Whether you are a CEO, VP Product or a Web Developer, you are constantly evaluating your progress through a series of metrics or analytics, and generally against pre-defined goals. But, are you using the right dashboard to track your metrics day-to-day, and does your dashboard contain rich enough data to allow you to act proactively to ensure you reach your goals?
I recently read the book called Information Dashboard Design: The Effective Visual Communication of Data by Stephen Few. Although it took some digging to find real value, there were great nuggets of wisdom scattered throughout.
Getting back to the sole premise of a dashboard – its purpose is to act as a visual display of the most important information (note: not ALL information) needed to track progress toward your stated goals. In designing your dashboard, it is extremely important that the information is consolidated onto a single screen so that each metric being tracked can be viewed together – at a glance – so that the user can pick up on any trends and relationships between metrics and overall goals.
The book cites two great quotes that drives this concept home and explores a new facet of this equation, our visual perception:
“Dashboards and visualization are cognitive tools that improve your ‘span of control’ over a lot of business data. These tools help people visually identify trends, patterns and anomalies, reason about what they see and help guide them toward effective decisions. As such, these tools need to leverage people’s visual capabilities.” (Source: Richard Brath and Michael Peters, Dashboard Design: Why Design is Important)
“[We should be interested in visualization because the human visual system in a pattern seeker of enormous power and subtlety. The eye and the visual cortex of the brain form a massively parallel processor that provides the highest-bandwidth channel into human cognitive centers. At higher levels of processing, perception and cognition are closely interrelated. However, the visual system has its own rules. We can easily see patterns presented in certain ways, but if they are presented in other ways, they become invisible… If we can understand how perception works, our knowledge can be translated into rules for displaying information. Following perception-based rules, we can present our data in such a way that the important and informative patterns stand out. If we disobey the rules, our data will be incomprehensible or misleading.” (Source: Colin Ware, Information Visualization: Perception for Design, Second Edition)
Limitations of Man
Unfortunately, even the best of us are limited by our biological construct. Humans have limited short-term memory capacities and this is the main reason why information that belongs together shouldn’t be fragmented across multiple pages or dashboards. Once one set of information is no longer visible, it loses its position in short-term memory (unless you have a photographic memory, I suppose); on the flip-side, if all information is within one field of view, your brain can rapidly process information to and from your short-term memory. [HR Moment: If you’re hiring, consider those with photographic memories for data analyst positions!]
To design a most-effective dashboard, ensure to only include information that you absolutely need, in its most summarized form (without the loss of crucial value). This is where the KISS principle (”Keep It Simple, Stupid”) shines bright. The information should be well organized, condensed, specific to its audience/objectives and displayed concisely and clearly with emphasis on the data itself and not on background graphics or fancy designs (which tend to lose meaning and value quickly).
In reading the book, there were a few graphs that I found used space in a very effective way, whilst also allowing the dashboard reader to effectively take in a number of data points in a glance. The first of those graphs is called the “Bullet Graph” (details of how it works in diagram):
The second graph is called a “Pareto Chart” and below is demonstrated in a sales capacity, which quickly shows off what proportion of overall sales is contributed to by each product. Think about measuring the sales quota of each sales employee as a percentage of total sales (this will help sales managers know who to keep and who to let go using a clear and measurable decision-making tool:
My favourite graph, however, is the Sparkline. Its simplicity is unmatched and its span can be adjusted according to the scale you which to present. It is also great for summarizing large datasets into a small graphics that can be displayed alongside each other in dashboards. Sparklines are particularly good for analyzing trending data. In fact, this is used by Google in its Google Analytics product (below, Sparklines on the left of data and represent 3-month trending curves).
At the end of the book, Few shows a few sample designs of dashboards. I think these are among the best dashboards I have ever seen from a design, usability, trending and notifications standpoint. I have included images of dashboards for both sales managers and CIOs below, as designed by Stephen Few and presented in the book.
(Source: Information Dashboard Design, by Stephen Few)
(Source: Information Dashboard Design, by Stephen Few)
In the early days of 2010, I have undertaken a few new year’s resolutions. One of these resolutions is to record and track a number of daily activities and fitness metrics. I was incentivized to do this by Brad Feld, whose 2009 metrics were pretty impressive! In 2010, I am going to be tracking the number of books and magazines I read (and their genre, of course), workouts (broken down by type) and logging net time as well as unique instances, daily mood (or “feeling today”) and number of hours of sleep logged. I’ve also set goals in each of these categories and I’m excited to see how the presence of a tracking mechanism affects my net performance and my choices of what I do with my ever-decreasing spare time.
There are a few tools that can help to keep track of this data for you such as Daytum, but that requires a $4/month fee; I simply created a Google Spreadsheet with inputs on one tab and a dashboard of progress on another – an economy version of sorts. Let me know if you want a copy.
Some more granular tools can keep track of some specific details if you are really into this stuff. For example, a company called Zeo has a product for $249 that tracks minute details of your night’s sleep such as time in REM and disturbances and can upload data to it’s website for further analysis and coaching on how to get a better night’s sleep; I’d love to try it, but I heard it was only semi-effective. There are also plenty of tools to track running including a suite of pedometers, GPS-enabled units and embedded heart rate monitoring to ensure that you maintain an ideal cardiac output during your workout. No need to venture into more detail here. Let me know your favourite tools that you use to track your life, workouts and whatever else you track!
Yesterday I finished reading Guns, Germs, and Steel by Jared Diamond, and in the final hour of reading something sparked my attention:
Throughout history and despite relatively uniform intelligence across all of humankind, Diamond argues that widespread innovation had been limited to only certain countries in particular geographical contexts. He goes on to mention that innovation (as seen in those countries) was driven by the presence of higher population densities, close proximity to a number of neighbouring countries, and higher degrees of competitiveness between countries.
Naturally, I wondered, could this concept explain why so much technology innovation has led to an abundance of successful tech companies in the Bay Area, and to a lesser but still significant extent, the Greater Boston Area? On the flip-side, could this concept also explain why so many technology companies created in other regions have higher failure rates?
According to Diamond, innovation is driven by population densities of sorts. The Bay Area has one of the richest selections of successful and pioneering IT/internet/mobile technology entrepreneurs on the planet. As far as competitiveness, the US is the epidemy of a Capitalist nation, and competition is as fierce domestically as it is internationally (if not more fierce).
Note: As far as the Bay Area goes, I believe it remains at the apex of innovation due to its abundance of human capital, sharing of know-how, entrepreneurial culture, access to world-class research facilities/universities and venture capital financing. However, I do buy into the fact that proximate competition can help to turn good ideas into great ideas when the developers of the ideas have the ability to see and innovate on top of other very good ideas very quickly.
Although I don’t have the time and/or resources to explore this in further detail, I find this to be an interesting theoretical discussion about how a local geography can evolve in such a way that promotes rapid innovation in a particular niche. If you have an opinion on the matter, I invite you to please share it below.