How Can Managers Work More Efficiently with IT?

Would you rather work under someone who is an excellent developer but lacks people skills or leadership capabilities - or for someone that has excellent people skills, communicates well, and is a great leader but has limited understanding of productive coding practices? That’s not to say that the choice is one or the other but in many professional situations it does.

Managing an IT staff comes with numerous challenges, especially if the manager has no previous experience with the coding necessary for completing the project. Managing a business and IT's execution of tasks vary greatly in required skill sets, but it's important to find a cohesive and cooperative middle ground in order to see a project to its end. To fully grasp the intricacies of IT's involvement in the project at hand, managers can do the following to help further their efforts.

Get a basic understanding of coding and technical practices necessary for the project at hand by taking the time to research and practice enough to get a grip on the concept. This will allow managers insight on what their IT folks are really working on daily. Expertise in a programming language is not required, only an overview of the stuff that matters, i.e. understanding the concept of OOP (Object Oriented Programming.) Having this knowledge cannot be overlooked and will gain respect among multiple spectrums in the organization.

Data has always been important to business. While it wasn't long ago that businesses kept minimal information on people who bought their products, nowadays companies keep vast amounts of data. In the late 20th century, marketers began to take demographics seriously. It was hard to keep track of so much information without the help of computers.

Only large companies in the '60s and '70s could afford the research necessary to deliver real marketing insight. The marketers of yesteryear relied upon focus groups and expensive experiments to gauge consumer behavior in a controlled environment. Today even the smallest of companies can have access to a rich array of real-world data about their consumers' behavior and their consumers. The amount of data that is stored today dwarfs the data of only a few years ago by several orders of magnitude.

So what kind of information are businesses storing for marketing purposes? Some examples include:

- Demographic information — age, gender, ethnicity, education, occupation and various other individual characteristics.

In this tutorial I am going to give you a gentle introduction to network programming in Python. If you are new to programming or new to Python then that may seem like a daunting thought. But read on and you will be pleasantly surprised how easy it is.

Like most modern programming languages, Python was designed for networking from the very beginning, and thanks to that, a lot of the networking tasks you would want to accomplish with the language are made a whole lot easier.

Network communication is a large topic, but if it is something that interests you then read on because in this tutorial I will show you how to download a web page. I will show you how easy Python makes tasks like this.

Take a look at the following code:

import urllib
	
con = urllib.urlopen("http://hartmannsoftware.com")
page = con.read()
con.close()
print page

I suspect that many of you are familiar with the term "hard coding a value" whereby the age of an individual or their location is written into the condition (or action) of a business rule (in this case) as shown below:

if customer.age > 21 and customer.city == 'denver'

then ...

Such coding practices are perfectly expectable provided that the conditional values, age and city, never change. They become entirely unacceptable if a need for different values could be anticipated. A classic example of where this practice occurred that caused considerable heartache in the IT industry was the Y2K issue where dates were updated using only the last 2 digits of a four digit number because the first 2 digits were hard-coded to 19 i.e. 1998, 1999. All was well provided that the date did not advance to a time beyond the 1900’s since no one could be certain of what would happen when the millennia arrived (2000). A considerably amount of work (albeit boring) and money, approximately $200 billion, went into revising systems by way of software rewrites and computer chip replacements in order to thwart any detrimental outcomes. It is obvious how a simple change or an assumption can have sweeping consequences.

You may wonder what Y2K has to do with Business Rule Management Systems (BRMS). Well, what if we considered rules themselves to be hard-coded. If we were to write 100s of rules in Java, .NET or whatever language that only worked for a given scenario or assumption, would that not constitute hard-coded logic? By hard-coded, we obviously mean compiled. For example, if a credit card company has a variety of bonus campaigns, each with their own unique list of rules that may change within a week’s time, what would be the most effective way of writing software to deal with these responsibilities?