“It Pays to Be Square” Analytics blog has moved!

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Looking forward to seeing you on our new site!


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Police Start to use ‘Threat’ Scores

While officers raced to a recent 911 call about a man threatening his ex-girlfriend, a police operator in headquarters consulted software that scored the suspect’s potential for violence the way a bank might run a credit report.

The program scoured billions of data points, including arrest reports, property records, commercial databases, deep Web searches and the man’s social- media postings. It calculated his threat level as the highest of three color-coded scores: a bright red warning.

The man had a firearm conviction and gang associations, so out of caution police called a negotiator. The suspect surrendered, and police said the intelligence helped them make the right call — it turned out he had a gun.

As a national debate has played out over mass surveillance by the National Security Agency, a new generation of technology such as the Beware software being used in Fresno has given local law enforcement officers unprecedented power to peer into the lives of citizens.

Full text article available via The Washington Post, 1/10/2016.

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Command Line & cvsstat

Last night I was working on a project and learned a new way to use the command line using csvkit’s csvstat.  Csvkit  is a set of small programs that were created to work with and process text files and I used the csvstat to produce descriptive statistics in my command line.  I did this because I was not sure what my file looked like or what was in it, but I did know the file was large and would have taken time to open the CSV or process in SPSS or python.

Here is an example of using csvstat on the train Titanic data from Kaggle:


This screenshot sample provides a view of the csvstat output which includes  headers, if null values are present, the data type, how many unique values are present, statistical information such as sum, and frequent values.

Have any of you used this or any other csvkit tools like csvlook or csvcut before?

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Weekend Project

In some of my spare time at home I have been focusing on working with Python “pandas”, the data analysis library. This weekend I learned that I was able to import data through the clipboard (that is, whatever you last copied), rather than saving data to a file on disk.  I think using the clipboard is novel and can very helpful when practicing and learning data processing, plotting, or using other functions for exploratory analysis . One thing to remember about using the clipboard is if you copy different data you will get unexpected results!

Here is a sample of what reading data from clipboard looks like and the output in line 26 displays the data I copied:


What projects have any of you been working on in your spare time?

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Happy Friday

I saw this incredible photo on the web earlier this week and wanted to share for fun.

The image is of Margaret Hamilton, a computer scientist who was the lead software engineer for Project Apollo.  This photo, snapped in 1969, shows Margaret standing next to source code that she and her colleagues developed to make the moon landing possible.

Pretty amazing to think about technology and its advancements.

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Prospecting at the Speed of Philanthropy

Predictive modeling, the process of using data patterns to predict future activity, is well established in fundraising for identifying prospects, prioritizing portfolios, and increasing return on annual giving investments. However, for many organizations, these likelihood indicators remain static for many years despite the dynamic nature of donor relationships. Now, it is within the reach of development programs to have scores that change as donor activity change.

From Wealth Screening to Predictive Modeling

Screening and modeling initially emerged to scale the filtering process in prospect identification. A seasoned major gift officer knows to assess capacity and inclination upon meeting a prospect for the first time. Prospect researchers have assessed these same criteria using found indicators of wealth, connection, and aligning interests. Yet, historically this work was done one prospect at a time. Through the establishment of consolidated data providers, fundraising programs were able to scale the capacity assessment to include large sections of the database. This wealth screening brought efficiency to the research process. Predictive modeling enabled these teams to scale the inclination question. In other words, fundraisers could screen for propensity.

As fundraising programs became more complex, we saw an increase in the frequency of wealth assessment. Perhaps the most frequent iteration is found in grateful patient programs because of the time-sensitive nature of patient affinity. We also see more frequent assessments in membership programs in the arts, in new parent populations in education, and following gift-level triggers in complex programs. For most organizations, though, the frequency of modeling remains about once every three years.

A Prospecting Innovation

Now, we are at a point where the frequency of inclination assessment can match the frequency of wealth assessment. A few innovative organizations have embedded the characteristic weightings from predictive models directly into their donor relationship management systems. As constituents give new gifts, volunteer, participate in activities, attend performances, or respond to appeals, their scores change dynamically.

The benefits of dynamic predictive modeling scoring include:

  • Managing the flow of new prospects by fresh levels of urgency.
  • Removing the often stagnant nature of major gift portfolios.
  • Targeting the timing of appeals.
  • Converting members to donors.
  • Increasing our responsiveness with our closest constituents.

Your Opportunity

We are excited to announce that DonorCast, the analytics division of Bentz Whaley Flessner, has successfully produced dynamic scoring with predictive modeling clients across nonprofit sectors. Dynamic scoring is now an option for any predictive modeling project.
Furthermore, clients can receive dynamic scoring for attractive prices during our pilot period now through December 31, 2015.

You can get in on this opportunity today. Contact us to take the next step in this dynamic world of predictive modeling!

For more information about Donorcast, the analytics division of Bentz Whaley Flessner, click here.

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Become A Better Public Speaker

No matter what your job responsibilities entail, effective written and verbal communication skills are critical to success (yes, even if you’re in Advancement Services!) Think back to the last five job postings you saw: how many didn’t require one or both of these important skills? However, fear of public speaking is not uncommon. Many of us have reservations about getting up in front of a group of peers; after all, it’s much easier and safer to stay behind our desks!

The good news is that confronting these fears is fairly straightforward: challenge yourself to take on an active public speaking role once every few months. Whether it’s presenting at a conference or just to a smaller group of co-workers, the idea is basically the same. Speaking on a topic that you are very familiar with is an easy way to start, but chances are you will learn something new about the material you are presenting on in the process! The Harvard Business Review recently posted a few tips on becoming an effective public speaker:

  • Prepare thoroughly. Research your topic, anticipate tough questions, and practice your delivery.
  • Imagine giving the presentation. How will it feel? How will you begin? What will the audience look like?
  • Stay calm and loose. In most cases, people can’t tell that you’re nervous. If you stumble, act as though it didn’t happen.
  • Get used to looking at blank faces. When you’re talking to someone one-on-one, they give physical and verbal cues that they’re listening. Groups of people don’t always do that.
  • Get comfortable with uncertainty. At a certain point you have to trust that you’ve done all you can to prepare. Remember: the likelihood that your worst fears will come true is slim.

I would add one more tip to the excellent list above: watch an experienced speaker practicing their craft. You can pick up invaluable information by watching any of the amazing Ted talks, or seeing an expert public speaker live and in person. The full article from the Harvard Business Review is available here.

Andy Schultz is the Director of Analytics at Bentz Whaley Flessner. To learn more about DonorCast analytics services, click here.

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