Defuse the tension between designers and technologists – educate on your BI tools capabilities upfront

Posted on March 19, 2011 by Ron Keler

When working with designers, or users who are interested in designing their dashboards, you will undoubtedly run into tensions between what “should be” and what “can be”. While you can argue that with software there are really no limitations, and any requirements can be met given unlimited time and money, none of our projects enjoy that kind of a situation. We are always working within the constraints of time, budget, resources, etc, and the designs are bound to the possibilities of the technology that is being used. Your users and designers may want to incorporate charts that are not available in the technology of choice, develop complex navigational schemes that cannot be met, or want a very particular interaction driven by a certain type of fly-out, swirly, fade-in, color changing menu that you simply cannot produce.
If you are using Xcelsius as your dashboard technology, you can use the following file as a way to help mitigate this tension. This file lays out all the key components of Xcelsius, all the chart types, selectors gauges and sliders, and some of the other components, in a way that can be articulated and demonstrated to designers and business users. While each components, and certainly combinations of components are highly configurable through their properties sheets, in general, this type of an “upfront review” will give your users and designers a good understating of the capabilities of the tool and help set the stage for a productive collaboration around the tool capabilities.

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Good to Great Dashboard

Posted on March 15, 2011 by Ron Keler

In his famous book “Good to Great”, Jim Collins describes his research into eleven great companies that presented consistent outstanding results, compared to other companies that were in seemingly similar situation, but failed to achieve sustainable greatness. Collins describes the framework that he found in his research to have been at the heart of the transformation from good, or in some cases not so good, companies, into great ones. This framework, as you would expect, transcends companies and businesses in general, and can be extended into any field where excellence can be pursued.

At the heart of the transformation from good to great, argues Collins, you will find not technology, or fads, or superstar power. At the heart of greatness, you will find great people, who expect greatness from themselves and their surroundings, and who have the discipline to execute on a core idea for as long as it takes to achieve greatness. He uses colorful terms such as hedgehog concepts and flywheels to bring his ideas to life.

Collins makes two points that really caught my attention in relation to BI:

  • Technology, his research argues, is never a sustainable change agent in the transformation from good to great. Technology, he found, can be an accelerating factor, but in essence, is merely a tool, used by disciplined people to achieve great results.
  • The good to great companies had systems that allowed them to “raise red flags” and present not just information, but information that cannot be ignored. Thus, allowing management and employees to “face the brutal facts” and take a real and honest look at the reality of their business, in order to make real and good decisions, directly related to their reality.

I find the combination of these two points to be the essence at the heart of the dashboarding concept. Great dashboards are used by disciplined managers who look for factual data about their business in order to make decisions that keep their flywheel spinning in the right direction. This discipline drives them to not just commission dashboards to be constructed and showcased, but to actually use them, as often as needed, to understand their reality. It is a tool to raise red flags, literally, around problems that arise, and present the brutal facts, as derived directly from the underlying data, unfiltered or arbitrated.

When I look at my car dashboard as I’m driving, I make sure my sight is not diverted from the road for more than a split second. In that split second, I look for one, two or three pieces of information:

  • how fast am I going (actually, how fast am I going in relation to the speeding limit, which our cars are not yet telling us),
  • I might also look to see if I am getting close to being out of gas,
  • and occasionally check if the engine is overheated.
  • I also expect my dashboard to flash some red flag if something wrong is happening.

Modern car dashboards also house entertainment centers, GPS navigation systems, A/C and heat controls and much more. But these, and all the other controls built into the car dashboard are add-ons, and always come after the fundamentals are in place. So, when trying to create a great dashboard, consider these factors:

  1. Do you have a disciplined audience that would use the dashboard? What can you do to help instill this discipline?
  2. Do you have the “fundamentals” covered: how fast (in relation to the “speed limit”), gas situation, heat situation and other red flagged enabled
  3. Once you cover the basics, what other controls do you need to add to make the dashboard more functional and attractive

For example, maybe your business speed should be measured in terms of your pipeline. You need to understand what is your current sales pipeline (in relation to your delivery capabilities.

Your gas situation might be measured in your cash flow. Are your billings and collections at pace with your bookings and revenues?

Maybe your business temperature can be measured by your churn. How many people join or exit your company, what are your recruiting levels, and how does attrition look like?

