My Web Reading Stats

…Ten months later, I’ve accumulated a ton of material. As I already mentioned, I’ve read 732 articles since I started organizing and keeping track of my reading in this way. The general trends that are clear from the graph above—which shows the number of articles read in 25 categories over the course of ten months—are similar to what was shown by visualizing only one week of material. “Design” had the highest number of articles—over 60% more material than the next top categories. Based upon my own memory, I wouldn’t have guessed this. I knew that “design” would be high, but thinking back over the material I read this year, the “digital literacy” material stands out the most…

4:37 pm  •  10 May 2010

Another day, another set of data… I’ve been investigating what I call “peripheral” data sets in order to get a different perspective on how previously unseen or unmeasured activity affects the overall operation of our company. In my last post, I looked at how our busyness could be represented by the volume of communication over our internal project management system from one month to the next. In looking at that picture, I realized that the volume of activity is much more drastically affected by maintenance work for our clients than by new projects. I classify “maintenance” as any work done for an existing client- it’s a pretty broad spectrum, but since our new project process is so regimented, the split in categories is pretty realistic as far as our company’s day to day experience is concerned. When I noticed that October of 2008 had the highest volume of communication, I wondered what our maintenance sales were that month and how they related to new project sales. Sales data is the easiest information for me to dig up, but I wasn’t interested in the particular sales totals as much as the relationship between the numbers.

This brings me to the graph you see above. As I said, I wasn’t so much interested in how much we sold from one month to the next as I was about the breakdown of sales- how much of it was new business and how much of it was maintenance. So, I determined the percentage of each month’s sales total for the past few years that came from new projects and maintenance. For example, the graph above shows that in October, 2008, 37% of the month’s sales total came from new project sales while 63% came from maintenance. No wonder we had so many posts to our project management system that month! As you can tell from glancing at the graph, this is a relatively infrequent occurrence; more often than not, the new project sales account for the majority of the total. When I first plotted the data, I didn’t add the percentage values because I was more interested in the general relationship, as well as any trends that might be perceivable from visualizing the data. Again, glancing at the graph seems sufficient to conclude that there are no obvious patterns, nor an obvious trend in any direction (i.e. maintenance percentages trending upward or downward).

Averages and Average Averages
Then I wondered about averages. The data set covers three years, but it isn’t three full years. Additionally, the current year has a couple of extreme cases (January, in which maintenance accounted for only 19% of the sales total, and September, in which new projects accounted for only 2%), so I decided to look only at 2008’s average.

In the chart above, I plotted out a spectrum displaying only the percentages of total sales accounted for by maintenance sales— the lowest, 24%, came in July of 2008, while the highest, 71%, came in August. Two concurrent months bookending the spectrum seems to clearly show that there isn’t a seasonal correlation. But back to averages, the average maintenance sales percentage for 2008 was 41%. What’s interesting about this is that 8 months out of 12 were less than or equal to the average, leaving only 4 months in 2008 that exceeded it. If I isolate 2007, the average maintenance percentage for the 7 months plotted is 42%. If I isolate 2010, the average maintenance percentage for the 10 months plotted so far is 38%. These numbers are pretty close together. In fact, only 11 months out of the plotted 29 had maintenance percentages that exceeded 41%, which is a “score” of 40%. Maybe there is some significance to 40%…?

Ultimately, I’d love to see the percentage of maintenance account for more consistently higher amount. I think doing more work for fewer clients is to our and our clients’ advantage- it fits in with my motto of what we want to do: Serve fewer clients at a higher level. I believe we’ll get there.

One last thing: The graph above doesn’t show the number of new projects sold on a month to month basis. In 2007, the average was 4.1. In 2008, the average was 4. This year, the average so far is 2.6. To me, that’s the kind of decrease I want to see. It means that we’re selling fewer projects on a monthly basis this year, but at higher costs each (fewer at a higher level). So, all in all, one more piece of the puzzle…

9:00 am  •  20 November 2009

Measuring “Busyness”

In my last post in what is becoming series on measurement, I started off with my hypothesis that our company is like an ecosystem, “comprised of many areas of unseen activity” in addition to the sort of seen activity you’d expect (sales, individual projects, relationships, etc.). So, in trying to verify my hypothesis, I’ve been gathering data representing all kinds of unseen and unmeasured activity to see how it relates to the big picture as I’ve understood it so far. I started with looking at our blogging activity over the past three years and noticed that the months where we posted less loosely corresponded to what we tend to think of anecdotally as “busy” times for our company. That made me wonder- how else could I measure “busyness”? Looking at sales data wouldn’t quite do it, because those numbers would correspond to the beginning of a project, so the trendline of sales may not match up exactly with that of volume of work over time. However, looking at the volume of communication using our internal project management system might help me discern at trendline for “busyness.”

Unfortunately, there was no simple way to do this…

Read On >

9:00 am  •  19 November 2009  •  1 note

Visualizing Blogging Activity

I have a hypothesis that our company is much like an ecosystem—comprised of many areas ofunseen activity in addition to the very visible activity. With that in mind, I’ve been collecting data for the past few weeks that is a bit different from what I might normally look at (i.e. website and financial data). I want to see what unknown connections there might be between what we do intentionally and what we do unintentionally.

The graph above, containing one set of data from my “peripheral data collection” of late, shows the number of blog posts we’ve published since starting the Newfangled blog back in October, 2006. Throughout these three years, we’ve never had any established quota for publishing frequency, so I wondered what conclusions I might be able to make from looking at post frequency from the beginning until now. One immediate conclusion I can make is that this is not a large enough sample of data to support identifying significant cycles. There are only two full years represented, and the truth of the matter is that our blogging was fairly inconsistent during those three years for pretty discernable reasons. The first is due to population. From 2007 through 2009, we added 9 new employees to our team, all of whom have contributed to the blog. We also lost a few who blogged from time to time. The second is due to a sense of purpose. When we first started, many of our post were culturally oriented, “look-what-I-found” kinds of posts. It wasn’t really until July of 2008, when I published a post called Newfangled Blogging 2.0 that we really began to focus our efforts. In fact, July of 2008 was a time when we were focusing on defining a web content strategy in earnest, blogging being just one piece. After that, we started to plan our writing- identifying topics we wanted to see covered in the blog, making the frequency more consistent and encouraging more people to write. We’ve been moderately successful in that; our production schedule does make it a challenge to do all that we want to do. But, we’re getting the hang of it.

Note, for example, the May-June-July pattern that shows up in 2008 and repeats in 2009. That’s an interesting trend. It used to be that summers were a slower time at Newfangled. But since 2007, summers have been the opposite. They’ve been very, very busy, so I’m not surprised to see the decrease in blogging at the outset of that season. I also wonder if we’ll uncover a similar pattern in October-November-December. Time will tell.

9:00 am  •  18 November 2009

World Bank Now Included in Google Public Data

Google has just released World Bank public data, which allows you to sift through various metrics and create embeddable graphs. This graph compares the number of internet users as percentage of population in the United States vs. Malaysia (where I lived from 2005-2006). It’s interesting that the rate of growth is very similar between the two countries, only delayed by a handful of years in Malaysia.

2:22 pm  •  11 November 2009

Last week, I threw together a chart showing the various articles I’d read that week broken down by category. I was tracking the same idea this week and thought it would be more interesting to compare the two weeks. This week, less architecture, more futurism…

3:46 pm  •  2 October 2009  •  2 notes