Category Archives: rants

The Patriot Act In Layman’s Terms: The NSA Has Your Dick-Pic!

The Patriot Act is due to be reauthorized again in a mere six weeks on June 1, 2015. While no one doubts the importance of this act, or the continued need for foreign surveillance and border security, the act does contain some controversial provisions on domestic surveillance and security. Controversial provisions which, since the act came into law on October 26, 2001, have resulted in one arrest of one taxi driver who wanted to give $8,500 to a known terrorist group. (In other words, the controversial provisions never resulted in the ends they hoped to achieve.)

If no fuss is made, the Senate will just rubber stamp it back into law, as is, on June 1, 2015 and that might be the right thing to do. However, before the Senate does this, every American should decide if that is what she wants and advise the senator she elected accordingly. Because, whether she knows it or not, the provisions of the act not only allow the NSA to essentially tap and store just about every piece of electronic communication created by everyone in the US and by everyone communicating with someone in the US, but it allows the NSA to intercept, store, and view all of your private pictures, including those naked selfies the average American is so fond of taking.

In layman’s terms, if you took a dick-pic between October 26, 2001 and today, the NSA has it and there’s a good chance that someone who was not the intended recipient has looked at it. Listen to the interview below between Edward Snowden and John Oliver (who was the first to put the provisions in layman’s terms) where Snowden not only confirms that multiple sections of the Patriot act give the NSA these rights, but recounts his experience where NSA employees casually shared private pictures of various individuals’ naked parts for fun.

If you are happy with this, then by all means tell your Senator to re-authorize the Patriot act as is. But if you aren’t, tell your Senator that while you fully support the foreign surveillance and border security provisions of the act, domestically, you have a right to your privacy and you would like to see the controversial provisions amended to where the government agencies can only collect your personal, private data with probable cause and a warrant.


 

What do you think of this, LOLCat?


I iz Shocked!

Societal Damnation 45: Lack of Math Competency

Back in 2010, SI ran a post on how This is Scary! We Have To Fix This that referenced a MSNBC article on Why American Consumers Can’t Add that reported on a recent study that found:

  • Only 2 in 5 Americans can pick out two items on a menu, add them, and calculate a tip,
  • Only 1 in 5 Americans can reliably calculate mortgage interest, and, most importantly
  • Only 13% of Americans were deemed “proficient”. That meansless than 1 in 7 American adults are “proficient” at math.

Ouch!

And while Procurement needs to be able to deal from a full deck of skills (and SI has compiled a list of 52 unique IQ, EQ, and TQ skills a CPO will need to succeed which will be explored in future posts over on the new Spend Matters CPO site where the doctor and the maverick are co-authoring a number of series on the CPO job description and the requirements therefore, starting with “The CPO Job Description: An Overview”), many of them rely on math. In fact, with so many C-Suites demanding savings, if a Procurement Pro can’t adequately, and accurately, compute a cost savings number that the C-Suite will accept, one will be tossed out the door faster than Jazzy Jeff gets tossed out of the Banks manner.

However, the United States is not the only country with a numeracy issue. If you review the recent OECD Skills Outlook report that presented the initial results of the global Survey of Adult Skills (that focussed on reading, X, and numeracy), you see that of the 23 countries listed, Australia, Canada, UK, and France, all of which are home to head-offices of global multi-nationals with big Procurement budgets and bigger need for top talent, are all below average with the United States. While over 60% of Japanese adults have a higher level of Math proficiency, in Australia and Canada, it’s slightly over 40% and in the US it’s barely over 30%. However, this still doesn’t meant that these people can do basic calculations required for tips, mortgages, or savings calculations. For example, higher starts at Level 3 (where the survey respondent scored 276 to 326 points) and the description of level 3 is “tasks at this level require the respondent to understand mathematical information that may be less explicit, embedded in contexts that are not always familiar and represented in more complex ways“. Tasks involving multiple steps and problem solving are level 4, and the percentages here are dismal. Less than 10% in the US and barely over 10% in Australia and Canada. (In Japan, it’s around 20%!) This means that less than 1 in 10 adults in many countries have the basic math skills necessary to do mathematically intensive jobs which include the majority of the sciences, economics and finance, and Supply Management!

And performance seems to be getting worse every year. This is not a good sign in an inflationary economy with restricted demand where advanced analysis, modelling, and optimization is required to find efficiency and savings. We need more math, and less electro-mechanical devices that purport to do it for us. (Otherwise, we won’t even be able to compute just how damned we are!)

Decisions Should be Data-Derived – But They Should Not Be Big Data Driven!

In our recent post where we noted that it’s nice to see CNN run a piece that says big data is big trouble we noted that big data is big danger because more data does not automatically translate into better decisions. Better data translates into better decisions. And often that better data comes in the form of a small set of focussed data. For example, if one is trying to determine the right set of features to include in the next version of a product, the best data points are those that represent the desires of your best current customers who are most likely to buy the product. This is especially true if the most profitable market segment are enterprise business customers that buy thousands of licenses or units. If you only have a few dozen of these customers, these few dozen data points are more relevant than thousands of data points you’d get from a mass-market survey which would likely include hundreds of data points from customers who are only vaguely interested in your product (and who would likely never buy it).

Data does matter. But only the right data matters. That’s why only companies in the top-third of their industry in the use of data-driven decision making are 5% more productive and 6% or profitable than their competitors (as per “an introduction to data-driven decisions”. If it was just a matter of lots of data, then all companies would be more productive and half would be noticeably more profitable than their peers.

So how do you know if the data is good? Ask the right questions. In the HBR piece, the author lists six key questions that should be asked before acting on any data:

  1. What is the data source?
  2. How well does the data sample represent the population?
  3. Does the data distribution include outliers? Do they affect the results?
  4. What assumptions are behind the analysis? Are there conditions that would render the assumptions and model invalid?
  5. What were the reasons behind selecting the data and approach?
  6. How likely is it that independent variables are actually causing changes in the dependent variable?

And the answers that are received should be relevant to the problem at hand. For example, if we go back to our software / hand-held device example, the answers received should be along the lines of:

  1. Business Customer Surveys
  2. Over 70% of the organization’s largest accounts are represented
  3. Some small customers are included as well, but they are less than 10% of respondents and do not affect the results
  4. The assumptions are that the largest accounts provide the most relevant data. Currently, major account satisfaction is good and the data can be relied on so there are no current conditions that would affect assumptions.
  5. Large corporate customers represent over 60% of the company’s profit, so focussing on their needs first was the rationale.
  6. The surveys were designed to minimize the impact of independent variables, so the likelihood is low.

In this situation, you know the data is good, the approach is good, and the assumptions are relatively sound and you can likely count on the results. And, more importantly, the organization should act on them because it’s likely that any frequent correlation in the data indicates a causal hypothesis (if you add the indicated features, then the current customer base will buy the next version) and the benefits outweigh the risk (as a sufficient sales volume will cover the R&D costs).

And, just like the HBR article says, you don’t even have to like math to make the right decision. (Although there’s no reason not to like math.)