And perhaps you should configure your dashboard to flash red flags in case certain operational measurements such as key vendor costs, or certain types of expenses breach a certain threshold.

If you manage to bring the key concepts of your business to life using a dashboard, you will likely achieve a great dashboard. And once you created a great dashboard, you can continue to add controls, navigation systems, entertainment centers and a whole slew of tools to help manage and tweak different aspects of your business, as long as you do it in ways that do not subtract from your kep concept.

*Good To Great is a registered trademark of Jim Collins.

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Scale matters

Posted on March 12, 2011 by Ron Keler

Charts have become an invaluable way to communicate information and articulate data. Charts help us not just convey data, but to also “tell a story”. With Charts, we can highlight certain points and help the people who need to act on the information we provide quickly understand it. Many considerations go into selecting appropriate charting types for your information. But in almost any conceivable chart type you plan to use, you will need to be thoughtful and plan how to address the scaling issue.

When I think about what can go wrong with chart scaling, I imagine a massively obese and happy guy standing smiling on a scale, next to a sad and stunned thin guy, who is also on a scale. Both of their scales only go up to 120lbs. You could argue this is great for the fat guy and bad for the skinny guy, but the fact is this is terrible for both of them, because they are both looking at a wrong reflection of their reality that will most certainly guide them to make the wrong choices.

One piece of advice you should consider up front and save yourself a lot of headaches down the road: if you plan to have any sort of charting capabilities in your BI application, report, dashboard, etc., make sure you understand how chart scales are handled. Most tools handle scaling automatically, and do not provide a lot of flexibility in terms of scale options. This would probably be ok most of the time, but I guarantee you will run into a data situation where these automatic settings would simply not be the right way to handle the picture. So, all you can do is try to be prepared.
Here are a few examples for some of the considerations you need to take into account when thinking about your charts scale.
Consider a relatively simple requirement: you are asked to create a report that will depict performance across regions for a national company. The company has presence in all US regions at this point, and is growing rapidly. It recently expanded into the Southwest. Performance is measured using two key measurements: revenues and margins.
You might start out with collecting the needed information and placing it in a table.

This is pretty good. It’s a clean simple table, it contains all the relevant numbers management would be looking for in a concise format. However, it does not tell a story. It’s difficult to analyze. It provides information, but it is not information management cannot ignore. You may decide at this point that a chart would do wonders to bring this information to life. 

This is the first example of how scale, when not handled, can turn into a major problem. This chart plots both the revenues and the margin across the same axis. Furthermore, the scale was hard coded, based on prior months results, to go from 50-150, so the Southwest region is simply not represented in the chart and the Southeast is cutoff. The picture depicted here is incorrect and misleading.

The next attempt is much improved. Instead of trying to plot revenues and margins on the same scale, you add another axis on the right, and you increase the scale limits to accommodate the data. The Southwest is not in the picture. Nice. However, something is still a miss. It is represented as a “blimp” compared to the other regions, and management looking at this depiction may not notice that the ratio of revenues to margins in this new region seems to be different than in other regions.

This final version plots revenues on the left vertical axis and margin percentages on the right vertical axis. In this picture, the newly added Southwestern region immediately draws attention. It dominates the margin picture. While revenues are still relatively low, something very interesting is happening down there, helping grow profits, and management will have a much easier time not being able to ignore this picture.
BusinessObjects Xcelsius charts have a good variety of scaling options, including primary and secondary axis, linear and logarithmic scales, and the ability to calculate min and max values for the Y (and Z) axis. This is a relatively understated feature of the product, but in fact, not many charting tools have this capability. It’s an invaluable tool and you should always keep an eye for the right choice of scale in your charts.

Controlling your charts scales will also allow you to come up with new charts types, overlay different types on top of each other to create interesting combinations. In a prior post I explored such concept of a Step Chart, made out of several synchronized scale charts. You will be able to handle a wide variety of data and filtering combinations that would otherwise result in misleading pictorial depictions.

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Broken windows theory applied to BI – clean up your reports so they don’t end up in the trash

Posted on March 9, 2011 by Ron Keler

The broken windows theory is a social sciences theory. It claims that maintaining the form of the environment prevents crime and social disorder. Malcolm Gladwell discusses this theory in his book The Tipping Point and examines how it was used to address the crime “epidemic” in New York in the mid 1980’s. This theory was put to the test in other areas of the country and succeeded every time. The concept is simple: if a burglar walks down a street and sees a broken window, he is more likely to enter through it. Or in a simpler form, if you walk down a dirty sidewalk, you are more likely to drop the dirty napkin you are left holding after finishing your hotdog, then holding on to it until you see a trash can.

