demand.

    “3-D options may look nice, but they add a lot of excess ‘chartjunk’ and detract from the story you’re trying to tell.”Information design
    You should keep in mind that dashboard projects often come about because of frustration with existing systems. Often, the current BI systems have not been stitched together in a meaningful way (there are too many of them, or they are not integrated), or the systems are less than useful because the information is presented in a way that is not immediately comprehensible or useful.

    For an information architect (at least for me) this is the most exciting challenge: Organizing data in a way that is meaningful for the user, as opposed to reflecting how the systems collect and manage data. It is the essential Tufte challenge: how to take massive amounts of data and clearly tell the story inherent within it.

    Tables, charts, and graphs
    Most KPIs, if not all of them, will be displayed using tables, charts, and graphs. Most reporting software packages offer the basic graph options—pie charts, column graphs, bar graphs, and line graphs—and then some. These should be enough to represent the KPIs you’ve selected for the dashboard. However, even within these basic types, there are variations you should be aware of. Review Information Graphics by Robert L. Harris for a complete exploration of data displays. You should be able to find the appropriate table, chart, or graph from this book.

    When using reporting software, be wary of options that look great, but don’t tell the story you’d like to communicate. For example, 3-D options may look nice, but they add a lot of excess “chartjunk” and detract from the story you’re trying to tell. For the busy executive, quick comprehension outweighs a pretty picture every time.

    Data exploration
    There are two important dimensions to data that the executive or manager must be allowed to explore: time and scope.

    The user must be able to compare the data to either the past or the projected future. Incorporating past data will help give the executive or manager perspective on current data. Incorporating projections will help the user see where they are headed if the current state remains unchanged. Almost every KPI should have some time element incorporated into it for these reasons.

    Scope refers to the ability to drill down into data, or roll up data. For example, if an executive is experiencing extreme growth for his or her business unit, they will want to know who or what is responsible. Giving them the ability to drill down in data based on geography, or sub-group, or some other variable, will help provide them with answers to their critical questions.

    The ability to navigate along these dimensions will improve the value of the dashboard immeasurably.

    Conclusion
    The steps one follows to build an executive dashboard are not too different, if at all, from the steps one would follow to build a “normal” website (if there is such a thing). However, the target audience, and the types of information being presented, place demands on the project which are different from the average web project. It may also require the Information Architect to spend more time worrying about technology than he or she is used to.

    But, putting these issues aside, designing an executive dashboard presents an almost pure data-design challenge-one of the few an IA can find in the web world. It gives the IA an opportunity to understand specific questions, and then try to answer those questions using data presented in tables, charts, and graphs. As an IA who also considers himself an information designer, this is a wonderful opportunity indeed.


    Articles

    • Betts, Mitch (April 14, 2003). “Management Dashboards Becoming Mainstream:” ComputerWorld.
    • Krell, Eric” (March 1, 2003). “Gauge Performance by the Dashboard:” Internet World
      Magazine.
    • Orlov, Laurie M. (December 2002). “Use Business Intelligence To Manage
      Velocity:” Forrester TechStrategy Report.
    • Tedeschi, Bob (July 29, 2002).“E-Commerce Report; Digital cockpits are a faster,
      much closer way of tracking performance in a corporation’s every corner:” New York
      Times.

    Books

    • Harris, Robert L. (1999). Information Graphics: A Comprehensive Illustrated Reference:
      Institute of Electrical & Electronics Engine.
    • Norton, David P. and Kaplan, Robert S. (1996). The Balanced Scorecard: Translating
      Strategy into Action
      : Harvard Business School Press.
    • Any of the Tufte books

    • Alex Kirtland is a Senior Information Architect and Experience Lead at SBI.Razorfish where he’s
      worked for the past three-and-a-half years. He’s worked with a variety of companies and
      organizations, including Kodak, Verizon, Avaya, Western Union, and the Federal Reserve Bank
      of New York. Besides executive dashboards, he’s also worked on metadata strategy and
      user research/usability projects. If you want to learn more about him please visit his website www.huangkirtland.com.