 The idea is that the details of the environment affect how we perceive it and ultimately interact with it and with others that surround us within it.
While this makes perfect sense and passes most people “reality check”, others find it highly controversial since it implies that our behavior is more influenced by our external surrounding then our inner characteristics. While I understand this point of view, and like to think of myself as someone who generally “does not litter”, I have to be honest with myself and admit that walking down that filthy sidewalk, I might accidentally drop the dirty napkin…
What does all that have to do with BI?

The concept of attention to detail is what makes the difference between a crime ridden neighborhood, and a safe one, the same way that it does between a widely adopted and trusted report and one that is almost never used.
In a prior post, I wrote about  “The two prerequisites for any BI project: It has to be right. It has to be pretty”. Another way to phrase this same concept is: you must pay attention to the details of your BI project and assure that every tiny aspect of the design is addressed in order to be successful.
If your report does not reflect utmost thoughtfulness and care for the basic usability and aesthetic scenes of your users, It will not be adopted, and even if it is a marvel of technology, it will fail.
If the report labels have spelling mistakes, unnecessary complex formatting and coloring, bad use of screen/page realestate, etc, your users will get that “dirty sidewalk” feeling and the fate of the report is likely to be the same as that dirty napkin.

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Spin the bike wheel and track your performance

Posted on March 7, 2011 by Ron Keler

While working out at the gym today, I thought up this little Xcelsius dashboard to track biking performance. While the hardware components needed are a bit out of reach for me right now, the illustration below would have to suffice for now… J.

Spin the front wheel with your mouse, and track your progress with a line chart on the top.

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Automatically Close Xcelsius Dashboard When User Is Idle

Posted on March 4, 2011 by Ron Keler

A colleague approached me the other day with a requirement to “Logoff” users when they have not been active in an Xcelsius dashboard for a certain amount of time. I am sure there are many approaches and ways to accommodate this. The one that strike me first was to use an External Interface Connection (EIC) to capture all the user inputs in the dashboard, and use a counter to check how long they have not changed.

This approach is relatively simple to implement and requires little custom coding. It relies on Xcelsius EIC functionality, which is easy to configure and deploy, and works very well.

All I needed to do was concatenate all the user input cells in an Excel function in the Xcelsius model, point an EIC connection to this cell, and then write a quick timer java script function that resets each time the EIC changes. If the counter reaches 10 seconds (meaning the user has not interacted for 10 seconds), it hides the dashboard. Below is a screen shot of the example, you can also download it here

Keep clicking to keep the dashboard alive...

 

This is what happens when you stop clicking for more then 10 seconds...

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The two prerequisites for any BI project: It has to be right. It has to be pretty.

Posted on March 1, 2011 by Ron Keler

Business Intelligence is an agent of change. It’s a tool to examine existing processes, highlight which aspects of them work, which do not, and point the way towards improvement. It is disruptive technology and can have major impact on individuals’ day-to-day work as well on the entire organization of course. And yet, with all this power and promise, the biggest challenge any BI project faces is around adoption. Why is that?

Well, for one, using a report, a dashboard or an application to examine information is not necessarily a step people HAVE to get through to complete their work. Over time, everyone establishes ways for gathering the information they need to perform their work. They learn to vet the information, trust it, and work around the effort it takes to produce it. A common response to the latest BI marvel just rolled out is “So what if the new report takes 1 minute to run, and it takes me 4 hours to gather the data I need otherwise? It’s time well spent, and at the end of the day, I trust my manual process more than the work of those folks in IT who have no idea what I’m doing anyway, since they never really talk to me.”

Change is hard, and efficiencies are not always desirable by everyone in the organization. In fact, many employees in large organizations rely on inefficiencies for their livelihood.

When you roll out a new financial software to manage your invoices and revenues, everyone in accounting starts using it immediately. They have no choice. When you roll out a new reporting capability, it’s not as simple. Everyone can continue doing their work without it. They just don’t know they can do it better.

What can you do about that? There is no easy or simple answer to the question of BI adoption. It is certainly one of the most difficult feats you will face. There are, however, two basic things you MUST do to assure adoption is possible. Consider the following two as the fundamental pre-requisites for your roll out plan to even get off the ground. You simply cannot succeed without both of these elements:

   1. It has to be right. 100% right. There is no room for error on the information you provide. If you roll out wrong information, and the people who are using the information perceive it as such, they will never trust it again, and will look for other ways to get the information they seek. If you’re not sure the information is trust worthy, delay your rollout until you get it right.

 

This table looks reasonable and is easy to read and understand. The use of colors, fonts, formats, sizes and alignment have all been applied to focus attention on information. However, looking at the Sales number for 2004 Q3, it is obvious a gross mistake was made. You do not need to be an accountant to understand that if the average sales per month is in the $2M-$4M range, a $134M number for the same quantity of product as other quarter just can’t be right. While this report may look nice, it is doomed, shunned as a silly mistake by technologists who don’t understand the first thing about the business.

   2. It has to look good. You have to employ intuitive navigation, controls, look and feel in the display of information. Someone who has never seen the report, but is familiar with the subject matter, should be able to take one brief look at it and immediately understand the story it is telling. The information has to be presented in an appealing and thoughtful way that will be easy and simple to understand.

The data in this report is correct and has been verified beyond any doubt. However, it is so unappealing that no one would actually be able to use it. The colors are distracting, the formatting is poor and misleading, and it radiates lack of thoughtfulness for the folks who should actually be using it.

The first prerequisite is obvious. There’s really no need to explain it much and I don’t think anyone would argue otherwise. The second prerequisite is less trivial, and in fact, many technologist ignore it all together. They focus all their efforts around the technology, and the accuracy, and at the end produce a very weak presentation of their many months of very hard work on things that no one would ever be able to see, touch or understand.

It’s also not a tradeoff between the two. They are both equally important. There is simply no way to succeed in a BI project without both the data accuracy and the information design to be considered together as the two fundamentals that must be in place before go-live.

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Data is surprising

Posted on February 27, 2011 by Ron Keler

The only sure thing about data is that it will surely hold surprises you are not expecting. Data is generated from systems that ultimately collect information entered by people. And as people are surprising and act in unpredictable ways, the data they generate follows suit.

This fact has impact on all the stages of your BI project. As I’ve written in a prior post, you can make faster progress in and move in the direction of your goal by working on your data/ETL and reporting/visual tracks in parallel. On both tracks though, you need to be mindful of the challenges you will need to overcome stemming from the unpredictable nature of the data and information you are working with.

For example, on your data and ETL track, you will face many challenges, starting with ambiguous business rules, unclear hierarchies, muddy relationships between entities and gaps between what the data you are working with “should look like” and what it actually is. The budgets that you supposed to tie to projects over time, is actually only available for the entire project length, and not broken by period. The physicians that are supposed to work in no more than three offices, sometimes work in five, or seven, and products that cannot be discounted at more than 20% are sold for half their list price. The reality of business is the reality of life, it’s messy, confusing and chaotic, so surprises are more of the norm then the abnormal. Then, what do you do as an ETL developer? Do you write code to handle every conceivable possibility that may ever occur? Well, if you have a few years to work on your project, you might be able to do that. But if you are under some sort of a realistic timeline, you will make assumptions, solve the problems you are faced with to the best of your current knowledge and move on.

On your reporting and visual presentation side, things are not any easier. The bar chart that was going to be the most appealing part of the report, suddenly does not make any sense because out of the 8 data points you were going to plot on it, 7 are in the 50-100 range, and one is at 23000, rendering your scale meaningless. Or maybe the item you were going to group your report by does not make sense anymore because instead of 7 or 8 members in the group, you learn that there are actually 178.

Any software project has an inherent level of risk due to the fact that what is being built is new and in essence, “imaginary”. Software is always abstract and is hard to to “spec”. Creating specifications for BI projects is particularly difficult because of the inherent unpredictability that comes with the domain, to boot.

What can you do about all this unpredictability? You can shriek in panic and run for the hills, or you can stay calm, and be prepared to adjust your plan as you progress. Rather than trying to specify each and every aspect of your BI project up front, leave yourself some wiggle room to accommodate new findings. Make sure your logical model is robust and extensible, address error handling in your ETL design, and be prepared to quickly address them as they happen. Design your user interfaces in principal to illustrate and visualize the data that will become available as the project progresses, don’t create the expectation from the get go that each and every chart or graph you plan to have will actually materialize. Explain to your stake holders that new and additional ways to illustrate the point, deliver information and make the project successful by choosing the best representation as supported by the data.

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Embed LinkedIn search in your BI application!

Posted on February 20, 2011 by Ron Keler

I recently got to listen to a presentation about using LinkedIn in the context of sales and marketing. LinkedIn is a wonderfully successful and rich professional/social network, where you can find co-workers, past colleagues, old school mates etc. The difference between LinkedIn and other social media sites is that most folks consider their Facebook or twitter accounts for non-work activity, as well as work occasionally. LinkedIn is focused primarily on work experience and expertise, and more of a “professionals” network. Well, the speaker was pointing out all the wonderful ways in which LinkedIn can help those in sales and marketing obtain leads and introductions into companies and individuals, and while he was speaking I started imagining how combining the power of the social network/media with the power of BI can produce some pretty powerful apps. So, as an example, I tried to see if I can create a simple BI app that will connect to, say, the corporate CRM system, pull names and stats of companies and contacts within the companies, and in parallel, search for the LinkedIn profiles of those companies or individuals. Neat, right?

Well, fortunately, LinkedIn has a simple url query string that is used for searching, so it was not hard to come up with the search convention. The app I created has two sections:

The top section illustrates the connectivity to the company CRM system. In this example, I hard coded some “test” data to demonstrate a use case, or navigation flow:

  1. Scroll through a list of companies (can add search of course as well).
  2. Click a company name to get stats from CRM system (some overall stats, sales + pipeline numbers)
  3. Review the contacts in the CRM system from that company

 

Pretty simple right? Well, the kicker is that the bottom half of the screen will refresh with the appropriate LinkedIn search results based on each click. So, click on a company name, and the company name gets searched on. Click on an individual name, and the individual name + company name gets searched on. This kind of interface can help sales and marketing folks quickly mine internal databases for information stored in them, and connect it with their own personal network data, to come up with new connections and opportunities! And do all this quickly and easily. Feel free to download the example app here. You will need to extract the .zip file and launch the “LinkedInBIApp.html” file. This file embeds the BI app (a BusinessObjects Xcelsius based swf file) and has a few lines of javascript that control the integration of the content between the BI app and LinkedIn. You might be prompted by the Flash plugin to enable security on the file (since it communicated with an external website). And, you will need to login to your LinkedIn account to see search results. That’s about it! The rest should be self-explanatory.

I am convinced that the two major trends that will influence the BI industry over the next few years are social media and mobile devices. I am hoping to continue exploring both and deliver new and exciting new ideas for converging the two worlds, as they come together.

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Mashups are still cool! – Webi/Google mashup example

Posted on February 12, 2011 by Ron Keler

Mashups have been around as a concept for many year, and as a term for a few. The term mashup became very popular when google released its maps API. Suddenly, everyone had maps mashed up on their web sites. The BI vendors were quick to catch on, and provide ways (sometimes easy, sometimes not so much) to integrate external mashed up content into their html based reporting applications. And while you don’t hear about mashups so much these days, I still think they are a very powerful, inventive and cost effective way to produce powerful applications. The concept of combining functionality and content from different web based applications and providers and mashing it into a coherent and new kind of application works great in the context of a BI app or a report. In the example below, I mashedup a google map and a custom google search into a BusinessObjects web intelligence (webi) report. The resulting report is interesting, fun and contains functionality that neither app would have been able to provide on its own, making it unique and fresh.

The top left corner of the report contains a regular block of data from the e-Fashion universe (a sample database and semantic model that ships with the product). Next to it, is an embedded google map, that includes the city and sales revenue. On the left bottom corner is a custom google search on the page that allows the users to search the local web site (boston.com) and finally on the lower right corner is a regular webi chart with sales, discounts and margins data.

What could have been another boring tabular report is now teaming with interactivity and life, begging the users to explore and understand the information presented and look beyond.

The map was embedded in the webi report using an iframe that references a jsp file that was created on the businessobjects server. The jsp file takes the address parameters from the webi report, passes them to the maps api, along with the sales data, and creates the map. The custom search uses a similar concept, leveraging an iframe to embed the custom search div content.

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